Identifying city PV roof resource based on Gabor filter

NASA Astrophysics Data System (ADS)

Ruhang, Xu; Zhilin, Liu; Yong, Huang; Xiaoyu, Zhang

2017-06-01

To identify a city’s PV roof resources, the area and ownership distribution of residential buildings in an urban district should be assessed. To achieve this assessment, remote sensing data analysing is a promising approach. Urban building roof area estimation is a major topic for remote sensing image information extraction. There are normally three ways to solve this problem. The first way is pixel-based analysis, which is based on mathematical morphology or statistical methods; the second way is object-based analysis, which is able to combine semantic information and expert knowledge; the third way is signal-processing view method. This paper presented a Gabor filter based method. This result shows that the method is fast and with proper accuracy.

Score level fusion scheme based on adaptive local Gabor features for face-iris-fingerprint multimodal biometric

NASA Astrophysics Data System (ADS)

He, Fei; Liu, Yuanning; Zhu, Xiaodong; Huang, Chun; Han, Ye; Chen, Ying

2014-05-01

A multimodal biometric system has been considered a promising technique to overcome the defects of unimodal biometric systems. We have introduced a fusion scheme to gain a better understanding and fusion method for a face-iris-fingerprint multimodal biometric system. In our case, we use particle swarm optimization to train a set of adaptive Gabor filters in order to achieve the proper Gabor basic functions for each modality. For a closer analysis of texture information, two different local Gabor features for each modality are produced by the corresponding Gabor coefficients. Next, all matching scores of the two Gabor features for each modality are projected to a single-scalar score via a trained, supported, vector regression model for a final decision. A large-scale dataset is formed to validate the proposed scheme using the Facial Recognition Technology database-fafb and CASIA-V3-Interval together with FVC2004-DB2a datasets. The experimental results demonstrate that as well as achieving further powerful local Gabor features of multimodalities and obtaining better recognition performance by their fusion strategy, our architecture also outperforms some state-of-the-art individual methods and other fusion approaches for face-iris-fingerprint multimodal biometric systems.

Information Theory for Gabor Feature Selection for Face Recognition

NASA Astrophysics Data System (ADS)

Shen, Linlin; Bai, Li

2006-12-01

A discriminative and robust feature—kernel enhanced informative Gabor feature—is proposed in this paper for face recognition. Mutual information is applied to select a set of informative and nonredundant Gabor features, which are then further enhanced by kernel methods for recognition. Compared with one of the top performing methods in the 2004 Face Verification Competition (FVC2004), our methods demonstrate a clear advantage over existing methods in accuracy, computation efficiency, and memory cost. The proposed method has been fully tested on the FERET database using the FERET evaluation protocol. Significant improvements on three of the test data sets are observed. Compared with the classical Gabor wavelet-based approaches using a huge number of features, our method requires less than 4 milliseconds to retrieve a few hundreds of features. Due to the substantially reduced feature dimension, only 4 seconds are required to recognize 200 face images. The paper also unified different Gabor filter definitions and proposed a training sample generation algorithm to reduce the effects caused by unbalanced number of samples available in different classes.

Non-invasive health status detection system using Gabor filters based on facial block texture features.

PubMed

Shu, Ting; Zhang, Bob

2015-04-01

Blood tests allow doctors to check for certain diseases and conditions. However, using a syringe to extract the blood can be deemed invasive, slightly painful, and its analysis time consuming. In this paper, we propose a new non-invasive system to detect the health status (Healthy or Diseased) of an individual based on facial block texture features extracted using the Gabor filter. Our system first uses a non-invasive capture device to collect facial images. Next, four facial blocks are located on these images to represent them. Afterwards, each facial block is convolved with a Gabor filter bank to calculate its texture value. Classification is finally performed using K-Nearest Neighbor and Support Vector Machines via a Library for Support Vector Machines (with four kernel functions). The system was tested on a dataset consisting of 100 Healthy and 100 Diseased (with 13 forms of illnesses) samples. Experimental results show that the proposed system can detect the health status with an accuracy of 93 %, a sensitivity of 94 %, a specificity of 92 %, using a combination of the Gabor filters and facial blocks.

Ranging through Gabor logons-a consistent, hierarchical approach.

PubMed

Chang, C; Chatterjee, S

1993-01-01

In this work, the correspondence problem in stereo vision is handled by matching two sets of dense feature vectors. Inspired by biological evidence, these feature vectors are generated by a correlation between a bank of Gabor sensors and the intensity image. The sensors consist of two-dimensional Gabor filters at various scales (spatial frequencies) and orientations, which bear close resemblance to the receptive field profiles of simple V1 cells in visual cortex. A hierarchical, stochastic relaxation method is then used to obtain the dense stereo disparities. Unlike traditional hierarchical methods for stereo, feature based hierarchical processing yields consistent disparities. To avoid false matchings due to static occlusion, a dual matching, based on the imaging geometry, is used.

Log-Gabor Weber descriptor for face recognition

NASA Astrophysics Data System (ADS)

Li, Jing; Sang, Nong; Gao, Changxin

2015-09-01

The Log-Gabor transform, which is suitable for analyzing gradually changing data such as in iris and face images, has been widely used in image processing, pattern recognition, and computer vision. In most cases, only the magnitude or phase information of the Log-Gabor transform is considered. However, the complementary effect taken by combining magnitude and phase information simultaneously for an image-feature extraction problem has not been systematically explored in the existing works. We propose a local image descriptor for face recognition, called Log-Gabor Weber descriptor (LGWD). The novelty of our LGWD is twofold: (1) to fully utilize the information from the magnitude or phase feature of multiscale and orientation Log-Gabor transform, we apply the Weber local binary pattern operator to each transform response. (2) The encoded Log-Gabor magnitude and phase information are fused at the feature level by utilizing kernel canonical correlation analysis strategy, considering that feature level information fusion is effective when the modalities are correlated. Experimental results on the AR, Extended Yale B, and UMIST face databases, compared with those available from recent experiments reported in the literature, show that our descriptor yields a better performance than state-of-the art methods.

Theory, implementation and applications of nonstationary Gabor frames

PubMed Central

Balazs, P.; Dörfler, M.; Jaillet, F.; Holighaus, N.; Velasco, G.

2011-01-01

Signal analysis with classical Gabor frames leads to a fixed time–frequency resolution over the whole time–frequency plane. To overcome the limitations imposed by this rigidity, we propose an extension of Gabor theory that leads to the construction of frames with time–frequency resolution changing over time or frequency. We describe the construction of the resulting nonstationary Gabor frames and give the explicit formula for the canonical dual frame for a particular case, the painless case. We show that wavelet transforms, constant-Q transforms and more general filter banks may be modeled in the framework of nonstationary Gabor frames. Further, we present the results in the finite-dimensional case, which provides a method for implementing the above-mentioned transforms with perfect reconstruction. Finally, we elaborate on two applications of nonstationary Gabor frames in audio signal processing, namely a method for automatic adaptation to transients and an algorithm for an invertible constant-Q transform. PMID:22267893

Gabor Jets for Clutter Rejection in Infrared Imagery

DTIC Science & Technology

2004-12-01

application of a suitable model like Gabor Jets in facial recognition is well motivated by the observation that some low level, spatial-frequency...set. This is a simplified form of the Gabor Jet procedure and will not require any elastic graph matching procedures used in facial recognition . Another...motivation for employing Gabor jets as a post processing clutter rejecter is attributed to the great deal of research in facial recognition , invariant

Automatic detection of echolocation clicks based on a Gabor model of their waveform.

PubMed

Madhusudhana, Shyam; Gavrilov, Alexander; Erbe, Christine

2015-06-01

Prior research has shown that echolocation clicks of several species of terrestrial and marine fauna can be modelled as Gabor-like functions. Here, a system is proposed for the automatic detection of a variety of such signals. By means of mathematical formulation, it is shown that the output of the Teager-Kaiser Energy Operator (TKEO) applied to Gabor-like signals can be approximated by a Gaussian function. Based on the inferences, a detection algorithm involving the post-processing of the TKEO outputs is presented. The ratio of the outputs of two moving-average filters, a Gaussian and a rectangular filter, is shown to be an effective detection parameter. Detector performance is assessed using synthetic and real (taken from MobySound database) recordings. The detection method is shown to work readily with a variety of echolocation clicks and in various recording scenarios. The system exhibits low computational complexity and operates several times faster than real-time. Performance comparisons are made to other publicly available detectors including pamguard.

A Novel Marking Reader for Progressive Addition Lenses Based on Gabor Holography.

PubMed

Perucho, Beatriz; Picazo-Bueno, José Angel; Micó, Vicente

2016-05-01

Progressive addition lenses (PALs) are marked with permanent engraved marks (PEMs) at standardized locations. Permanent engraved marks are very useful through the manufacturing and mounting processes, act as locator marks to re-ink the removable marks, and contain useful information about the PAL. However, PEMs are often faint and weak, obscured by scratches, partially occluded, and difficult to recognize on tinted lenses or with antireflection or scratch-resistant coatings. The aim of this article is to present a new generation of portable marking reader based on an extremely simplified concept for visualization and identification of PEMs in PALs. Permanent engraved marks on different PALs are visualized using classical Gabor holography as underlying principle. Gabor holography allows phase sample visualization with adjustable magnification and can be implemented in either classical or digital versions. Here, visual Gabor holography is used to provide a magnified defocused image of the PEMs onto a translucent visualization screen where the PEM is clearly identified. Different types of PALs (conventional, personalized, old and scratched, sunglasses, etc.) have been tested to visualize PEMs with the proposed marking reader. The PEMs are visible in every case, and variable magnification factor can be achieved simply moving up and down the PAL in the instrument. In addition, a second illumination wavelength is also tested, showing the applicability of this novel marking reader for different illuminations. A new concept of marking reader ophthalmic instrument has been presented and validated in the laboratory. The configuration involves only a commercial-grade laser diode and a visualization screen for PEM identification. The instrument is portable, economic, and easy to use, and it can be used for identifying patient's current PAL model and for marking removable PALs again or finding test points regardless of the age of the PAL, its scratches, tints, or coatings.

Gabor fusion master slave optical coherence tomography

PubMed Central

Cernat, Ramona; Bradu, Adrian; Israelsen, Niels Møller; Bang, Ole; Rivet, Sylvain; Keane, Pearse A.; Heath, David-Garway; Rajendram, Ranjan; Podoleanu, Adrian

2017-01-01

This paper describes the application of the Gabor filtering protocol to a Master/Slave (MS) swept source optical coherence tomography (SS)-OCT system at 1300 nm. The MS-OCT system delivers information from selected depths, a property that allows operation similar to that of a time domain OCT system, where dynamic focusing is possible. The Gabor filtering processing following collection of multiple data from different focus positions is different from that utilized by a conventional swept source OCT system using a Fast Fourier transform (FFT) to produce an A-scan. Instead of selecting the bright parts of A-scans for each focus position, to be placed in a final B-scan image (or in a final volume), and discarding the rest, the MS principle can be employed to advantageously deliver signal from the depths within each focus range only. The MS procedure is illustrated on creating volumes of data of constant transversal resolution from a cucumber and from an insect by repeating data acquisition for 4 different focus positions. In addition, advantage is taken from the tolerance to dispersion of the MS principle that allows automatic compensation for dispersion created by layers above the object of interest. By combining the two techniques, Gabor filtering and Master/Slave, a powerful imaging instrument is demonstrated. The master/slave technique allows simultaneous display of three categories of images in one frame: multiple depth en-face OCT images, two cross-sectional OCT images and a confocal like image obtained by averaging the en-face ones. We also demonstrate the superiority of MS-OCT over its FFT based counterpart when used with a Gabor filtering OCT instrument in terms of the speed of assembling the fused volume. For our case, we show that when more than 4 focus positions are required to produce the final volume, MS is faster than the conventional FFT based procedure. PMID:28270987

Time efficient Gabor fused master slave optical coherence tomography

NASA Astrophysics Data System (ADS)

Cernat, Ramona; Bradu, Adrian; Rivet, Sylvain; Podoleanu, Adrian

2018-02-01

In this paper the benefits in terms of operation time that Master/Slave (MS) implementation of optical coherence tomography can bring in comparison to Gabor fused (GF) employing conventional fast Fourier transform based OCT are presented. The Gabor Fusion/Master Slave Optical Coherence Tomography architecture proposed here does not need any data stitching. Instead, a subset of en-face images is produced for each focus position inside the sample to be imaged, using a reduced number of theoretically inferred Master masks. These en-face images are then assembled into a final volume. When the channelled spectra are digitized into 1024 sampling points, and more than 4 focus positions are required to produce the final volume, the Master Slave implementation of the instrument is faster than the conventional fast Fourier transform based procedure.

Stochastic Gabor reflectivity and acoustic impedance inversion

NASA Astrophysics Data System (ADS)

Hariri Naghadeh, Diako; Morley, Christopher Keith; Ferguson, Angus John

2018-02-01

To delineate subsurface lithology to estimate petrophysical properties of a reservoir, it is possible to use acoustic impedance (AI) which is the result of seismic inversion. To change amplitude to AI, removal of wavelet effects from the seismic signal in order to get a reflection series, and subsequently transforming those reflections to AI, is vital. To carry out seismic inversion correctly it is important to not assume that the seismic signal is stationary. However, all stationary deconvolution methods are designed following that assumption. To increase temporal resolution and interpretation ability, amplitude compensation and phase correction are inevitable. Those are pitfalls of stationary reflectivity inversion. Although stationary reflectivity inversion methods are trying to estimate reflectivity series, because of incorrect assumptions their estimations will not be correct, but may be useful. Trying to convert those reflection series to AI, also merging with the low frequency initial model, can help us. The aim of this study was to apply non-stationary deconvolution to eliminate time variant wavelet effects from the signal and to convert the estimated reflection series to the absolute AI by getting bias from well logs. To carry out this aim, stochastic Gabor inversion in the time domain was used. The Gabor transform derived the signal’s time-frequency analysis and estimated wavelet properties from different windows. Dealing with different time windows gave an ability to create a time-variant kernel matrix, which was used to remove matrix effects from seismic data. The result was a reflection series that does not follow the stationary assumption. The subsequent step was to convert those reflections to AI using well information. Synthetic and real data sets were used to show the ability of the introduced method. The results highlight that the time cost to get seismic inversion is negligible related to general Gabor inversion in the frequency domain. Also

Editorial: Special issue dedicated to Gabor Somorjai's 80th birthday

NASA Astrophysics Data System (ADS)

2016-06-01

This special issue of Surface Science has been prepared to honor Professor Gabor A. Somorjai on the occasion of his 80th birthday. Professor Somorjai was born on May 4, 1935 in Budapest, Hungary. In 1953 he enrolled as a chemical engineering student at the Technical University of Budapest. Gabor was an active participant in the Hungarian Revolution of 1956. When the Soviet military crushed the revolution, he had to leave the country by walking across the border with his sister and his future wife. After immigrating to the USA in 1957, he applied to begin graduate studies and was accepted at the University of California, Berkeley. Gabor received a PhD in Chemistry in 1960, only three years later. Following a short sojourn at IBM, he returned to Berkeley in 1964 to take up a faculty position in the Department of Chemistry and the Lawrence Berkeley National Laboratory, which he still holds today. For the interested reader, more can be learned about Gabor's fascinating life in his autobiography, ;An American Scientist: The Autobiography of Gabor A. Somorjai.

Research on autonomous identification of airport targets based on Gabor filtering and Radon transform

NASA Astrophysics Data System (ADS)

Yi, Juan; Du, Qingyu; Zhang, Hong jiang; Zhang, Yao lei

2017-11-01

Target recognition is a leading key technology in intelligent image processing and application development at present, with the enhancement of computer processing ability, autonomous target recognition algorithm, gradually improve intelligence, and showed good adaptability. Taking the airport target as the research object, analysis the airport layout characteristics, construction of knowledge model, Gabor filter and Radon transform based on the target recognition algorithm of independent design, image processing and feature extraction of the airport, the algorithm was verified, and achieved better recognition results.

Gabor filter for the segmentation of skin lesions from ultrasonographic images

NASA Astrophysics Data System (ADS)

Petrella, Lorena I.; Gómez, W.; Alvarenga, André V.; Pereira, Wagner C. A.

2012-05-01

The present work applies Gabor filters bank for texture analysis of skin lesions images, obtained by ultrasound biomicroscopy. The regions affected by the lesions were differentiated from surrounding tissue in all the analyzed cases; however the accuracy of the traced borders showed some limitations in part of the images. Future steps are being contemplated, attempting to enhance the technique performance.

Automated detection scheme of architectural distortion in mammograms using adaptive Gabor filter

NASA Astrophysics Data System (ADS)

Yoshikawa, Ruriha; Teramoto, Atsushi; Matsubara, Tomoko; Fujita, Hiroshi

2013-03-01

Breast cancer is a serious health concern for all women. Computer-aided detection for mammography has been used for detecting mass and micro-calcification. However, there are challenges regarding the automated detection of the architectural distortion about the sensitivity. In this study, we propose a novel automated method for detecting architectural distortion. Our method consists of the analysis of the mammary gland structure, detection of the distorted region, and reduction of false positive results. We developed the adaptive Gabor filter for analyzing the mammary gland structure that decides filter parameters depending on the thickness of the gland structure. As for post-processing, healthy mammary glands that run from the nipple to the chest wall are eliminated by angle analysis. Moreover, background mammary glands are removed based on the intensity output image obtained from adaptive Gabor filter. The distorted region of the mammary gland is then detected as an initial candidate using a concentration index followed by binarization and labeling. False positives in the initial candidate are eliminated using 23 types of characteristic features and a support vector machine. In the experiments, we compared the automated detection results with interpretations by a radiologist using 50 cases (200 images) from the Digital Database of Screening Mammography (DDSM). As a result, true positive rate was 82.72%, and the number of false positive per image was 1.39. There results indicate that the proposed method may be useful for detecting architectural distortion in mammograms.

Multi-resolution Gabor wavelet feature extraction for needle detection in 3D ultrasound

NASA Astrophysics Data System (ADS)

Pourtaherian, Arash; Zinger, Svitlana; Mihajlovic, Nenad; de With, Peter H. N.; Huang, Jinfeng; Ng, Gary C.; Korsten, Hendrikus H. M.

2015-12-01

Ultrasound imaging is employed for needle guidance in various minimally invasive procedures such as biopsy guidance, regional anesthesia and brachytherapy. Unfortunately, a needle guidance using 2D ultrasound is very challenging, due to a poor needle visibility and a limited field of view. Nowadays, 3D ultrasound systems are available and more widely used. Consequently, with an appropriate 3D image-based needle detection technique, needle guidance and interventions may significantly be improved and simplified. In this paper, we present a multi-resolution Gabor transformation for an automated and reliable extraction of the needle-like structures in a 3D ultrasound volume. We study and identify the best combination of the Gabor wavelet frequencies. High precision in detecting the needle voxels leads to a robust and accurate localization of the needle for the intervention support. Evaluation in several ex-vivo cases shows that the multi-resolution analysis significantly improves the precision of the needle voxel detection from 0.23 to 0.32 at a high recall rate of 0.75 (gain 40%), where a better robustness and confidence were confirmed in the practical experiments.

3D Gabor wavelet based vessel filtering of photoacoustic images.

PubMed

Haq, Israr Ul; Nagoaka, Ryo; Makino, Takahiro; Tabata, Takuya; Saijo, Yoshifumi

2016-08-01

Filtering and segmentation of vasculature is an important issue in medical imaging. The visualization of vasculature is crucial for the early diagnosis and therapy in numerous medical applications. This paper investigates the use of Gabor wavelet to enhance the effect of vasculature while eliminating the noise due to size, sensitivity and aperture of the detector in 3D Optical Resolution Photoacoustic Microscopy (OR-PAM). A detailed multi-scale analysis of wavelet filtering and Hessian based method is analyzed for extracting vessels of different sizes since the blood vessels usually vary with in a range of radii. The proposed algorithm first enhances the vasculature in the image and then tubular structures are classified by eigenvalue decomposition of the local Hessian matrix at each voxel in the image. The algorithm is tested on non-invasive experiments, which shows appreciable results to enhance vasculature in photo-acoustic images.

Mass detection with digitized screening mammograms by using Gabor features

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Agyepong, Kwabena

2007-03-01

Breast cancer is the leading cancer among American women. The current lifetime risk of developing breast cancer is 13.4% (one in seven). Mammography is the most effective technology presently available for breast cancer screening. With digital mammograms computer-aided detection (CAD) has proven to be a useful tool for radiologists. In this paper, we focus on mass detection that is a common category of breast cancers relative to calcification and architecture distortion. We propose a new mass detection algorithm utilizing Gabor filters, termed as "Gabor Mass Detection" (GMD). There are three steps in the GMD algorithm, (1) preprocessing, (2) generating alarms and (3) classification (reducing false alarms). Down-sampling, quantization, denoising and enhancement are done in the preprocessing step. Then a total of 30 Gabor filtered images (along 6 bands by 5 orientations) are produced. Alarm segments are generated by thresholding four Gabor images of full orientations (Stage-I classification) with image-dependent thresholds computed via histogram analysis. Next a set of edge histogram descriptors (EHD) are extracted from 24 Gabor images (6 by 4) that will be used for Stage-II classification. After clustering EHD features with fuzzy C-means clustering method, a k-nearest neighbor classifier is used to reduce the number of false alarms. We initially analyzed 431 digitized mammograms (159 normal images vs. 272 cancerous images, from the DDSM project, University of South Florida) with the proposed GMD algorithm. And a ten-fold cross validation was used for testing the GMD algorithm upon the available data. The GMD performance is as follows: sensitivity (true positive rate) = 0.88 at false positives per image (FPI) = 1.25, and the area under the ROC curve = 0.83. The overall performance of the GMD algorithm is satisfactory and the accuracy of locating masses (highlighting the boundaries of suspicious areas) is relatively high. Furthermore, the GMD algorithm can

Efficient iris texture analysis method based on Gabor ordinal measures

NASA Astrophysics Data System (ADS)

Tajouri, Imen; Aydi, Walid; Ghorbel, Ahmed; Masmoudi, Nouri

2017-07-01

With the remarkably increasing interest directed to the security dimension, the iris recognition process is considered to stand as one of the most versatile technique critically useful for the biometric identification and authentication process. This is mainly due to every individual's unique iris texture. A modestly conceived efficient approach relevant to the feature extraction process is proposed. In the first place, iris zigzag "collarette" is extracted from the rest of the image by means of the circular Hough transform, as it includes the most significant regions lying in the iris texture. In the second place, the linear Hough transform is used for the eyelids' detection purpose while the median filter is applied for the eyelashes' removal. Then, a special technique combining the richness of Gabor features and the compactness of ordinal measures is implemented for the feature extraction process, so that a discriminative feature representation for every individual can be achieved. Subsequently, the modified Hamming distance is used for the matching process. Indeed, the advanced procedure turns out to be reliable, as compared to some of the state-of-the-art approaches, with a recognition rate of 99.98%, 98.12%, and 95.02% on CASIAV1.0, CASIAV3.0, and IIT Delhi V1 iris databases, respectively.

The norms and variances of the Gabor, Morlet and general harmonic wavelet functions

NASA Astrophysics Data System (ADS)

Simonovski, I.; Boltežar, M.

2003-07-01

This paper deals with certain properties of the continuous wavelet transform and wavelet functions. The norms and the spreads in time and frequency of the common Gabor and Morlet wavelet functions are presented. It is shown that the norm of the Morlet wavelet function does not satisfy the normalization condition and that the normalized Morlet wavelet function is identical to the Gabor wavelet function with the parameter σ=1. The general harmonic wavelet function is developed using frequency modulation of the Hanning and Hamming window functions. Several properties of the general harmonic wavelet function are also presented and compared to the Gabor wavelet function. The time and frequency spreads of the general harmonic wavelet function are only slightly higher than the time and frequency spreads of the Gabor wavelet function. However, the general harmonic wavelet function is simpler to use than the Gabor wavelet function. In addition, the general harmonic wavelet function can be constructed in such a way that the zero average condition is truly satisfied. The average value of the Gabor wavelet function can approach a value of zero but it cannot reach it. When calculating the continuous wavelet transform, errors occur at the start- and the end-time indexes. This is called the edge effect and is caused by the fact that the wavelet transform is calculated from a signal of finite length. In this paper, we propose a method that uses signal mirroring to reduce the errors caused by the edge effect. The success of the proposed method is demonstrated by using a simulated signal.

Investigation on improved Gabor order tracking technique and its applications

NASA Astrophysics Data System (ADS)

Pan, Min-Chun; Chiu, Chun-Ching

2006-08-01

The study proposes an improved Gabor order tracking (GOT) technique to cope with crossing-order/spectral components that cannot be effectively separated by using the original GOT scheme. The improvement aids both the reconstruction and interpretation of two crossing orders/spectra such as a transmission-element-regarding order and a structural resonance. The dual function of the Gabor elementary function can affect the precision of tracked orders. In the paper, its influence on the computed Gabor expansion coefficients is investigated. For applying the improved scheme in practical works, the separation and extraction of close-order components of vibration signals measured from a transmission-element test bench is illustrated by using both the GOT and Vold-Kalman filtering OT methods. Additionally, comparisons between these two schemes are summarized from processing results. The other experimental work demonstrates the ranking of noise components from a riding electric scooter. Singled-out dominant noise sources can be referred for subsequent design-remodeling tasks.

Investigation on improved Gabor order tracking technique

NASA Astrophysics Data System (ADS)

Pan, Min-Chun; Chiu, Chun-Ching

2004-07-01

The study proposes an improved Gabor order tracking (GOT) technique to cope with crossing orders that cannot be effectively separated using the original GOT scheme. The improvement aids both the reconstruction and interpretation of two crossing orders such as a transmission-element-regarding order component and a structural resonant component. In the paper, the influence of the dual function to Gabor expansion coefficients is investigated, which can affect the precision of the tracked order component. Additionally, using the GOT scheme in noise conditions is demonstrated as well. For applying the improved GOT in real tasks, separation and extraction of close-order components of vibration signals measured from a transmission-element test bench is illustrated using both the GOT and Vold-Kalman filtering (VKF) OT schemes. Finally, comprehensive comparisons between the improved GOT and VKF_OT schemes are made from processing results.

Regional income inequality model based on theil index decomposition and weighted variance coeficient

NASA Astrophysics Data System (ADS)

Sitepu, H. R.; Darnius, O.; Tambunan, W. N.

2018-03-01

Regional income inequality is an important issue in the study on economic development of a certain region. Rapid economic development may not in accordance with people’s per capita income. The method of measuring the regional income inequality has been suggested by many experts. This research used Theil index and weighted variance coefficient in order to measure the regional income inequality. Regional income decomposition which becomes the productivity of work force and their participation in regional income inequality, based on Theil index, can be presented in linear relation. When the economic assumption in j sector, sectoral income value, and the rate of work force are used, the work force productivity imbalance can be decomposed to become the component in sectors and in intra-sectors. Next, weighted variation coefficient is defined in the revenue and productivity of the work force. From the quadrate of the weighted variation coefficient result, it was found that decomposition of regional revenue imbalance could be analyzed by finding out how far each component contribute to regional imbalance which, in this research, was analyzed in nine sectors of economic business.

Retinal identification based on an Improved Circular Gabor Filter and Scale Invariant Feature Transform.

PubMed

Meng, Xianjing; Yin, Yilong; Yang, Gongping; Xi, Xiaoming

2013-07-18

Retinal identification based on retinal vasculatures in the retina provides the most secure and accurate means of authentication among biometrics and has primarily been used in combination with access control systems at high security facilities. Recently, there has been much interest in retina identification. As digital retina images always suffer from deformations, the Scale Invariant Feature Transform (SIFT), which is known for its distinctiveness and invariance for scale and rotation, has been introduced to retinal based identification. However, some shortcomings like the difficulty of feature extraction and mismatching exist in SIFT-based identification. To solve these problems, a novel preprocessing method based on the Improved Circular Gabor Transform (ICGF) is proposed. After further processing by the iterated spatial anisotropic smooth method, the number of uninformative SIFT keypoints is decreased dramatically. Tested on the VARIA and eight simulated retina databases combining rotation and scaling, the developed method presents promising results and shows robustness to rotations and scale changes.

Retinal Identification Based on an Improved Circular Gabor Filter and Scale Invariant Feature Transform

PubMed Central

Meng, Xianjing; Yin, Yilong; Yang, Gongping; Xi, Xiaoming

2013-01-01

Retinal identification based on retinal vasculatures in the retina provides the most secure and accurate means of authentication among biometrics and has primarily been used in combination with access control systems at high security facilities. Recently, there has been much interest in retina identification. As digital retina images always suffer from deformations, the Scale Invariant Feature Transform (SIFT), which is known for its distinctiveness and invariance for scale and rotation, has been introduced to retinal based identification. However, some shortcomings like the difficulty of feature extraction and mismatching exist in SIFT-based identification. To solve these problems, a novel preprocessing method based on the Improved Circular Gabor Transform (ICGF) is proposed. After further processing by the iterated spatial anisotropic smooth method, the number of uninformative SIFT keypoints is decreased dramatically. Tested on the VARIA and eight simulated retina databases combining rotation and scaling, the developed method presents promising results and shows robustness to rotations and scale changes. PMID:23873409

Log-Gabor Energy Based Multimodal Medical Image Fusion in NSCT Domain

PubMed Central

Yang, Yong; Tong, Song; Huang, Shuying; Lin, Pan

2014-01-01

Multimodal medical image fusion is a powerful tool in clinical applications such as noninvasive diagnosis, image-guided radiotherapy, and treatment planning. In this paper, a novel nonsubsampled Contourlet transform (NSCT) based method for multimodal medical image fusion is presented, which is approximately shift invariant and can effectively suppress the pseudo-Gibbs phenomena. The source medical images are initially transformed by NSCT followed by fusing low- and high-frequency components. The phase congruency that can provide a contrast and brightness-invariant representation is applied to fuse low-frequency coefficients, whereas the Log-Gabor energy that can efficiently determine the frequency coefficients from the clear and detail parts is employed to fuse the high-frequency coefficients. The proposed fusion method has been compared with the discrete wavelet transform (DWT), the fast discrete curvelet transform (FDCT), and the dual tree complex wavelet transform (DTCWT) based image fusion methods and other NSCT-based methods. Visually and quantitatively experimental results indicate that the proposed fusion method can obtain more effective and accurate fusion results of multimodal medical images than other algorithms. Further, the applicability of the proposed method has been testified by carrying out a clinical example on a woman affected with recurrent tumor images. PMID:25214889

Near-infrared spectral image analysis of pork marbling based on Gabor filter and wide line detector techniques.

