Miracle-dz/UniFAR-FTUs huggingface dataset:
Outlier-Preserving Focus+Context Visualization in Parallel Coordinates

Focus+context visualization integrates a visually accentuated representation of selected data items in focus (more details, more opacity, etc.) with a visually deemphasized representation of the rest of the data, i.e., the context. The role of context visualization is to provide an overview of the data for improved user orientation and improved navigation. A good overview comprises the representation of both outliers and trends. Up to now, however, context visualization not really treated outliers sufficiently. In this paper we present a new approach to focus+context visualization in parallel coordinates which is truthful to outliers in the sense that small-scale features are detected before visualization and then treated specially during context visualization. Generally, we present a solution which enables context visualization at several levels of abstraction, both for the representation of outliers and trends. We introduce outlier detection and context generation to parallel coordinates on the basis of a binned data representation. This leads to an output-oriented visualization approach which means that only those parts of the visualization process are executed which actually affect the final rendering. Accordingly, the performance of this solution is much more dependent on the visualization size than on the data size which makes it especially interesting for large datasets. Previous approaches are outperformed, the new solution was successfully applied to datasets with up to 3 million data records and up to 50 dimensions
Combining Variation in the Bayesian Face Recognition

In the Bayesian face recognition algorithm, the similarity of two images is estimated on one intrapersonal variation subspace which is based on all variation training data. In fact, the intrapersonal variation is complicated and there are many factors which will lead to the variation. Different factor brings different influence to the face image. In the paper, we divide the intrapersonal variation subspace into four independent subspaces, and estimate the similarity of two images on each subspace, then combine the estimation results to give the final recognition results. Experiment results show that the algorithm is effective.
A time, space and color-based classification of different weather conditions

Evaluation of different weather conditions provides a first step support for many different applications of outdoor video analysis and computer vision. In this paper, a simple but effective classification method on visual effects of different weather conditions is proposed. Due to the complex manifestations of weather conditions, we firstly provide a two-stage classification scheme. Then, we extract spatio-temporal and chromatic features to represent different weather situations. Using these features, we develop a classifier based on an experiential decision binary tree associated with C-SVM. The experimental results of classification on our newly-built video dataset indicate the effectiveness of our method.
A Formal Framework of Virtual Organisations as Agent Societies

We propose a formal framework that supports a model of agent-based Virtual Organisations (VOs) for service grids and provides an associated operational model for the creation of VOs. The framework is intended to be used for describing different service grid applications based on multiple agents and, as a result, it abstracts away from any realisation choices of the service grid application, the agents involved to support the applications and their interactions. Within the proposed framework VOs are seen as emerging from societies of agents, where agents are abstractly characterised by goals and roles they can play within VOs. In turn, VOs are abstractly characterised by the agents participating in them with specific roles, as well as the workflow of services and corresponding contracts suitable for achieving the goals of the participating agents. We illustrate the proposed framework with an earth observation scenario.
Automated recognition of oil drops in images of multiphase dispersions via gradient direction pattern

A novel feature designed to enable the automated recognition of oil drops from other circular objects found in images obtained in-situ of a multiphase dispersion model (oil in water) is described. The conditions inside a stirring tank are highly dynamic; this is reflected in the complexity of the images obtained, which in turn makes the problem of automating the recognition of objects of interest a very difficult one. To the best of our knowledge this is the first reported attempt to achieve fully-automated recognition of oil drops in this type of images. The proposed feature synthesizes local gradient orientation patterns that are characteristic of the boundary of the oil drops. The feature was tested as part of a supervised recognition framework based on a Bayesian classifier and employing the Hough transform for circles as a pre-selector of objects with circular shapes. By using the proposed feature alone, the classifier obtained a sensitivity value of 85% and a false-positive reduction of 33% (in this context a false-positive is an image-artifact with an approximately circular shape that was detected by the Hough transform but that does not correspond to an oil drop).
Virtual TCAM for Data Center switches

Software Defined Data Center Networks utilize a large number of rules to define routes for network flows. SDN controllers install rules at each switch in order to maximize metrics such as efficiency, delay or energy consumption. This requires each switch to store a substantial number of rules, which is not possible for current Top-of-Rack (ToR) switches as they usually have capacities of 2-4k rules. In this paper we present T-Flex (short for flexible TCAM), a technique for implementing virtual TCAM for data center switches. T-Flex can enhance the rule storage capabilities of a switch by up to 10x, and can forward incoming flows at line rate under most circumstances. Moreover, it provides full OpenFlow compatibility for use in SDN environments, and has been tested to work on a data center production grade Intel switch. Designed as an extension to virtual switches, T-Flex can provide the illusion of an unlimited TCAM in a data center switch.
Structural Performances of Concrete Beams with Hybrid (Fiber-Reinforced Polymer-Steel) Reinforcements

