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Yong Zhang, Meng Joo Er, Rui Zhao, Mahardhika Pratama
Multidocument summarization has gained popularity in many real world applications because vital information can be extracted within a short time. Extractive summarization aims to generate a summary of a document or a set of documents by ranking sentences and the ranking results rely heavily on the quality of sentence features. However, almost all previous algorithms require hand-crafted features for sentence representation. In this paper, we leverage on word embedding to represent sentences so as to avoid the intensive labor in feature engineering...
November 28, 2016: IEEE Transactions on Cybernetics
Nian Liu, Junwei Han, Tianming Liu, Xuelong Li
Eye movements in the case of freely viewing natural scenes are believed to be guided by local contrast, global contrast, and top-down visual factors. Although a lot of previous works have explored these three saliency cues for several years, there still exists much room for improvement on how to model them and integrate them effectively. This paper proposes a novel computation model to predict eye fixations, which adopts a multiresolution convolutional neural network (Mr-CNN) to infer these three types of saliency cues from raw image data simultaneously...
November 29, 2016: IEEE Transactions on Neural Networks and Learning Systems
Sunil Jaiswal, Lu Fang, Vinit Jakhetiya, Jiahao Pang, Klaus Mueller, Oscar C Au
Color filter array (CFA) interpolation, or 3-band demosaicking, is a process of interpolating the missing color samples in each band to reconstruct a full color image. In this paper, we are concerned with the challenging problem of multispectral demosaicking, where each band is significantly undersampled due to the increment in the number of bands. Specifically, we demonstrate a frequency-domain analysis of the subsampled color-difference signal and observe that the conventional assumption of highly correlated spectral bands for estimating undersampled components is not precise...
December 1, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Qingshan Liu, Jiankang Deng, Jing Yang, Guangcan Liu, Dacheng Tao
Cascade regression is a popular face alignment approach, and it has achieved good performances on the wild databases. However, it depends heavily on local features in estimating reliable landmark locations and therefore suffers from corrupted images, such as images with occlusion, which often exists in real-world face images. In this paper, we present a new adaptive cascade regression model for robust face alignment. In each iteration, the shape-indexed appearance is introduced to estimate the occlusion level of each landmark, and each landmark is then weighted according to its estimated occlusion level...
December 1, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
L Shi, E J Valeo, B J Tobias, G J Kramer, L Hausammann, W M Tang, M Chen
A Synthetic Diagnostics Platform (SDP) for fusion plasmas has been developed which provides state of the art synthetic reflectometry, beam emission spectroscopy, and Electron Cyclotron Emission (ECE) diagnostics. Interfaces to the plasma simulation codes GTC, XGC-1, GTS, and M3D-C(1) are provided, enabling detailed validation of these codes. In this paper, we give an overview of SDP's capabilities, and introduce the synthetic diagnostic modules. A recently developed synthetic ECE Imaging module which self-consistently includes refraction, diffraction, emission, and absorption effects is discussed in detail...
November 2016: Review of Scientific Instruments
Magdalena Markowicz-Piasecka, Kristiina Maria Huttunen, Łukasz Mateusiak, Elżbieta Mikiciuk-Olasik, Joanna Sikora
Metformin, a synthetic biguanide, is currently one of the most frequently recommended medications for type 2 diabetes treatment around the world. In this review, we present the latest discoveries in the pharmacokinetics of metformin, especially the role of transporters (e.g. Organic Cation Transporters OCTs, Multidrug and Toxin Extrusion transporters MATE) in oral absorption, distribution, elimination and biochemical effects of metformin in humans. We also review the associations between genetic variations of metformin transporters, their pharmacokinetics and drug efficacy or drug responses...
December 1, 2016: Current Pharmaceutical Design
Angélica Atehortúa, Maria A Zuluaga, Juan D García, Eduardo Romero
PURPOSE: Accurate measurement of the right ventricle (RV) volume is important for the assessment of the ventricular function and a biomarker of the progression of any cardiovascular disease. However, the high RV variability makes difficult a proper delineation of the myocardium wall. This paper introduces a new automatic method for segmenting the RV volume from short axis cardiac magnetic resonance (MR) images by a salient analysis of temporal and spatial observations. METHODS: The RV volume estimation starts by localizing the heart as the region with the most coherent motion during the cardiac cycle...