PubMed

Huang, Hui; Liu, Li; Ngadi, Michael O; Gariépy, Claude; Prasher, Shiv O

2014-01-01

Marbling is an important quality attribute of pork. Detection of pork marbling usually involves subjective scoring, which raises the efficiency costs to the processor. In this study, the ability to predict pork marbling using near-infrared (NIR) hyperspectral imaging (900-1700 nm) and the proper image processing techniques were studied. Near-infrared images were collected from pork after marbling evaluation according to current standard chart from the National Pork Producers Council. Image analysis techniques-Gabor filter, wide line detector, and spectral averaging-were applied to extract texture, line, and spectral features, respectively, from NIR images of pork. Samples were grouped into calibration and validation sets. Wavelength selection was performed on calibration set by stepwise regression procedure. Prediction models of pork marbling scores were built using multiple linear regressions based on derivatives of mean spectra and line features at key wavelengths. The results showed that the derivatives of both texture and spectral features produced good results, with correlation coefficients of validation of 0.90 and 0.86, respectively, using wavelengths of 961, 1186, and 1220 nm. The results revealed the great potential of the Gabor filter for analyzing NIR images of pork for the effective and efficient objective evaluation of pork marbling.

Vessel extraction in retinal images using automatic thresholding and Gabor Wavelet.

PubMed

Ali, Aziah; Hussain, Aini; Wan Zaki, Wan Mimi Diyana

2017-07-01

Retinal image analysis has been widely used for early detection and diagnosis of multiple systemic diseases. Accurate vessel extraction in retinal image is a crucial step towards a fully automated diagnosis system. This work affords an efficient unsupervised method for extracting blood vessels from retinal images by combining existing Gabor Wavelet (GW) method with automatic thresholding. Green channel image is extracted from color retinal image and used to produce Gabor feature image using GW. Both green channel image and Gabor feature image undergo vessel-enhancement step in order to highlight blood vessels. Next, the two vessel-enhanced images are transformed to binary images using automatic thresholding before combined to produce the final vessel output. Combining the images results in significant improvement of blood vessel extraction performance compared to using individual image. Effectiveness of the proposed method was proven via comparative analysis with existing methods validated using publicly available database, DRIVE.

Facial Emotions Recognition using Gabor Transform and Facial Animation Parameters with Neural Networks

NASA Astrophysics Data System (ADS)

Harit, Aditya; Joshi, J. C., Col; Gupta, K. K.

2018-03-01

The paper proposed an automatic facial emotion recognition algorithm which comprises of two main components: feature extraction and expression recognition. The algorithm uses a Gabor filter bank on fiducial points to find the facial expression features. The resulting magnitudes of Gabor transforms, along with 14 chosen FAPs (Facial Animation Parameters), compose the feature space. There are two stages: the training phase and the recognition phase. Firstly, for the present 6 different emotions, the system classifies all training expressions in 6 different classes (one for each emotion) in the training stage. In the recognition phase, it recognizes the emotion by applying the Gabor bank to a face image, then finds the fiducial points, and then feeds it to the trained neural architecture.

Contrast of slightly complex patterns: computing the perceived contrast of Gabor patches

NASA Astrophysics Data System (ADS)

Peli, Eli

1996-04-01

The local contrast in an image may be approximated by the contrast of a Gabor patch of varying phase and bandwidth. In a search for a metric for such local contrast, perceived (apparent) contrast, as indicated by matching of such patterns, were compared here to the physical contrast calculated by a number of methods. The 2 cycles/deg 1-octave Gabor patch stimuli of different phases were presented side by side separated by 4 degrees. During each session the subjects (n equals 5) were adapted to the average luminance, and four different contrast levels (0.1, 0.3, 0.6, and 0.8) were randomly interleaved. The task was repeated at four mean luminance levels between 0.75 and 37.5 cd/m2. The subject's task was to indicate which of the two patterns was lower in contrast. Equal apparent contrast was determined by fitting a psychometric function to the data from 40 to 70 presentations. There was no effect of mean luminance on the subjects settings. The matching results rejected the hypothesis that either the Michelson formula or the King-Smith & Kulikowski contrast (CKK equals (Lmax-Laverage)/Laverage) was used by the subjects to set the match. The use of the Nominal contrast (the Michelson contrast of the underlying sinusoid) as an estimate of apparent contrast could not be rejected. In a second experiment the apparent contrast of a 1-octave Gabor patch was matched to the apparent contrast of a 2-octave Gabor patch (of Nominal contrast of 0.1, 0.3, 0.6, 0.8) using the method of adjustment. The result of this experiment rejected the prediction of the Nominal contrast definition. The local band limited contrast measure (Peli, 1990), when used with the modifications suggested by Lubin (1995), as an estimate of apparent contrast could not be rejected by the results of either experiment. These results suggest that a computational contrast measure based on multi scale bandpass filtering is a better estimate of apparent perceived contrast than any of the other measures tested.

Osteoarthritis classification using self organizing map based on gabor kernel and contrast-limited adaptive histogram equalization.

PubMed

Anifah, Lilik; Purnama, I Ketut Eddy; Hariadi, Mochamad; Purnomo, Mauridhi Hery

2013-01-01

Localization is the first step in osteoarthritis (OA) classification. Manual classification, however, is time-consuming, tedious, and expensive. The proposed system is designed as decision support system for medical doctors to classify the severity of knee OA. A method has been proposed here to localize a joint space area for OA and then classify it in 4 steps to classify OA into KL-Grade 0, KL-Grade 1, KL-Grade 2, KL-Grade 3 and KL-Grade 4, which are preprocessing, segmentation, feature extraction, and classification. In this proposed system, right and left knee detection was performed by employing the Contrast-Limited Adaptive Histogram Equalization (CLAHE) and the template matching. The Gabor kernel, row sum graph and moment methods were used to localize the junction space area of knee. CLAHE is used for preprocessing step, i.e.to normalize the varied intensities. The segmentation process was conducted using the Gabor kernel, template matching, row sum graph and gray level center of mass method. Here GLCM (contrast, correlation, energy, and homogeinity) features were employed as training data. Overall, 50 data were evaluated for training and 258 data for testing. Experimental results showed the best performance by using gabor kernel with parameters α=8, θ=0, Ψ=[0 π/2], γ=0,8, N=4 and with number of iterations being 5000, momentum value 0.5 and α0=0.6 for the classification process. The run gave classification accuracy rate of 93.8% for KL-Grade 0, 70% for KL-Grade 1, 4% for KL-Grade 2, 10% for KL-Grade 3 and 88.9% for KL-Grade 4.

Osteoarthritis Classification Using Self Organizing Map Based on Gabor Kernel and Contrast-Limited Adaptive Histogram Equalization

PubMed Central

Anifah, Lilik; Purnama, I Ketut Eddy; Hariadi, Mochamad; Purnomo, Mauridhi Hery

2013-01-01

Localization is the first step in osteoarthritis (OA) classification. Manual classification, however, is time-consuming, tedious, and expensive. The proposed system is designed as decision support system for medical doctors to classify the severity of knee OA. A method has been proposed here to localize a joint space area for OA and then classify it in 4 steps to classify OA into KL-Grade 0, KL-Grade 1, KL-Grade 2, KL-Grade 3 and KL-Grade 4, which are preprocessing, segmentation, feature extraction, and classification. In this proposed system, right and left knee detection was performed by employing the Contrast-Limited Adaptive Histogram Equalization (CLAHE) and the template matching. The Gabor kernel, row sum graph and moment methods were used to localize the junction space area of knee. CLAHE is used for preprocessing step, i.e.to normalize the varied intensities. The segmentation process was conducted using the Gabor kernel, template matching, row sum graph and gray level center of mass method. Here GLCM (contrast, correlation, energy, and homogeinity) features were employed as training data. Overall, 50 data were evaluated for training and 258 data for testing. Experimental results showed the best performance by using gabor kernel with parameters α=8, θ=0, Ψ=[0 π/2], γ=0,8, N=4 and with number of iterations being 5000, momentum value 0.5 and α0=0.6 for the classification process. The run gave classification accuracy rate of 93.8% for KL-Grade 0, 70% for KL-Grade 1, 4% for KL-Grade 2, 10% for KL-Grade 3 and 88.9% for KL-Grade 4. PMID:23525188

Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification.

PubMed

Soares, João V B; Leandro, Jorge J G; Cesar Júnior, Roberto M; Jelinek, Herbert F; Cree, Michael J

2006-09-01

We present a method for automated segmentation of the vasculature in retinal images. The method produces segmentations by classifying each image pixel as vessel or nonvessel, based on the pixel's feature vector. Feature vectors are composed of the pixel's intensity and two-dimensional Gabor wavelet transform responses taken at multiple scales. The Gabor wavelet is capable of tuning to specific frequencies, thus allowing noise filtering and vessel enhancement in a single step. We use a Bayesian classifier with class-conditional probability density functions (likelihoods) described as Gaussian mixtures, yielding a fast classification, while being able to model complex decision surfaces. The probability distributions are estimated based on a training set of labeled pixels obtained from manual segmentations. The method's performance is evaluated on publicly available DRIVE (Staal et al., 2004) and STARE (Hoover et al., 2000) databases of manually labeled images. On the DRIVE database, it achieves an area under the receiver operating characteristic curve of 0.9614, being slightly superior than that presented by state-of-the-art approaches. We are making our implementation available as open source MATLAB scripts for researchers interested in implementation details, evaluation, or development of methods.

Separable spectro-temporal Gabor filter bank features: Reducing the complexity of robust features for automatic speech recognition.

PubMed

Schädler, Marc René; Kollmeier, Birger

2015-04-01

To test if simultaneous spectral and temporal processing is required to extract robust features for automatic speech recognition (ASR), the robust spectro-temporal two-dimensional-Gabor filter bank (GBFB) front-end from Schädler, Meyer, and Kollmeier [J. Acoust. Soc. Am. 131, 4134-4151 (2012)] was de-composed into a spectral one-dimensional-Gabor filter bank and a temporal one-dimensional-Gabor filter bank. A feature set that is extracted with these separate spectral and temporal modulation filter banks was introduced, the separate Gabor filter bank (SGBFB) features, and evaluated on the CHiME (Computational Hearing in Multisource Environments) keywords-in-noise recognition task. From the perspective of robust ASR, the results showed that spectral and temporal processing can be performed independently and are not required to interact with each other. Using SGBFB features permitted the signal-to-noise ratio (SNR) to be lowered by 1.2 dB while still performing as well as the GBFB-based reference system, which corresponds to a relative improvement of the word error rate by 12.8%. Additionally, the real time factor of the spectro-temporal processing could be reduced by more than an order of magnitude. Compared to human listeners, the SNR needed to be 13 dB higher when using Mel-frequency cepstral coefficient features, 11 dB higher when using GBFB features, and 9 dB higher when using SGBFB features to achieve the same recognition performance.

Linearity can account for the similarity among conventional, frequency-doubling, and gabor-based perimetric tests in the glaucomatous macula.

PubMed

Sun, Hao; Dul, Mitchell W; Swanson, William H

2006-07-01

The purposes of this study are to compare macular perimetric sensitivities for conventional size III, frequency-doubling, and Gabor stimuli in terms of Weber contrast and to provide a theoretical interpretation of the results. Twenty-two patients with glaucoma performed four perimetric tests: a conventional Swedish Interactive Threshold Algorithm (SITA) 10-2 test with Goldmann size III stimuli, two frequency-doubling tests (FDT 10-2, FDT Macula) with counterphase-modulated grating stimuli, and a laboratory-designed test with Gabor stimuli. Perimetric sensitivities were converted to the reciprocal of Weber contrast and sensitivities from different tests were compared using the Bland-Altman method. Effects of ganglion cell loss on perimetric sensitivities were then simulated with a two-stage neural model. The average perimetric loss was similar for all stimuli until advanced stages of ganglion cell loss, in which perimetric loss tended to be greater for size III stimuli than for frequency-doubling and Gabor stimuli. Comparison of the experimental data and model simulation suggests that, in the macula, linear relations between ganglion cell loss and perimetric sensitivity loss hold for all three stimuli. Linear relations between perimetric loss and ganglion cell loss for all three stimuli can account for the similarity in perimetric loss until advanced stages. The results do not support the hypothesis that redundancy for frequency-doubling stimuli is lower than redundancy for size III stimuli.

Fully automated muscle quality assessment by Gabor filtering of second harmonic generation images

NASA Astrophysics Data System (ADS)

Paesen, Rik; Smolders, Sophie; Vega, José Manolo de Hoyos; Eijnde, Bert O.; Hansen, Dominique; Ameloot, Marcel

2016-02-01

Although structural changes on the sarcomere level of skeletal muscle are known to occur due to various pathologies, rigorous studies of the reduced sarcomere quality remain scarce. This can possibly be explained by the lack of an objective tool for analyzing and comparing sarcomere images across biological conditions. Recent developments in second harmonic generation (SHG) microscopy and increasing insight into the interpretation of sarcomere SHG intensity profiles have made SHG microscopy a valuable tool to study microstructural properties of sarcomeres. Typically, sarcomere integrity is analyzed by fitting a set of manually selected, one-dimensional SHG intensity profiles with a supramolecular SHG model. To circumvent this tedious manual selection step, we developed a fully automated image analysis procedure to map the sarcomere disorder for the entire image at once. The algorithm relies on a single-frequency wavelet-based Gabor approach and includes a newly developed normalization procedure allowing for unambiguous data interpretation. The method was validated by showing the correlation between the sarcomere disorder, quantified by the M-band size obtained from manually selected profiles, and the normalized Gabor value ranging from 0 to 1 for decreasing disorder. Finally, to elucidate the applicability of our newly developed protocol, Gabor analysis was used to study the effect of experimental autoimmune encephalomyelitis on the sarcomere regularity. We believe that the technique developed in this work holds great promise for high-throughput, unbiased, and automated image analysis to study sarcomere integrity by SHG microscopy.

Coronary artery segmentation in X-ray angiograms using gabor filters and differential evolution.

PubMed

Cervantes-Sanchez, Fernando; Cruz-Aceves, Ivan; Hernandez-Aguirre, Arturo; Solorio-Meza, Sergio; Cordova-Fraga, Teodoro; Aviña-Cervantes, Juan Gabriel

2018-08-01

Segmentation of coronary arteries in X-ray angiograms represents an essential task for computer-aided diagnosis, since it can help cardiologists in diagnosing and monitoring vascular abnormalities. Due to the main disadvantages of the X-ray angiograms are the nonuniform illumination, and the weak contrast between blood vessels and image background, different vessel enhancement methods have been introduced. In this paper, a novel method for blood vessel enhancement based on Gabor filters tuned using the optimization strategy of Differential evolution (DE) is proposed. Because the Gabor filters are governed by three different parameters, the optimal selection of those parameters is highly desirable in order to maximize the vessel detection rate while reducing the computational cost of the training stage. To obtain the optimal set of parameters for the Gabor filters, the area (Az) under the receiver operating characteristics curve is used as objective function. In the experimental results, the proposed method achieves an A z =0.9388 in a training set of 40 images, and for a test set of 40 images it obtains the highest performance with an A z =0.9538 compared with six state-of-the-art vessel detection methods. Finally, the proposed method achieves an accuracy of 0.9423 for vessel segmentation using the test set. In addition, the experimental results have also shown that the proposed method can be highly suitable for clinical decision support in terms of computational time and vessel segmentation performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identification of everyday objects on the basis of Gaborized outline versions

PubMed Central

Sassi, Michaël; Vancleef, Kathleen; Machilsen, Bart; Panis, Sven; Wagemans, Johan

2010-01-01

Using outlines derived from a widely used set of line drawings, we created stimuli geared towards the investigation of contour integration and texture segmentation using shapes of everyday objects. Each stimulus consisted of Gabor elements positioned and oriented curvilinearly along the outline of an object, embedded within a larger Gabor array of homogeneous density. We created six versions of the resulting Gaborized outline stimuli by varying the orientations of elements inside and outside the outline. Data from two experiments, in which participants attempted to identify the objects in the stimuli, provide norms for identifiability and name agreement, and show differences in identifiability between stimulus versions. While there was substantial variability between the individual objects in our stimulus set, further analyses suggest a number of stimulus properties which are generally predictive of identification performance. The stimuli and the accompanying normative data, both available on our website (http://www.gestaltrevision.be/sources/gaboroutlines), provide a useful tool to further investigate contour integration and texture segmentation in both normal and clinical populations, especially when top-down influences on these processes, such as the role of prior knowledge of familiar objects, are of main interest. PMID:23145218

Identification of everyday objects on the basis of Gaborized outline versions.

PubMed

Sassi, Michaël; Vancleef, Kathleen; Machilsen, Bart; Panis, Sven; Wagemans, Johan

2010-01-01

Using outlines derived from a widely used set of line drawings, we created stimuli geared towards the investigation of contour integration and texture segmentation using shapes of everyday objects. Each stimulus consisted of Gabor elements positioned and oriented curvilinearly along the outline of an object, embedded within a larger Gabor array of homogeneous density. We created six versions of the resulting Gaborized outline stimuli by varying the orientations of elements inside and outside the outline. Data from two experiments, in which participants attempted to identify the objects in the stimuli, provide norms for identifiability and name agreement, and show differences in identifiability between stimulus versions. While there was substantial variability between the individual objects in our stimulus set, further analyses suggest a number of stimulus properties which are generally predictive of identification performance. The stimuli and the accompanying normative data, both available on our website (http://www.gestaltrevision.be/sources/gaboroutlines), provide a useful tool to further investigate contour integration and texture segmentation in both normal and clinical populations, especially when top-down influences on these processes, such as the role of prior knowledge of familiar objects, are of main interest.

Identity Recognition Algorithm Using Improved Gabor Feature Selection of Gait Energy Image

NASA Astrophysics Data System (ADS)

Chao, LIANG; Ling-yao, JIA; Dong-cheng, SHI

2017-01-01

This paper describes an effective gait recognition approach based on Gabor features of gait energy image. In this paper, the kernel Fisher analysis combined with kernel matrix is proposed to select dominant features. The nearest neighbor classifier based on whitened cosine distance is used to discriminate different gait patterns. The approach proposed is tested on the CASIA and USF gait databases. The results show that our approach outperforms other state of gait recognition approaches in terms of recognition accuracy and robustness.

Linearity Can Account for the Similarity Among Conventional, Frequency-Doubling, and Gabor-Based Perimetric Tests in the Glaucomatous Macula

PubMed Central

DUL, MITCHELL W.; SWANSON, WILLIAM H.

2006-01-01

Purposes The purposes of this study are to compare macular perimetric sensitivities for conventional size III, frequency-doubling, and Gabor stimuli in terms of Weber contrast and to provide a theoretical interpretation of the results. Methods Twenty-two patients with glaucoma performed four perimetric tests: a conventional Swedish Interactive Threshold Algorithm (SITA) 10-2 test with Goldmann size III stimuli, two frequency-doubling tests (FDT 10-2, FDT Macula) with counterphase-modulated grating stimuli, and a laboratory-designed test with Gabor stimuli. Perimetric sensitivities were converted to the reciprocal of Weber contrast and sensitivities from different tests were compared using the Bland-Altman method. Effects of ganglion cell loss on perimetric sensitivities were then simulated with a two-stage neural model. Results The average perimetric loss was similar for all stimuli until advanced stages of ganglion cell loss, in which perimetric loss tended to be greater for size III stimuli than for frequency-doubling and Gabor stimuli. Comparison of the experimental data and model simulation suggests that, in the macula, linear relations between ganglion cell loss and perimetric sensitivity loss hold for all three stimuli. Conclusions Linear relations between perimetric loss and ganglion cell loss for all three stimuli can account for the similarity in perimetric loss until advanced stages. The results do not support the hypothesis that redundancy for frequency-doubling stimuli is lower than redundancy for size III stimuli. PMID:16840860

Extracting tissue deformation using Gabor filter banks

NASA Astrophysics Data System (ADS)

Montillo, Albert; Metaxas, Dimitris; Axel, Leon

2004-04-01

This paper presents a new approach for accurate extraction of tissue deformation imaged with tagged MR. Our method, based on banks of Gabor filters, adjusts (1) the aspect and (2) orientation of the filter"s envelope and adjusts (3) the radial frequency and (4) angle of the filter"s sinusoidal grating to extract information about the deformation of tissue. The method accurately extracts tag line spacing, orientation, displacement and effective contrast. Existing, non-adaptive methods often fail to recover useful displacement information in the proximity of tissue boundaries while our method works in the proximity of the boundaries. We also present an interpolation method to recover all tag information at a finer resolution than the filter bank parameters. Results are shown on simulated images of translating and contracting tissue.

Gabor Deconvolution as Preliminary Method to Reduce Pitfall in Deeper Target Seismic Data

NASA Astrophysics Data System (ADS)

Oktariena, M.; Triyoso, W.

2018-03-01

Anelastic attenuation process during seismic wave propagation is the trigger of seismic non-stationary characteristic. An absorption and a scattering of energy are causing the seismic energy loss as the depth increasing. A series of thin reservoir layers found in the study area is located within Talang Akar Fm. Level, showing an indication of interpretation pitfall due to attenuation effect commonly occurred in deeper level seismic data. Attenuation effect greatly influences the seismic images of deeper target level, creating pitfalls in several aspect. Seismic amplitude in deeper target level often could not represent its real subsurface character due to a low amplitude value or a chaotic event nearing the Basement. Frequency wise, the decaying could be seen as the frequency content diminishing in deeper target. Meanwhile, seismic amplitude is the simple tool to point out Direct Hydrocarbon Indicator (DHI) in preliminary Geophysical study before a further advanced interpretation method applied. A quick-look of Post-Stack Seismic Data shows the reservoir associated with a bright spot DHI while another bigger bright spot body detected in the North East area near the field edge. A horizon slice confirms a possibility that the other bright spot zone has smaller delineation; an interpretation pitfall commonly occurs in deeper level of seismic. We evaluates this pitfall by applying Gabor Deconvolution to address the attenuation problem. Gabor Deconvolution forms a Partition of Unity to factorize the trace into smaller convolution window that could be processed as stationary packets. Gabor Deconvolution estimates both the magnitudes of source signature alongside its attenuation function. The enhanced seismic shows a better imaging in the pitfall area that previously detected as a vast bright spot zone. When the enhanced seismic is used for further advanced reprocessing process, the Seismic Impedance and Vp/Vs Ratio slices show a better reservoir delineation, in which the

Face Recognition Using Local Quantized Patterns and Gabor Filters

NASA Astrophysics Data System (ADS)

Khryashchev, V.; Priorov, A.; Stepanova, O.; Nikitin, A.

2015-05-01

The problem of face recognition in a natural or artificial environment has received a great deal of researchers' attention over the last few years. A lot of methods for accurate face recognition have been proposed. Nevertheless, these methods often fail to accurately recognize the person in difficult scenarios, e.g. low resolution, low contrast, pose variations, etc. We therefore propose an approach for accurate and robust face recognition by using local quantized patterns and Gabor filters. The estimation of the eye centers is used as a preprocessing stage. The evaluation of our algorithm on different samples from a standardized FERET database shows that our method is invariant to the general variations of lighting, expression, occlusion and aging. The proposed approach allows about 20% correct recognition accuracy increase compared with the known face recognition algorithms from the OpenCV library. The additional use of Gabor filters can significantly improve the robustness to changes in lighting conditions.

Segmentation of Coronary Angiograms Using Gabor Filters and Boltzmann Univariate Marginal Distribution Algorithm

PubMed Central

Cervantes-Sanchez, Fernando; Hernandez-Aguirre, Arturo; Solorio-Meza, Sergio; Ornelas-Rodriguez, Manuel; Torres-Cisneros, Miguel

2016-01-01

This paper presents a novel method for improving the training step of the single-scale Gabor filters by using the Boltzmann univariate marginal distribution algorithm (BUMDA) in X-ray angiograms. Since the single-scale Gabor filters (SSG) are governed by three parameters, the optimal selection of the SSG parameters is highly desirable in order to maximize the detection performance of coronary arteries while reducing the computational time. To obtain the best set of parameters for the SSG, the area (A z) under the receiver operating characteristic curve is used as fitness function. Moreover, to classify vessel and nonvessel pixels from the Gabor filter response, the interclass variance thresholding method has been adopted. The experimental results using the proposed method obtained the highest detection rate with A z = 0.9502 over a training set of 40 images and A z = 0.9583 with a test set of 40 images. In addition, the experimental results of vessel segmentation provided an accuracy of 0.944 with the test set of angiograms. PMID:27738422

Experimental foundation of the Gabor-Nelson theory applied to boundaries which are non-insulating.

PubMed

Troquet, J; Lambin, P; Nelson, C V

1985-06-07

In order to found the application of the Gabor-Nelson theory to non-insulating boundaries, we have used a network which we have divided into two parts: a core energized by a source sink pair and an appendage, the conductivity of which may or may not differ from that of the core. By ignoring the appendage and by applying the Gabor-Nelson method to the restricted perimeter as if it were totally insulating, we stress the errors made in computing the dipole strength, orientation and position and how they are influenced by the dipole eccentricity, by its orientation with respect to the junction between the added portion and the core, and by a change in conductivity between the same compartments. Finally, we restore the dipole characteristics by using the appropriate correction derived from theory. Comparing the later results to those obtained by applying the Gabor-Nelson method to the whole insulating boundary leads to the conclusion that the correction is founded and must be taken into account.

Hybrid Discrete Wavelet Transform and Gabor Filter Banks Processing for Features Extraction from Biomedical Images

PubMed Central

Lahmiri, Salim; Boukadoum, Mounir

2013-01-01

A new methodology for automatic feature extraction from biomedical images and subsequent classification is presented. The approach exploits the spatial orientation of high-frequency textural features of the processed image as determined by a two-step process. First, the two-dimensional discrete wavelet transform (DWT) is applied to obtain the HH high-frequency subband image. Then, a Gabor filter bank is applied to the latter at different frequencies and spatial orientations to obtain new Gabor-filtered image whose entropy and uniformity are computed. Finally, the obtained statistics are fed to a support vector machine (SVM) binary classifier. The approach was validated on mammograms, retina, and brain magnetic resonance (MR) images. The obtained classification accuracies show better performance in comparison to common approaches that use only the DWT or Gabor filter banks for feature extraction. PMID:27006906

Holonomy, quantum mechanics and the signal-tuned Gabor approach to the striate cortex

NASA Astrophysics Data System (ADS)

Torreão, José R. A.

2016-02-01

It has been suggested that an appeal to holographic and quantum properties will be ultimately required for the understanding of higher brain functions. On the other hand, successful quantum-like approaches to cognitive and behavioral processes bear witness to the usefulness of quantum prescriptions as applied to the analysis of complex non-quantum systems. Here, we show that the signal-tuned Gabor approach for modeling cortical neurons, although not based on quantum assumptions, also admits a quantum-like interpretation. Recently, the equation of motion for the signal-tuned complex cell response has been derived and proven equivalent to the Schrödinger equation for a dissipative quantum system whose solutions come under two guises: as plane-wave and Airy-packet responses. By interpreting the squared magnitude of the plane-wave solution as a probability density, in accordance with the quantum mechanics prescription, we arrive at a Poisson spiking probability — a common model of neuronal response — while spike propagation can be described by the Airy-packet solution. The signal-tuned approach is also proven consistent with holonomic brain theories, as it is based on Gabor functions which provide a holographic representation of the cell’s input, in the sense that any restricted subset of these functions still allows stimulus reconstruction.

Advanced Beamforming Concepts: Source Localization Using the Bispectrum, Gabor Transform, Wigner-Ville Distribution, and Nonstationary Signal Representation

DTIC Science & Technology

1991-12-01

TRANSFORM, WIGNER - VILLE DISTRIBUTION , AND NONSTATIONARY SIGNAL REPRESENTATIONS 6. AUTHOR(S) J. C. Allen 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS...bispectrum yields a bispectral direction finder. Estimates of time-frequency distributions produce Wigner - Ville and Gabor direction-finders. Some types...Beamforming Concepts: Source Localization Using the Bispectrum, Gabor Transform, Wigner - Ville Distribution , and Nonstationary Signal Representations

Hierarchical probabilistic Gabor and MRF segmentation of brain tumours in MRI volumes.

PubMed

Subbanna, Nagesh K; Precup, Doina; Collins, D Louis; Arbel, Tal

2013-01-01

In this paper, we present a fully automated hierarchical probabilistic framework for segmenting brain tumours from multispectral human brain magnetic resonance images (MRIs) using multiwindow Gabor filters and an adapted Markov Random Field (MRF) framework. In the first stage, a customised Gabor decomposition is developed, based on the combined-space characteristics of the two classes (tumour and non-tumour) in multispectral brain MRIs in order to optimally separate tumour (including edema) from healthy brain tissues. A Bayesian framework then provides a coarse probabilistic texture-based segmentation of tumours (including edema) whose boundaries are then refined at the voxel level through a modified MRF framework that carefully separates the edema from the main tumour. This customised MRF is not only built on the voxel intensities and class labels as in traditional MRFs, but also models the intensity differences between neighbouring voxels in the likelihood model, along with employing a prior based on local tissue class transition probabilities. The second inference stage is shown to resolve local inhomogeneities and impose a smoothing constraint, while also maintaining the appropriate boundaries as supported by the local intensity difference observations. The method was trained and tested on the publicly available MICCAI 2012 Brain Tumour Segmentation Challenge (BRATS) Database [1] on both synthetic and clinical volumes (low grade and high grade tumours). Our method performs well compared to state-of-the-art techniques, outperforming the results of the top methods in cases of clinical high grade and low grade tumour core segmentation by 40% and 45% respectively.

