13,282 research outputs found
Anveshak - A Groundtruth Generation Tool for Foreground Regions of Document Images
We propose a graphical user interface based groundtruth generation tool in
this paper. Here, annotation of an input document image is done based on the
foreground pixels. Foreground pixels are grouped together with user interaction
to form labeling units. These units are then labeled by the user with the user
defined labels. The output produced by the tool is an image with an XML file
containing its metadata information. This annotated data can be further used in
different applications of document image analysis.Comment: Accepted in DAR 201
Determination of the Gyrotropic Characteristics of Hexaferrite Ceramics From 75 to 600 GHz
(c) 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works
High Fidelity Tape Transfer Printing Based On Chemically Induced Adhesive Strength Modulation
Transfer printing, a two-step process (i.e. picking up and printing) for heterogeneous integration, has been widely exploited for the fabrication of functional electronics system. To ensure a reliable process, strong adhesion for picking up and weak or no adhesion for printing are required. However, it is challenging to meet the requirements of switchable stamp adhesion. Here we introduce a simple, high fidelity process, namely tape transfer printing(TTP), enabled by chemically induced dramatic modulation in tape adhesive strength. We describe the working mechanism of the adhesion modulation that governs this process and demonstrate the method by high fidelity tape transfer printing several types of materials and devices, including Si pellets arrays, photodetector arrays, and electromyography (EMG) sensors, from their preparation substrates to various alien substrates. High fidelity tape transfer printing of components onto curvilinear surfaces is also illustrated
Recommended from our members
Ultrahigh power and energy density in partially ordered lithium-ion cathode materials
The rapid market growth of rechargeable batteries requires electrode materials that combine high power and energy and are made from earth-abundant elements. Here we show that combining a partial spinel-like cation order and substantial lithium excess enables both dense and fast energy storage. Cation overstoichiometry and the resulting partial order is used to eliminate the phase transitions typical of ordered spinels and enable a larger practical capacity, while lithium excess is synergistically used with fluorine substitution to create a high lithium mobility. With this strategy, we achieved specific energies greater than 1,100 Wh kg–1 and discharge rates up to 20 A g–1. Remarkably, the cathode materials thus obtained from inexpensive manganese present a rare case wherein an excellent rate capability coexists with a reversible oxygen redox activity. Our work shows the potential for designing cathode materials in the vast space between fully ordered and disordered compounds
Reduction of the size of datasets by using evolutionary feature selection: the case of noise in a modern city
Smart city initiatives have emerged to mitigate the negative effects of a very fast growth of urban areas. Most of the population in our cities are exposed to high levels of noise that generate discomfort and different health problems. These issues may be mitigated by applying different smart cities solutions, some of them require high accurate noise information to provide the best quality of serve possible. In this study, we have designed a machine learning approach based on genetic algorithms to analyze noise data captured in the university campus. This method reduces the amount of data required to classify the noise by addressing a feature selection optimization problem. The experimental results have shown that our approach improved the accuracy in 20% (achieving an accuracy of 87% with a reduction of up to 85% on the original dataset).Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
This research has been partially funded by the Spanish MINECO and FEDER projects TIN2016-81766-REDT (http://cirti.es), and TIN2017-88213-R (http://6city.lcc.uma.es)
Hemodynamic Measurement Using Four-Dimensional Phase-Contrast MRI: Quantification of Hemodynamic Parameters and Clinical Applications
Recent improvements have been made to the use of time-resolved, three-dimensional phase-contrast (PC) magnetic resonance imaging (MRI), which is also named four-dimensional (4D) PC-MRI or 4D flow MRI, in the investigation of spatial and temporal variations in hemodynamic features in cardiovascular blood flow. The present article reviews the principle and analytical procedures of 4D PC-MRI. Various fluid dynamic biomarkers for possible clinical usage are also described, including wall shear stress, turbulent kinetic energy, and relative pressure. Lastly, this article provides an overview of the clinical applications of 4D PC-MRI in various cardiovascular regions.113Ysciescopuskc
Super-Resolved Enhancement of a Single Image and Its Application in Cardiac MRI
Super-resolved image enhancement is of great importance in medical imaging. Conventional methods often require multiple low resolution (LR) images from different views of the same object or learning from large amount of training datasets to achieve success. However, in real clinical environments, these prerequisites are rarely fulfilled. In this paper, we present a self-learning based method to perform superresolution (SR) from a single LR input. The mappings between the given LR image and its downsampled versions are modeled using support vector regression on features extracted from sparse coded dictionaries, coupled with dual-tree complex wavelet transform based denoising. We demonstrate the efficacy of our method in application of cardiac MRI enhancement. Both quantitative and qualitative results show that our SR method is able to preserve fine textural details that can be corrupted by noise, and therefore can maintain crucial diagnostic information
An Exact No Free Lunch Theorem for Community Detection
A precondition for a No Free Lunch theorem is evaluation with a loss function
which does not assume a priori superiority of some outputs over others. A
previous result for community detection by Peel et al. (2017) relies on a
mismatch between the loss function and the problem domain. The loss function
computes an expectation over only a subset of the universe of possible outputs;
thus, it is only asymptotically appropriate with respect to the problem size.