The paper analyzes the structural behavior of concrete beams reinforced with hybrid fiber-reinforced polymer (FRP)-steel reinforcements. The analysis refers to concrete beams reinforced with FRP rebars placed near the outer surface of the tensile zone, with low cover thickness values, and steel rebars placed at the inner level of the tensile zone, with high cover thickness values, able to protect the steel from the corrosion. Such reinforcement allows one to optimize the structural behavior of beams and guarantees a good level of ductility and rigidity. Results of an experimental and theoretical investigation are presented and discussed. Significant features of the structural behavior regarding deflection, curvature, ductility, crack width, and spacing are pointed out. Ultimate and serviceability conditions are examined, highlighting the influence of mechanical and geometrical parameters affecting the behavior of hybrid reinforced-concrete beams.
Structural properties of pulsed laser deposited zinc oxide thin films annealed at various temperatures

Abstract Zinc oxide (ZnO) thin films were prepared by pulsed laser deposition (PLD) technique using XeCl excimer laser with a wavelength of 308 nm at room temperature on quartz and single crystal silicon (100) substrates. The oxygen gas pressure was set at 6 torr during the deposition. The deposited films were post-heat treated (HT) in air at different annealing temperatures (ATs) for 30 min. The X-ray diffraction (XRD), optical and electrical properties were measured to study the properties of the films as a function of AT. XRD analysis showed that the strength of (002) peak increases and full width at the half maximum (FWHM) value decreases as the AT increases from 200 to 600°C. The films HT at higher AT of ∼600°C showed dominant c axis oriented hexagonal wurtize crystal structure. The films HT at 600°C exhibit high average transmittance of ∼85% in the visible region and very sharp absorption edge at 376 nm with energy band gap of ∼3·46 eV. Electrical measurement indicates that the resistivity of films decreases with the AT up to 600°C, after which there is an increase at higher AT. The complex of hydrogen defect and oxygen vacancy in the ZnO films may be the reason for low conductivity in undoped ZnO films.
PASSAGE: from French Parser Evaluation to Large Sized Treebank

In this paper we present the PASSAGE project which aims at building automatically a French Treebank of large size by combining the output of several parsers, using the EASY annotation scheme. We present also the results of the of the first evaluation campaign of the project and the preliminary results we have obtained with our ROVER procedure for combining parsers automatically.
Word spotting via spatial point processes

This paper presents a statistically based method for spotting target words in documents. The crux of the method is the representation of a word by a spatial (planar) point process evolving on a regular lattice of coordinate pairs. This is accomplished by extracting the coordinate pairs, i.e. pixel locations, where the binary bitmap values of the word are non-zero. With this representation the word is completely determined by the spatial intensity function, i.e. the unnormalized spatial probability density function, associated with the extracted set of coordinate pairs. In this work, we use a finite number of moments of the intensity function to characterize the word. Location and scale invariance are obtained by transforming the coordinate pairs to have zero mean and unit variance. Finally, optimal detection strategies are applied to the moments to make the decision.
The Observation of Width Quantization Impact on Device Performance and Reliability for High-k/Metal Tri-Gate FinFET

In this paper, the impact of width quantization on device characteristic and stressing induced device degradation for high-k/metal tri-gate n/p-type FinFET was investigated well including electrical characteristic clarification and simulation. Carrier conduction in the trapezoidal shape Si-fin body of FinFETs is different for devices with different Fin bottom widths (WFin_bottom), which will impact the device performance and reliability. For n-type FinFETs, the experimental results show that the thinner WFin_bottom device performs better reliability under HCI stress due to higher inversion carrier density at the center of Si-fin channel. For p-type FinFETs under negative bias stressing, the thinner WFin_bottom device shows more serious degradation on drain current (ID) and subthreshold swing (SS) with the increasing of stressing voltage due to larger electric field within the Si-fin and higher energy of inversion holes, while the thicker WFin_bottom device shows almost insensitively degradation with the variation of stressing voltage.
Adaptive Bayesian quantum tomography

In this letter we revisit the problem of optimal design of quantum tomographic experiments. In contrast to previous approaches where an optimal set of measurements is decided in advance of the experiment, we allow for measurements to be adaptively and efficiently re-optimised depending on data collected so far. We develop an adaptive statistical framework based on Bayesian inference and Shannon's information, and demonstrate a ten-fold reduction in the total number of measurements required as compared to non-adaptive methods, including mutually unbiased bases.
Fabrication of integrated channel waveguides in polydimethylsiloxane (PDMS) using proton beam writing (PBW): applications for fluorescence detection in microfluidic channels