The Two-Dimensional Gabor Function Adapted to Natural Image Statistics: A Model of Simple-Cell Receptive Fields and Sparse Structure in Images.

PubMed

Loxley, P N

2017-10-01

The two-dimensional Gabor function is adapted to natural image statistics, leading to a tractable probabilistic generative model that can be used to model simple cell receptive field profiles, or generate basis functions for sparse coding applications. Learning is found to be most pronounced in three Gabor function parameters representing the size and spatial frequency of the two-dimensional Gabor function and characterized by a nonuniform probability distribution with heavy tails. All three parameters are found to be strongly correlated, resulting in a basis of multiscale Gabor functions with similar aspect ratios and size-dependent spatial frequencies. A key finding is that the distribution of receptive-field sizes is scale invariant over a wide range of values, so there is no characteristic receptive field size selected by natural image statistics. The Gabor function aspect ratio is found to be approximately conserved by the learning rules and is therefore not well determined by natural image statistics. This allows for three distinct solutions: a basis of Gabor functions with sharp orientation resolution at the expense of spatial-frequency resolution, a basis of Gabor functions with sharp spatial-frequency resolution at the expense of orientation resolution, or a basis with unit aspect ratio. Arbitrary mixtures of all three cases are also possible. Two parameters controlling the shape of the marginal distributions in a probabilistic generative model fully account for all three solutions. The best-performing probabilistic generative model for sparse coding applications is found to be a gaussian copula with Pareto marginal probability density functions.

Local gradient Gabor pattern (LGGP) with applications in face recognition, cross-spectral matching, and soft biometrics

NASA Astrophysics Data System (ADS)

Chen, Cunjian; Ross, Arun

2013-05-01

Researchers in face recognition have been using Gabor filters for image representation due to their robustness to complex variations in expression and illumination. Numerous methods have been proposed to model the output of filter responses by employing either local or global descriptors. In this work, we propose a novel but simple approach for encoding Gradient information on Gabor-transformed images to represent the face, which can be used for identity, gender and ethnicity assessment. Extensive experiments on the standard face benchmark FERET (Visible versus Visible), as well as the heterogeneous face dataset HFB (Near-infrared versus Visible), suggest that the matching performance due to the proposed descriptor is comparable against state-of-the-art descriptor-based approaches in face recognition applications. Furthermore, the same feature set is used in the framework of a Collaborative Representation Classification (CRC) scheme for deducing soft biometric traits such as gender and ethnicity from face images in the AR, Morph and CAS-PEAL databases.

Detection of retinal nerve fiber layer defects in retinal fundus images using Gabor filtering

NASA Astrophysics Data System (ADS)

Hayashi, Yoshinori; Nakagawa, Toshiaki; Hatanaka, Yuji; Aoyama, Akira; Kakogawa, Masakatsu; Hara, Takeshi; Fujita, Hiroshi; Yamamoto, Tetsuya

2007-03-01

Retinal nerve fiber layer defect (NFLD) is one of the most important findings for the diagnosis of glaucoma reported by ophthalmologists. However, such changes could be overlooked, especially in mass screenings, because ophthalmologists have limited time to search for a number of different changes for the diagnosis of various diseases such as diabetes, hypertension and glaucoma. Therefore, the use of a computer-aided detection (CAD) system can improve the results of diagnosis. In this work, a technique for the detection of NFLDs in retinal fundus images is proposed. In the preprocessing step, blood vessels are "erased" from the original retinal fundus image by using morphological filtering. The preprocessed image is then transformed into a rectangular array. NFLD regions are observed as vertical dark bands in the transformed image. Gabor filtering is then applied to enhance the vertical dark bands. False positives (FPs) are reduced by a rule-based method which uses the information of the location and the width of each candidate region. The detected regions are back-transformed into the original configuration. In this preliminary study, 71% of NFLD regions are detected with average number of FPs of 3.2 per image. In conclusion, we have developed a technique for the detection of NFLDs in retinal fundus images. Promising results have been obtained in this initial study.

Adaptive phase extraction: incorporating the Gabor transform in the matching pursuit algorithm.

PubMed

Wacker, Matthias; Witte, Herbert

2011-10-01

Short-time Fourier transform (STFT), Gabor transform (GT), wavelet transform (WT), and the Wigner-Ville distribution (WVD) are just some examples of time-frequency analysis methods which are frequently applied in biomedical signal analysis. However, all of these methods have their individual drawbacks. The STFT, GT, and WT have a time-frequency resolution that is determined by algorithm parameters and the WVD is contaminated by cross terms. In 1993, Mallat and Zhang introduced the matching pursuit (MP) algorithm that decomposes a signal into a sum of atoms and uses a cross-term free pseudo-WVD to generate a data-adaptive power distribution in the time-frequency space. Thus, it solved some of the problems of the GT and WT but lacks phase information that is crucial e.g., for synchronization analysis. We introduce a new time-frequency analysis method that combines the MP with a pseudo-GT. Therefore, the signal is decomposed into a set of Gabor atoms. Afterward, each atom is analyzed with a Gabor analysis, where the time-domain gaussian window of the analysis matches that of the specific atom envelope. A superposition of the single time-frequency planes gives the final result. This is the first time that a complete analysis of the complex time-frequency plane can be performed in a fully data-adaptive and frequency-selective manner. We demonstrate the capabilities of our approach on a simulation and on real-life magnetoencephalogram data.

Gabor Filters and Neural Networks for Segmentation of Synthetic Aperture Radar Imagery

DTIC Science & Technology

1990-12-01

unending enthusiasm focused my efforts. I would also like to thank Dr Matthew Kabrisky and Maj Rogers for their enlightening pattern recognition courses...merit in neurophysiology . Specifically, interest in the Gabor function results from recent research demonstrating its close approximation to measured

Face recognition via Gabor and convolutional neural network

NASA Astrophysics Data System (ADS)

Lu, Tongwei; Wu, Menglu; Lu, Tao

2018-04-01

In recent years, the powerful feature learning and classification ability of convolutional neural network have attracted widely attention. Compared with the deep learning, the traditional machine learning algorithm has a good explanatory which deep learning does not have. Thus, In this paper, we propose a method to extract the feature of the traditional algorithm as the input of convolution neural network. In order to reduce the complexity of the network, the kernel function of Gabor wavelet is used to extract the feature from different position, frequency and direction of target image. It is sensitive to edge of image which can provide good direction and scale selection. The extraction of the image from eight directions on a scale are as the input of network that we proposed. The network have the advantage of weight sharing and local connection and texture feature of the input image can reduce the influence of facial expression, gesture and illumination. At the same time, we introduced a layer which combined the results of the pooling and convolution can extract deeper features. The training network used the open source caffe framework which is beneficial to feature extraction. The experiment results of the proposed method proved that the network structure effectively overcame the barrier of illumination and had a good robustness as well as more accurate and rapid than the traditional algorithm.

3D shape recovery from image focus using Gabor features

NASA Astrophysics Data System (ADS)

Mahmood, Fahad; Mahmood, Jawad; Zeb, Ayesha; Iqbal, Javaid

2018-04-01

Recovering an accurate and precise depth map from a set of acquired 2-D image dataset of the target object each having different focus information is an ultimate goal of 3-D shape recovery. Focus measure algorithm plays an important role in this architecture as it converts the corresponding color value information into focus information which will be then utilized for recovering depth map. This article introduces Gabor features as focus measure approach for recovering depth map from a set of 2-D images. Frequency and orientation representation of Gabor filter features is similar to human visual system and normally applied for texture representation. Due to its little computational complexity, sharp focus measure curve, robust to random noise sources and accuracy, it is considered as superior alternative to most of recently proposed 3-D shape recovery approaches. This algorithm is deeply investigated on real image sequences and synthetic image dataset. The efficiency of the proposed scheme is also compared with the state of art 3-D shape recovery approaches. Finally, by means of two global statistical measures, root mean square error and correlation, we claim that this approach, in spite of simplicity, generates accurate results.

Analysis of frequency shifting in seismic signals using Gabor-Wigner transform

NASA Astrophysics Data System (ADS)

Kumar, Roshan; Sumathi, P.; Kumar, Ashok

2015-12-01

A hybrid time-frequency method known as Gabor-Wigner transform (GWT) is introduced in this paper for examining the time-frequency patterns of earthquake damaged buildings. GWT is developed by combining the Gabor transform (GT) and Wigner-Ville distribution (WVD). GT and WVD have been used separately on synthetic and recorded earthquake data to identify frequency shifting due to earthquake damages, but GT is prone to windowing effect and WVD involves ambiguity function. Hence to obtain better clarity and to remove the cross terms (frequency interference), GT and WVD are judiciously combined and the resultant GWT used to identify frequency shifting. Synthetic seismic response of an instrumented building and real-time earthquake data recorded on the building were investigated using GWT. It is found that GWT offers good accuracy for even slow variations in frequency, good time-frequency resolution, and localized response. Presented results confirm the efficacy of GWT when compared with GT and WVD used separately. Simulation results were quantified by the Renyi entropy measures and GWT shown to be an adequate technique in identifying localized response for structural damage detection.

Properties of an improved Gabor wavelet transform and its applications to seismic signal processing and interpretation

NASA Astrophysics Data System (ADS)

Ji, Zhan-Huai; Yan, Sheng-Gang

2017-12-01

This paper presents an analytical study of the complete transform of improved Gabor wavelets (IGWs), and discusses its application to the processing and interpretation of seismic signals. The complete Gabor wavelet transform has the following properties. First, unlike the conventional transform, the improved Gabor wavelet transform (IGWT) maps time domain signals to the time-frequency domain instead of the time-scale domain. Second, the IGW's dominant frequency is fixed, so the transform can perform signal frequency division, where the dominant frequency components of the extracted sub-band signal carry essentially the same information as the corresponding components of the original signal, and the subband signal bandwidth can be regulated effectively by the transform's resolution factor. Third, a time-frequency filter consisting of an IGWT and its inverse transform can accurately locate target areas in the time-frequency field and perform filtering in a given time-frequency range. The complete IGW transform's properties are investigated using simulation experiments and test cases, showing positive results for seismic signal processing and interpretation, such as enhancing seismic signal resolution, permitting signal frequency division, and allowing small faults to be identified.

Crack Detection in Concrete Tunnels Using a Gabor Filter Invariant to Rotation.

PubMed

Medina, Roberto; Llamas, José; Gómez-García-Bermejo, Jaime; Zalama, Eduardo; Segarra, Miguel José

2017-07-20

In this article, a system for the detection of cracks in concrete tunnel surfaces, based on image sensors, is presented. Both data acquisition and processing are covered. Linear cameras and proper lighting are used for data acquisition. The required resolution of the camera sensors and the number of cameras is discussed in terms of the crack size and the tunnel type. Data processing is done by applying a new method called Gabor filter invariant to rotation, allowing the detection of cracks in any direction. The parameter values of this filter are set by using a modified genetic algorithm based on the Differential Evolution optimization method. The detection of the pixels belonging to cracks is obtained to a balanced accuracy of 95.27%, thus improving the results of previous approaches.

Improvement on Gabor order tracking and objective comparison with Vold Kalman filtering order tracking

NASA Astrophysics Data System (ADS)

Pan, Min-Chun; Liao, Shiu-Wei; Chiu, Chun-Chin

2007-02-01

The waveform-reconstruction schemes of order tracking (OT) such as the Gabor and the Vold-Kalman filtering (VKF) techniques can extract specific order and/or spectral components in addition to characterizing the processed signal in rpm-frequency domain. The study first improves the Gabor OT (GOT) technique to handle the order-crossing problem, and then objectively compares the features of the improved GOT scheme and the angular-displacement VKF OT technique. It is numerically observed the improved method performs less accurately than the VKF_OT scheme at the crossing occurrences, but without end effect in the reconstructed waveform. As OT is not exact science, it may well be that the decrease in computation time can justify the reduced accuracy. The characterisation and discrimination of riding noise with crossing orders emitted by an electrical scooter are conducted as an example of the application.

3D wide field-of-view Gabor-domain optical coherence microscopy advancing real-time in-vivo imaging and metrology

NASA Astrophysics Data System (ADS)

Canavesi, Cristina; Cogliati, Andrea; Hayes, Adam; Tankam, Patrice; Santhanam, Anand; Rolland, Jannick P.

2017-02-01

Real-time volumetric high-definition wide-field-of-view in-vivo cellular imaging requires micron-scale resolution in 3D. Compactness of the handheld device and distortion-free images with cellular resolution are also critically required for onsite use in clinical applications. By integrating a custom liquid lens-based microscope and a dual-axis MEMS scanner in a compact handheld probe, Gabor-domain optical coherence microscopy (GD-OCM) breaks the lateral resolution limit of optical coherence tomography through depth, overcoming the tradeoff between numerical aperture and depth of focus, enabling advances in biotechnology. Furthermore, distortion-free imaging with no post-processing is achieved with a compact, lightweight handheld MEMS scanner that obtained a 12-fold reduction in volume and 17-fold reduction in weight over a previous dual-mirror galvanometer-based scanner. Approaching the holy grail of medical imaging - noninvasive real-time imaging with histologic resolution - GD-OCM demonstrates invariant resolution of 2 μm throughout a volume of 1 x 1 x 0.6 mm3, acquired and visualized in less than 2 minutes with parallel processing on graphics processing units. Results on the metrology of manufactured materials and imaging of human tissue with GD-OCM are presented.

Thermographic image analysis for classification of ACL rupture disease, bone cancer, and feline hyperthyroid, with Gabor filters

NASA Astrophysics Data System (ADS)

Alvandipour, Mehrdad; Umbaugh, Scott E.; Mishra, Deependra K.; Dahal, Rohini; Lama, Norsang; Marino, Dominic J.; Sackman, Joseph

2017-05-01

Thermography and pattern classification techniques are used to classify three different pathologies in veterinary images. Thermographic images of both normal and diseased animals were provided by the Long Island Veterinary Specialists (LIVS). The three pathologies are ACL rupture disease, bone cancer, and feline hyperthyroid. The diagnosis of these diseases usually involves radiology and laboratory tests while the method that we propose uses thermographic images and image analysis techniques and is intended for use as a prescreening tool. Images in each category of pathologies are first filtered by Gabor filters and then various features are extracted and used for classification into normal and abnormal classes. Gabor filters are linear filters that can be characterized by the two parameters wavelength λ and orientation θ. With two different wavelength and five different orientations, a total of ten different filters were studied. Different combinations of camera views, filters, feature vectors, normalization methods, and classification methods, produce different tests that were examined and the sensitivity, specificity and success rate for each test were produced. Using the Gabor features alone, sensitivity, specificity, and overall success rates of 85% for each of the pathologies was achieved.

Shape detection of Gaborized outline versions of everyday objects

PubMed Central

Sassi, Michaël; Machilsen, Bart; Wagemans, Johan

2012-01-01

We previously tested the identifiability of six versions of Gaborized outlines of everyday objects, differing in the orientations assigned to elements inside and outside the outline. We found significant differences in identifiability between the versions, and related a number of stimulus metrics to identifiability [Sassi, M., Vancleef, K., Machilsen, B., Panis, S., & Wagemans, J. (2010). Identification of everyday objects on the basis of Gaborized outline versions. i-Perception, 1(3), 121–142]. In this study, after retesting the identifiability of new variants of three of the stimulus versions, we tested their robustness to local orientation jitter in a detection experiment. In general, our results replicated the key findings from the previous study, and allowed us to substantiate our earlier interpretations of the effects of our stimulus metrics and of the performance differences between the different stimulus versions. The results of the detection task revealed a different ranking order of stimulus versions than the identification task. By examining the parallels and differences between the effects of our stimulus metrics in the two tasks, we found evidence for a trade-off between shape detectability and identifiability. The generally simple and smooth shapes that yield the strongest contour integration and most robust detectability tend to lack the distinguishing features necessary for clear-cut identification. Conversely, contours that do contain such identifying features tend to be inherently more complex and, therefore, yield weaker integration and less robust detectability. PMID:23483752

Adaptive polarization image fusion based on regional energy dynamic weighted average

NASA Astrophysics Data System (ADS)

Zhao, Yong-Qiang; Pan, Quan; Zhang, Hong-Cai

2005-11-01

According to the principle of polarization imaging and the relation between Stokes parameters and the degree of linear polarization, there are much redundant and complementary information in polarized images. Since man-made objects and natural objects can be easily distinguished in images of degree of linear polarization and images of Stokes parameters contain rich detailed information of the scene, the clutters in the images can be removed efficiently while the detailed information can be maintained by combining these images. An algorithm of adaptive polarization image fusion based on regional energy dynamic weighted average is proposed in this paper to combine these images. Through an experiment and simulations, most clutters are removed by this algorithm. The fusion method is used for different light conditions in simulation, and the influence of lighting conditions on the fusion results is analyzed.

Gabor domain optical coherence microscopy

NASA Astrophysics Data System (ADS)

Murali, Supraja

Time domain Optical Coherence Tomography (TD-OCT), first reported in 1991, makes use of the low temporal coherence properties of a NIR broadband laser to create depth sectioning of up to 2mm under the surface using optical interferometry and point to point scanning. Prior and ongoing work in OCT in the research community has concentrated on improving axial resolution through the development of broadband sources and speed of image acquisition through new techniques such as Spectral domain OCT (SD-OCT). In SD-OCT, an entire depth scan is acquired at once with a low numerical aperture (NA) objective lens focused at a fixed point within the sample. In this imaging geometry, a longer depth of focus is achieved at the expense of lateral resolution, which is typically limited to 10 to 20 mum. Optical Coherence Microscopy (OCM), introduced in 1994, combined the advantages of high axial resolution obtained in OCT with high lateral resolution obtained by increasing the NA of the microscope placed in the sample arm. However, OCM presented trade-offs caused by the inverse quadratic relationship between the NA and the DOF of the optics used. For applications requiring high lateral resolution, such as cancer diagnostics, several solutions have been proposed including the periodic manual re-focusing of the objective lens in the time domain as well as the spectral domain C-mode configuration in order to overcome the loss in lateral resolution outside the DOF. In this research, we report for the first time, high speed, sub-cellular imaging (lateral resolution of 2 mum) in OCM using a Gabor domain image processing algorithm with a custom designed and fabricated dynamic focus microscope interfaced to a Ti:Sa femtosecond laser centered at 800 nm within an SD-OCM configuration. It is envisioned that this technology will provide a non-invasive replacement for the current practice of multiple biopsies for skin cancer diagnosis. The research reported here presents three important advances

Phase stability analysis of chirp evoked auditory brainstem responses by Gabor frame operators.

PubMed

Corona-Strauss, Farah I; Delb, Wolfgang; Schick, Bernhard; Strauss, Daniel J

2009-12-01

We have recently shown that click evoked auditory brainstem responses (ABRs) can be efficiently processed using a novelty detection paradigm. Here, ABRs as a large-scale reflection of a stimulus locked neuronal group synchronization at the brainstem level are detected as novel instance-novel as compared to the spontaneous activity which does not exhibit a regular stimulus locked synchronization. In this paper we propose for the first time Gabor frame operators as an efficient feature extraction technique for ABR single sweep sequences that is in line with this paradigm. In particular, we use this decomposition technique to derive the Gabor frame phase stability (GFPS) of sweep sequences of click and chirp evoked ABRs. We show that the GFPS of chirp evoked ABRs provides a stable discrimination of the spontaneous activity from stimulations above the hearing threshold with a small number of sweeps, even at low stimulation intensities. It is concluded that the GFPS analysis represents a robust feature extraction method for ABR single sweep sequences. Further studies are necessary to evaluate the value of the presented approach for clinical applications.

Weight Perturbation Alters Leptin Signal Transduction in a Region-Specific Manner throughout the Brain

PubMed Central

Morabito, Michael V.; Ravussin, Yann; Mueller, Bridget R.; Skowronski, Alicja A.; Watanabe, Kazuhisa; Foo, Kylie S.; Lee, Samuel X.; Lehmann, Anders; Hjorth, Stephan; Zeltser, Lori M.; LeDuc, Charles A.; Leibel, Rudolph L.

2017-01-01

Diet-induced obesity (DIO) resulting from consumption of a high fat diet (HFD) attenuates normal neuronal responses to leptin and may contribute to the metabolic defense of an acquired higher body weight in humans; the molecular bases for the persistence of this defense are unknown. We measured the responses of 23 brain regions to exogenous leptin in 4 different groups of weight- and/or diet-perturbed mice. Responses to leptin were assessed by quantifying pSTAT3 levels in brain nuclei 30 minutes following 3 mg/kg intraperitoneal leptin. HFD attenuated leptin sensing throughout the brain, but weight loss did not restore central leptin signaling to control levels in several brain regions important in energy homeostasis, including the arcuate and dorsomedial hypothalamic nuclei. Effects of diet on leptin signaling varied by brain region, with results dependent on the method of weight loss (restriction of calories of HFD, ad lib intake of standard mouse chow). High fat diet attenuates leptin signaling throughout the brain, but some brain regions maintain their ability to sense leptin. Weight loss restores leptin sensing to some degree in most (but not all) brain regions, while other brain regions display hypersensitivity to leptin following weight loss. Normal leptin sensing was restored in several brain regions, with the pattern of restoration dependent on the method of weight loss. PMID:28107353

LMethyR-SVM: Predict Human Enhancers Using Low Methylated Regions based on Weighted Support Vector Machines.

PubMed

Xu, Jingting; Hu, Hong; Dai, Yang

The identification of enhancers is a challenging task. Various types of epigenetic information including histone modification have been utilized in the construction of enhancer prediction models based on a diverse panel of machine learning schemes. However, DNA methylation profiles generated from the whole genome bisulfite sequencing (WGBS) have not been fully explored for their potential in enhancer prediction despite the fact that low methylated regions (LMRs) have been implied to be distal active regulatory regions. In this work, we propose a prediction framework, LMethyR-SVM, using LMRs identified from cell-type-specific WGBS DNA methylation profiles and a weighted support vector machine learning framework. In LMethyR-SVM, the set of cell-type-specific LMRs is further divided into three sets: reliable positive, like positive and likely negative, according to their resemblance to a small set of experimentally validated enhancers in the VISTA database based on an estimated non-parametric density distribution. Then, the prediction model is obtained by solving a weighted support vector machine. We demonstrate the performance of LMethyR-SVM by using the WGBS DNA methylation profiles derived from the human embryonic stem cell type (H1) and the fetal lung fibroblast cell type (IMR90). The predicted enhancers are highly conserved with a reasonable validation rate based on a set of commonly used positive markers including transcription factors, p300 binding and DNase-I hypersensitive sites. In addition, we show evidence that the large fraction of the LMethyR-SVM predicted enhancers are not predicted by ChromHMM in H1 cell type and they are more enriched for the FANTOM5 enhancers. Our work suggests that low methylated regions detected from the WGBS data are useful as complementary resources to histone modification marks in developing models for the prediction of cell-type-specific enhancers.

Optimal Window and Lattice in Gabor Transform. Application to Audio Analysis.

PubMed

Lachambre, Helene; Ricaud, Benjamin; Stempfel, Guillaume; Torrésani, Bruno; Wiesmeyr, Christoph; Onchis-Moaca, Darian

2015-01-01

This article deals with the use of optimal lattice and optimal window in Discrete Gabor Transform computation. In the case of a generalized Gaussian window, extending earlier contributions, we introduce an additional local window adaptation technique for non-stationary signals. We illustrate our approach and the earlier one by addressing three time-frequency analysis problems to show the improvements achieved by the use of optimal lattice and window: close frequencies distinction, frequency estimation and SNR estimation. The results are presented, when possible, with real world audio signals.

The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.

PubMed

St-Yves, Ghislain; Naselaris, Thomas

2017-06-20

We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map-a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: "where" parameters that characterize the location and extent of pooling over visual features, and "what" parameters that characterize tuning to visual features. The "where" parameters are analogous to classical receptive fields, while "what" parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation. We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model's application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep

Regional and seasonal analyses of weights in growing Angus cattle.

PubMed

Bradford, H L; Fragomeni, B O; Bertrand, J K; Lourenco, D A L; Misztal, I

2016-10-01

This study evaluated the impact of region and season on growth in Angus seed stock. To assess geographic differences, the United States was partitioned into 9 regions based on similar climate and topography related to cow-calf production. Seasonal effects were associated with the month that animals were weighed. The American Angus Association provided growth data, and records were assigned to regions based on the owner's zip code. Most Angus cattle were in the Cornbelt, Lower Plains, Rocky Mountain, Upper Plains, and Upper South regions, with proportionally fewer Angus in Texas compared with the national cow herd. Most calves were born in the spring, especially February and March. Weaning weights (WW; = 49,886) and yearling weights (YW; = 45,168) were modeled with fixed effects of age-of-dam class (WW only), weigh month, region, month-region interaction, and linear covariate of age. Random effects included contemporary group nested within month-region combination and residual. The significant month-region interaction ( < 0.0001) was expected because of the diverse production environments across the country and cyclical fluctuations in forage availability. Additionally, significant seasonal contrasts existed for several regions. Fall-born calves were heavier ( < 0.01) than spring-born calves in the hot and humid Lower South region coinciding with fall being the primary calving season. The North and Upper Plains regions had heavier, spring-born calves ( < 0.01), more than 90% spring calving, and colder climates. Interestingly, no seasonal WW or YW differences existed between spring- and fall-born calves in the upper South region despite challenging environmental conditions. Angus seed stock producers have used calving seasons to adapt to the specific environmental conditions in their regions and to optimize growth in young animals.

Identity with Jesus Christ: the case of Leon Gabor.

PubMed

Capps, Donald

2010-12-01

From July 1, 1959 to August 15, 1961, Milton Rokeach studied three male patients at Ypsilanti State Hospital who believed that they were Jesus Christ. They met regularly together with Rokeach and his research staff, a procedure designed to challenge their delusional systems. He believed that Leon Gabor, the youngest of the three, would be the most likely to abandon his delusional beliefs. Instead, Leon met the challenges that the procedure posed by creative elaborations of his delusional system, especially through the adoption of a new name that gave the initial appearance of the abandonment of his Christ identity but in fact drew on aspects of the real Jesus Christ's identity that were missing from his earlier self-representation.

Wigner-Ville distribution and Gabor transform in Doppler ultrasound signal processing.

PubMed

Ghofrani, S; Ayatollahi, A; Shamsollahi, M B

2003-01-01

Time-frequency distributions have been used extensively for nonstationary signal analysis, they describe how the frequency content of a signal is changing in time. The Wigner-Ville distribution (WVD) is the best known. The draw back of WVD is cross-term artifacts. An alternative to the WVD is Gabor transform (GT), a signal decomposition method, which displays the time-frequency energy of a signal on a joint t-f plane without generating considerable cross-terms. In this paper the WVD and GT of ultrasound echo signals are computed analytically.

Automated human skull landmarking with 2D Gabor wavelets

NASA Astrophysics Data System (ADS)

de Jong, Markus A.; Gül, Atilla; de Gijt, Jan Pieter; Koudstaal, Maarten J.; Kayser, Manfred; Wolvius, Eppo B.; Böhringer, Stefan

2018-05-01

Landmarking of CT scans is an important step in the alignment of skulls that is key in surgery planning, pre-/post-surgery comparisons, and morphometric studies. We present a novel method for automatically locating anatomical landmarks on the surface of cone beam CT-based image models of human skulls using 2D Gabor wavelets and ensemble learning. The algorithm is validated via human inter- and intra-rater comparisons on a set of 39 scans and a skull superimposition experiment with an established surgery planning software (Maxilim). Automatic landmarking results in an accuracy of 1–2 mm for a subset of landmarks around the nose area as compared to a gold standard derived from human raters. These landmarks are located in eye sockets and lower jaw, which is competitive with or surpasses inter-rater variability. The well-performing landmark subsets allow for the automation of skull superimposition in clinical applications. Our approach delivers accurate results, has modest training requirements (training set size of 30–40 items) and is generic, so that landmark sets can be easily expanded or modified to accommodate shifting landmark interests, which are important requirements for the landmarking of larger cohorts.

Digital tool for detecting diabetic retinopathy in retinography image using gabor transform

NASA Astrophysics Data System (ADS)

Morales, Y.; Nuñez, R.; Suarez, J.; Torres, C.

2017-01-01

Diabetic retinopathy is a chronic disease and is the leading cause of blindness in the population. The fundamental problem is that diabetic retinopathy is usually asymptomatic in its early stage and, in advanced stages, it becomes incurable, hence the importance of early detection. To detect diabetic retinopathy, the ophthalmologist examines the fundus by ophthalmoscopy, after sends the patient to get a Retinography. Sometimes, these retinography are not of good quality. This paper show the implementation of a digital tool that facilitates to ophthalmologist provide better patient diagnosis suffering from diabetic retinopathy, informing them that type of retinopathy has and to what degree of severity is find . This tool develops an algorithm in Matlab based on Gabor transform and in the application of digital filters to provide better and higher quality of retinography. The performance of algorithm has been compared with conventional methods obtaining resulting filtered images with better contrast and higher.

Accurate measurement of imaging photoplethysmographic signals based camera using weighted average

NASA Astrophysics Data System (ADS)

Pang, Zongguang; Kong, Lingqin; Zhao, Yuejin; Sun, Huijuan; Dong, Liquan; Hui, Mei; Liu, Ming; Liu, Xiaohua; Liu, Lingling; Li, Xiaohui; Li, Rongji

2018-01-01

Imaging Photoplethysmography (IPPG) is an emerging technique for the extraction of vital signs of human being using video recordings. IPPG technology with its advantages like non-contact measurement, low cost and easy operation has become one research hot spot in the field of biomedicine. However, the noise disturbance caused by non-microarterial area cannot be removed because of the uneven distribution of micro-arterial, different signal strength of each region, which results in a low signal noise ratio of IPPG signals and low accuracy of heart rate. In this paper, we propose a method of improving the signal noise ratio of camera-based IPPG signals of each sub-region of the face using a weighted average. Firstly, we obtain the region of interest (ROI) of a subject's face based camera. Secondly, each region of interest is tracked and feature-based matched in each frame of the video. Each tracked region of face is divided into 60x60 pixel block. Thirdly, the weights of PPG signal of each sub-region are calculated, based on the signal-to-noise ratio of each sub-region. Finally, we combine the IPPG signal from all the tracked ROI using weighted average. Compared with the existing approaches, the result shows that the proposed method takes modest but significant effects on improvement of signal noise ratio of camera-based PPG estimated and accuracy of heart rate measurement.

