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https://www.readbyqxmd.com/read/28604832/insects-and-associated-arthropods-analyzed-during-medicolegal-death-investigations-in-harris-county-texas-usa-january-2013-april-2016
#1
Michelle R Sanford
The application of insect and arthropod information to medicolegal death investigations is one of the more exacting applications of entomology. Historically limited to homicide investigations, the integration of full time forensic entomology services to the medical examiner's office in Harris County has opened up the opportunity to apply entomology to a wide variety of manner of death classifications and types of scenes to make observations on a number of different geographical and species-level trends in Harris County, Texas, USA...
2017: PloS One
https://www.readbyqxmd.com/read/28600256/a-graphical-model-for-online-auditory-scene-modulation-using-eeg-evidence-for-attention
#2
Marzieh Haghighi, Mohammad Moghadamfalahi, Murat Akcakaya, Deniz Erdogmus
Recent findings indicate that brain interfaces have the potential to enable attention-guided auditory scene analysis and manipulation in applications such as hearing aids and augmented/ virtual environments. Specifically, noninvasively acquired electroencephalography (EEG) signals have been demonstrated to carry some evidence regarding which of multiple synchronous speech waveforms the subject attends to. In this paper we demonstrate that: (1) using data- and model-driven cross-correlation features yield competitive binary auditory attention classification results with at most 20 seconds of EEG from 16 channels or even a single well-positioned channel; (2) a model calibrated using equal-energy speech waveforms competing for attention could perform well on estimating attention in closed-loop unbalancedenergy speech waveform situations, where the speech amplitudes are modulated by the estimated attention posterior probability distribution; (3) such a model would perform even better if it is corrected (linearly, in this instance) based on EEG evidence dependency on speech weights in the mixture; (4) calibrating a model based on population EEG could result in acceptable performance for new individuals/users; therefore EEG-based auditory attention classifiers may generalize across individuals, leading to reduced or eliminated calibration time and effort...
June 6, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28592372/scene-time-interval-and-good-neurological-recovery-in-out-of-hospital-cardiac-arrest
#3
Ki Hong Kim, Sang Do Shin, Kyoung Jun Song, Young Sun Ro, Yu Jin Kim, Ki Jeong Hong, Joo Jeong
OBJECTIVES: It is unclear whether scene time interval (STI) is associated with better neurological recovery in the emergency medical service (EMS) system with intermediate service level. METHODS: Adult out-of-hospital cardiac arrest (OHCA) patients with presumed cardiac etiology (2012 to 2014) were analyzed, excluding patients not-resuscitated, occurred in ambulance/medical/nursing facility, unknown STI or extremely longer STI (>60 min), and unknown outcomes...
May 29, 2017: American Journal of Emergency Medicine
https://www.readbyqxmd.com/read/28493106/human-classifier-observers-can-deduce-task-solely-from-eye-movements
#4
Brett Bahle, Mark Mills, Michael D Dodd
Computer classifiers have been successful at classifying various tasks using eye movement statistics. However, the question of human classification of task from eye movements has rarely been studied. Across two experiments, we examined whether humans could classify task based solely on the eye movements of other individuals. In Experiment 1, human classifiers were shown one of three sets of eye movements: Fixations, which were displayed as blue circles, with larger circles meaning longer fixation durations; Scanpaths, which were displayed as yellow arrows; and Videos, in which a neon green dot moved around the screen...
May 10, 2017: Attention, Perception & Psychophysics
https://www.readbyqxmd.com/read/28476562/a-novel-alignment-free-method-to-classify-protein-folding-types-by-combining-spectral-graph-clustering-with-chou-s-pseudo-amino-acid-composition
#5
Pooja Tripathi, Paras N Pandey
The present work employs pseudo amino acid composition (PseAAC) for encoding the protein sequences in their numeric form. Later this will be arranged in the similarity matrix, which serves as input for spectral graph clustering method. Spectral methods are used previously also for clustering of protein sequences, but they uses pair wise alignment scores of protein sequences, in similarity matrix. The alignment score depends on the length of sequences, so clustering short and long sequences together may not good idea...
May 3, 2017: Journal of Theoretical Biology
https://www.readbyqxmd.com/read/28475756/shared-states-using-mvpa-to-test-neural-overlap-between-self-focused-emotion-imagery-and-other-focused-emotion-understanding
#6
Suzanne Oosterwijk, Lukas Snoek, Mark Rotteveel, Lisa F Barrett, H Steven Scholte
The present study tested whether the neural patterns that support imagining "performing an action", "feeling a bodily sensation" or "being in a situation" are directly involved in understanding other people's actions, bodily sensations and situations. Subjects imagined the content of short sentences describing emotional actions, interoceptive sensations and situations (self-focused task), and processed scenes and focused on how the target person was expressing an emotion, what this person was feeling, and why this person was feeling an emotion (other-focused task)...