December 2016: Medical Physics
Minghui Deng, Renping Yu, Li Wang, Feng Shi, Pew-Thian Yap, Dinggang Shen
PURPOSE: Segmentation of brain magnetic resonance (MR) images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) is crucial for brain structural measurement and disease diagnosis. Learning-based segmentation methods depend largely on the availability of good training ground truth. However, the commonly used 3T MR images are of insufficient image quality and often exhibit poor intensity contrast between WM, GM, and CSF. Therefore, they are not ideal for providing good ground truth label data for training learning-based methods...
December 2016: Medical Physics
Ming Tu, Alan Wisler, Visar Berisha, Julie M Liss
State-of-the-art automatic speech recognition (ASR) engines perform well on healthy speech; however recent studies show that their performance on dysarthric speech is highly variable. This is because of the acoustic variability associated with the different dysarthria subtypes. This paper aims to develop a better understanding of how perceptual disturbances in dysarthric speech relate to ASR performance. Accurate ratings of a representative set of 32 dysarthric speakers along different perceptual dimensions are obtained and the performance of a representative ASR algorithm on the same set of speakers is analyzed...
November 2016: Journal of the Acoustical Society of America
Michele Scaravilli, Giuseppe Castaldi, Andrea Cusano, Vincenzo Galdi
In this paper, we investigate the possibility to excite Bloch surface waves (BSWs) on the tip of single-mode optical fibers. Within this framework, after exploring an idealized, proof-of-principle grating-coupling-based scheme for on-tip excitation of BSWs, we focus on an alternative configuration that is more robust with respect to fabrication-related non-idealities. Subsequently, with a view towards label-free chemical and biological sensing, we present a specific design aimed at enhancing the sensitivity (in terms of wavelength shift) of the arising resonance with respect to changes in the refractive properties of the surrounding environment...
November 28, 2016: Optics Express
Woon Cho, Jinbeum Jang, Andreas Koschan, Mongi A Abidi, Joonki Paik
A fundamental limitation of hyperspectral imaging is the inter-band misalignment correlated with subject motion during data acquisition. One way of resolving this problem is to assess the alignment quality of hyperspectral image cubes derived from the state-of-the-art alignment methods. In this paper, we present an automatic selection framework for the optimal alignment method to improve the performance of face recognition. Specifically, we develop two qualitative prediction models based on: 1) a principal curvature map for evaluating the similarity index between sequential target bands and a reference band in the hyperspectral image cube as a full-reference metric; and 2) the cumulative probability of target colors in the HSV color space for evaluating the alignment index of a single sRGB image rendered using all of the bands of the hyperspectral image cube as a no-reference metric...
November 28, 2016: Optics Express
Hong Li, Enhua Wu, Wen Wu
Boundary priors have been extensively studied in salient region detection problems over the past few decades. Although several models based on the boundary prior have achieved good detection performance, there still exist drawbacks. The most common one is that they fail to detect the salient object when the background is complex or the salient object touches the image boundary. In this paper, we propose a novel model to detect the salient region. It is based on background cues and one complementary cue, that is, a foreground cue...
December 1, 2016: Journal of the Optical Society of America. A, Optics, Image Science, and Vision
Ayush Singhal, Michael Simmons, Zhiyong Lu
The practice of precision medicine will ultimately require databases of genes and mutations for healthcare providers to reference in order to understand the clinical implications of each patient's genetic makeup. Although the highest quality databases require manual curation, text mining tools can facilitate the curation process, increasing accuracy, coverage, and productivity. However, to date there are no available text mining tools that offer high-accuracy performance for extracting such triplets from biomedical literature...
November 2016: PLoS Computational Biology
Tianci Song, Yan Wang, Wei Du, Sha Cao, Yuan Tian, Yanchun Liang
Breast cancer histologic grade represents the morphological assessment of the tumor's malignancy and aggressiveness, which is vital in clinically planning treatment and estimating prognosis for patients. Therefore, the prediction of breast cancer grade can markedly elevate the detection of early breast cancer and efficiently guide its treatment. With the advent of high-throughput profiling technology, a large number of data of different types are rapidly generated, and each data provides its unique biological insight...