Automated railroad reconstruction from remote sensing image based on texture filter

NASA Astrophysics Data System (ADS)

Xiao, Jie; Lu, Kaixia

2018-03-01

Techniques of remote sensing have been improved incredibly in recent years and very accurate results and high resolution images can be acquired. There exist possible ways to use such data to reconstruct railroads. In this paper, an automated railroad reconstruction method from remote sensing images based on Gabor filter was proposed. The method is divided in three steps. Firstly, the edge-oriented railroad characteristics (such as line features) in a remote sensing image are detected using Gabor filter. Secondly, two response images with the filtering orientations perpendicular to each other are fused to suppress the noise and acquire a long stripe smooth region of railroads. Thirdly, a set of smooth regions can be extracted by firstly computing global threshold for the previous result image using Otsu's method and then converting it to a binary image based on the previous threshold. This workflow is tested on a set of remote sensing images and was found to deliver very accurate results in a quickly and highly automated manner.

Entropy Econometrics for combining regional economic forecasts: A Data-Weighted Prior Estimator

NASA Astrophysics Data System (ADS)

Fernández-Vázquez, Esteban; Moreno, Blanca

2017-10-01

Forecast combination has been studied in econometrics for a long time, and the literature has shown the superior performance of forecast combination over individual predictions. However, there is still controversy on which is the best procedure to specify the forecast weights. This paper explores the possibility of using a procedure based on Entropy Econometrics, which allows setting the weights for the individual forecasts as a mixture of different alternatives. In particular, we examine the ability of the Data-Weighted Prior Estimator proposed by Golan (J Econom 101(1):165-193, 2001) to combine forecasting models in a context of small sample sizes, a relative common scenario when dealing with time series for regional economies. We test the validity of the proposed approach using a simulation exercise and a real-world example that aims at predicting gross regional product growth rates for a regional economy. The forecasting performance of the Data-Weighted Prior Estimator proposed is compared with other combining methods. The simulation results indicate that in scenarios of heavily ill-conditioned datasets the approach suggested dominates other forecast combination strategies. The empirical results are consistent with the conclusions found in the numerical experiment.

Gestational weight gain and its associated factors in Harari Regional State: Institution based cross-sectional study, Eastern Ethiopia.

PubMed

Asefa, Fekede; Nemomsa, Dereje

2016-08-30

Gestational weight gain is an important factor that supports optimal outcome for mothers and their infant. Whereas women who do not gain enough weight during pregnancy have a risk of bearing a baby with low birth weight, those who gain excessive weight are at increased risk of preeclampsia and gestational diabetes. Nonetheless, data on gestational weight gain and its determinants are scarce in developing countries, as it is difficult to collect the information throughout the pregnancy period. Therefore, the aim of the study was to assess weight gain during pregnancy and its associated factors. The study employed a health facility based quantitative cross-sectional study design in Harari Regional State. The study included 411 women who had given birth at health institutions from January to July of 2014. The researchers collected both primary and secondary data by using a structured questionnaire and a checklist. Using logistic regression, the factors associated with gestational weight gain were assessed and, based on the United States Institute of Medicine criteria, gestational weight gains were categorized as inadequate, adequate and excessive. The study revealed that 69.3 %, 28 %, and 2.7 % of the women gained inadequate, adequate and excess gestational weight, respectively. The mean gestational weight gain was 8.96 (SD ±3.27) kg. The factors associated with adequate gestational weight gain were body mass index ≥ 25Kg/m(2) at early pregnancy (AOR = 3.2, 95 % CI 1.6, 6.3); engaging in regular physical exercise (AOR = 2.1, 95 % CI 1.2, 3.6); Antenatal care visit of ≥4 times (AOR = 2.9, 95 % CI 1.7, 5.2); consuming fruit and vegetable (AOR = 2.7, 95 % CI 1.2, 6.6), and meat (AOR = 2.7, 95 % CI 1.1, 97.2). Generally, a small proportion of the women gained adequate gestational weight. The women who were with higher body mass index at early pregnancy, who frequently visited Antenatal care visit, and who consumed diverse food items were

Multivariate matching pursuit in optimal Gabor dictionaries: theory and software with interface for EEG/MEG via Svarog

PubMed Central

2013-01-01

Background Matching pursuit algorithm (MP), especially with recent multivariate extensions, offers unique advantages in analysis of EEG and MEG. Methods We propose a novel construction of an optimal Gabor dictionary, based upon the metrics introduced in this paper. We implement this construction in a freely available software for MP decomposition of multivariate time series, with a user friendly interface via the Svarog package (Signal Viewer, Analyzer and Recorder On GPL, http://braintech.pl/svarog), and provide a hands-on introduction to its application to EEG. Finally, we describe numerical and mathematical optimizations used in this implementation. Results Optimal Gabor dictionaries, based on the metric introduced in this paper, for the first time allowed for a priori assessment of maximum one-step error of the MP algorithm. Variants of multivariate MP, implemented in the accompanying software, are organized according to the mathematical properties of the algorithms, relevant in the light of EEG/MEG analysis. Some of these variants have been successfully applied to both multichannel and multitrial EEG and MEG in previous studies, improving preprocessing for EEG/MEG inverse solutions and parameterization of evoked potentials in single trials; we mention also ongoing work and possible novel applications. Conclusions Mathematical results presented in this paper improve our understanding of the basics of the MP algorithm. Simple introduction of its properties and advantages, together with the accompanying stable and user-friendly Open Source software package, pave the way for a widespread and reproducible analysis of multivariate EEG and MEG time series and novel applications, while retaining a high degree of compatibility with the traditional, visual analysis of EEG. PMID:24059247

Order-crossing removal in Gabor order tracking by independent component analysis

NASA Astrophysics Data System (ADS)

Guo, Yu; Tan, Kok Kiong

2009-08-01

Order-crossing problems in Gabor order tracking (GOT) of rotating machinery often occur when noise due to power-frequency interference, local structure resonance, etc., is prominent in applications. They can render the analysis results and the waveform-reconstruction tasks in GOT inaccurate or even meaningless. An approach is proposed in this paper to address the order-crossing problem by independent component analysis (ICA). With the approach, accurate order analysis results can be obtained and the waveforms of the order components of interest can be reconstructed or extracted from the recorded noisy data series. In addition, the ambiguities (permutation and scaling) of ICA results are also solved with the approach. The approach is amenable to applications in condition monitoring and fault diagnosis of rotating machinery. The evaluation of the approach is presented in detail based on simulations and an experiment on a rotor test rig. The results obtained using the proposed approach are compared with those obtained using the standard GOT. The comparison shows that the presented approach is more effective to solve order-crossing problems in GOT.

Wavelet processing and digital interferometric contrast to improve reconstructions from X-ray Gabor holograms.

PubMed

Aguilar, Juan C; Misawa, Masaki; Matsuda, Kiyofumi; Suzuki, Yoshio; Takeuchi, Akihisa; Yasumoto, Masato

2018-05-01

In this work, the application of an undecimated wavelet transformation together with digital interferometric contrast to improve the resulting reconstructions in a digital hard X-ray Gabor holographic microscope is shown. Specifically, the starlet transform is used together with digital Zernike contrast. With this contrast, the results show that only a small set of scales from the hologram are, in effect, useful, and it is possible to enhance the details of the reconstruction.

Multi-Patches IRIS Based Person Authentication System Using Particle Swarm Optimization and Fuzzy C-Means Clustering

NASA Astrophysics Data System (ADS)

Shekar, B. H.; Bhat, S. S.

2017-05-01

Locating the boundary parameters of pupil and iris and segmenting the noise free iris portion are the most challenging phases of an automated iris recognition system. In this paper, we have presented person authentication frame work which uses particle swarm optimization (PSO) to locate iris region and circular hough transform (CHT) to device the boundary parameters. To undermine the effect of the noise presented in the segmented iris region we have divided the candidate region into N patches and used Fuzzy c-means clustering (FCM) to classify the patches into best iris region and not so best iris region (noisy region) based on the probability density function of each patch. Weighted mean Hammimng distance is adopted to find the dissimilarity score between the two candidate irises. We have used Log-Gabor, Riesz and Taylor's series expansion (TSE) filters and combinations of these three for iris feature extraction. To justify the feasibility of the proposed method, we experimented on the three publicly available data sets IITD, MMU v-2 and CASIA v-4 distance.

An applet for the Gabor similarity scaling of the differences between complex stimuli.

PubMed

Margalit, Eshed; Biederman, Irving; Herald, Sarah B; Yue, Xiaomin; von der Malsburg, Christoph

2016-11-01

It is widely accepted that after the first cortical visual area, V1, a series of stages achieves a representation of complex shapes, such as faces and objects, so that they can be understood and recognized. A major challenge for the study of complex shape perception has been the lack of a principled basis for scaling of the physical differences between stimuli so that their similarity can be specified, unconfounded by early-stage differences. Without the specification of such similarities, it is difficult to make sound inferences about the contributions of later stages to neural activity or psychophysical performance. A Web-based app is described that is based on the Malsburg Gabor-jet model (Lades et al., 1993), which allows easy specification of the V1 similarity of pairs of stimuli, no matter how intricate. The model predicts the psycho physical discriminability of metrically varying faces and complex blobs almost perfectly (Yue, Biederman, Mangini, von der Malsburg, & Amir, 2012), and serves as the input stage of a large family of contemporary neurocomputational models of vision.

The existence of a sticking region in free weight squats.

PubMed

van den Tillaar, Roland; Andersen, Vidar; Saeterbakken, Atle Hole

2014-09-29

The aim of this study was to investigate the existence of the sticking region in two legged free weight squats. Fifteen resistance-training males (age 24 ± 4 years, body mass 82 ± 11 kg, body height 179 ± 6 cm) with 6 ± 3 years of resistance-training experience performed 6-RM in free weight squats. The last repetition was analyzed for the existence of a sticking region. Only in 10 out of 15 participants a sticking region was observed. The observed sticking region was much shorter than in the bench press. Furthermore, rectus femoris decreased the EMG activity in contrast to increased EMG activity in biceps femoris around the sticking and surrounding region. No significant change in EMG activity was found for the lateral and medial vastus muscles. It is suggested that a combination of these muscle activity changes could be one of the causes of the existence of the sticking region in free weight squats.

The Existence of a Sticking Region in Free Weight Squats

PubMed Central

van den Tillaar, Roland; Andersen, Vidar; Saeterbakken, Atle Hole

2014-01-01

The aim of this study was to investigate the existence of the sticking region in two legged free weight squats. Fifteen resistance-training males (age 24 ± 4 years, body mass 82 ± 11 kg, body height 179 ± 6 cm) with 6 ± 3 years of resistance-training experience performed 6-RM in free weight squats. The last repetition was analyzed for the existence of a sticking region. Only in 10 out of 15 participants a sticking region was observed. The observed sticking region was much shorter than in the bench press. Furthermore, rectus femoris decreased the EMG activity in contrast to increased EMG activity in biceps femoris around the sticking and surrounding region. No significant change in EMG activity was found for the lateral and medial vastus muscles. It is suggested that a combination of these muscle activity changes could be one of the causes of the existence of the sticking region in free weight squats. PMID:25414740

Dynamic biometric identification from multiple views using the GLBP-TOP method.

PubMed

Wang, Yu; Shen, Xuanjing; Chen, Haipeng; Zhai, Yujie

2014-01-01

To realize effective and rapid dynamic biometric identification with low computational complexity, a video-based facial texture program that extracts local binary patterns from three orthogonal planes in the frequency domain of the Gabor transform (GLBP-TOP) was proposed. Firstly, each normalized face was transformed by Gabor wavelet to get the enhanced Gabor magnitude map, and then the LBP-TOP operator was applied to the maps to extract video texture. Finally, weighted Chi square statistics based on the Fisher Criterion were used to realize the identification. The proposed algorithm was proved effective through the biometric experiments using the Honda/UCSD database, and was robust against changes of illumination and expressions.

Mean curvature and texture constrained composite weighted random walk algorithm for optic disc segmentation towards glaucoma screening.

PubMed

Panda, Rashmi; Puhan, N B; Panda, Ganapati

2018-02-01

Accurate optic disc (OD) segmentation is an important step in obtaining cup-to-disc ratio-based glaucoma screening using fundus imaging. It is a challenging task because of the subtle OD boundary, blood vessel occlusion and intensity inhomogeneity. In this Letter, the authors propose an improved version of the random walk algorithm for OD segmentation to tackle such challenges. The algorithm incorporates the mean curvature and Gabor texture energy features to define the new composite weight function to compute the edge weights. Unlike the deformable model-based OD segmentation techniques, the proposed algorithm remains unaffected by curve initialisation and local energy minima problem. The effectiveness of the proposed method is verified with DRIVE, DIARETDB1, DRISHTI-GS and MESSIDOR database images using the performance measures such as mean absolute distance, overlapping ratio, dice coefficient, sensitivity, specificity and precision. The obtained OD segmentation results and quantitative performance measures show robustness and superiority of the proposed algorithm in handling the complex challenges in OD segmentation.

Efficient Iris Recognition Based on Optimal Subfeature Selection and Weighted Subregion Fusion

PubMed Central

Deng, Ning

2014-01-01

In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. Firstly, we introduce the process of feature extraction and representation based on scale invariant feature transformation (SIFT) in detail. Secondly, three strategies are described, which are orientation probability distribution function (OPDF) based strategy to delete some redundant feature keypoints, magnitude probability distribution function (MPDF) based strategy to reduce dimensionality of feature element, and compounded strategy combined OPDF and MPDF to further select optimal subfeature. Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region's weights and then weighted different subregions' matching scores to generate the final decision. The experimental results, on three public and renowned iris databases (CASIA-V3 Interval, Lamp, andMMU-V1), demonstrate that our proposed methods outperform some of the existing methods in terms of correct recognition rate, equal error rate, and computation complexity. PMID:24683317

Efficient iris recognition based on optimal subfeature selection and weighted subregion fusion.

PubMed

Chen, Ying; Liu, Yuanning; Zhu, Xiaodong; He, Fei; Wang, Hongye; Deng, Ning

2014-01-01

In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. Firstly, we introduce the process of feature extraction and representation based on scale invariant feature transformation (SIFT) in detail. Secondly, three strategies are described, which are orientation probability distribution function (OPDF) based strategy to delete some redundant feature keypoints, magnitude probability distribution function (MPDF) based strategy to reduce dimensionality of feature element, and compounded strategy combined OPDF and MPDF to further select optimal subfeature. Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region's weights and then weighted different subregions' matching scores to generate the final decision. The experimental results, on three public and renowned iris databases (CASIA-V3 Interval, Lamp, and MMU-V1), demonstrate that our proposed methods outperform some of the existing methods in terms of correct recognition rate, equal error rate, and computation complexity.

Iris Matching Based on Personalized Weight Map.

PubMed

Dong, Wenbo; Sun, Zhenan; Tan, Tieniu

2011-09-01

Iris recognition typically involves three steps, namely, iris image preprocessing, feature extraction, and feature matching. The first two steps of iris recognition have been well studied, but the last step is less addressed. Each human iris has its unique visual pattern and local image features also vary from region to region, which leads to significant differences in robustness and distinctiveness among the feature codes derived from different iris regions. However, most state-of-the-art iris recognition methods use a uniform matching strategy, where features extracted from different regions of the same person or the same region for different individuals are considered to be equally important. This paper proposes a personalized iris matching strategy using a class-specific weight map learned from the training images of the same iris class. The weight map can be updated online during the iris recognition procedure when the successfully recognized iris images are regarded as the new training data. The weight map reflects the robustness of an encoding algorithm on different iris regions by assigning an appropriate weight to each feature code for iris matching. Such a weight map trained by sufficient iris templates is convergent and robust against various noise. Extensive and comprehensive experiments demonstrate that the proposed personalized iris matching strategy achieves much better iris recognition performance than uniform strategies, especially for poor quality iris images.

Automatic localization of the nipple in mammograms using Gabor filters and the Radon transform

NASA Astrophysics Data System (ADS)

Chakraborty, Jayasree; Mukhopadhyay, Sudipta; Rangayyan, Rangaraj M.; Sadhu, Anup; Azevedo-Marques, P. M.

2013-02-01

The nipple is an important landmark in mammograms. Detection of the nipple is useful for alignment and registration of mammograms in computer-aided diagnosis of breast cancer. In this paper, a novel approach is proposed for automatic detection of the nipple based on the oriented patterns of the breast tissues present in mammograms. The Radon transform is applied to the oriented patterns obtained by a bank of Gabor filters to detect the linear structures related to the tissue patterns. The detected linear structures are then used to locate the nipple position using the characteristics of convergence of the tissue patterns towards the nipple. The performance of the method was evaluated with 200 scanned-film images from the mini-MIAS database and 150 digital radiography (DR) images from a local database. Average errors of 5:84 mm and 6:36 mm were obtained with respect to the reference nipple location marked by a radiologist for the mini-MIAS and the DR images, respectively.

Risk of adverse outcomes among infants of immigrant women according to birth-weight curves tailored to maternal world region of origin.

PubMed

Urquia, Marcelo L; Berger, Howard; Ray, Joel G

2015-01-06

Infants of immigrant women in Western nations generally have lower birth weights than infants of native-born women. Whether this difference is physiologic or pathological is unclear. We determined whether the use of birth-weight curves tailored to maternal world region of origin would discriminate adverse neonatal and obstetric outcomes more accurately than a single birth-weight curve based on infants of Canadian-born women. We performed a retrospective cohort study of in-hospital singleton live births (328,387 to immigrant women, 761,260 to nonimmigrant women) in Ontario between 2002 and 2012 using population health services data linked to the national immigration database. We classified infants as small for gestational age (<10th percentile) or large for gestational age (≥90th percentile) using both Canadian and world region-specific birth-weight curves and compared associations with adverse neonatal and obstetric outcomes. Compared with world region-specific birth-weight curves, the Canadian curve classified 20 431 (6.2%) additional newborns of immigrant women as small for gestational age, of whom 15,467 (75.7%) were of East or South Asian descent. The odds of neonatal death were lower among small-for-gestational-age infants of immigrant women than among those of nonimmigrant women based on the Canadian birth-weight curve (adjusted odds ratio [OR] 0.83, 95% confidence interval [CI] 0.72-0.95), but higher when small for gestational age was defined by the world region-specific curves (adjusted OR 1.24, 95% CI 1.08-1.42). Conversely, the odds of some adverse outcomes were lower among large-for-gestational-age infants of immigrant women than among those of nonimmigrant women based on world region-specific birth-weight curves, but were similar based on the Canadian curve. World region-specific birth-weight curves seemed to be more appropriate than a single Canadian population-based curve for assessing the risk of adverse neonatal and obstetric outcomes among small

Pigmented skin lesion detection using random forest and wavelet-based texture

NASA Astrophysics Data System (ADS)

Hu, Ping; Yang, Tie-jun

2016-10-01

The incidence of cutaneous malignant melanoma, a disease of worldwide distribution and is the deadliest form of skin cancer, has been rapidly increasing over the last few decades. Because advanced cutaneous melanoma is still incurable, early detection is an important step toward a reduction in mortality. Dermoscopy photographs are commonly used in melanoma diagnosis and can capture detailed features of a lesion. A great variability exists in the visual appearance of pigmented skin lesions. Therefore, in order to minimize the diagnostic errors that result from the difficulty and subjectivity of visual interpretation, an automatic detection approach is required. The objectives of this paper were to propose a hybrid method using random forest and Gabor wavelet transformation to accurately differentiate which part belong to lesion area and the other is not in a dermoscopy photographs and analyze segmentation accuracy. A random forest classifier consisting of a set of decision trees was used for classification. Gabor wavelets transformation are the mathematical model of visual cortical cells of mammalian brain and an image can be decomposed into multiple scales and multiple orientations by using it. The Gabor function has been recognized as a very useful tool in texture analysis, due to its optimal localization properties in both spatial and frequency domain. Texture features based on Gabor wavelets transformation are found by the Gabor filtered image. Experiment results indicate the following: (1) the proposed algorithm based on random forest outperformed the-state-of-the-art in pigmented skin lesions detection (2) and the inclusion of Gabor wavelet transformation based texture features improved segmentation accuracy significantly.

Use of Gabor filters and deep networks in the segmentation of retinal vessel morphology

NASA Astrophysics Data System (ADS)

Leopold, Henry A.; Orchard, Jeff; Zelek, John; Lakshminarayanan, Vasudevan

2017-02-01

The segmentation of retinal morphology has numerous applications in assessing ophthalmologic and cardiovascular disease pathologies. The early detection of many such conditions is often the most effective method for reducing patient risk. Computer aided segmentation of the vasculature has proven to be a challenge, mainly due to inconsistencies such as noise, variations in hue and brightness that can greatly reduce the quality of fundus images. Accurate fundus and/or retinal vessel maps give rise to longitudinal studies able to utilize multimodal image registration and disease/condition status measurements, as well as applications in surgery preparation and biometrics. This paper further investigates the use of a Convolutional Neural Network as a multi-channel classifier of retinal vessels using the Digital Retinal Images for Vessel Extraction database, a standardized set of fundus images used to gauge the effectiveness of classification algorithms. The CNN has a feed-forward architecture and varies from other published architectures in its combination of: max-pooling, zero-padding, ReLU layers, batch normalization, two dense layers and finally a Softmax activation function. Notably, the use of Adam to optimize training the CNN on retinal fundus images has not been found in prior review. This work builds on prior work of the authors, exploring the use of Gabor filters to boost the accuracy of the system to 0.9478 during post processing. The mean of a series of Gabor filters with varying frequencies and sigma values are applied to the output of the network and used to determine whether a pixel represents a vessel or non-vessel.

Characterization of age-associated changes in peripheral organ and brain region weights in C57BL/6 mice.

PubMed

Lessard-Beaudoin, Mélissa; Laroche, Mélissa; Demers, Marie-Josée; Grenier, Guillaume; Graham, Rona K

2015-03-01

In order to further understand age-related physiological changes and to have in depth reference values for C57BL/6 mice, we undertook a study to assess the effects of aging on peripheral organ weights, and brain region weights in wild type C57BL/6 male mice. Peripheral organs, body and brain region weights were collected from young (3-4 months), mid (12 months), old (23-28 months) and very old (>30 months) mice. Significant increases are observed with aging in body, liver, heart, kidney and spleen organ weights. A decrease in organ weight is observed with aging in liver and kidney only in the very old mice. In contrast, testes weight decreases with age. Within the brain, hippocampi, striata and olfactory bulbs weight decreases with age. These data further our knowledge of the anatomical and biological changes that occur with aging and provide reference values for physiological-based pharmacokinetic studies in C57BL/6 mice. Copyright © 2015 Elsevier Inc. All rights reserved.

Image features dependant correlation-weighting function for efficient PRNU based source camera identification.

PubMed

Tiwari, Mayank; Gupta, Bhupendra

2018-04-01

For source camera identification (SCI), photo response non-uniformity (PRNU) has been widely used as the fingerprint of the camera. The PRNU is extracted from the image by applying a de-noising filter then taking the difference between the original image and the de-noised image. However, it is observed that intensity-based features and high-frequency details (edges and texture) of the image, effect quality of the extracted PRNU. This effects correlation calculation and creates problems in SCI. For solving this problem, we propose a weighting function based on image features. We have experimentally identified image features (intensity and high-frequency contents) effect on the estimated PRNU, and then develop a weighting function which gives higher weights to image regions which give reliable PRNU and at the same point it gives comparatively less weights to the image regions which do not give reliable PRNU. Experimental results show that the proposed weighting function is able to improve the accuracy of SCI up to a great extent. Copyright © 2018 Elsevier B.V. All rights reserved.

WeightLifter: Visual Weight Space Exploration for Multi-Criteria Decision Making.

PubMed

Pajer, Stephan; Streit, Marc; Torsney-Weir, Thomas; Spechtenhauser, Florian; Muller, Torsten; Piringer, Harald

2017-01-01

A common strategy in Multi-Criteria Decision Making (MCDM) is to rank alternative solutions by weighted summary scores. Weights, however, are often abstract to the decision maker and can only be set by vague intuition. While previous work supports a point-wise exploration of weight spaces, we argue that MCDM can benefit from a regional and global visual analysis of weight spaces. Our main contribution is WeightLifter, a novel interactive visualization technique for weight-based MCDM that facilitates the exploration of weight spaces with up to ten criteria. Our technique enables users to better understand the sensitivity of a decision to changes of weights, to efficiently localize weight regions where a given solution ranks high, and to filter out solutions which do not rank high enough for any plausible combination of weights. We provide a comprehensive requirement analysis for weight-based MCDM and describe an interactive workflow that meets these requirements. For evaluation, we describe a usage scenario of WeightLifter in automotive engineering and report qualitative feedback from users of a deployed version as well as preliminary feedback from decision makers in multiple domains. This feedback confirms that WeightLifter increases both the efficiency of weight-based MCDM and the awareness of uncertainty in the ultimate decisions.

GOCO05c: A New Combined Gravity Field Model Based on Full Normal Equations and Regionally Varying Weighting

NASA Astrophysics Data System (ADS)

Fecher, T.; Pail, R.; Gruber, T.

2017-05-01

GOCO05c is a gravity field model computed as a combined solution of a satellite-only model and a global data set of gravity anomalies. It is resolved up to degree and order 720. It is the first model applying regionally varying weighting. Since this causes strong correlations among all gravity field parameters, the resulting full normal equation system with a size of 2 TB had to be solved rigorously by applying high-performance computing. GOCO05c is the first combined gravity field model independent of EGM2008 that contains GOCE data of the whole mission period. The performance of GOCO05c is externally validated by GNSS-levelling comparisons, orbit tests, and computation of the mean dynamic topography, achieving at least the quality of existing high-resolution models. Results show that the additional GOCE information is highly beneficial in insufficiently observed areas, and that due to the weighting scheme of individual data the spectral and spatial consistency of the model is significantly improved. Due to usage of fill-in data in specific regions, the model cannot be used for physical interpretations in these regions.

Hebbian based learning with winner-take-all for spiking neural networks

NASA Astrophysics Data System (ADS)

Gupta, Ankur; Long, Lyle

2009-03-01

Learning methods for spiking neural networks are not as well developed as the traditional neural networks that widely use back-propagation training. We propose and implement a Hebbian based learning method with winner-take-all competition for spiking neural networks. This approach is spike time dependent which makes it naturally well suited for a network of spiking neurons. Homeostasis with Hebbian learning is implemented which ensures stability and quicker learning. Homeostasis implies that the net sum of incoming weights associated with a neuron remains the same. Winner-take-all is also implemented for competitive learning between output neurons. We implemented this learning rule on a biologically based vision processing system that we are developing, and use layers of leaky integrate and fire neurons. The network when presented with 4 bars (or Gabor filters) of different orientation learns to recognize the bar orientations (or Gabor filters). After training, each output neuron learns to recognize a bar at specific orientation and responds by firing more vigorously to that bar and less vigorously to others. These neurons are found to have bell shaped tuning curves and are similar to the simple cells experimentally observed by Hubel and Wiesel in the striate cortex of cat and monkey.

Weight-based discrimination: an ubiquitary phenomenon?

PubMed

Sikorski, C; Spahlholz, J; Hartlev, M; Riedel-Heller, S G

2016-02-01

Despite strong indications of a high prevalence of weight-related stigmatization in individuals with obesity, limited attention has been given to the role of weight discrimination in examining the stigma obesity. Studies, up to date, rely on a limited basis of data sets and additional studies are needed to confirm the findings of previous studies. In particular, data for Europe are lacking, and are needed in light of a recent ruling of the European Court of Justice that addressed weight-based discrimination. The data were derived from a large representative telephone survey in Germany (n=3003). The dependent variable, weight-based discrimination, was assessed with a one-item question. The lifetime prevalence of weight discrimination across different sociodemographic variables was determined. Logistic regression models were used to assess the association of independent and dependent variables. A sub-group analysis was conducted analyzing all participants with a body mass index ⩾25 kg m(-)(2). The overall prevalence of weight-based discrimination was 7.3%. Large differences, however, were observed regarding weight status. In normal weight and overweight participants the prevalence was 5.6%, but this number doubled in participants with obesity class I (10.2%), and quadrupled in participants with obesity class II (18.7%) and underweight (19.7%). In participants with obesity class III, every third participant reported accounts of weight-based discrimination (38%). In regression models, after adjustment, the associations of weight status and female gender (odds ratio: 2.59, P<0.001) remained highly significant. Discrimination seems to be an ubiquitary phenomenon at least for some groups that are at special risk, such as heavier individuals and women. Our findings therefore emphasize the need for research and intervention on weight discrimination among adults with obesity, including anti-discrimination legislation.

A novel iris patterns matching algorithm of weighted polar frequency correlation

NASA Astrophysics Data System (ADS)

Zhao, Weijie; Jiang, Linhua

2014-11-01

Iris recognition is recognized as one of the most accurate techniques for biometric authentication. In this paper, we present a novel correlation method - Weighted Polar Frequency Correlation(WPFC) - to match and evaluate two iris images, actually it can also be used for evaluating the similarity of any two images. The WPFC method is a novel matching and evaluating method for iris image matching, which is complete different from the conventional methods. For instance, the classical John Daugman's method of iris recognition uses 2D Gabor wavelets to extract features of iris image into a compact bit stream, and then matching two bit streams with hamming distance. Our new method is based on the correlation in the polar coordinate system in frequency domain with regulated weights. The new method is motivated by the observation that the pattern of iris that contains far more information for recognition is fine structure at high frequency other than the gross shapes of iris images. Therefore, we transform iris images into frequency domain and set different weights to frequencies. Then calculate the correlation of two iris images in frequency domain. We evaluate the iris images by summing the discrete correlation values with regulated weights, comparing the value with preset threshold to tell whether these two iris images are captured from the same person or not. Experiments are carried out on both CASIA database and self-obtained images. The results show that our method is functional and reliable. Our method provides a new prospect for iris recognition system.