May 5, 2017: Social Cognitive and Affective Neuroscience
https://www.readbyqxmd.com/read/28454031/automatic-and-adaptive-paddy-rice-mapping-using-landsat-images-case-study-in-songnen-plain-in-northeast-china
#7
Bingwen Qiu, Difei Lu, Zhenghong Tang, Chongcheng Chen, Fengli Zou
Spatiotemporal explicit information on paddy rice distribution is essential for ensuring food security and sustainable environmental management. Paddy rice mapping algorithm through the Combined Consideration of Vegetation phenology and Surface water variations (CCVS) has been efficiently applied based on the 8day composites time series datasets. However, the great challenge for phenology-based algorithms introduced by unpromising data availability in middle/high spatial resolution imagery, such as frequent cloud cover and coarse temporal resolution, remained unsolved...
November 15, 2017: Science of the Total Environment
https://www.readbyqxmd.com/read/28436874/track-everything-limiting-prior-knowledge-in-online-multi-object-recognition
#8
Sebastien C Wong, Victor Stamatescu, Adam Gatt, David Kearney, Ivan Lee, Mark D McDonnell
This paper addresses the problem of online tracking and classification of multiple objects in an image sequence. Our proposed solution is to first track all objects in the scene without relying on object-specific prior knowledge, which in other systems can take the form of hand-crafted features or user-based track initialization. We then classify the tracked objects with a fastlearning image classifier that is based on a shallow convolutional neural network architecture and demonstrate that object recognition improves when this is combined with object state information from the tracking algorithm...
April 24, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28435902/emergency-medical-service-personnel-need-to-improve-knowledge-and-attitude-regarding-prehospital-sepsis-care
#9
Joongmin Park, Sung Yeon Hwang, Tae Gun Shin, Ik Joon Jo, Hee Yoon, Tae Rim Lee, Won Chul Cha, Min Seob Sim
OBJECTIVE: We aimed to evaluate the knowledge and attitudes of emergency medical service (EMS) personnel pertaining to sepsis. We also compared EMS personnel's knowledge of sepsis and their intention to engage in prehospital sepsis management. METHODS: The survey was conducted during education conferences for EMS personnel in December 2013 and January 2015 in Seoul, Korea. The questionnaire composed of 10 questions relevant to sepsis, was distributed on-scene, and was retrieved by investigators after the conference...
March 2017: Clinical and Experimental Emergency Medicine
https://www.readbyqxmd.com/read/28410105/dynamic-textures-modeling-via-joint-video-dictionary-learning
#10
Xian Wei, Yuanxiang Li, Hao Shen, Fang Chen, Martin Kleinsteuber, Zhongfeng Wang
Video representation is an important and challenging task in the computer vision community. In this paper, we consider the problem of modeling and classifying video sequences of dynamic scenes which could be modeled in a dynamic textures (DT) framework. At first, we assume that image frames of a moving scene can be modeled as a Markov random process. We propose a sparse coding framework, named joint video dictionary learning (JVDL), to model a video adaptively. By treating the sparse coefficients of image frames over a learned dictionary as the underlying "states", we learn an efficient and robust linear transition matrix between two adjacent frames of sparse events in time series...
April 6, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28401988/a-rapid-nuclear-staining-test-using-cationic-dyes-contributes-to-efficient-str-analysis-of-telogen-hair-roots
#11
So-Yeon Lee, Eun-Ju Ha, Seung-Kyun Woo, So-Min Lee, Kyung-Hee Lim, Yong-Bin Eom
Telogen hairs presented in the crime scene are commonly encountered as trace evidence. However, short tandem repeat (STR) profiling of the hairs currently have low and limited use due to poor success rate. To increase the success rate of STR profiling of telogen hairs, we developed a rapid and cost-effective method to estimate the number of nuclei in the hair roots. Five cationic dyes, Methyl green (MG), Harris hematoxylin (HH), Methylene blue (MB), Toluidine blue (TB) and Safranin O (SO) were evaluated in this study...
April 12, 2017: Electrophoresis
https://www.readbyqxmd.com/read/28399149/sequential-monte-carlo-guided-ensemble-tracking
#12
Yuru Wang, Qiaoyuan Liu, Longkui Jiang, Minghao Yin, Shengsheng Wang
A great deal of robustness is allowed when visual tracking is considered as a classification problem. This paper combines a finite number of weak classifiers in a SMC framework as a strong classifier. The time-varying ensemble parameters (confidence of weak classifiers) are regarded as sequential arriving states and their posterior distribution is estimated in a Bayesian manner. Therefore, both the adaptiveness and stability are kept for the ensemble classification in handling scene changes and target deformation...
2017: PloS One
https://www.readbyqxmd.com/read/28387587/multiple-object-tracking-as-a-tool-for-parametrically-modulating-memory-reactivation
#13
Jordan Poppenk, Kenneth A Norman
Converging evidence supports the "nonmonotonic plasticity" hypothesis, which states that although complete retrieval may strengthen memories, partial retrieval weakens them. Yet, the classic experimental paradigms used to study effects of partial retrieval are not ideally suited to doing so, because they lack the parametric control needed to ensure that the memory is activated to the appropriate degree (i.e., that there is some retrieval but not enough to cause memory strengthening). Here, we present a novel procedure designed to accommodate this need...