Proton beam writing (PBW) is a lithographic technique that utilizes MeV protons in a direct write mode to fabricate micro/nano features in suitable resist material (E.g PMMA, SU-8, silicon, Foturan). These micro/nano structures may be used in an electroplating step to yield robust metallic stamps/molds for the replication of the original and lends itself to the fabrication of micro/nano fluidic channels that are important components in devices such as biophotonic chips. Another feature of proton bombardment is its ability to induce an increase in refractive index along the ions path, in particular at the end of its range where there is substantial nuclear scattering. This allows PBW to directly write buried waveguides that can be accurately aligned with fluidic channels. Polydimethylsiloxane (PDMS) is an optically clear, biocompatible polymer that can be readily used with a mold (such as that created with PBW) and easily sealed so as to produce biophotonic chips containing micro/nano fluidic channels. This has lead us to favour PDMS as the base material for our work on the development of these biophotonic chips. The present work is concerned with the production of integrating channel waveguides in PDMS chips, so as to have a working device that may be used to detect fluorescently tagged biological samples. For this we have adopted two approaches, namely(1) directly embedding optical fibres in the polymer and (2) using PBW to directly write buried waveguides in the polymer.
Avatar Mobility in Networked Virtual Environments: Measurements, Analysis, and Implications

We collected mobility traces of 84,208 avatars spanning 22 regions over two months in Second Life, a popular networked virtual environment. We analyzed the traces to characterize the dynamics of the avatars mobility and behavior, both temporally and spatially. We discuss the implications of the our findings to the design o f peer-to-peer networked virtual environments, interest management, mobility modeling of avatars, server load balancing and zone partitioning, client-side caching, and prefetching.
Molecular Mechanisms of Low Intensity Pulsed Ultrasound in Human Skin Fibroblasts*

Soluble factors such as polypeptide growth factors, mitogenic lipids, inflammatory cytokines, and hormones are known regulators of cell proliferation. However, the effect of mechanical stimuli on cell proliferation is less well understood. Here we examined the effect of low intensity pulsed ultrasound (US), which is used to promote wound healing, on the proliferation of primary human foreskin fibroblasts and the underlying signaling mechanisms. We show that a single 6-11-min US stimulation increases bromodeoxyuridine incorporation. In addition, an increase in the total cell number is observed after sequential US stimulation. US induced stress fiber and focal adhesion formation via activation of Rho. We further observed that US selectively induced activation of extracellular signal-regulated kinase (ERK) 1/2. Inhibition of Rho-associated coiled-coil-containing protein kinase (ROCK) prevented US-induced ERK1/2 activation, demonstrating that the Rho/ROCK pathway is an upstream regulator of ERK activation in response to US. Consequently, activation of ROCK and MEK-1 was required for US-induced DNA synthesis. Finally, an integrin β1 blocking antibody as well as a RGD peptide prevented US-induced DNA synthesis. In addition, US slightly increased phosphorylation of Src at Tyr416, and Src activity was found to be required for ERK1/2 activation in response to US. In conclusion, our data demonstrate for the first time that US promotes cell proliferation via activation of integrin receptors and a Rho/ROCK/Src/ERK signaling pathway.
MAP Model for Large-scale 3D Reconstruction and Coarse Matching for Unordered Wide-baseline Photos

In this paper we presented a novel idea for large-scale 3D scene reconstruction and annealing based image grouping algorithm for unordered wide-baseline photos. Firstly, an alternative maximum a posterior (MAP) model which can easily incorporate image clustering prior knowledge is proposed. Second, an efficient annealing clustering algorithm is developed for organizing photos into clusters by calculating matching number of invariant features. Thirdly, we analyze the time complexity and efficiency of the proposed approach. Finally a series of experiments are performed on the real image data and synthetic data. The experimental result shows that the MAP model and relative annealing algorithm are efficient enough to tackle the large-scale 3D reconstruction problem, and it can be extended to solve other similar SFM parameters estimation problem as well.
Applying Secure Data Aggregation techniques for a Structure and Density Independent Group Based Key Management Protocol

In many applications of Wireless Sensor Networks a Sink is interested in aggregated data instead of exact values from all sensors. To send aggregated data, it is also helpful to reduce the amount of data to be transmitted and thereby conserve energy. Indeed current in-network aggregation schemes are helpful to conserve energy but they are designed without considering possible security issues related to data privacy. Often we find wireless sensor networks designed with neighbouring nodes sharing keys or with decryption at aggregator nodes. In either situation the potential for aggregator nodes to be physically compromised means data privacy is at high risk. Therefore secure data aggregation is desirable where data can be aggregated without the need for decryption at aggregator nodes. Aggregation becomes especially challenging if end-to-end privacy between a source and a destination (sink or group leader) is required. In this paper we extend our Structure and Density Independent Group Based Key Management Protocol with the additional feature of secure data aggregation to provide better data privacy to every single node in a large scale Wireless Sensor Network.
Data Mining Technology Applications in Tobacco Commercial Enterprise