Improving Stiffness-to-weight Ratio of Spot-welded Structures based upon Nonlinear Finite Element Modelling

NASA Astrophysics Data System (ADS)

Zhang, Shengyong

2017-07-01

Spot welding has been widely used for vehicle body construction due to its advantages of high speed and adaptability for automation. An effort to increase the stiffness-to-weight ratio of spot-welded structures is investigated based upon nonlinear finite element analysis. Topology optimization is conducted for reducing weight in the overlapping regions by choosing an appropriate topology. Three spot-welded models (lap, doubt-hat and T-shape) that approximate “typical” vehicle body components are studied for validating and illustrating the proposed method. It is concluded that removing underutilized material from overlapping regions can result in a significant increase in structural stiffness-to-weight ratio.

Influence of previous body mass index and sex on regional fat changes in a weight loss intervention.

PubMed

Benito, Pedro J; Cupeiro, Rocio; Peinado, Ana B; Rojo, Miguel A; Maffulli, Nicola

2017-11-01

Men and women may lose weight in a different fashion. This study compares the changes in different anatomical regions after a well-controlled weight loss program by sex and initial BMI. A total of 180 subjects (48 overweight women, 36 overweight men, and 48 obese women and 48 obese men) were recruited to participate in a 22-week weight loss programme (diet + exercise). Regarding percentage body weight change from baseline, there was no triple interaction (BMI, sex and anatomical region), but there was interaction between BMI and anatomical region (F2,840 = 34.5; p < 0.001), and between sex and anatomical region (F2,840 = 98.8; p < 0.001). Usually, the arms and legs are the regions that lose more weight in obese participants, but men lose the highest percentage of mass from the trunk. There were differences between men and women for the areas of left trunk mass (750g), right trunk mass (700g), total mass of the trunk (1400g), android mass (350g), and finally in the total mass in overweight participants (1300g), with higher values for men than for women. The region that loses more weight and fat is the trunk, followed by the legs, and then the arms, when the loss is observed in function of the total weight or fat lost. Both BMI and sex exert a definite influence fat loss, especially in some anatomical regions.

Assessing microstructures of the cornea with Gabor-domain optical coherence microscopy: pathway for corneal physiology and diseases.

PubMed

Tankam, Patrice; He, Zhiguo; Chu, Ying-Ju; Won, Jungeun; Canavesi, Cristina; Lepine, Thierry; Hindman, Holly B; Topham, David J; Gain, Philippe; Thuret, Gilles; Rolland, Jannick P

2015-03-15

Gabor-domain optical coherence microscopy (GD-OCM) was applied ex vivo in the investigation of corneal cells and their surrounding microstructures with particular attention to the corneal endothelium. Experiments using fresh pig eyeballs, excised human corneal buttons from patients with Fuchs' endothelial dystrophy (FED), and healthy donor corneas were conducted. Results show in a large field of view (1  mm×1  mm) high definition images of the different cell types and their surrounding microstructures through the full corneal thickness at both the central and peripheral locations of porcine corneas. Particularly, an image of the endothelial cells lining the bottom of the cornea is highlighted. As compared to healthy human corneas, the corneas of individuals with FED show characteristic microstructural alterations of the Descemet's membrane and increased size and number of keratocytes. The GD-OCM-based imaging system developed may constitute a novel tool for corneal imaging and disease diagnosis. Also, importantly, it may provide insights into the mechanism of corneal physiology and pathology, particularly in diseases of the corneal endothelium.

Facial Affect Recognition Using Regularized Discriminant Analysis-Based Algorithms

NASA Astrophysics Data System (ADS)

Lee, Chien-Cheng; Huang, Shin-Sheng; Shih, Cheng-Yuan

2010-12-01

This paper presents a novel and effective method for facial expression recognition including happiness, disgust, fear, anger, sadness, surprise, and neutral state. The proposed method utilizes a regularized discriminant analysis-based boosting algorithm (RDAB) with effective Gabor features to recognize the facial expressions. Entropy criterion is applied to select the effective Gabor feature which is a subset of informative and nonredundant Gabor features. The proposed RDAB algorithm uses RDA as a learner in the boosting algorithm. The RDA combines strengths of linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA). It solves the small sample size and ill-posed problems suffered from QDA and LDA through a regularization technique. Additionally, this study uses the particle swarm optimization (PSO) algorithm to estimate optimal parameters in RDA. Experiment results demonstrate that our approach can accurately and robustly recognize facial expressions.

A population-level analysis of birth weight indices in Peel Region, Ontario: the impact of ethnic diversity.

PubMed

Ramuscak, Nancy L; Jiang, Depeng; Dooling, Kathleen L; Mowat, David L

2012-07-18

The purpose of this paper is to examine whether the elevated rate of low birth weight (LBW) in the Region of Peel, Ontario can be attributed to the high proportion of immigrants in the population. In addition, we examined how the infant birth weight distribution in Peel differs by maternal region of birth. Provincial live birth registration data were used to compare rates of LBW, preterm birth and small-for-gestational-age (SGA) births in Peel and Ontario for the years 2002 through 2006 by maternal region of birth. Birth weight for gestational age curves were developed for singletons and were specific for infant sex and maternal region of birth using the lambda-mu-sigma (LMS) method. Quantile regression was used to examine whether the median birth weight at term (37 to 42 weeks) differed by maternal region of birth. The rate of LBW was higher in Peel than in Ontario (6.8% and 6.0%, respectively). This is the result of a higher SGA rate and not due to differences in rates of preterm birth. Infants of immigrant mothers had significantly lower median birth weights at all gestations, showing that the birth weight distribution among infants of immigrant mothers is shifted towards lower birth weights. At the population level, the shifted birth weight distribution among singleton infants of immigrant mothers has significant impact on the LBW rate observed in Peel.

Teammates and social influence affect weight loss outcomes in a team-based weight loss competition

PubMed Central

Leahey, Tricia M.; Kumar, Rajiv; Weinberg, Brad M.; Wing, Rena R.

2013-01-01

Team-based Internet interventions are increasing in popularity as a way of promoting weight loss in large numbers of individuals. Given that social networks influence health behavior change, this study investigated the effects of teammates and social influence on individual weight loss during a team-based weight loss competition. Shape Up Rhode Island 2009 was a 12-week online program open to adult residents of Rhode Island. Participants joined with a team and competed with other teams on weight loss and/or physical activity. OW/OB individuals (N=3,330; 76%female; age=46.1±10.8; BMI=31.2±5.3kg/m2), representing 987 teams, completed the weight loss program. Multilevel modeling was used to examine whether weight loss clustered among teammates and whether percentage of teammates in the weight loss division and reported teammate influence on weight loss were associated with individual weight outcomes. OW/OB completers reported losing 4.2±3.4% of initial body weight. Weight loss was similar among teammates (ICC=.10, p<.001). Moreover, having a greater percentage of teammates in the weight loss division and reporting higher social influence for weight loss were associated with greater percent weight loss (p’s≤.002). Similarly, achieving a clinically significant (5%) weight loss tended to cluster within teams (ICC=0.09;p<.001) and having more teammates in the weight loss division and higher social influence for weight loss were associated with increased likelihood of achieving a 5% weight loss (OR=1.06; OR=1.20, respectively). These results suggest that teammates affect weight loss outcomes during a team-based intervention. Harnessing and maximizing teammate influence for weight loss may enhance weight losses in large-scale team-based weight loss programs. PMID:22310234

Tensor manifold-based extreme learning machine for 2.5-D face recognition

NASA Astrophysics Data System (ADS)

Chong, Lee Ying; Ong, Thian Song; Teoh, Andrew Beng Jin

2018-01-01

We explore the use of the Gabor regional covariance matrix (GRCM), a flexible matrix-based descriptor that embeds the Gabor features in the covariance matrix, as a 2.5-D facial descriptor and an effective means of feature fusion for 2.5-D face recognition problems. Despite its promise, matching is not a trivial problem for GRCM since it is a special instance of a symmetric positive definite (SPD) matrix that resides in non-Euclidean space as a tensor manifold. This implies that GRCM is incompatible with the existing vector-based classifiers and distance matchers. Therefore, we bridge the gap of the GRCM and extreme learning machine (ELM), a vector-based classifier for the 2.5-D face recognition problem. We put forward a tensor manifold-compliant ELM and its two variants by embedding the SPD matrix randomly into reproducing kernel Hilbert space (RKHS) via tensor kernel functions. To preserve the pair-wise distance of the embedded data, we orthogonalize the random-embedded SPD matrix. Hence, classification can be done using a simple ridge regressor, an integrated component of ELM, on the random orthogonal RKHS. Experimental results show that our proposed method is able to improve the recognition performance and further enhance the computational efficiency.

Measurement of subcellular texture by optical Gabor-like filtering with a digital micromirror device

PubMed Central

Pasternack, Robert M.; Qian, Zhen; Zheng, Jing-Yi; Metaxas, Dimitris N.; White, Eileen; Boustany, Nada N.

2010-01-01

We demonstrate an optical Fourier processing method to quantify object texture arising from subcellular feature orientation within unstained living cells. Using a digital micromirror device as a Fourier spatial filter, we measured cellular responses to two-dimensional optical Gabor-like filters optimized to sense orientation of nonspherical particles, such as mitochondria, with a width around 0.45 μm. Our method showed significantly rounder structures within apoptosis-defective cells lacking the proapoptotic mitochondrial effectors Bax and Bak, when compared with Bax/Bak expressing cells functional for apoptosis, consistent with reported differences in mitochondrial shape in these cells. By decoupling spatial frequency resolution from image resolution, this method enables rapid analysis of nonspherical submicrometer scatterers in an under-sampled large field of view and yields spatially localized morphometric parameters that improve the quantitative assessment of biological function. PMID:18830354

Teammates and social influence affect weight loss outcomes in a team-based weight loss competition.

PubMed

Leahey, Tricia M; Kumar, Rajiv; Weinberg, Brad M; Wing, Rena R

2012-07-01

Team-based internet interventions are increasing in popularity as a way of promoting weight loss in large numbers of individuals. Given that social networks influence health behavior change, this study investigated the effects of teammates and social influence on individual weight loss during a team-based weight loss competition. Shape Up Rhode Island (SURI) 2009 was a 12-week online program open to adult residents of Rhode Island. Participants joined with a team and competed with other teams on weight loss and/or physical activity. Overweight/obese (OW/OB) individuals (N = 3,330; 76% female; age = 46.1 ± 10.8; BMI = 31.2 ± 5.3 kg/m(2)), representing 987 teams, completed the weight loss program. Multilevel modeling was used to examine whether weight loss clustered among teammates and whether percentage of teammates in the weight loss division and reported teammate influence on weight loss were associated with individual weight outcomes. OW/OB completers reported losing 4.2 ± 3.4% of initial body weight. Weight loss was similar among teammates (intraclass correlation coefficient (ICC) = 0.10, P < 0.001). Moreover, having a greater percentage of teammates in the weight loss division and reporting higher social influence for weight loss were associated with greater percent weight loss (P's ≤ 0.002). Similarly, achieving a clinically significant (5%) weight loss tended to cluster within teams (ICC = 0.09; P < 0.001) and having more teammates in the weight loss division and higher social influence for weight loss were associated with increased likelihood of achieving a 5% weight loss (odds ratio (OR) = 1.06; OR = 1.20, respectively). These results suggest that teammates affect weight loss outcomes during a team-based intervention. Harnessing and maximizing teammate influence for weight loss may enhance weight outcomes in large-scale team-based programs.

Science-based Region-of-Interest Image Compression

NASA Technical Reports Server (NTRS)

Wagstaff, K. L.; Castano, R.; Dolinar, S.; Klimesh, M.; Mukai, R.

2004-01-01

As the number of currently active space missions increases, so does competition for Deep Space Network (DSN) resources. Even given unbounded DSN time, power and weight constraints onboard the spacecraft limit the maximum possible data transmission rate. These factors highlight a critical need for very effective data compression schemes. Images tend to be the most bandwidth-intensive data, so image compression methods are particularly valuable. In this paper, we describe a method for prioritizing regions in an image based on their scientific value. Using a wavelet compression method that can incorporate priority information, we ensure that the highest priority regions are transmitted with the highest fidelity.

A liver cirrhosis classification on B-mode ultrasound images by the use of higher order local autocorrelation features

NASA Astrophysics Data System (ADS)

Sasaki, Kenya; Mitani, Yoshihiro; Fujita, Yusuke; Hamamoto, Yoshihiko; Sakaida, Isao

2017-02-01

In this paper, in order to classify liver cirrhosis on regions of interest (ROIs) images from B-mode ultrasound images, we have proposed to use the higher order local autocorrelation (HLAC) features. In a previous study, we tried to classify liver cirrhosis by using a Gabor filter based approach. However, the classification performance of the Gabor feature was poor from our preliminary experimental results. In order accurately to classify liver cirrhosis, we examined to use the HLAC features for liver cirrhosis classification. The experimental results show the effectiveness of HLAC features compared with the Gabor feature. Furthermore, by using a binary image made by an adaptive thresholding method, the classification performance of HLAC features has improved.

Comparison of weight loss by weight classification in a commercial, community-based weight loss program

USDA-ARS?s Scientific Manuscript database

The objective of our study was to determine the impact of grade of obesity on weight-loss outcomes of a community-based, intensive behavioral counseling program (Weight Watchers Points-Plus). Previous studies have shown that individuals with a higher body mass index (BMI) at the beginning of treatme...

Global Contrast Based Salient Region Detection.

PubMed

Cheng, Ming-Ming; Mitra, Niloy J; Huang, Xiaolei; Torr, Philip H S; Hu, Shi-Min

2015-03-01

Automatic estimation of salient object regions across images, without any prior assumption or knowledge of the contents of the corresponding scenes, enhances many computer vision and computer graphics applications. We introduce a regional contrast based salient object detection algorithm, which simultaneously evaluates global contrast differences and spatial weighted coherence scores. The proposed algorithm is simple, efficient, naturally multi-scale, and produces full-resolution, high-quality saliency maps. These saliency maps are further used to initialize a novel iterative version of GrabCut, namely SaliencyCut, for high quality unsupervised salient object segmentation. We extensively evaluated our algorithm using traditional salient object detection datasets, as well as a more challenging Internet image dataset. Our experimental results demonstrate that our algorithm consistently outperforms 15 existing salient object detection and segmentation methods, yielding higher precision and better recall rates. We also show that our algorithm can be used to efficiently extract salient object masks from Internet images, enabling effective sketch-based image retrieval (SBIR) via simple shape comparisons. Despite such noisy internet images, where the saliency regions are ambiguous, our saliency guided image retrieval achieves a superior retrieval rate compared with state-of-the-art SBIR methods, and additionally provides important target object region information.

Genotype by region and season interactions on weaning weight in United States Angus cattle.

PubMed

Williams, J L; Lukaszewicz, M; Bertrand, J K; Misztal, I

2012-10-01

The objective of this study was to determine if weaning weight performance is genetically consistent across different environments in the United States. The American Angus Association provided weight and pedigree data. Weaning weights observed in the Southeast (SoE) and Northwest (NW) were the focus of this study, as these regions are perceived as opposite extremes in climate. The 2 most represented calving seasons in each region were fall and winter in the SoE and winter and spring in the NW. The original data were edited to remove weaning weight records outside of 3 SD from the respective region-season mean, contemporary groups smaller than 20, and single-sire contemporary groups. The final dataset included 884,465 weaning weight records with 64,907 from fall-born calves in the SoE, 74,820 from winter-born calves in the SoE, 346,724 from winter-born calves in the NW and 398,014 from spring-born calves in the NW. Weaning weights of calves born in different region-season classes adjusted to 205 d of age were considered different but genetically correlated traits in a multivariate analysis. The sole fixed effect was weaning contemporary group and random effects included direct, maternal, maternal permanent environment, and a residual. Direct heritability estimates differed little across environments: 0.31 and 0.35 for weight in fall- and winter-born calves in the SoE, and 0.29 and 0.32 for winter- and spring-born calves in NW. Maternal heritability estimates ranged from 0.12 in the NW to 0.16 the SoE. Genetic correlations spanned from 0.69 to 0.93 among direct effects and from 0.65 to 0.95 among maternal effects. All heritability estimates had small (0.01 to 0.04) SE. The most distinct environments appeared to be winter in SoE and spring in NW (correlations of 0.69 and 0.65 for the direct and maternal effects). Different choices of sires for different environments might be justified to achieve the growth performance expected.

Low body weight/thinness, overweight and obesity of children and adolescents from a Brazilian region of low economic status.

PubMed

Guedes, Dartagnan Pinto; Almeida, Francisléia Nascimento; Neto, Jaime Tolentino M; Maia, Maria de Fátima de M; Tolentino, Thatiana Maia

2013-12-01

To assess the prevalence of low body weight/thinness, overweight and obesity in a representative sample of children and adolescents from a Brazilian region with low economic development. A total of 982 girls and 986 boys, aged seven to 17 years old and assisted by Segundo Tempo Program, from Montes Claros, Minas Gerais, Brazil, were included in the study. Low body weight/thinness, overweight and obesity were defined based on body mass cut-off indexes recommended by the International Obesity Task Force. The prevalence of the nutritional status according to sex and age was compared by chi-square test. In girls, the frequency of low body weight/thinness, overweight and obesity was 4.1, 18.4 and 3.8%, respectively; in boys, these percentages were 6.3, 13.2 and 2.9%, respectively. The low body weight/thinness for girls raised from 2.7% (7-10 years old) to 5.5% (15-17 years old); the body weight excess (overweight and obesity) decreased from 30.1 to 16.2% for the same age groups. In boys, the corresponding trends were from 3.2 to 9.4% for low body weight/thinness, and from 23.4 to 9.2%, for body weight excess. The data indicate that, even in a region with low economic status, the body weight excess was the main problem associated with nutritional health. The high overweight and obesity prevalence rates indicate the need of public policies for promoting healthy feeding behaviors and physical activity.

Half-Fan-Based Intensity-Weighted Region-of-Interest Imaging for Low-Dose Cone-Beam CT in Image-Guided Radiation Therapy.

PubMed

Yoo, Boyeol; Son, Kihong; Pua, Rizza; Kim, Jinsung; Solodov, Alexander; Cho, Seungryong

2016-10-01

With the increased use of computed tomography (CT) in clinics, dose reduction is the most important feature people seek when considering new CT techniques or applications. We developed an intensity-weighted region-of-interest (IWROI) imaging method in an exact half-fan geometry to reduce the imaging radiation dose to patients in cone-beam CT (CBCT) for image-guided radiation therapy (IGRT). While dose reduction is highly desirable, preserving the high-quality images of the ROI is also important for target localization in IGRT. An intensity-weighting (IW) filter made of copper was mounted in place of a bowtie filter on the X-ray tube unit of an on-board imager (OBI) system such that the filter can substantially reduce radiation exposure to the outer ROI. In addition to mounting the IW filter, the lead-blade collimation of the OBI was adjusted to produce an exact half-fan scanning geometry for a further reduction of the radiation dose. The chord-based rebinned backprojection-filtration (BPF) algorithm in circular CBCT was implemented for image reconstruction, and a humanoid pelvis phantom was used for the IWROI imaging experiment. The IWROI image of the phantom was successfully reconstructed after beam-quality correction, and it was registered to the reference image within an acceptable level of tolerance. Dosimetric measurements revealed that the dose is reduced by approximately 61% in the inner ROI and by 73% in the outer ROI compared to the conventional bowtie filter-based half-fan scan. The IWROI method substantially reduces the imaging radiation dose and provides reconstructed images with an acceptable level of quality for patient setup and target localization. The proposed half-fan-based IWROI imaging technique can add a valuable option to CBCT in IGRT applications.

Low body weight/thinness, overweight and obesity of children and adolescents from a Brazilian region of low economic status

PubMed Central

Guedes, Dartagnan Pinto; Almeida, Francisléia Nascimento; M., Jaime Tolentino; Maia, Maria de Fátima de M.; Tolentino, Thatiana Maia

2013-01-01

OBJECTIVE: To assess the prevalence of low body weight/thinness, overweight and obesity in a representative sample of children and adolescents from a Brazilian region with low economic development. METHODS: A total of 982 girls and 986 boys, aged seven to 17 years old and assisted by Segundo Tempo Program, from Montes Claros, Minas Gerais, Brazil, were included in the study. Low body weight/thinness, overweight and obesity were defined based on body mass cut-off indexes recommended by the International Obesity Task Force. The prevalence of the nutritional status according to sex and age was compared by chi-square test. RESULTS: In girls, the frequency of low body weight/thinness, overweight and obesity was 4.1, 18.4 and 3.8%, respectively; in boys, these percentages were 6.3, 13.2 and 2.9%, respectively. The low body weight/thinness for girls raised from 2.7% (7-10 years old) to 5.5% (15-17 years old); the body weight excess (overweight and obesity) decreased from 30.1 to 16.2% for the same age groups. In boys, the corresponding trends were from 3.2 to 9.4% for low body weight/thinness, and from 23.4 to 9.2%, for body weight excess. CONCLUSIONS: The data indicate that, even in a region with low economic status, the body weight excess was the main problem associated with nutritional health. The high overweight and obesity prevalence rates indicate the need of public policies for promoting healthy feeding behaviors and physical activity. PMID:24473947

Interactive computer-based interventions for weight loss or weight maintenance in overweight or obese people

PubMed Central

Wieland, L. Susan; Falzon, Louise; Sciamanna, Chris N; Trudeau, Kimberlee J; Folse, Suzanne Brodney; Schwartz, Joseph E; Davidson, Karina W

2014-01-01

Background The World Health Organization (WHO) estimates that the number of obese or overweight individuals worldwide will increase to 1.5 billion by 2015. Chronic diseases associated with overweight or obesity include diabetes, heart disease, hypertension and stroke. Objectives To assess the effects of interactive computer-based interventions for weight loss or weight maintenance in overweight or obese people. Search methods We searched several electronic databases, including CENTRAL, MEDLINE, EMBASE, CINAHL, LILACS and PsycINFO, through 25 May 2011. We also searched clinical trials registries to identify studies. We scanned reference lists of included studies and relevant systematic reviews. Selection criteria Studies were included if they were randomized controlled trials or quasi-randomized controlled trials that evaluated interactive computer-based weight loss or weight maintenance programs in adults with overweight or obesity. We excluded trials if the duration of the intervention was less than four weeks or the loss to follow-up was greater than 20% overall. Data collection and analysis Two authors independently extracted study data and assessed risk of bias. Where interventions, control conditions, outcomes and time frames were similar between studies, we combined study data using meta-analysis. Main results We included 14 weight loss studies with a total of 2537 participants, and four weight maintenance studies with a total of 1603 participants. Treatment duration was between four weeks and 30 months. At six months, computer-based interventions led to greater weight loss than minimal interventions (mean difference (MD) −1.5 kg; 95% confidence interval (CI) −2.1 to −0.9; two trials) but less weight loss than in-person treatment (MD 2.1 kg; 95% CI 0.8 to 3.4; one trial). At six months, computer-based interventions were superior to a minimal control intervention in limiting weight regain (MD −0.7 kg; 95% CI −1.2 to −0.2; two trials), but not

Region based feature extraction from non-cooperative iris images using triplet half-band filter bank

NASA Astrophysics Data System (ADS)

Barpanda, Soubhagya Sankar; Majhi, Banshidhar; Sa, Pankaj Kumar

2015-09-01

In this paper, we have proposed energy based features using a multi-resolution analysis (MRA) on iris template. The MRA is based on our suggested triplet half-band filter bank (THFB). The THFB derivation process is discussed in detail. The iris template is divided into six equispaced sub-templates and two level decomposition has been made to each sub-template using THFB except second one. The reason for discarding the second template is due to the fact that it mostly contains the noise due to eyelids, eyelashes, and occlusion due to segmentation failure. Subsequently, energy features are derived from the decomposed coefficients of each sub-template. The proposed feature has been experimented on standard databases like CASIAv3, UBIRISv1, and IITD and mostly on iris images which encounter a segmentation failure. Comparative analysis has been done with existing features based on Gabor transform, Fourier transform, and CDF 9/7 filter bank. The proposed scheme shows superior performance with respect to FAR, GAR and AUC.

Weight-based dosing in medication use: what should we know?

PubMed Central

Pan, Sheng-dong; Zhu, Ling-ling; Chen, Meng; Xia, Ping; Zhou, Quan

2016-01-01

Background Weight-based dosing strategy is still challenging due to poor awareness and adherence. It is necessary to let clinicians know of the latest developments in this respect and the correct circumstances in which weight-based dosing is of clinical relevance. Methods A literature search was conducted using PubMed. Results Clinical indications, physiological factors, and types of medication may determine the applicability of weight-based dosing. In some cases, the weight effect may be minimal or the proper dosage can only be determined when weight is combined with other factors. Medications within similar therapeutic or structural class (eg, anticoagulants, antitumor necrosis factor medications, P2Y12-receptor antagonists, and anti-epidermal growth factor receptor antibodies) may exhibit differences in requirements on weight-based dosing. In some cases, weight-based dosing is superior to currently recommended fixed-dose regimen in adult patients (eg, hydrocortisone, vancomycin, linezolid, and aprotinin). On the contrary, fixed dosing is noninferior to or even better than currently recommended weight-based regimen in adult patients in some cases (eg, cyclosporine microemulsion, recombinant activated Factor VII, and epoetin α). Ideal body-weight-based dosing may be superior to the currently recommended total body-weight-based regimen (eg, atracurium and rocuronium). For dosing in pediatrics, whether weight-based dosing is better than body surface-area-based dosing is dependent on the particular medication (eg, methotrexate, prednisone, prednisolone, zidovudine, didanosine, growth hormone, and 13-cis-retinoic acid). Age-based dosing strategy is better than weight-based dosing in some cases (eg, intravenous busulfan and dalteparin). Dosing guided by pharmacogenetic testing did not show pharmacoeconomic advantage over weight-adjusted dosing of 6-mercaptopurine. The common viewpoint (ie, pediatric patients should be dosed on the basis of body weight) is not always

Are neonatal intensive care resources located according to need? Regional variation in neonatologists, beds, and low birth weight newborns.

PubMed

Goodman, D C; Fisher, E S; Little, G A; Stukel, T A; Chang , C H

2001-08-01

Despite marked growth in neonatal intensive care during the past 30 years, it is not known if neonatologists and beds are preferentially located in regions with greater newborn risk. This study reports the relationship between regional measures of intensive care capacity and low birth weight infants using newly developed market-based regions of neonatal intensive care. Cross-sectional small-area analysis of 246 neonatal intensive care regions (NICRs). 1996 American Medical Association and American Osteopathic Association masterfiles data of clinically active neonatologists; 1999 American Academy of Pediatrics Section on Perinatal Pediatrics survey of directors of neonatal intensive care units in the United States with 100% response rate; 1995 linked birth/death data. The number of total births per neonatologist across NICRs ranged from 390 to 8197 (median: 1722) and the number of total births per intensive care bed ranged from 72 to 1319 (median: 317). The associations between capacity measures and low birth weight rates across NICRs were statistically significant but negligible (R(2): 0.04 for neonatologists; 0.05 for beds). NICRs in the quintile with the greatest neonatologist capacity (average of only 863 births per neonatologist) had very low birth weight (VLBW) rates of 1.5% while those in the quintile of lowest neonatologist capacity (average of 3718 births per neonatologist) had VLBW rates of 1.3%; a similar lack of meaningful difference in VLBW rates was noted across quintiles of intensive care bed capacity. Including midlevel providers and intermediate care beds to the analyses did not alter the findings. Neonatal intensive care capacity is not preferentially located in regions with greater newborn need as measured by low birth weight rates. Whether greater capacity affords benefits to the newborns remains unknown.

Effect of rotation age and physiographic region on weight per cubic foot of planted loblolly pine

Treesearch

Alexander Clark; Richard F. Daniels; Bruce E. Borders

2006-01-01

Most harvested southern pine is sold by weight. We discuss how the weight of wood and bark per cubic foot of wood (the weight scaling factor) for plantation-grown loblolly pine (Pinus taeda L.) varies with tree age across the coastal and inland regions of the Southern United States. To determine the weight scaling factor for plantation trees in the...

Entropy-based link prediction in weighted networks

NASA Astrophysics Data System (ADS)

Xu, Zhongqi; Pu, Cunlai; Ramiz Sharafat, Rajput; Li, Lunbo; Yang, Jian

2017-01-01

Information entropy has been proved to be an effective tool to quantify the structural importance of complex networks. In the previous work (Xu et al, 2016 \\cite{xu2016}), we measure the contribution of a path in link prediction with information entropy. In this paper, we further quantify the contribution of a path with both path entropy and path weight, and propose a weighted prediction index based on the contributions of paths, namely Weighted Path Entropy (WPE), to improve the prediction accuracy in weighted networks. Empirical experiments on six weighted real-world networks show that WPE achieves higher prediction accuracy than three typical weighted indices.

An Improved Iris Recognition Algorithm Based on Hybrid Feature and ELM

NASA Astrophysics Data System (ADS)

Wang, Juan

2018-03-01

The iris image is easily polluted by noise and uneven light. This paper proposed an improved extreme learning machine (ELM) based iris recognition algorithm with hybrid feature. 2D-Gabor filters and GLCM is employed to generate a multi-granularity hybrid feature vector. 2D-Gabor filter and GLCM feature work for capturing low-intermediate frequency and high frequency texture information, respectively. Finally, we utilize extreme learning machine for iris recognition. Experimental results reveal our proposed ELM based multi-granularity iris recognition algorithm (ELM-MGIR) has higher accuracy of 99.86%, and lower EER of 0.12% under the premise of real-time performance. The proposed ELM-MGIR algorithm outperforms other mainstream iris recognition algorithms.

Combining Gabor and Talbot bands techniques to enhance the sensitivity with depth in Fourier domain optical coherence tomography

NASA Astrophysics Data System (ADS)

Bradu, Adrian; Marques, Manuel J.; Bouchal, Petr; Podoleanu, Adrian Gh.