April 7, 2017: Journal of Cognitive Neuroscience
https://www.readbyqxmd.com/read/28343000/evidence-for-similar-patterns-of-neural-activity-elicted-by-picture-and-word-based-representations-of-natural-scenes
#14
Manoj Kumar, Kara D Federmeier, Li Fei-Fei, Diane M Beck
A long-standing core question in cognitive science is whether different modalities and representation types (pictures, words, sounds, etc.) access a common store of semantic information. Although different input types have been shown to activate a shared network of brain regions, this does not necessitate that there is a common representation, as the neurons in these regions could still differentially process the different modalities. However, multi-voxel pattern analysis can be used to assess whether, e.g...
March 22, 2017: NeuroImage
https://www.readbyqxmd.com/read/28336425/characterizing-object-and-position-dependent-response-profiles-to-uni-and-bilateral-stimulus-configurations-in-human-higher-visual-cortex-a-7t-fmri-study
#15
Joel Reithler, Judith C Peters, Rainer Goebel
Visual scenes are initially processed via segregated neural pathways dedicated to either of the two visual hemifields. Although higher-order visual areas are generally believed to utilize invariant object representations (abstracted away from features such as stimulus position), recent findings suggest they retain more spatial information than previously thought. Here, we assessed the nature of such higher-order object representations in human cortex using high-resolution fMRI at 7T, supported by corroborative 3T data...
March 21, 2017: NeuroImage
https://www.readbyqxmd.com/read/28333644/random-forest-classifier-for-zero-shot-learning-based-on-relative-attribute
#16
Yuhu Cheng, Xue Qiao, Xuesong Wang, Qiang Yu
For the zero-shot image classification with relative attributes (RAs), the traditional method requires that not only all seen and unseen images obey Gaussian distribution, but also the classifications on testing samples are made by maximum likelihood estimation. We therefore propose a novel zero-shot image classifier called random forest based on relative attribute. First, based on the ordered and unordered pairs of images from the seen classes, the idea of ranking support vector machine is used to learn ranking functions for attributes...
March 21, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28316563/a-saccade-based-framework-for-real-time-motion-segmentation-using-event-based-vision-sensors
#17
Abhishek Mishra, Rohan Ghosh, Jose C Principe, Nitish V Thakor, Sunil L Kukreja
Motion segmentation is a critical pre-processing step for autonomous robotic systems to facilitate tracking of moving objects in cluttered environments. Event based sensors are low power analog devices that represent a scene by means of asynchronous information updates of only the dynamic details at high temporal resolution and, hence, require significantly less calculations. However, motion segmentation using spatiotemporal data is a challenging task due to data asynchrony. Prior approaches for object tracking using neuromorphic sensors perform well while the sensor is static or a known model of the object to be followed is available...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28294963/voxel-based-neighborhood-for-spatial-shape-pattern-classification-of-lidar-point-clouds-with-supervised-learning
#18
Victoria Plaza-Leiva, Jose Antonio Gomez-Ruiz, Anthony Mandow, Alfonso GarcĂ­a-Cerezo
Improving the effectiveness of spatial shape features classification from 3D lidar data is very relevant because it is largely used as a fundamental step towards higher level scene understanding challenges of autonomous vehicles and terrestrial robots. In this sense, computing neighborhood for points in dense scans becomes a costly process for both training and classification. This paper proposes a new general framework for implementing and comparing different supervised learning classifiers with a simple voxel-based neighborhood computation where points in each non-overlapping voxel in a regular grid are assigned to the same class by considering features within a support region defined by the voxel itself...
March 15, 2017: Sensors
https://www.readbyqxmd.com/read/28268456/emotion-classification-using-single-channel-scalp-eeg-recording
#19
Amir Jalilifard, Ednaldo Brigante Pizzolato, Md Kafiul Islam
Several studies have found evidence for corticolimbic Theta electroencephalographic (EEG) oscillation in the neural processing of visual stimuli perceived as fear or threatening scene. Recent studies showed that neural oscillations' patterns in Theta, Alpha, Beta and Gamma sub-bands play a main role in brain's emotional processing. The main goal of this study is to classify two different emotional states by means of EEG data recorded through a single-electrode EEG headset. Nineteen young subjects participated in an EEG experiment while watching a video clip that evoked three emotional states: neutral, relaxation and scary...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28241028/deploying-a-quantum-annealing-processor-to-detect-tree-cover-in-aerial-imagery-of-california
#20
Edward Boyda, Saikat Basu, Sangram Ganguly, Andrew Michaelis, Supratik Mukhopadhyay, Ramakrishna R Nemani
Quantum annealing is an experimental and potentially breakthrough computational technology for handling hard optimization problems, including problems of computer vision. We present a case study in training a production-scale classifier of tree cover in remote sensing imagery, using early-generation quantum annealing hardware built by D-wave Systems, Inc. Beginning within a known boosting framework, we train decision stumps on texture features and vegetation indices extracted from four-band, one-meter-resolution aerial imagery from the state of California...
2017: PloS One
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