The wide application of information technology has greatly improve the work efficiency but also caused a large and complex data accumulation. How to get the valuable information from vast amounts of data are the key issues in data processing. This paper studied the application of data mining technology in tobacco commercial enterprise from three aspects: market demand forecasting, customer relationship management and historical data processing. Analysis of how to use data mining technology to make full use of large amounts of data to provide a basis for tobacco commercial enterprise’s decision-making.
Parameterized Complexity of Geometric Problems

This paper surveys parameterized complexity results for hard geometric algorithmic problems. It includes fixed-parameter tractable problems in graph drawing, geometric graphs, geometric covering and several other areas, together with an overview of the algorithmic techniques used. Fixed-parameter intractability results are surveyed as well. Finally, we give some directions for future research.
Remote Acoustic Monitoring of Thin Laminates

Understanding the change in material properties in time is necessary for in-service diagnosis of structures and prevention of accidents. Therefore, a new experimental technique for evaluating Young’s (or elastic) modulus of a vibrating thin sheet from a dynamic measurement is presented. The technique utilizes bending resonance from a remote acoustic excitation. Equations relating the natural frequencies to the mechanical properties are obtained, and Young’s modulus is subsequently determined experimentally using the implemented dynamic measurement method. Young’s modulus values from the dynamic test are then compared with those (static) obtained by a standard tensile test and those obtained by the theory of laminated materials. The proposed technique appears relatively simple and is applied in this paper to laminates initially having no (or negligible) bending stiffness, and used in packaging industries. This work emphasizes the feasibility of a remote condition monitoring of components in-service by evaluating changes in the material properties.
Study of Liquid Metals by Electrostatic Levitation

With the development of bulk metallic glasses (BMG) in recent years, more and more scientists in solid state physics are trying to understand the mechanism of glass-formation in terms of thermodynamics and kinetics, while engineers in metallurgy are trying different compositions and processes to improve the mechanical properties of BMGs and their composites. Glasses are nothing but frozen liquids. So far most of the studies of metallic glasses have been below the glass transition temperature because molten metallic liquids are chemically reactive with the container walls. For this reason, we used the Electrostatic Levitation (ESL) method that was developed by Dr. Won-Kyu Rhim. In this thesis, the instrumentation of the ESL is described. Discussion on the advantages and disadvantages of ESL is given by comparing with the other levitation methods. Because of the advantage in sample position stability over all the other levitation methods, the ESL facility at Caltech is uniquely capable of measuring the viscosity and thermophysical properties of liquid metals in the undercooled temperature range. The ESL was further improved at Caltech to reduce temperature gradients on a sample and increase the stability of the sample positioning with a tetrahedral laser heating system. Using such an improved ESL, thermophysical properties of some evaporative metallic liquids such as Ti and silicon-germanium alloys have been successfully studied and mass loss as well as composition changes could be accounted for. Several BMGs developed at Johnson group at Caltech have been studied using ESL. Among the liquid thermodynamics and kinetic properties of interest, special attention has been paid on to measurements of the TTT curve, viscosity, and volume changes with temperature. These data give useful insight on the glass-forming mechanism. Through these studies, guidelines in the search for good ductile metallic glass-formers have emerged. Discussing these guidelines is an important part of this thesis. Finally, we discuss an investigation to understand observed hysteresis in the viscosity and the so-called threshold temperature that has been observed in some of the best glass-forming metallic liquids. We conclude this investigation with a hypothesis of a liquid-to-liquid phase transition that occurs above liquidus temperatures in several systems that we have studied.
Identification and Characterization of the Iron Regulatory Element in the Ferritin Gene of a Plant (Soybean)*

Iron increases ferritin synthesis, targeting plant DNA and animal mRNA. The ferritin promoter in plants has not been identified, in contrast to the ferritin promoter and mRNA iron-responsive element (IRE) in animals. The soybean leaf, a natural tissue for ferritin expression, and DNA, with promoter deletions and luciferase or glucuronidase reporters, delivered with particle bombardment, were used to show that an 86-base pair fragment (iron regulatory element (FRE)) controlled iron-mediated derepression of the ferritin gene. Mutagenesis with linkers of random sequence detected two subdomains separated by 21 base pairs. FRE has no detectable homology to the animal IRE or to known promoters in DNA and bound atrans-acting factor in leaf cell extracts. FRE/factor binding was abrogated by increased tissue iron, in analogy to mRNA (IRE)/iron regulatory protein in animals. Maximum ferritin derepression was obtained with 50 μm iron citrate (1:10) or 500 μm iron citrate (1:1) but Fe-EDTA was ineffective, although the leaf iron concentration was increased; manganese, zinc, and copper had no effect. The basis for different responses in ferritin expression to different iron complexes, as well as the significance of using DNA but not mRNA as an iron regulatory target in plants, remain unknown.