2013-03-01

The purpose of this study was to show how to favorably mix two e_ects to improve the sensitivity with depth in Fourier domain optical coherence tomography (OCT): Talbot bands (TB) and Gabor-based fusion (GF) technique. TB operation is achieved by directing the two beams, from the object arm and from the reference arm in the OCT interferometer, along parallel separate paths towards the spectrometer. By changing the lateral gap between the two beams in their path towards the spectrometer, the position for the maximum sensitivity versus the optical path difference in the interferometer is adjusted. For five values of the focus position, the gap between the two beams is readjusted to reach maximum sensitivity. Then, similar to the procedure employed in the GF technique, a composite image is formed by edging together the parts of the five images that exhibited maximum brightness. The combined procedure, TB/GF is examined for four different values of the beam diameters of the two beams. Also we demonstrate volumetric FD-OCT images with mirror term attenuation and sensitivity profile shifted towards higher OPD values by applying a Talbot bands configuration.

Pornographic image detection with Gabor filters

NASA Astrophysics Data System (ADS)

Durrell, Kevan; Murray, Daniel J. C.

2002-04-01

As Internet-enabled computers become ubiquitous in homes, schools, and other publicly accessible locations, there are more people 'surfing the net' who would prefer not to be exposed to offensive material. There is a lot of material freely available on the Internet that we, as a responsible and caring society, would like to keep our children from viewing. Pornographic image content is one category of material over which we would like some control. We have been conducting experiments to determine the effectiveness of using characteristic feature vectors and neural networks to identify semantic image content. This paper will describe our approach to identifying pornographic images using Gabor filters, Principal Component Analysis (PCA), Correllograms, and Neural Networks. In brief, we used a set of 5,000 typical images available from the Internet, 20% of which were judged to be pornographic, to train a neural network. We then apply the trained neural network to feature vectors from images that had not been used in training. We measure our performance as Recall, how many of the verification images labeled pornographic were correctly identified, and Precision, how many images deemed pornographic by the neural network are in fact pornographic. The set of images that were used in the experiment described in this paper for its training and validation sets are freely available on the Internet. Freely available is an important qualifier, since high-resolution, studio-quality pornographic images are often protected by portals that charge members a fee to gain access to their material. Although this is not a hard and fast rule, many of the pornographic images that are available easily and without charge on the Internet are of low image quality. Some of these images are collages or contain textual elements or have had their resolution intentionally lowered to reduce their file size. These are the offensive images that a user, without a credit card, might inadvertently come

Income-based equity weights in healthcare planning and policy.

PubMed

Herlitz, Anders

2017-08-01

Recent research indicates that there is a gap in life expectancy between the rich and the poor. This raises the question: should we on egalitarian grounds use income-based equity weights when we assess benefits of alternative benevolent interventions, so that health benefits to the poor count for more? This article provides three egalitarian arguments for using income-based equity weights under certain circumstances. If income inequality correlates with inequality in health, we have reason to use income-based equity weights on the ground that health inequality is bad. If income inequality correlates with inequality in opportunity for health, we have reason to use such weights on the ground that inequality in opportunity for health is bad. If income inequality correlates with inequality in well-being, income-based equity weights should be used to mitigate inequality in well-being. Three different ways in which to construe income-based equity weights are introduced and discussed. They can be based on relative income inequality, on income rankings and on capped absolute income. The article does not defend any of these types of weighting schemes, but argues that in order to settle which of these types of weighting scheme to choose, more empirical research is needed. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Differential privacy based on importance weighting

PubMed Central

Ji, Zhanglong

2014-01-01

This paper analyzes a novel method for publishing data while still protecting privacy. The method is based on computing weights that make an existing dataset, for which there are no confidentiality issues, analogous to the dataset that must be kept private. The existing dataset may be genuine but public already, or it may be synthetic. The weights are importance sampling weights, but to protect privacy, they are regularized and have noise added. The weights allow statistical queries to be answered approximately while provably guaranteeing differential privacy. We derive an expression for the asymptotic variance of the approximate answers. Experiments show that the new mechanism performs well even when the privacy budget is small, and when the public and private datasets are drawn from different populations. PMID:24482559

A review of technology-based interventions to maintain weight loss.

PubMed

Lee, Sohye; Lindquist, Ruth

2015-03-01

For many decades, healthcare providers and researchers have developed weight-loss interventions to help people achieve weight loss. Unfortunately, it is typical for people to lose weight quickly during the intervention period but then slowly regain weight until they return to their approximate baseline. Technology-based maintenance interventions are among the newest approaches to long-term weight loss. Several advantages make technology helpful for maintaining weight loss. The purpose of this article was to review and critique the randomized controlled trials of technology-based weight-loss maintenance interventions (WLMIs) for adults. A systematic search through electronic databases and a manual citation search were conducted. Limited numbers of controlled trials published since 2000 that included randomization, and technology-based WLMIs were identified. The characteristics of the eight studies were diverse. The average score of study design quality was moderate. The results of the effectiveness of technology-based WLMIs were mixed. Technology-based WLMIs are more likely to be effective than usual care but not more effective than personal contact. Based on the review, guidelines were established for the selection and potential success of technology-based WLMIs. The effectiveness of technology-based maintenance interventions for weight loss varied, and potential strategies and approaches are discussed to improve their effectiveness. Further studies are needed to better evaluate and refine the efficacy of technology-based WLMIs.

Weight change in a commercial web-based weight loss program and its association with website use: cohort study.

PubMed

Neve, Melinda; Morgan, Philip J; Collins, Clare E

2011-10-12

There is a paucity of information in the scientific literature on the effectiveness of commercial weight loss programs, including Web-based programs. The potential of Web-based weight loss programs has been acknowledged, but their ability to achieve significant weight loss has not been proven. The objectives were to evaluate the weight change achieved within a large cohort of individuals enrolled in a commercial Web-based weight loss program for 12 or 52 weeks and to describe participants' program use in relation to weight change. Participants enrolled in an Australian commercial Web-based weight loss program from August 15, 2007, through May 31, 2008. Self-reported weekly weight records were used to determine weight change after 12- and 52-week subscriptions. The primary analysis estimated weight change using generalized linear mixed models (GLMMs) for all participants who subscribed for 12 weeks and also for those who subscribed for 52 weeks. A sensitivity analysis was conducted using the last observation carried forward (LOCF) method. Website use (ie, the number of days participants logged on, made food or exercise entries to the Web-based diary, or posted to the discussion forum) was described from program enrollment to 12 and 52 weeks, and differences in website use by percentage weight change category were tested using Kruskal-Wallis test for equality of populations. Participants (n = 9599) had a mean (standard deviation [SD]) age of 35.7 (9.5) years and were predominantly female (86% or 8279/9599) and obese (61% or 5866/9599). Results from the primary GLMM analysis including all enrollees found the mean percentage weight change was -6.2% among 12-week subscribers (n = 6943) and -6.9% among 52-week subscribers (n = 2656). Sensitivity analysis using LOCF revealed an average weight change of -3.0% and -3.5% after 12 and 52 weeks respectively. The use of all website features increased significantly (P < .01) as percentage weight change improved. The weight loss

a Region-Based Multi-Scale Approach for Object-Based Image Analysis

NASA Astrophysics Data System (ADS)

Kavzoglu, T.; Yildiz Erdemir, M.; Tonbul, H.

2016-06-01

Within the last two decades, object-based image analysis (OBIA) considering objects (i.e. groups of pixels) instead of pixels has gained popularity and attracted increasing interest. The most important stage of the OBIA is image segmentation that groups spectrally similar adjacent pixels considering not only the spectral features but also spatial and textural features. Although there are several parameters (scale, shape, compactness and band weights) to be set by the analyst, scale parameter stands out the most important parameter in segmentation process. Estimating optimal scale parameter is crucially important to increase the classification accuracy that depends on image resolution, image object size and characteristics of the study area. In this study, two scale-selection strategies were implemented in the image segmentation process using pan-sharped Qickbird-2 image. The first strategy estimates optimal scale parameters for the eight sub-regions. For this purpose, the local variance/rate of change (LV-RoC) graphs produced by the ESP-2 tool were analysed to determine fine, moderate and coarse scales for each region. In the second strategy, the image was segmented using the three candidate scale values (fine, moderate, coarse) determined from the LV-RoC graph calculated for whole image. The nearest neighbour classifier was applied in all segmentation experiments and equal number of pixels was randomly selected to calculate accuracy metrics (overall accuracy and kappa coefficient). Comparison of region-based and image-based segmentation was carried out on the classified images and found that region-based multi-scale OBIA produced significantly more accurate results than image-based single-scale OBIA. The difference in classification accuracy reached to 10% in terms of overall accuracy.

Parent weight change predicts child weight change in family-based weight control program for pre-school children (Buffalo healthy tots)

USDA-ARS?s Scientific Manuscript database

Title: PARENT WEIGHT CHANGE PREDICTS CHILD WEIGHT CHANGE IN FAMILY-BASED WEIGHT CONTROL PROGRAM FOR PRE-SCHOOL CHILDREN (BUFFALO HEALTHY TOTS), Teresa Quattrin, MOl, James N Roemmich, PhDI, Rocco Paluch, MAl, Jihnhee Yu, PhD2, Leonard H Epstein, PhDI and Michelle A Ecker, RD, CDEI . lpediatrics, Uni...

A new phase-correlation-based iris matching for degraded images.

PubMed

Krichen, Emine; Garcia-Salicetti, Sonia; Dorizzi, Bernadette

2009-08-01

In this paper, we present a new phase-correlation-based iris matching approach in order to deal with degradations in iris images due to unconstrained acquisition procedures. Our matching system is a fusion of global and local Gabor phase-correlation schemes. The main originality of our local approach is that we do not only consider the correlation peak amplitudes but also their locations in different regions of the images. Results on several degraded databases, namely, the CASIA-BIOSECURE and Iris Challenge Evaluation 2005 databases, show the improvement of our method compared to two available reference systems, Masek and Open Source for Iris (OSRIS), in verification mode.

Regional fat placement in physically fit males and changes with weight loss.

PubMed

Nindl, B C; Friedl, K E; Marchitelli, L J; Shippee, R L; Thomas, C D; Patton, J F

1996-07-01

The abdomen is the principal site of fat deposition in men, and because abdominal fat is readily mobilized during exercise, the relative proportion of fat in the abdominal site may negatively correlate with the amount of regular physical activity, and even with physical fitness. This study presents data for regional fatness in 165 fit young men (U.S. Army Ranger candidates; initial body fat = 14.7 +/- 4.7%) assessed by dual-energy x-ray absorptiometry (DEXA), and for relative changes occurring following a 13% weight loss produced by a 1000 kcal.d-1 energy deficit over 8 wk. Fat-free mass was constant across quintiles of percent body fat; only fat mass was different (16.2 +/- 2.2 kg and 6.0 +/- 1.4 kg at upper and lower quintiles, respectively). Truncal fat accounted for about 41% of total body fat in all quintiles; only the proportion of fat distributed to the arms was significantly higher in the fattest quintiles of men. Among a group of less intensely trained soldiers with the same average fatness as the highest quintile of Ranger students (20%), relative fat distribution to the trunk approached 50% of the total fat. Following weight loss, Ranger students lost half of the fat in all regions assessed (legs, arms, and trunk). The only significant association between regional losses and initial fatness was a greater proportion of fat lost from the arms in the fattest Rangers. These data suggest a "fit fat" distribution in active young men in which fat remains in the arms and legs until extreme weight loss occurs and the metabolically more active abdominal fat approaches depletion.

Point spread function based classification of regions for linear digital tomosynthesis

NASA Astrophysics Data System (ADS)

Israni, Kenny; Avinash, Gopal; Li, Baojun

2007-03-01

In digital tomosynthesis, one of the limitations is the presence of out-of-plane blur due to the limited angle acquisition. The point spread function (PSF) characterizes blur in the imaging volume, and is shift-variant in tomosynthesis. The purpose of this research is to classify the tomosynthesis imaging volume into four different categories based on PSF-driven focus criteria. We considered linear tomosynthesis geometry and simple back projection algorithm for reconstruction. The three-dimensional PSF at every pixel in the imaging volume was determined. Intensity profiles were computed for every pixel by integrating the PSF-weighted intensities contained within the line segment defined by the PSF, at each slice. Classification rules based on these intensity profiles were used to categorize image regions. At background and low-frequency pixels, the derived intensity profiles were flat curves with relatively low and high maximum intensities respectively. At in-focus pixels, the maximum intensity of the profiles coincided with the PSF-weighted intensity of the pixel. At out-of-focus pixels, the PSF-weighted intensity of the pixel was always less than the maximum intensity of the profile. We validated our method using human observer classified regions as gold standard. Based on the computed and manual classifications, the mean sensitivity and specificity of the algorithm were 77+/-8.44% and 91+/-4.13% respectively (t=-0.64, p=0.56, DF=4). Such a classification algorithm may assist in mitigating out-of-focus blur from tomosynthesis image slices.

Rebuttal to "On the distribution of the modulus of Gabor wavelet coefficients and the upper bound of the dimensionless smoothness index in the case of additive Gaussian noises: Revisited" by Dong Wang, Qiang Zhou, and Kwok-Leung Tsui

NASA Astrophysics Data System (ADS)

Soltani Bozchalooi, Iman; Liang, Ming

2018-04-01

A discussion paper entitled "On the distribution of the modulus of Gabor wavelet coefficients and the upper bound of the dimensionless smoothness index in the case of additive Gaussian noises: revisited" by Dong Wang, Qiang Zhou, Kwok-Leung Tsui has been brought to our attention recently. This discussion paper (hereafter called Wang et al. paper) is based on arguments that are fundamentally incorrect and which we rebut within this commentary. However, as the flaws in the arguments proposed by Wang et al. are clear, we will keep this rebuttal as brief as possible.

Effectiveness of employee internet-based weight management program.

PubMed

Petersen, Ruth; Sill, Stewart; Lu, Chifung; Young, Joyce; Edington, Dee W

2008-02-01

To evaluate an employee Internet-based weight management program. Changes in eating habits, stage of change, body weight, and weight categories were compared between enrollment and 6 months after enrollment. Weights and weight categories were compared among a subset of participants and non-participants at 12 months. Seven thousand seven hundred forty-three International Business Machines employees enrolled in the program between December 2004 and February 2006, and 74% were overweight or obese (body mass index > or =25). At 6 months, follow-up survey respondents (1639) had significantly increased most healthy eating habits (eg, 20% decrease in junk foods) and the frequency of healthy foods eaten (eg, 12% increase in fruits). The percentage of participants in the normal weight category had increased from 27.0% to 29.8%, while average weight decreased from 182.6 to 180.2 lbs (P < 0.05). Increased web site usage was associated with increased weight loss and stage of change improvements. At 12 months, a higher percentage of participants had moved into the normal weight category compared with the percentage of non-participants (+2.0% points; P < 0.05), although there were no differences in average weight change. Despite issues of limited penetration and potential self-selection, this Internet-based program had utility in reaching a large number of employees in dispersed work settings, and it led to improved eating habits and improved stage of change at 6 months and more individuals moving into the normal weight category at 6 and 12 months.

Vehicle Maximum Weight Limitation Based on Intelligent Weight Sensor

NASA Astrophysics Data System (ADS)

Raihan, W.; Tessar, R. M.; Ernest, C. O. S.; E Byan, W. R.; Winda, A.

2017-03-01

Vehicle weight is an important factor to be maintained for transportation safety. A weight limitation system is proposed to make sure the vehicle weight is always below its designation prior the vehicle is being used by the driver. The proposed system is divided into two systems, namely vehicle weight confirmation system and weight warning system. In vehicle weight confirmation system, the weight sensor work for the first time after the ignition switch is turned on. When the weight is under the weight limit, the starter engine can be switched on to start the engine system, otherwise it will be locked. The seconds system, will operated after checking all the door at close position, once the door of the car is closed, the weight warning system will check once again the weight during runing engine condition. The results of these two systems, vehicle weight confirmation system and weight warning system have 100 % accuracy, respectively. These show that the proposed vehicle weight limitation system operate well.

The degrees to which transtrochanteric rotational osteotomy moves the region of osteonecrotic femoral head out of the weight-bearing area as evaluated by computer simulation.

PubMed

Chen, Weng-Pin; Tai, Ching-Lung; Tan, Chih-Feng; Shih, Chun-Hsiung; Hou, Shun-Hsin; Lee, Mel S

2005-01-01

Transtrochanteric rotational osteotomy is a technical demanding procedure. Currently, the pre-operative planning of the transtrochanteric rotational osteotomy is mostly based on X-ray images. The surgeons would need to reconstruct the three-dimensional structure of the femoral head and the necrosis in their mind. This study develops a simulation platform using computer models based on the computed tomography images of the femoral head to evaluate the degree to which transtrochanteric rotational osteotomy moves the region of osteonecrotic femoral head out of the weight-bearing area in stance and gait cycle conditions. Based on this simulation procedure, the surgeons would be better informed before the surgery and the indication can be carefully assessed. A case with osteonecrosis involving 15% of the femoral head was recruited. Virtual models with the same size lesion but at different locations were devised. Computer models were created using SolidWorks 2000 CAD software. The area ratio of weight-bearing zone occupied by the necrotic lesion on two conditions, stance and gait cycle, were measured after surgery simulations. For the specific case and virtual models devised in this study, computer simulation showed the following two findings: (1) The degrees needed to move the necrosis out of the weight-bearing zone in stance were less by anterior rotational osteotomy as compared to that of posterior rotational osteotomy. However, the necrotic region would still overlap with the weight-bearing area during gait cycle. (2) Because the degrees allowed for posterior rotation were less restricted than anterior rotation, posterior rotational osteotomies were often more effective to move the necrotic region out of the weight-bearing area during gait cycle. The computer simulation platform by registering actual CT images is a useful tool to assess the direction and degrees needed for transtrochanteric rotational osteotomy. Although the results indicated that anterior rotational

Segmentation of Hyperacute Cerebral Infarcts Based on Sparse Representation of Diffusion Weighted Imaging.

PubMed

Zhang, Xiaodong; Jing, Shasha; Gao, Peiyi; Xue, Jing; Su, Lu; Li, Weiping; Ren, Lijie; Hu, Qingmao

2016-01-01

Segmentation of infarcts at hyperacute stage is challenging as they exhibit substantial variability which may even be hard for experts to delineate manually. In this paper, a sparse representation based classification method is explored. For each patient, four volumetric data items including three volumes of diffusion weighted imaging and a computed asymmetry map are employed to extract patch features which are then fed to dictionary learning and classification based on sparse representation. Elastic net is adopted to replace the traditional L 0 -norm/ L 1 -norm constraints on sparse representation to stabilize sparse code. To decrease computation cost and to reduce false positives, regions-of-interest are determined to confine candidate infarct voxels. The proposed method has been validated on 98 consecutive patients recruited within 6 hours from onset. It is shown that the proposed method could handle well infarcts with intensity variability and ill-defined edges to yield significantly higher Dice coefficient (0.755 ± 0.118) than the other two methods and their enhanced versions by confining their segmentations within the regions-of-interest (average Dice coefficient less than 0.610). The proposed method could provide a potential tool to quantify infarcts from diffusion weighted imaging at hyperacute stage with accuracy and speed to assist the decision making especially for thrombolytic therapy.

Children's judgements and emotions about social exclusion based on weight.

PubMed

Nguyen, Christine; Malti, Tina

2014-09-01

This study examined children's judgements and emotions associated with weight-based social exclusion using an ethnically diverse sample of one hundred and seventeen 9- and 13-year-old children. Children were interviewed about three scenarios depicting weight-based exclusion in athletic, academic, and social contexts. Children's judgements of exclusion, emotions attributed to the excluder and excluded targets, and justifications for judgements and emotions were examined. Overall, children judged weight-based exclusion to be wrong for moral reasons. However, they viewed weight-based exclusion in athletic contexts as less wrong compared with academic contexts, and they used more social-conventional reasoning to justify judgements and emotions attributed to excluders in athletic contexts compared with academic and social contexts. Children also expected excluded targets to feel negative emotions, whereas a range of positive and negative emotions was attributed to excluders. In addition, older children were more accepting of weight-based exclusion in athletic contexts than in academic and social contexts. We discuss the results in relation to the development of children's understanding of, and emotions associated with, exclusion based on weight. © 2014 The British Psychological Society.

Fusion of pan-tropical biomass maps using weighted averaging and regional calibration data

NASA Astrophysics Data System (ADS)

Ge, Yong; Avitabile, Valerio; Heuvelink, Gerard B. M.; Wang, Jianghao; Herold, Martin

2014-09-01

Biomass is a key environmental variable that influences many biosphere-atmosphere interactions. Recently, a number of biomass maps at national, regional and global scales have been produced using different approaches with a variety of input data, such as from field observations, remotely sensed imagery and other spatial datasets. However, the accuracy of these maps varies regionally and is largely unknown. This research proposes a fusion method to increase the accuracy of regional biomass estimates by using higher-quality calibration data. In this fusion method, the biases in the source maps were first adjusted to correct for over- and underestimation by comparison with the calibration data. Next, the biomass maps were combined linearly using weights derived from the variance-covariance matrix associated with the accuracies of the source maps. Because each map may have different biases and accuracies for different land use types, the biases and fusion weights were computed for each of the main land cover types separately. The conceptual arguments are substantiated by a case study conducted in East Africa. Evaluation analysis shows that fusing multiple source biomass maps may produce a more accurate map than when only one biomass map or unweighted averaging is used.

Technology- and Phone-Based Weight Loss Intervention

PubMed Central

Hartman, Sheri J.; Nelson, Sandahl H.; Cadmus-Bertram, Lisa A.; Patterson, Ruth E.; Parker, Barbara A.; Pierce, John P.

2017-01-01

Introduction For women with an increased breast cancer risk, reducing excess weight and increasing physical activity are believed to be important approaches for reducing their risk. This study tested a weight loss intervention that combined commercially available technology-based self-monitoring tools with individualized phone calls. Design Women were randomized to a weight loss intervention arm (n=36) or a usual care arm (n=18). Setting/Participants Participants were women with a BMI ≥ 27.5 kg/m2 and elevated breast cancer risk recruited from the mammography clinic at the Moores Cancer Center at the University of California San Diego. Intervention Intervention participants used the MyFitnessPal website and phone app to monitor diet and a Fitbit to monitor physical activity. Participants received 12 standardized coaching calls with trained counselors over 6 months. Usual care participants received the U.S. Dietary Guidelines for Americans at baseline and two brief calls over the 6 months. Main outcome measures Weight and accelerometer-measured physical activity were assessed at baseline and 6 months. Data were collected in San Diego, CA, from 2012 to 2014 and analyzed in 2015. Results Participants (n=54) had a mean age of 59.5 (SD=5.6) years, BMI of 31.9 (SD=3.5), and a mean Gail Model score of 2.5 (SD=1.4). At 6 months, intervention participants had lost significantly more weight (4.4 kg vs 0.8 kg, p=0.004) and a greater percentage of starting weight (5.3% vs 1.0%, p=0.005) than usual care participants. Across arms, greater increases in moderate-to-vigorous physical activity resulted in greater weight loss (p=0.01). Conclusions Combining technology-based self-monitoring tools with phone counseling supported weight loss over 6 months in women at increased risk for breast cancer. PMID:27593420

Pros, Cons, and Alternatives to Weight Based Cost Estimating

NASA Technical Reports Server (NTRS)

Joyner, Claude R.; Lauriem, Jonathan R.; Levack, Daniel H.; Zapata, Edgar

2011-01-01

Many cost estimating tools use weight as a major parameter in projecting the cost. This is often combined with modifying factors such as complexity, technical maturity of design, environment of operation, etc. to increase the fidelity of the estimate. For a set of conceptual designs, all meeting the same requirements, increased weight can be a major driver in increased cost. However, once a design is fixed, increased weight generally decreases cost, while decreased weight generally increases cost - and the relationship is not linear. Alternative approaches to estimating cost without using weight (except perhaps for materials costs) have been attempted to try to produce a tool usable throughout the design process - from concept studies through development. This paper will address the pros and cons of using weight based models for cost estimating, using liquid rocket engines as the example. It will then examine approaches that minimize the impct of weight based cost estimating. The Rocket Engine- Cost Model (RECM) is an attribute based model developed internally by Pratt & Whitney Rocketdyne for NASA. RECM will be presented primarily to show a successful method to use design and programmatic parameters instead of weight to estimate both design and development costs and production costs. An operations model developed by KSC, the Launch and Landing Effects Ground Operations model (LLEGO), will also be discussed.

A hospital-based birth weight analysis using computerized perinatal data base for a Chinese population.

PubMed

Fu, Jing; Yu, Mei

2011-04-01

We aimed to construct birth weight-for-gestational age nomograms based on a computerized perinatal data base in a hospital-based Chinese population. Retrospectively collected 28,052 singleton deliveries at Women and Children's Medical Center, Guangzhou, China. Standard curves of birth weight from 27 to 43 week's gestation were computed. The nomograms included the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles and standard deviations. 79.9% pregnant women delivered between 38, 39, and 40 gestational week, and the mean birth weights are 3160, 3282, and 3388 g, respectively. Preterm birth is 5.7%. In general, male birth weights are greater than females at each gestational week. The hospital-based Chinese population birth weight is lower than that of North American and Scandinavian population. A different standard birth weight is needed for different population. A hospital-based birth weight curve by gestational week is established, which can be a useful tool to estimate intrauterine fetal growth to define SGA or LGA fetuses.

Impact of parental weight status on a school-based weight management programme designed for Mexican-American children.

PubMed

Moreno, J P; Johnston, C A; Hernandez, D C; LeNoble, J; Papaioannou, M A; Foreyt, J P

2016-10-01

While overweight and obese children are more likely to have overweight or obese parents, less is known about the effect of parental weight status on children's success in weight management programmes. This study was a secondary data analysis of a randomized controlled trial and investigated the impact of having zero, one or two obese parents on children's success in a school-based weight management programme. Sixty-one Mexican-American children participated in a 24-week school-based weight management intervention which took place in 2005-2006. Children's heights and weights were measured at baseline, 3, 6 and 12 months. Parental weight status was assessed at baseline. Repeated measures anova and ancova were conducted to compare changes in children's weight within and between groups, respectively. Within-group comparisons revealed that the intervention led to significant decreases in standardized body mass index (zBMI) for children with zero (F = 23.16, P < .001) or one obese (F = 4.99, P < .05) parent. Between-group comparisons indicated that children with zero and one obese parents demonstrated greater decreases in zBMI compared to children with two obese parents at every time point. The school-based weight management programme appears to be most efficacious for children with one or no obese parents compared to children with two obese parents. These results demonstrate the need to consider parental weight status when engaging in childhood weight management efforts. © 2015 World Obesity.

A feasibility study of automatic lung nodule detection in chest digital tomosynthesis with machine learning based on support vector machine

NASA Astrophysics Data System (ADS)

Lee, Donghoon; Kim, Ye-seul; Choi, Sunghoon; Lee, Haenghwa; Jo, Byungdu; Choi, Seungyeon; Shin, Jungwook; Kim, Hee-Joung

2017-03-01

The chest digital tomosynthesis(CDT) is recently developed medical device that has several advantage for diagnosing lung disease. For example, CDT provides depth information with relatively low radiation dose compared to computed tomography (CT). However, a major problem with CDT is the image artifacts associated with data incompleteness resulting from limited angle data acquisition in CDT geometry. For this reason, the sensitivity of lung disease was not clear compared to CT. In this study, to improve sensitivity of lung disease detection in CDT, we developed computer aided diagnosis (CAD) systems based on machine learning. For design CAD systems, we used 100 cases of lung nodules cropped images and 100 cases of normal lesion cropped images acquired by lung man phantoms and proto type CDT. We used machine learning techniques based on support vector machine and Gabor filter. The Gabor filter was used for extracting characteristics of lung nodules and we compared performance of feature extraction of Gabor filter with various scale and orientation parameters. We used 3, 4, 5 scales and 4, 6, 8 orientations. After extracting features, support vector machine (SVM) was used for classifying feature of lesions. The linear, polynomial and Gaussian kernels of SVM were compared to decide the best SVM conditions for CDT reconstruction images. The results of CAD system with machine learning showed the capability of automatically lung lesion detection. Furthermore detection performance was the best when Gabor filter with 5 scale and 8 orientation and SVM with Gaussian kernel were used. In conclusion, our suggested CAD system showed improving sensitivity of lung lesion detection in CDT and decide Gabor filter and SVM conditions to achieve higher detection performance of our developed CAD system for CDT.

Computer-aided diagnosis of breast cancer via Gabor wavelet bank and binary-class SVM in mammographic images

NASA Astrophysics Data System (ADS)

Torrents-Barrena, Jordina; Puig, Domenec; Melendez, Jaime; Valls, Aida

2016-03-01

Breast cancer is one of the most dangerous diseases that attack women in their 40s worldwide. Due to this fact, it is estimated that one in eight women will develop a malignant carcinoma during their life. In addition, the carelessness of performing regular screenings is an important reason for the increase of mortality. However, computer-aided diagnosis systems attempt to enhance the quality of mammograms as well as the detection of early signs related to the disease. In this paper we propose a bank of Gabor filters to calculate the mean, standard deviation, skewness and kurtosis features by four-sized evaluation windows. Therefore, an active strategy is used to select the most relevant pixels. Finally, a supervised classification stage using two-class support vector machines is utilised through an accurate estimation of kernel parameters. In order to show the development of our methodology based on mammographic image analysis, two main experiments are fulfilled: abnormal/normal breast tissue classification and the ability to detect the different breast cancer types. Moreover, the public screen-film mini-MIAS database is compared with a digitised breast cancer database to evaluate the method robustness. The area under the receiver operating characteristic curve is used to measure the performance of the method. Furthermore, both confusion matrix and accuracy are calculated to assess the results of the proposed algorithm.

DRD2 Promoter Region Variation Predicts Antipsychotic-Induced Weight Gain in First Episode Schizophrenia

PubMed Central

Lencz, Todd; Robinson, Delbert G.; Napolitano, Barbara; Sevy, Serge; Kane, John M.; Goldman, David; Malhotra, Anil K.