November 29, 2016: Journal of Bioinformatics and Computational Biology
Peng-Bo Zhang, Zhi-Xin Yang
The AdaBoost algorithm is a popular ensemble method that combines several weak learners to boost generalization performance. However, conventional AdaBoost.RT algorithms suffer from the limitation that the threshold value must be manually specified rather than chosen through a self-adaptive mechanism, which cannot guarantee a result in an optimal model for general cases. In this paper, we present a generic AdaBoost framework with robust threshold mechanism and structural optimization on regression problems...
November 24, 2016: IEEE Transactions on Cybernetics
Kaimo Hu, Dong-Ming Yan, David Bommes, Pierre Alliez, Bedrich Benes
The typical goal of surface remeshing consists in finding a mesh that is (1) geometrically faithful to the original geometry, (2) as coarse as possible to obtain a low-complexity representation and (3) free of bad elements that would hamper the desired application. In this paper, we design an algorithm to address all three optimization goals simultaneously. The user specifies desired bounds on approximation error , minimal interior angle and maximum mesh complexity N (number of vertices). Since such a desired mesh might not even exist, our optimization framework treats only the approximation error bound as a hard constraint and the other two criteria as optimization goals...
November 24, 2016: IEEE Transactions on Visualization and Computer Graphics
Mingxia Liu, Jun Zhang, Pew-Thian Yap, Dinggang Shen
Effectively utilizing incomplete multi-modality data for the diagnosis of Alzheimer's disease (AD) and its prodrome (i.e., mild cognitive impairment, MCI) remains an active area of research. Several multi-view learning methods have been recently developed for AD/MCI diagnosis by using incomplete multi-modality data, with each view corresponding to a specific modality or a combination of several modalities. However, existing methods usually ignore the underlying coherence among views, which may lead to sub-optimal learning performance...
November 16, 2016: Medical Image Analysis
Lenka Zdeborová, Pan Zhang, Hai-Jun Zhou
Decycling and dismantling of complex networks are underlying many important applications in network science. Recently these two closely related problems were tackled by several heuristic algorithms, simple and considerably sub-optimal, on the one hand, and involved and accurate message-passing ones that evaluate single-node marginal probabilities, on the other hand. In this paper we propose a simple and extremely fast algorithm, CoreHD, which recursively removes nodes of the highest degree from the 2-core of the network...
November 29, 2016: Scientific Reports
Jack Lanchantin, Ritambhara Singh, Beilun Wang, Yanjun Qi
Deep neural network (DNN) models have recently obtained state-of-the-art prediction accuracy for the transcription factor binding (TFBS) site classification task. However, it remains unclear how these approaches identify meaningful DNA sequence signals and give insights as to why TFs bind to certain locations. In this paper, we propose a toolkit called the Deep Motif Dashboard (DeMo Dashboard) which provides a suite of visualization strategies to extract motifs, or sequence patterns from deep neural network models for TFBS classification...
2016: Pacific Symposium on Biocomputing
Fabio Staderini, Caterina Foppa, Alessio Minuzzo, Benedetta Badii, Etleva Qirici, Giacomo Trallori, Beatrice Mallardi, Gabriele Lami, Giuseppe Macrì, Andrea Bonanomi, Siro Bagnoli, Giuliano Perigli, Fabio Cianchi
Laparoscopic rectal surgery has demonstrated its superiority over the open approach, however it still has some technical limitations that lead to the development of robotic platforms. Nevertheless the literature on this topic is rapidly expanding there is still no consensus about benefits of robotic rectal cancer surgery over the laparoscopic one. For this reason a review of all the literature examining robotic surgery for rectal cancer was performed. Two reviewers independently conducted a search of electronic databases (PubMed and EMBASE) using the key words "rectum", "rectal", "cancer", "laparoscopy", "robot"...
November 15, 2016: World Journal of Gastrointestinal Oncology
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