By using the correct random model for the problem domain, we provide a
stronger, exact No Free Lunch theorem for community detection. The claim
generalizes to other set-partitioning tasks including core/periphery
separation, -clustering, and graph partitioning. Finally, we review the
literature of proposed evaluation functions and identify functions which
(perhaps with slight modifications) are compatible with an exact No Free Lunch
theorem
Improved prediction of RNA secondary structure by integrating the free energy model with restraints derived from experimental probing data.
PublishedEvaluation StudiesJournal ArticleResearch Support, Non-U.S. Gov'tRecently, several experimental techniques have emerged for probing RNA structures based on high-throughput sequencing. However, most secondary structure prediction tools that incorporate probing data are designed and optimized for particular types of experiments. For example, RNAstructure-Fold is optimized for SHAPE data, while SeqFold is optimized for PARS data. Here, we report a new RNA secondary structure prediction method, restrained MaxExpect (RME), which can incorporate multiple types of experimental probing data and is based on a free energy model and an MEA (maximizing expected accuracy) algorithm. We first demonstrated that RME substantially improved secondary structure prediction with perfect restraints (base pair information of known structures). Next, we collected structure-probing data from diverse experiments (e.g. SHAPE, PARS and DMS-seq) and transformed them into a unified set of pairing probabilities with a posterior probabilistic model. By using the probability scores as restraints in RME, we compared its secondary structure prediction performance with two other well-known tools, RNAstructure-Fold (based on a free energy minimization algorithm) and SeqFold (based on a sampling algorithm). For SHAPE data, RME and RNAstructure-Fold performed better than SeqFold, because they markedly altered the energy model with the experimental restraints. For high-throughput data (e.g. PARS and DMS-seq) with lower probing efficiency, the secondary structure prediction performances of the tested tools were comparable, with performance improvements for only a portion of the tested RNAs. However, when the effects of tertiary structure and protein interactions were removed, RME showed the highest prediction accuracy in the DMS-accessible regions by incorporating in vivo DMS-seq data.National Key Basic Research Program of China [2012CB316503]; National High-Tech Research and Development Program of China [2014AA021103]; National Natural Science Foundation of China [31271402]; Tsinghua University Initiative Scientific Research Program [2014z21045]; Hong Kong Research Grants Council Early Career Scheme [419612 to K.Y.]; National Science Foundation [1339282 to D.H.M.]; Computing Platform of the National Protein Facilities (Tsinghua University). Funding for open access charge: National Natural Science Foundation of China [31271402]
Osteogenesis evaluation of duck’s feet derived collagen/hydroxyapatite sponges immersed in dexamethasone
Background: The aim of this study was to investigate the osteogenesis effects of DC and DC/HAp sponge immersed in without and with dexamethasone.
Methods: The experimental groups in this study were DC and DC/HAp sponge immersed in without dexamethasone (Dex(â )DC and Dex(â )-DC/HAp group) and with dexamethasone (Dex(+)-DC and Dex(+)-DC/HAp group). We characterized DC and DC/HAp sponge using compressive strength, scanning electron microscopy (SEM). Also, osteogenic differentiation of BMSCs on sponge (Dex(â )DC, Dex(â )-DC/HAp, Dex(+)-DC and Dex(+)-DC/HAp group) was assessed by SEM, 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazoliumbromide (MTT) assay, alkaline phosphatase (ALP) activity assay and reverse transcription-PCR (RT-PCR).
Results: In this study, we assessed osteogenic differentiation of BMSCs on Duckâ s feet-derived collagen (DC)/ HAp sponge immersed with dexamethasone Dex(+)-DC/HAp. These results showed that Dex(+)-DC/HAp group increased cell proliferation and osteogenic differentiation of BMSCs during 28 days.
Conclusion: From these results, Dex(+)-DC/HAp can be envisioned as a potential biomaterial for bone regeneration applications.This work was supported by Technology Commercialization Support Program [grant number 814005-03-3-HD020], Ministry for Food, Agriculture, Forestry and Fisheries (MIFAFF).info:eu-repo/semantics/publishedVersio
- …