2010-01-01

Many antipsychotic medications carry a substantial liability for weight gain, and one mechanism common to all antipsychotics is binding to the dopamine D2 receptor. We therefore examined the relationship between −141C Ins/Del (rs1799732), a functional promoter region polymorphism in DRD2, and antipsychotic-induced weight gain in 58 first episode schizophrenia patients enrolled in a randomized trial of risperidone (RIS) vs. olanzapine (OLZ). Carriers of the deletion allele (n=29) were compared to Ins/Ins homozygotes (non-carriers, n=29) in a mixed model encompassing 10 weight measurements over 16 weeks. Deletion allele carriers demonstrated significantly more weight gain after 6 weeks of treatment regardless of assigned medication. While deletion carriers were prescribed higher doses of OLZ (but not RIS), dose did not appear to account for the genotype effects on weight gain. Given previous evidence that deletion carriers demonstrate reduced symptom response to medication, additional study of appropriate treatment options for these patients appears warranted. PMID:20664489

Weight-Based Victimization toward Overweight Adolescents: Observations and Reactions of Peers

ERIC Educational Resources Information Center

Puhl, Rebecca M.; Luedicke, Joerg; Heuer, Cheslea

2011-01-01

Background: Weight-based victimization has become increasingly reported among overweight youth, but little is known about adolescents' perceptions and observations of weight-based teasing and bullying. This study examined adolescents' observations of and reactions to weight-based victimization toward overweight students at school. Methods:…

Weight maintenance, behaviors and barriers among previous participants of a university-based weight control program.

PubMed

Befort, C A; Stewart, E E; Smith, B K; Gibson, C A; Sullivan, D K; Donnelly, J E

2008-03-01

To examine weight loss maintenance among previous participants of a university-based behavioral weight management program and to compare behavioral strategies and perceived barriers between successful and unsuccessful maintainers. Previous program participants (n=179) completed mailed surveys assessing current weight, weight control behaviors and perceived barriers to weight loss maintenance. At 14.1+/-10.8 months following completion of treatment, survey respondents were on average 12.6+/-12.6 kg, or 11.3+/-10.7%, below baseline weight; 76.5% of respondents had successfully maintained weight, defined as maintaining a weight loss of at least 5% below baseline. Compared to unsuccessful maintainers, successful maintainers reported practicing four dietary and three physical activity weight control strategies more often and experiencing five barriers to healthy eating and exercise less often. After accounting for time since treatment and maximum weight loss while in treatment, the strongest correlates of successful weight loss maintenance were frequent exercise and perceived difficulty of weight management. Clinically meaningful weight loss maintenance was achieved by the majority of participants. Findings support the literature indicating that physical activity is one of the strongest predictors of successful weight loss maintenance. Findings also suggest that strategies to reduce the level of perceived effort required for long-term weight control may improve maintenance outcomes.

Imperfect pitch: Gabor's uncertainty principle and the pitch of extremely brief sounds.

PubMed

Hsieh, I-Hui; Saberi, Kourosh

2016-02-01

How brief must a sound be before its pitch is no longer perceived? The uncertainty tradeoff between temporal and spectral resolution (Gabor's principle) limits the minimum duration required for accurate pitch identification or discrimination. Prior studies have reported that pitch can be extracted from sinusoidal pulses as brief as half a cycle. This finding has been used in a number of classic papers to develop models of pitch encoding. We have found that phase randomization, which eliminates timbre confounds, degrades this ability to chance, raising serious concerns over the foundation on which classic pitch models have been built. The current study investigated whether subthreshold pitch cues may still exist in partial-cycle pulses revealed through statistical integration in a time series containing multiple pulses. To this end, we measured frequency-discrimination thresholds in a two-interval forced-choice task for trains of partial-cycle random-phase tone pulses. We found that residual pitch cues exist in these pulses but discriminating them requires an order of magnitude (ten times) larger frequency difference than that reported previously, necessitating a re-evaluation of pitch models built on earlier findings. We also found that as pulse duration is decreased to less than two cycles its pitch becomes biased toward higher frequencies, consistent with predictions of an auto-correlation model of pitch extraction.

Trends in simulated chemical composition of global and regional population-weighted fine particulate matter over the recent 25 years

NASA Astrophysics Data System (ADS)

Li, C.; Martin, R.; van Donkelaar, A.; Boys, B.; Hammer, M. S.; Xu, J.; Marais, E. A.; Reff, A.; Strum, M.; Ridley, D. A.; Crippa, M.; Zhang, Q.

2017-12-01

We interpret in situ and satellite observations with a chemical transport model (GEOS-Chem) to understand global trends in population-weighted mean chemical composition of fine particulate matter (PM2.5) over 1989-2013. Simulated PM2.5 composition concentrations at 2˚ × 2.5˚ resolution are downscaled to 0.1˚ × 0.1˚ with satellite-based estimates of PM2.5 to better represent population exposure. Trends in simulated and observed population-weighted mean PM2.5 composition over 1989-2013 exhibit a high degree of consistency for (in situ vs. downscaled simulation) PM2.5 (-2.4 vs. -2.4 % yr-1), secondary inorganic aerosols (-4.3 vs. -4.1% yr-1), organic aerosols (OA, -3.6 vs. -3.0 % yr-1) and black carbon (-4.3 vs. -3.9 % yr-1) over North America, as well as sulfate (-4.7 vs. -5.8 % yr-1) over Europe. The downscaled simulation also has overlapping 95% confidence intervals with satellite-derived trends in population-weighted mean PM2.5 for 20 of the 21 Global Burden of Disease Study (GBD) regions over 1998-2013. Over 1989-2013, most (79%) of the simulated increase in global population-weighted mean PM2.5 of 0.28 μg m-3yr-1 is explained by significantly (p < 0.05) increasing OA (0.10 μg m-3yr-1), nitrate (0.05 μg m-3yr-1), sulfate (0.04 μg m-3yr-1) and ammonium (0.03 μg m-3yr-1). These species predominantly drive trends in population-weighted mean PM2.5 over populous regions of South Asia (0.94 μg m-3yr-1), East Asia (0.66 μg m-3yr-1), Western Europe (-0.47 μg m-3yr-1) and North America (-0.32 μg m-3yr-1), primarily due to changes in anthropogenic emissions. Mineral dust from deserts and OA over open burning regions usually cause weak, insignificant trends in population-weighted mean PM2.5, despite strong inter-annual variation. Global trends in area-weighted mean PM2.5 differ significantly from population-weighted trends in both the magnitude and sign, indicating the importance of population weighting for relevance to human exposure studies. This study

Does Successful Weight Loss in an Internet-Based Worksite Weight Loss Program Improve Employee Presenteeism and Absenteeism?

PubMed Central

Harden, Samantha M.; You, Wen; Almeida, Fabio A.; Hill, Jennie L.; Linnan, Laura A.; Allen, Kacie C.; Estabrooks, Paul A.

2017-01-01

Certain risk factors associated with overweight and obesity may lead to reduced productivity in the workforce (i.e., increased absenteeism and presenteeism). Participants in a large, Internet-based worksite weight loss intervention, who were present at follow-up (N = 1,030), completed a self-reported productivity measure (World Health Organization’s Health and Work Performance Questionnaire) at baseline and postintervention. Twenty-two percent of the participants lost a clinically meaningful amount of weight (≥5% weight loss). There were no statistically significant (p < .05) relationships between weight change from baseline to 12 months and change scores of absolute or relative absenteeism or for absolute or relative presenteeism. Within a modestly successful Internet-based, worksite weight loss intervention, weight loss did not improve self-reported absenteeism or presenteeism. Further studies are needed to explore the sensitivity of the World Health Organization’s Health and Work Performance Questionnaire and the long-term effects of weight loss on productivity. PMID:25842385

Does Successful Weight Loss in an Internet-Based Worksite Weight Loss Program Improve Employee Presenteeism and Absenteeism?

PubMed

Harden, Samantha M; You, Wen; Almeida, Fabio A; Hill, Jennie L; Linnan, Laura A; Allen, Kacie C; Estabrooks, Paul A

2015-12-01

Certain risk factors associated with overweight and obesity may lead to reduced productivity in the workforce (i.e., increased absenteeism and presenteeism). Participants in a large, Internet-based worksite weight loss intervention, who were present at follow-up (N = 1,030), completed a self-reported productivity measure (World Health Organization's Health and Work Performance Questionnaire) at baseline and postintervention. Twenty-two percent of the participants lost a clinically meaningful amount of weight (≥5% weight loss). There were no statistically significant (p < .05) relationships between weight change from baseline to 12 months and change scores of absolute or relative absenteeism or for absolute or relative presenteeism. Within a modestly successful Internet-based, worksite weight loss intervention, weight loss did not improve self-reported absenteeism or presenteeism. Further studies are needed to explore the sensitivity of the World Health Organization's Health and Work Performance Questionnaire and the long-term effects of weight loss on productivity. © 2015 Society for Public Health Education.

Relating shape/weight based self-esteem, depression, and anxiety with weight and perceived physical health among young adults.

PubMed

Kamody, Rebecca C; Thurston, Idia B; Decker, Kristina M; Kaufman, Caroline C; Sonneville, Kendrin R; Richmond, Tracy K

2018-06-01

Simultaneous contributions of self-esteem, depression, and anxiety to weight and perceived physical health in young adults is understudied. A diverse sample of 424 young adults completed measures of shape/weight based self-esteem, depression, anxiety, and perceived physical health. Height and weight were measured to calculate body mass index (BMI). Latent profile analysis was conducted to derive patterns of depression, anxiety, and shape/weight based self-esteem. Then, we examined the association of the profiles with weight status and perceived physical health. Three profiles emerged: (1) High Shape/Weight Influence (HSWI); (2) Low Shape/Weight, Depression, & Anxiety Influence (LSWDAI); and (3) High Depression & Anxiety Influence (HDAI). The HSWI profile had significantly higher BMI than the LSWDAI and HDAI profiles, and significantly lower perceived physical health than the LSWDAI profile. Over emphasis on shape/weight, regardless of depression and anxiety, is associated with elevated weight and negative internalized health views. Copyright © 2018 Elsevier Ltd. All rights reserved.

Web-Based Interventions for Weight Loss or Weight Loss Maintenance in Overweight and Obese People: A Systematic Review of Systematic Reviews

PubMed Central

Sorgente, Angela; Manzoni, Gian Mauro; Re, Federica; Simpson, Susan; Perona, Sara; Rossi, Alessandro; Cattivelli, Roberto; Innamorati, Marco; Jackson, Jeffrey B; Castelnuovo, Gianluca

2017-01-01

Background Weight loss is challenging and maintenance of weight loss is problematic. Web-based programs offer good potential for delivery of interventions for weight loss or weight loss maintenance. However, the precise impact of Web-based weight management programs is still unclear. Objective The purpose of this meta-systematic review was to provide a comprehensive summary of the efficacy of Web-based interventions for weight loss and weight loss maintenance. Methods Electronic databases were searched for systematic reviews and meta-analyses that included at least one study investigating the effect of a Web-based intervention on weight loss and/or weight loss maintenance among samples of overweight and/or obese individuals. Twenty identified reviews met the inclusion criteria. The Revised Assessment of Multiple SysTemAtic Reviews (R-AMSTAR) was used to assess methodological quality of reviews. All included reviews were of sufficient methodological quality (R-AMSTAR score ≥22). Key methodological and outcome data were extracted from each review. Results Web-based interventions for both weight loss and weight loss maintenance were more effective than minimal or control conditions. However, when contrasted with comparable non-Web-based interventions, results were less consistent across reviews. Conclusions Overall, the efficacy of weight loss maintenance interventions was stronger than the efficacy of weight loss interventions, but further evidence is needed to more clearly understand the efficacy of both types of Web-based interventions. Trial Registration PROSPERO 2015: CRD42015029377; http://www.crd.york.ac.uk/PROSPERO/display_record.asp? ID=CRD42015029377 (Archived by WebCite at http://www.webcitation.org/6qkSafdCZ) PMID:28652225

Investigation of contrast-enhanced subtracted breast CT images with MAP-EM based on projection-based weighting imaging.

PubMed

Zhou, Zhengdong; Guan, Shaolin; Xin, Runchao; Li, Jianbo

2018-06-01

Contrast-enhanced subtracted breast computer tomography (CESBCT) images acquired using energy-resolved photon counting detector can be helpful to enhance the visibility of breast tumors. In such technology, one challenge is the limited number of photons in each energy bin, thereby possibly leading to high noise in separate images from each energy bin, the projection-based weighted image, and the subtracted image. In conventional low-dose CT imaging, iterative image reconstruction provides a superior signal-to-noise compared with the filtered back projection (FBP) algorithm. In this paper, maximum a posteriori expectation maximization (MAP-EM) based on projection-based weighting imaging for reconstruction of CESBCT images acquired using an energy-resolving photon counting detector is proposed, and its performance was investigated in terms of contrast-to-noise ratio (CNR). The simulation study shows that MAP-EM based on projection-based weighting imaging can improve the CNR in CESBCT images by 117.7%-121.2% compared with FBP based on projection-based weighting imaging method. When compared with the energy-integrating imaging that uses the MAP-EM algorithm, projection-based weighting imaging that uses the MAP-EM algorithm can improve the CNR of CESBCT images by 10.5%-13.3%. In conclusion, MAP-EM based on projection-based weighting imaging shows significant improvement the CNR of the CESBCT image compared with FBP based on projection-based weighting imaging, and MAP-EM based on projection-based weighting imaging outperforms MAP-EM based on energy-integrating imaging for CESBCT imaging.

Outcome based state budget allocation for diabetes prevention programs using multi-criteria optimization with robust weights.

PubMed

Mehrotra, Sanjay; Kim, Kibaek

2011-12-01

We consider the problem of outcomes based budget allocations to chronic disease prevention programs across the United States (US) to achieve greater geographical healthcare equity. We use Diabetes Prevention and Control Programs (DPCP) by the Center for Disease Control and Prevention (CDC) as an example. We present a multi-criteria robust weighted sum model for such multi-criteria decision making in a group decision setting. The principal component analysis and an inverse linear programming techniques are presented and used to study the actual 2009 budget allocation by CDC. Our results show that the CDC budget allocation process for the DPCPs is not likely model based. In our empirical study, the relative weights for different prevalence and comorbidity factors and the corresponding budgets obtained under different weight regions are discussed. Parametric analysis suggests that money should be allocated to states to promote diabetes education and to increase patient-healthcare provider interactions to reduce disparity across the US.

Multi-atlas based segmentation using probabilistic label fusion with adaptive weighting of image similarity measures.

PubMed

Sjöberg, C; Ahnesjö, A

2013-06-01

Label fusion multi-atlas approaches for image segmentation can give better segmentation results than single atlas methods. We present a multi-atlas label fusion strategy based on probabilistic weighting of distance maps. Relationships between image similarities and segmentation similarities are estimated in a learning phase and used to derive fusion weights that are proportional to the probability for each atlas to improve the segmentation result. The method was tested using a leave-one-out strategy on a database of 21 pre-segmented prostate patients for different image registrations combined with different image similarity scorings. The probabilistic weighting yields results that are equal or better compared to both fusion with equal weights and results using the STAPLE algorithm. Results from the experiments demonstrate that label fusion by weighted distance maps is feasible, and that probabilistic weighted fusion improves segmentation quality more the stronger the individual atlas segmentation quality depends on the corresponding registered image similarity. The regions used for evaluation of the image similarity measures were found to be more important than the choice of similarity measure. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Action spectrum conversion factors that change erythemally weighted to previtamin D3-weighted UV doses.

PubMed

Pope, Stanley J; Holick, Michael F; Mackin, Steven; Godar, Dianne E

2008-01-01

Many solar UV measurements, either terrestrial or personal, weight the raw data by the erythemal action spectrum. However, a problem arises when one tries to estimate the benefit of vitamin D(3) production based on erythemally weighted outdoor doses, like those measured by calibrated R-B meters or polysulphone badges, because the differences between action spectra give dissimilar values. While both action spectra peak in the UVB region, the erythemal action spectrum continues throughout the UVA region while the previtamin D(3) action spectrum stops near that boundary. When one uses the previtamin D(3) action spectrum to weight the solar spectra (D(eff)), one gets a different contribution in W m(-2) than what the erythemally weighted data predicts (E(eff)). Thus, to do proper benefit assessments, one must incorporate action spectrum conversion factors (ASCF) into the calculations to change erythemally weighted to previtamin D(3)-weighted doses. To date, all benefit assessments for vitamin D(3) production in human skin from outdoor exposures are overestimates because they did not account for the different contributions of each action spectrum with changing solar zenith angle and ozone and they did not account for body geometry. Here we describe how to normalize the ratios of the effective irradiances (D(eff)/E(eff)) to get ASCF that change erythemally weighted to previtamin D(3)-weighted doses. We also give the ASCF for each season of the year in the northern hemisphere every 5 degrees from 30 degrees N to 60 degrees N, based on ozone values. These ASCF, along with geometry conversion factors and other information, can give better vitamin D(3) estimates from erythemally weighted outdoor doses.

Frequency weightings based on biodynamics of fingers-hand-arm system.

PubMed

Dong, Ren G; Welcome, Daniel E; Wu, John Z

2005-07-01

The frequency weighting for assessing hand-transmitted vibration exposure is critical to obtaining a true dose-response relationship. Any valid weighting must have a solid theoretical foundation. The objectives of this study are to examine the biodynamic foundation for assessing the vibration exposure and to develop a set of biodynamic methods to formulate the frequency weightings for different anatomical locations of the fingers-hand-arm system. The vibration transmissibility measured on the fingers, hand, wrist, elbow, shoulder, and head was used to define the transmitted acceleration-based (TAB) frequency weighting. The apparent masses measured at the fingers and the palm of the hand were used to construct the biodynamic force-based (BFB) weightings. These weightings were compared with the ISO weighting specified in ISO 5349-1 (2001). The results of this study suggest that the frequency weightings for the vibration-induced problems at different anatomical locations of the hand-arm system can be basically divided into three groups: (a) the weighting for the fingers and hand, (b) the weighting for the wrist, elbow, and shoulder, and (c) the weighting for the head. The ISO weighting is highly correlated with the weighting for the second group but not with the first and third groups. The TAB and BFB finger weightings are quite different at frequencies lower than 100 Hz, but they show similar trends at higher frequencies. Both TAB and BFB finger weightings at frequencies higher than 20 Hz are greater than the ISO weighting.

Behavioural factors related with successful weight loss 15 months post-enrolment in a commercial web-based weight-loss programme.

PubMed

Neve, Melinda J; Morgan, Philip J; Collins, Clare E

2012-07-01

As further understanding is required of what behavioural factors are associated with long-term weight-loss success, the aim of the present study was to determine the prevalence of successful weight loss 15 months post-enrolment in a commercial web-based weight-loss programme and which behavioural factors were associated with success. An online survey was completed 15 months post-enrolment in a commercial web-based weight-loss programme to assess weight-related behaviours and current weight. Participants were classified as successful if they had lost ≥5 % of their starting weight after 15 months. Commercial users of a web-based weight-loss programme. Participants enrolled in the commercial programme between August 2007 and May 2008. Six hundred and seventy-seven participants completed the survey. The median (interquartile range) weight change was -2·7 (-8·2, 1·6) % of enrolment weight, with 37 % achieving ≥5 % weight loss. Multivariate logistic regression analysis found success was associated with frequency of weight self-monitoring, higher dietary restraint score, lower emotional eating score, not skipping meals, not keeping snack foods in the house and eating takeaway foods less frequently. The findings suggest that individuals trying to achieve or maintain ≥5 % weight loss should be advised to regularly weigh themselves, avoid skipping meals or keeping snack foods in the house, limit the frequency of takeaway food consumption, manage emotional eating and strengthen dietary restraint. Strategies to assist individuals make these changes to behaviour should be incorporated within obesity treatments to improve the likelihood of successful weight loss in the long term.

Finger vein recognition based on personalized weight maps.

PubMed

Yang, Gongping; Xiao, Rongyang; Yin, Yilong; Yang, Lu

2013-09-10

Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. Binary pattern based methods were thoroughly studied in order to cope with the difficulties of extracting the blood vessel network. However, current binary pattern based finger vein matching methods treat every bit of feature codes derived from different image of various individuals as equally important and assign the same weight value to them. In this paper, we propose a finger vein recognition method based on personalized weight maps (PWMs). The different bits have different weight values according to their stabilities in a certain number of training samples from an individual. Firstly we present the concept of PWM, and then propose the finger vein recognition framework, which mainly consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PWM achieves not only better performance, but also high robustness and reliability. In addition, PWM can be used as a general framework for binary pattern based recognition.

Finger Vein Recognition Based on Personalized Weight Maps

PubMed Central

Yang, Gongping; Xiao, Rongyang; Yin, Yilong; Yang, Lu

2013-01-01

Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. Binary pattern based methods were thoroughly studied in order to cope with the difficulties of extracting the blood vessel network. However, current binary pattern based finger vein matching methods treat every bit of feature codes derived from different image of various individuals as equally important and assign the same weight value to them. In this paper, we propose a finger vein recognition method based on personalized weight maps (PWMs). The different bits have different weight values according to their stabilities in a certain number of training samples from an individual. Firstly we present the concept of PWM, and then propose the finger vein recognition framework, which mainly consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PWM achieves not only better performance, but also high robustness and reliability. In addition, PWM can be used as a general framework for binary pattern based recognition. PMID:24025556

A Weight-Adaptive Laplacian Embedding for Graph-Based Clustering.

PubMed

Cheng, De; Nie, Feiping; Sun, Jiande; Gong, Yihong

2017-07-01

Graph-based clustering methods perform clustering on a fixed input data graph. Thus such clustering results are sensitive to the particular graph construction. If this initial construction is of low quality, the resulting clustering may also be of low quality. We address this drawback by allowing the data graph itself to be adaptively adjusted in the clustering procedure. In particular, our proposed weight adaptive Laplacian (WAL) method learns a new data similarity matrix that can adaptively adjust the initial graph according to the similarity weight in the input data graph. We develop three versions of these methods based on the L2-norm, fuzzy entropy regularizer, and another exponential-based weight strategy, that yield three new graph-based clustering objectives. We derive optimization algorithms to solve these objectives. Experimental results on synthetic data sets and real-world benchmark data sets exhibit the effectiveness of these new graph-based clustering methods.

Low-income women's reproductive weight patterns empirically based clusters of prepregnant, gestational, and postpartum weights.

PubMed

Walker, Lorraine O

2009-01-01

Women have varying weight responses to pregnancy and the postpartum period. The purpose of this study was to derive sub-groups of women based on differing reproductive weight clusters; to validate clusters by reference to adequacy of gestational weight gain (GWG) and postpartum incremental weight shifts; and to examine associations between clusters and demographic, behavioral, and psychosocial variables. A cluster analysis was conducted of a multi-ethnic/racial sample of low-income women (n = 247). Clusters were derived from three weight variables: prepregnant body mass index, GWG, and postpartum retained weight. Five clusters were derived: Cluster 1, normal weight-high prenatal gain-average retain; cluster 2, normal weight-low prenatal gain-zero retain; cluster 3, high normal weight-high prenatal gain-high retain; cluster 4, obese-low prenatal gain-average retain; and cluster 5, overweight-very high prenatal gain-very high retain. Clusters differed with regard to postpartum weight shifts (p < .001), with clusters 3, 4, and 5, mostly gaining weight between 6 weeks and 12 months postpartum, whereas clusters 1 and 2 were losing weight. Clusters were also associated with race/ethnicity (p < .01), breastfeeding immediately postdelivery (p < .01), smoking at 12 months (p < .05), and reaching weight goals at 6 and 12 months (p < .001), but not depressive symptoms, fat intake habits, or physical activity. In a five-cluster solution, postpartum weight shifts, ethnicity, and initial breastfeeding were among factors associated with clusters. Monitoring of weight and appropriate intervention beyond the 6 weeks after birth is needed for low-income women in high normal weight, overweight, and obese clusters.

Quantitative workflow based on NN for weighting criteria in landfill suitability mapping

NASA Astrophysics Data System (ADS)

Abujayyab, Sohaib K. M.; Ahamad, Mohd Sanusi S.; Yahya, Ahmad Shukri; Ahmad, Siti Zubaidah; Alkhasawneh, Mutasem Sh.; Aziz, Hamidi Abdul

2017-10-01

Our study aims to introduce a new quantitative workflow that integrates neural networks (NNs) and multi criteria decision analysis (MCDA). Existing MCDA workflows reveal a number of drawbacks, because of the reliance on human knowledge in the weighting stage. Thus, new workflow presented to form suitability maps at the regional scale for solid waste planning based on NNs. A feed-forward neural network employed in the workflow. A total of 34 criteria were pre-processed to establish the input dataset for NN modelling. The final learned network used to acquire the weights of the criteria. Accuracies of 95.2% and 93.2% achieved for the training dataset and testing dataset, respectively. The workflow was found to be capable of reducing human interference to generate highly reliable maps. The proposed workflow reveals the applicability of NN in generating landfill suitability maps and the feasibility of integrating them with existing MCDA workflows.

Weighted functional linear regression models for gene-based association analysis.

PubMed

Belonogova, Nadezhda M; Svishcheva, Gulnara R; Wilson, James F; Campbell, Harry; Axenovich, Tatiana I

2018-01-01

Functional linear regression models are effectively used in gene-based association analysis of complex traits. These models combine information about individual genetic variants, taking into account their positions and reducing the influence of noise and/or observation errors. To increase the power of methods, where several differently informative components are combined, weights are introduced to give the advantage to more informative components. Allele-specific weights have been introduced to collapsing and kernel-based approaches to gene-based association analysis. Here we have for the first time introduced weights to functional linear regression models adapted for both independent and family samples. Using data simulated on the basis of GAW17 genotypes and weights defined by allele frequencies via the beta distribution, we demonstrated that type I errors correspond to declared values and that increasing the weights of causal variants allows the power of functional linear models to be increased. We applied the new method to real data on blood pressure from the ORCADES sample. Five of the six known genes with P < 0.1 in at least one analysis had lower P values with weighted models. Moreover, we found an association between diastolic blood pressure and the VMP1 gene (P = 8.18×10-6), when we used a weighted functional model. For this gene, the unweighted functional and weighted kernel-based models had P = 0.004 and 0.006, respectively. The new method has been implemented in the program package FREGAT, which is freely available at https://cran.r-project.org/web/packages/FREGAT/index.html.

Assessment of global and local region-based bilateral mammographic feature asymmetry to predict short-term breast cancer risk

NASA Astrophysics Data System (ADS)

Li, Yane; Fan, Ming; Cheng, Hu; Zhang, Peng; Zheng, Bin; Li, Lihua

2018-01-01

This study aims to develop and test a new imaging marker-based short-term breast cancer risk prediction model. An age-matched dataset of 566 screening mammography cases was used. All ‘prior’ images acquired in the two screening series were negative, while in the ‘current’ screening images, 283 cases were positive for cancer and 283 cases remained negative. For each case, two bilateral cranio-caudal view mammograms acquired from the ‘prior’ negative screenings were selected and processed by a computer-aided image processing scheme, which segmented the entire breast area into nine strip-based local regions, extracted the element regions using difference of Gaussian filters, and computed both global- and local-based bilateral asymmetrical image features. An initial feature pool included 190 features related to the spatial distribution and structural similarity of grayscale values, as well as of the magnitude and phase responses of multidirectional Gabor filters. Next, a short-term breast cancer risk prediction model based on a generalized linear model was built using an embedded stepwise regression analysis method to select features and a leave-one-case-out cross-validation method to predict the likelihood of each woman having image-detectable cancer in the next sequential mammography screening. The area under the receiver operating characteristic curve (AUC) values significantly increased from 0.5863  ±  0.0237 to 0.6870  ±  0.0220 when the model trained by the image features extracted from the global regions and by the features extracted from both the global and the matched local regions (p  =  0.0001). The odds ratio values monotonically increased from 1.00-8.11 with a significantly increasing trend in slope (p  =  0.0028) as the model-generated risk score increased. In addition, the AUC values were 0.6555  ±  0.0437, 0.6958  ±  0.0290, and 0.7054  ±  0.0529 for the three age groups of 37

Classification of polycystic ovary based on ultrasound images using competitive neural network

NASA Astrophysics Data System (ADS)

Dewi, R. M.; Adiwijaya; Wisesty, U. N.; Jondri

2018-03-01

Infertility in the women reproduction system due to inhibition of follicles maturation process causing the number of follicles which is called polycystic ovaries (PCO). PCO detection is still operated manually by a gynecologist by counting the number and size of follicles in the ovaries, so it takes a long time and needs high accuracy. In general, PCO can be detected by calculating stereology or feature extraction and classification. In this paper, we designed a system to classify PCO by using the feature extraction (Gabor Wavelet method) and Competitive Neural Network (CNN). CNN was selected because this method is the combination between Hemming Net and The Max Net so that the data classification can be performed based on the specific characteristics of ultrasound data. Based on the result of system testing, Competitive Neural Network obtained the highest accuracy is 80.84% and the time process is 60.64 seconds (when using 32 feature vectors as well as weight and bias values respectively of 0.03 and 0.002).

Parallelized multi-graphics processing unit framework for high-speed Gabor-domain optical coherence microscopy.

PubMed

Tankam, Patrice; Santhanam, Anand P; Lee, Kye-Sung; Won, Jungeun; Canavesi, Cristina; Rolland, Jannick P

2014-07-01

Gabor-domain optical coherence microscopy (GD-OCM) is a volumetric high-resolution technique capable of acquiring three-dimensional (3-D) skin images with histological resolution. Real-time image processing is needed to enable GD-OCM imaging in a clinical setting. We present a parallelized and scalable multi-graphics processing unit (GPU) computing framework for real-time GD-OCM image processing. A parallelized control mechanism was developed to individually assign computation tasks to each of the GPUs. For each GPU, the optimal number of amplitude-scans (A-scans) to be processed in parallel was selected to maximize GPU memory usage and core throughput. We investigated five computing architectures for computational speed-up in processing 1000×1000 A-scans. The proposed parallelized multi-GPU computing framework enables processing at a computational speed faster than the GD-OCM image acquisition, thereby facilitating high-speed GD-OCM imaging in a clinical setting. Using two parallelized GPUs, the image processing of a 1×1×0.6  mm3 skin sample was performed in about 13 s, and the performance was benchmarked at 6.5 s with four GPUs. This work thus demonstrates that 3-D GD-OCM data may be displayed in real-time to the examiner using parallelized GPU processing.

Feature-based attentional modulation increases with stimulus separation in divided-attention tasks.

PubMed

Sally, Sharon L; Vidnyánsky, Zoltán; Papathomas, Thomas V

2009-01-01

Attention modifies our visual experience by selecting certain aspects of a scene for further processing. It is therefore important to understand factors that govern the deployment of selective attention over the visual field. Both location and feature-specific mechanisms of attention have been identified and their modulatory effects can interact at a neural level (Treue and Martinez-Trujillo, 1999). The effects of spatial parameters on feature-based attentional modulation were examined for the feature dimensions of orientation, motion and color using three divided-attention tasks. Subjects performed concurrent discriminations of two briefly presented targets (Gabor patches) to the left and right of a central fixation point at eccentricities of +/-2.5 degrees , 5 degrees , 10 degrees and 15 degrees in the horizontal plane. Gabors were size-scaled to maintain consistent single-task performance across eccentricities. For all feature dimensions, the data show a linear increase in the attentional effects with target separation. In a control experiment, Gabors were presented on an isoeccentric viewing arc at 10 degrees and 15 degrees at the closest spatial separation (+/-2.5 degrees ) of the main experiment. Under these conditions, the effects of feature-based attentional effects were largely eliminated. Our results are consistent with the hypothesis that feature-based attention prioritizes the processing of attended features. Feature-based attentional mechanisms may have helped direct the attentional focus to the appropriate target locations at greater separations, whereas similar assistance may not have been necessary at closer target spacings. The results of the present study specify conditions under which dual-task performance benefits from sharing similar target features and may therefore help elucidate the processes by which feature-based attention operates.

Weighed down by stigma: How weight-based social identity threat contributes to weight gain and poor health

PubMed Central

Hunger, Jeffrey M.; Major, Brenda; Blodorn, Alison; Miller, Carol T.

2015-01-01

Weight stigma is pervasive, and a number of scholars argue that this profound stigma contributes to the negative effects of weight on psychological and physical health. Some lay individuals and health professionals assume that stigmatizing weight can actually motivate healthier behaviors and promote weight loss. However, as we review, weight stigma is consistently associated with poorer mental and physical health outcomes. In this article we propose a social identity threat model elucidating how weight stigma contributes to weight gain and poorer mental and physical health among overweight individuals. We propose that weight-based social identity threat increases physiological stress, undermines self-regulation, compromises psychological health, and increases the motivation to avoid stigmatizing domains (e.g., the gym) and escape the stigma by engaging in unhealthy weight loss behaviors. Given the prevalence of overweight and obesity in the US, weight stigma thus has the potential to undermine the health and wellbeing of millions of Americans. PMID:29225670

Results of a faith-based weight loss intervention for black women.

PubMed

Fitzgibbon, Marian L; Stolley, Melinda R; Ganschow, Pamela; Schiffer, Linda; Wells, Anita; Simon, Nolanna; Dyer, Alan

2005-10-01

Obesity is a risk factor for a variety of chronic diseases. Although weight loss may reduce these risks, weight loss programs designed for black women have yielded mixed results. Studies suggest that religion/spirituality is a prominent component of black culture. Given this, the inclusion of religion/spirituality as an active component of a weight loss program may enhance the benefits of the program. The role of religion/spirituality, however, has not been specifically tested as a mechanism that enhances the weight loss process. This paper presents the results of "Faith on the Move," a randomized pilot study of a faith-based weight loss program for black women. The goals of the study were to estimate the effects of a 12-week culturally tailored, faith-based weight loss intervention on weight loss, dietary fat consumption and physical activity. The culturally tailored, faith-based weight loss intervention was compared to a culturally tailored weight loss intervention with no active faith component. Fifty-nine overweight/obese black women were randomized to one of the two interventions. Although the results were not statistically significant, the effect size suggests that the addition of the faith component improved results. These promising preliminary results will need to be tested in an adequately powered trial.

X-33 Base Region Thermal Protection System Design Study

NASA Technical Reports Server (NTRS)

Lycans, Randal W.

1998-01-01

The X-33 is an advanced technology demonstrator for validating critical technologies and systems required for an operational Single-Stage-to-Orbit (SSTO) Reusuable Launch Vehicle (RLV). Currently under development by a unique contractor/government team led by Lockheed- Martin Skunk Works (LMSW), and managed by Marshall Space Flight Center (MSFC), the X-33 will be the prototype of the first new launch system developed by the United States since the advent of the space shuttle. This paper documents a design trade study of the X-33 base region thermal protection system (TPS). Two candidate designs were evaluated for thermal performance and weight. The first candidate was a fully reusable metallic TPS using Inconel honeycomb panels insulated with high temperature fibrous insulation, while the second was an ablator/insulator sprayed on the metallic skin of the vehicle. The TPS configurations and insulation thickness requirements were determined for the predicted main engine plume heating environments and base region entry aerothermal environments. In addition to thermal analysis of the design concepts, sensitivity studies were performed to investigate the effect of variations in key parameters of the base TPS analysis.

Patterns of brain structural connectivity differentiate normal weight from overweight subjects

PubMed Central

Gupta, Arpana; Mayer, Emeran A.; Sanmiguel, Claudia P.; Van Horn, John D.; Woodworth, Davis; Ellingson, Benjamin M.; Fling, Connor; Love, Aubrey; Tillisch, Kirsten; Labus, Jennifer S.

2015-01-01

Background Alterations in the hedonic component of ingestive behaviors have been implicated as a possible risk factor in the pathophysiology of overweight and obese individuals. Neuroimaging evidence from individuals with increasing body mass index suggests structural, functional, and neurochemical alterations in the extended reward network and associated networks. Aim To apply a multivariate pattern analysis to distinguish normal weight and overweight subjects based on gray and white-matter measurements. Methods Structural images (N = 120, overweight N = 63) and diffusion tensor images (DTI) (N = 60, overweight N = 30) were obtained from healthy control subjects. For the total sample the mean age for the overweight group (females = 32, males = 31) was 28.77 years (SD = 9.76) and for the normal weight group (females = 32, males = 25) was 27.13 years (SD = 9.62). Regional segmentation and parcellation of the brain images was performed using Freesurfer. Deterministic tractography was performed to measure the normalized fiber density between regions. A multivariate pattern analysis approach was used to examine whether brain measures can distinguish overweight from normal weight individuals. Results 1. White-matter classification: The classification algorithm, based on 2 signatures with 17 regional connections, achieved 97% accuracy in discriminating overweight individuals from normal weight individuals. For both brain signatures, greater connectivity as indexed by increased fiber density was observed in overweight compared to normal weight between the reward network regions and regions of the executive control, emotional arousal, and somatosensory networks. In contrast, the opposite pattern (decreased fiber density) was found between ventromedial prefrontal cortex and the anterior insula, and between thalamus and executive control network regions. 2. Gray-matter classification: The classification algorithm, based on 2 signatures with 42

Cross-national perspectives about weight-based bullying in youth: nature, extent and remedies.

PubMed

Puhl, R M; Latner, J D; O'Brien, K; Luedicke, J; Forhan, M; Danielsdottir, S

2016-08-01

No cross-national studies have examined public perceptions about weight-based bullying in youth. To conduct a multinational examination of public views about (i) the prevalence/seriousness of weight-based bullying in youth; (ii) the role of parents, educators, health providers and government in addressing this problem and (iii) implementing policy actions to reduce weight-based bullying. A cross-sectional survey of adults in the United States, Canada, Iceland and Australia (N = 2866). Across all countries, weight-based bullying was identified as the most prevalent reason for youth bullying, by a substantial margin over other forms of bullying (race/ethnicity, sexual orientation and religion). Participants viewed parents and teachers as playing major roles in efforts to reduce weight-based bullying. Most participants across countries (77-94%) viewed healthcare providers to be important intervention agents. Participants (65-87%) supported government augmentation of anti-bullying laws to include prohibiting weight-based bullying. Women expressed higher agreement for policy actions than men, with no associations found for participants' race/ethnicity or weight. Causal beliefs about obesity were associated with policy support across countries. Across countries, strong recognition exists of weight-based bullying and the need to address it. These findings may inform policy-level actions and clinical practices concerning youth vulnerable to weight-based bullying. © 2015 World Obesity.

Region-of-interest image reconstruction with intensity weighting in circular cone-beam CT for image-guided radiation therapy

PubMed Central

Cho, Seungryong; Pearson, Erik; Pelizzari, Charles A.; Pan, Xiaochuan

2009-01-01

Imaging plays a vital role in radiation therapy and with recent advances in technology considerable emphasis has been placed on cone-beam CT (CBCT). Attaching a kV x-ray source and a flat panel detector directly to the linear accelerator gantry has enabled progress in target localization techniques, which can include daily CBCT setup scans for some treatments. However, with an increasing number of CT scans there is also an increasing concern for patient exposure. An intensity-weighted region-of-interest (IWROI) technique, which has the potential to greatly reduce CBCT dose, in conjunction with the chord-based backprojection-filtration (BPF) reconstruction algorithm, has been developed and its feasibility in clinical use is demonstrated in this article. A nonuniform filter is placed in the x-ray beam to create regions of two different beam intensities. In this manner, regions outside the target area can be given a reduced dose but still visualized with a lower contrast to noise ratio. Image artifacts due to transverse data truncation, which would have occurred in conventional reconstruction algorithms, are avoided and image noise levels of the low- and high-intensity regions are well controlled by use of the chord-based BPF reconstruction algorithm. The proposed IWROI technique can play an important role in image-guided radiation therapy. PMID:19472624

Image processing based detection of lung cancer on CT scan images

NASA Astrophysics Data System (ADS)

Abdillah, Bariqi; Bustamam, Alhadi; Sarwinda, Devvi

2017-10-01

In this paper, we implement and analyze the image processing method for detection of lung cancer. Image processing techniques are widely used in several medical problems for picture enhancement in the detection phase to support the early medical treatment. In this research we proposed a detection method of lung cancer based on image segmentation. Image segmentation is one of intermediate level in image processing. Marker control watershed and region growing approach are used to segment of CT scan image. Detection phases are followed by image enhancement using Gabor filter, image segmentation, and features extraction. From the experimental results, we found the effectiveness of our approach. The results show that the best approach for main features detection is watershed with masking method which has high accuracy and robust.

Weighted-MSE based on saliency map for assessing video quality of H.264 video streams

NASA Astrophysics Data System (ADS)

Boujut, H.; Benois-Pineau, J.; Hadar, O.; Ahmed, T.; Bonnet, P.

2011-01-01

Human vision system is very complex and has been studied for many years specifically for purposes of efficient encoding of visual, e.g. video content from digital TV. There have been physiological and psychological evidences which indicate that viewers do not pay equal attention to all exposed visual information, but only focus on certain areas known as focus of attention (FOA) or saliency regions. In this work, we propose a novel based objective quality assessment metric, for assessing the perceptual quality of decoded video sequences affected by transmission errors and packed loses. The proposed method weights the Mean Square Error (MSE), Weighted-MSE (WMSE), according to the calculated saliency map at each pixel. Our method was validated trough subjective quality experiments.

TH-A-18C-10: Dynamic Intensity Weighted Region of Interest Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pearson, E; Pan, X; Pelizzari, C

2014-06-15

Purpose: For image guidance tasks full image quality is not required throughout the entire image. With dynamic filtration of the kV imaging beam the noise properties of the CT image can be locally controlled, providing a high quality image around the target volume with a lower quality surrounding region while providing substantial dose sparing to the patient as well as reduced scatter fluence on the detector. Methods: A dynamic collimation device with 3mm copper blades has been designed to mount in place of the bowtie filter on the On-Board Imager (Varian Medical Systems). The beam intensity is reduced by 95%more » behind the copper filters and the aperture is controlled dynamically to conformally illuminate a given ROI during a standard cone-beam CT scan. A data correction framework to account for the physical effects of the collimator prior to reconstruction was developed. Furthermore, to determine the dose savings and scatter reduction a monte carlo model was built in BEAMnrc with specifics from the Varian Monte Carlo Data Package. The MC model was validated with Gafchromic film. Results: The reconstructed image shows image quality comparable to a standard scan in the specified ROI, with higher noise and streaks in the outer region but still sufficient information for alignment to high contrast structures. The monte carlo modeling showed that the scatter-to-primary ratio was reduced from 1.26 for an unfiltered scan to 0.45 for an intensity weighted scan, suggesting that image quality may be improved in the inner ROI. Dose in the inner region was reduced 10–15% due to reduced scatter and by as much as 75% in the outer region. Conclusion: Dynamic intensity-weighted ROI imaging allows reduction of imaging dose to sensitive organs away from the target region while providing images that retain their utility for patient setup and procedure guidance. Funding was provided in part by Varian Medical Systems and NIH Grants 1RO1CA120540, T32EB002103, S10 RR021039 and P

Spectrotemporal weighting of binaural cues: Effects of a diotic interferer on discrimination of dynamic interaural differences

PubMed Central

Bibee, Jacqueline M.; Stecker, G. Christopher

2016-01-01

Spatial judgments are often dominated by low-frequency binaural cues and onset cues when binaural cues vary across the spectrum and duration, respectively, of a brief sound. This study combined these dimensions to assess the spectrotemporal weighting of binaural information. Listeners discriminated target interaural time difference (ITD) and interaural level difference (ILD) carried by the onset, offset, or full duration of a 4-kHz Gabor click train with a 2-ms period in the presence or absence of a diotic 500-Hz interferer tone. ITD and ILD thresholds were significantly elevated by the interferer in all conditions and by a similar amount to previous reports for static cues. Binaural interference was dramatically greater for ITD targets lacking onset cues compared to onset and full-duration conditions. Binaural interference for ILD targets was similar across dynamic-cue conditions. These effects mirror the baseline discriminability of dynamic ITD and ILD cues [Stecker and Brown. (2010). J. Acoust. Soc. Am. 127, 3092–3103], consistent with stronger interference for less-robust/higher-variance cues. The results support the view that binaural cue integration occurs simultaneously across multiple variance-weighted dimensions, including time and frequency. PMID:27794286

Spectrotemporal weighting of binaural cues: Effects of a diotic interferer on discrimination of dynamic interaural differences.

PubMed

Bibee, Jacqueline M; Stecker, G Christopher

2016-10-01

Spatial judgments are often dominated by low-frequency binaural cues and onset cues when binaural cues vary across the spectrum and duration, respectively, of a brief sound. This study combined these dimensions to assess the spectrotemporal weighting of binaural information. Listeners discriminated target interaural time difference (ITD) and interaural level difference (ILD) carried by the onset, offset, or full duration of a 4-kHz Gabor click train with a 2-ms period in the presence or absence of a diotic 500-Hz interferer tone. ITD and ILD thresholds were significantly elevated by the interferer in all conditions and by a similar amount to previous reports for static cues. Binaural interference was dramatically greater for ITD targets lacking onset cues compared to onset and full-duration conditions. Binaural interference for ILD targets was similar across dynamic-cue conditions. These effects mirror the baseline discriminability of dynamic ITD and ILD cues [Stecker and Brown. (2010). J. Acoust. Soc. Am. 127, 3092-3103], consistent with stronger interference for less-robust/higher-variance cues. The results support the view that binaural cue integration occurs simultaneously across multiple variance-weighted dimensions, including time and frequency.

Finite Element Based HWB Centerbody Structural Optimization and Weight Prediction

NASA Technical Reports Server (NTRS)

Gern, Frank H.

2012-01-01

This paper describes a scalable structural model suitable for Hybrid Wing Body (HWB) centerbody analysis and optimization. The geometry of the centerbody and primary wing structure is based on a Vehicle Sketch Pad (VSP) surface model of the aircraft and a FLOPS compatible parameterization of the centerbody. Structural analysis, optimization, and weight calculation are based on a Nastran finite element model of the primary HWB structural components, featuring centerbody, mid section, and outboard wing. Different centerbody designs like single bay or multi-bay options are analyzed and weight calculations are compared to current FLOPS results. For proper structural sizing and weight estimation, internal pressure and maneuver flight loads are applied. Results are presented for aerodynamic loads, deformations, and centerbody weight.

Web-based weight loss in primary care: a randomized controlled trial.

PubMed

Bennett, Gary G; Herring, Sharon J; Puleo, Elaine; Stein, Evelyn K; Emmons, Karen M; Gillman, Matthew W

2010-02-01

Evidence is lacking regarding effective and sustainable weight loss approaches for use in the primary care setting. We conducted a 12-week randomized controlled trial to evaluate the short-term efficacy of a web-based weight loss intervention among 101 primary care patients with obesity and hypertension. Patients had access to a comprehensive website that used a moderate-intensity weight loss approach designed specifically for web-based implementation. Patients also participated in four (two in-person and two telephonic) counseling sessions with a health coach. Intent-to-treat analysis showed greater weight loss at 3 months (-2.56 kg; 95% CI -3.60, -1.53) among intervention participants (-2.28 +/- 3.21 kg), relative to usual care (0.28 +/- 1.87 kg). Similar findings were observed among intervention completers (-3.05 kg; 95% CI -4.24, -1.85). High rates of participant retention (84%) and website utilization were observed, with the greatest weight loss found among those with a high frequency of website logins (quartile 4 vs. 1: -4.16 kg; 95% CI -1.47, -6.84). The intervention's approach promoted moderate weight loss at 12 weeks, though greater weight loss was observed among those with higher levels of website utilization. Efficacious web-based weight loss interventions can be successfully offered in the primary care setting.

Determinants of Successful Weight Loss After Using a Commercial Web-Based Weight Reduction Program for Six Months: Cohort Study

PubMed Central

Postrach, Elisa; Aspalter, Rosa; Elbelt, Ulf; Koller, Michael; Longin, Rita; Schulzke, Jörg-Dieter

2013-01-01

Background The Internet is widely available and commonly used for health information; therefore, Web-based weight loss programs could provide support to large parts of the population in self-guided weight loss. Previous studies showed that Web-based weight loss interventions can be effective, depending on the quality of the program. The most effective program tools are visual progress charts or tools for the self-monitoring of weight, diet, and exercises. KiloCoach, a commercial program currently available in German-speaking countries, incorporates these features. A previous investigation showed that the program effectively supports users in losing weight. Objective We investigated weight loss dynamics stratified by weight loss success after 6-month use of KiloCoach. Furthermore, we analyzed possible associations between intensity of program use and weight loss. The results are intended for tailoring user recommendations for weight-loss Internet platforms. Methods Datasets of KiloCoach users (January 1, 2008 to December 31, 2011) who actively used the platform for 6 months or more were assigned to this retrospective analysis. Users (N=479) were 42.2% men, mean age of 44.0 years (SD 11.7), with a mean body mass index (BMI) of 31.7 kg/m2 (SD 3.2). Based on the weight loss achieved after 6 months, 3 success groups were generated. The unsuccessful group lost <5%, the moderate success group lost 5%-9.9%, and the high success group lost ≥10% of their baseline body weight. At baseline, the unsuccessful (n=261, 54.5%), moderate success (n=133, 27.8%), and high success (n=85, 17.8%) groups were similar in age, weight, BMI, and gender distribution. Results After 6 months, the unsuccessful group lost 1.2% (SD 2.4), the moderate success group lost 7.4% (SD 1.5), and the high success group lost 14.2% (SD 3.8) of their initial weight (P<.001). Multivariate regression showed that early weight loss (weeks 3-4), the total number of dietary protocols, and the total number of

Relationships among Subjective Social Status, Weight Perception, Weight Control Behaviors, and Weight Status in Adolescents: Findings from the 2009 Korea Youth Risk Behaviors Web-Based Survey

ERIC Educational Resources Information Center

Ha, Yeongmi; Choi, Eunsook; Seo, Yeongmi; Kim, Tae-gu

2013-01-01

Background: This study identified relationships among subjective social status (SSS), weight perception, weight control behaviors, and weight status in Korean adolescents using nationally representative data collected from the 2009 Korea Youth Risk Behaviors Web-Based Survey. Methods: Data from 67,185 students aged 12-18 years were analyzed.…

Finger-vein and fingerprint recognition based on a feature-level fusion method

NASA Astrophysics Data System (ADS)

Yang, Jinfeng; Hong, Bofeng

2013-07-01

Multimodal biometrics based on the finger identification is a hot topic in recent years. In this paper, a novel fingerprint-vein based biometric method is proposed to improve the reliability and accuracy of the finger recognition system. First, the second order steerable filters are used here to enhance and extract the minutiae features of the fingerprint (FP) and finger-vein (FV). Second, the texture features of fingerprint and finger-vein are extracted by a bank of Gabor filter. Third, a new triangle-region fusion method is proposed to integrate all the fingerprint and finger-vein features in feature-level. Thus, the fusion features contain both the finger texture-information and the minutiae triangular geometry structure. Finally, experimental results performed on the self-constructed finger-vein and fingerprint databases are shown that the proposed method is reliable and precise in personal identification.

Weight management for Mexican American adolescents: school-based program

USDA-ARS?s Scientific Manuscript database

The objective of the current study was to assess change in weight over time for children participating in a school-based weight management program. A total of 47 participants between the ages of 10 and 14 who exceeded the 85th percentile for BMI were randomized into an intensive intervention (II) o...

Optimal weight based on energy imbalance and utility maximization

NASA Astrophysics Data System (ADS)

Sun, Ruoyan

2016-01-01

This paper investigates the optimal weight for both male and female using energy imbalance and utility maximization. Based on the difference of energy intake and expenditure, we develop a state equation that reveals the weight gain from this energy gap. We ​construct an objective function considering food consumption, eating habits and survival rate to measure utility. Through applying mathematical tools from optimal control methods and qualitative theory of differential equations, we obtain some results. For both male and female, the optimal weight is larger than the physiologically optimal weight calculated by the Body Mass Index (BMI). We also study the corresponding trajectories to steady state weight respectively. Depending on the value of a few parameters, the steady state can either be a saddle point with a monotonic trajectory or a focus with dampened oscillations.

Parallelized multi–graphics processing unit framework for high-speed Gabor-domain optical coherence microscopy

PubMed Central

Tankam, Patrice; Santhanam, Anand P.; Lee, Kye-Sung; Won, Jungeun; Canavesi, Cristina; Rolland, Jannick P.

2014-01-01

Abstract. Gabor-domain optical coherence microscopy (GD-OCM) is a volumetric high-resolution technique capable of acquiring three-dimensional (3-D) skin images with histological resolution. Real-time image processing is needed to enable GD-OCM imaging in a clinical setting. We present a parallelized and scalable multi-graphics processing unit (GPU) computing framework for real-time GD-OCM image processing. A parallelized control mechanism was developed to individually assign computation tasks to each of the GPUs. For each GPU, the optimal number of amplitude-scans (A-scans) to be processed in parallel was selected to maximize GPU memory usage and core throughput. We investigated five computing architectures for computational speed-up in processing 1000×1000 A-scans. The proposed parallelized multi-GPU computing framework enables processing at a computational speed faster than the GD-OCM image acquisition, thereby facilitating high-speed GD-OCM imaging in a clinical setting. Using two parallelized GPUs, the image processing of a 1×1×0.6  mm3 skin sample was performed in about 13 s, and the performance was benchmarked at 6.5 s with four GPUs. This work thus demonstrates that 3-D GD-OCM data may be displayed in real-time to the examiner using parallelized GPU processing. PMID:24695868

Predictive classification of pediatric bipolar disorder using atlas-based diffusion weighted imaging and support vector machines.

PubMed

Mwangi, Benson; Wu, Mon-Ju; Bauer, Isabelle E; Modi, Haina; Zeni, Cristian P; Zunta-Soares, Giovana B; Hasan, Khader M; Soares, Jair C

2015-11-30

Previous studies have reported abnormalities of white-matter diffusivity in pediatric bipolar disorder. However, it has not been established whether these abnormalities are able to distinguish individual subjects with pediatric bipolar disorder from healthy controls with a high specificity and sensitivity. Diffusion-weighted imaging scans were acquired from 16 youths diagnosed with DSM-IV bipolar disorder and 16 demographically matched healthy controls. Regional white matter tissue microstructural measurements such as fractional anisotropy, axial diffusivity and radial diffusivity were computed using an atlas-based approach. These measurements were used to 'train' a support vector machine (SVM) algorithm to predict new or 'unseen' subjects' diagnostic labels. The SVM algorithm predicted individual subjects with specificity=87.5%, sensitivity=68.75%, accuracy=78.12%, positive predictive value=84.62%, negative predictive value=73.68%, area under receiver operating characteristic curve (AUROC)=0.7812 and chi-square p-value=0.0012. A pattern of reduced regional white matter fractional anisotropy was observed in pediatric bipolar disorder patients. These results suggest that atlas-based diffusion weighted imaging measurements can distinguish individual pediatric bipolar disorder patients from healthy controls. Notably, from a clinical perspective these findings will contribute to the pathophysiological understanding of pediatric bipolar disorder. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

STOCK Market Differences in Correlation-Based Weighted Network

NASA Astrophysics Data System (ADS)

Youn, Janghyuk; Lee, Junghoon; Chang, Woojin

We examined the sector dynamics of Korean stock market in relation to the market volatility. The daily price data of 360 stocks for 5019 trading days (from January, 1990 to August, 2008) in Korean stock market are used. We performed the weighted network analysis and employed four measures: the average, the variance, the intensity, and the coherence of network weights (absolute values of stock return correlations) to investigate the network structure of Korean stock market. We performed regression analysis using the four measures in the seven major industry sectors and the market (seven sectors combined). We found that the average, the intensity, and the coherence of sector (subnetwork) weights increase as market becomes volatile. Except for the "Financials" sector, the variance of sector weights also grows as market volatility increases. Based on the four measures, we can categorize "Financials," "Information Technology" and "Industrials" sectors into one group, and "Materials" and "Consumer Discretionary" sectors into another group. We investigated the distributions of intrasector and intersector weights for each sector and found the differences in "Financials" sector are most distinct.

A weighted variational gradient-based fusion method for high-fidelity thin cloud removal of Landsat images

NASA Astrophysics Data System (ADS)

Huang, Wei; Chen, Xiu; Wang, Yueyun

2018-03-01

Landsat data are widely used in various earth observations, but the clouds interfere with the applications of the images. This paper proposes a weighted variational gradient-based fusion method (WVGBF) for high-fidelity thin cloud removal of Landsat images, which is an improvement of the variational gradient-based fusion (VGBF) method. The VGBF method integrates the gradient information from the reference band into visible bands of cloudy image to enable spatial details and remove thin clouds. The VGBF method utilizes the same gradient constraints to the entire image, which causes the color distortion in cloudless areas. In our method, a weight coefficient is introduced into the gradient approximation term to ensure the fidelity of image. The distribution of weight coefficient is related to the cloud thickness map. The map is built on Independence Component Analysis (ICA) by using multi-temporal Landsat images. Quantitatively, we use R value to evaluate the fidelity in the cloudless regions and metric Q to evaluate the clarity in the cloud areas. The experimental results indicate that the proposed method has the better ability to remove thin cloud and achieve high fidelity.

Relation of trihalomethane concentrations in public water supplies to stillbirth and birth weight in three water regions in England.

PubMed

Toledano, Mireille B; Nieuwenhuijsen, Mark J; Best, Nicky; Whitaker, Heather; Hambly, Peter; de Hoogh, Cornelis; Fawell, John; Jarup, Lars; Elliott, Paul

2005-02-01

We investigated the association between total trihalomethanes (TTHMs) and risk of stillbirth and low and very low birth weight in three water regions in England, 1992-1998; associations with individual trihalomethanes (THMs) were also examined. Modeled estimates of quarterly TTHM concentrations in water zones, categorized as low (< 30 microg/L), medium (30-59 microg/L), or high (> or = 60 microg/L), were linked to approximately 1 million routine birth and stillbirth records using maternal residence at time of birth. In one region, where there was a positive socioeconomic deprivation gradient across exposure categories, there was also a positive, significant association of TTHM with risk of stillbirth and low and very low birth weight. Overall summary estimates across the three regions using a random-effects model to allow for between-region heterogeneity in exposure effects showed small excess risks in areas with high TTHM concentrations for stillbirths [odds ratio (OR) = 1.11; 95% confidence interval (CI), 1.00-1.23), low birth weight (OR = 1.09; 95% CI, 0.93-1.27), and very low birth weight (OR = 1.05; 95% CI, 0.82-1.34). Among the individual THMs, chloroform showed a similar pattern of risk as TTHM, but no association was found with concentrations of bromodichloromethane or total brominated THMs. Our findings overall suggest a significant association of stillbirths with maternal residence in areas with high TTHM exposure. Further work is needed looking at cause-specific stillbirths and effects of other disinfection by-products and to help differentiate between alternative (noncausal) explanations and those that may derive from the water supply.

LBP-based penalized weighted least-squares approach to low-dose cone-beam computed tomography reconstruction

NASA Astrophysics Data System (ADS)

Ma, Ming; Wang, Huafeng; Liu, Yan; Zhang, Hao; Gu, Xianfeng; Liang, Zhengrong

2014-03-01

Cone-beam computed tomography (CBCT) has attracted growing interest of researchers in image reconstruction. The mAs level of the X-ray tube current, in practical application of CBCT, is mitigated in order to reduce the CBCT dose. The lowering of the X-ray tube current, however, results in the degradation of image quality. Thus, low-dose CBCT image reconstruction is in effect a noise problem. To acquire clinically acceptable quality of image, and keep the X-ray tube current as low as achievable in the meanwhile, some penalized weighted least-squares (PWLS)-based image reconstruction algorithms have been developed. One representative strategy in previous work is to model the prior information for solution regularization using an anisotropic penalty term. To enhance the edge preserving and noise suppressing in a finer scale, a novel algorithm combining the local binary pattern (LBP) with penalized weighted leastsquares (PWLS), called LBP-PWLS-based image reconstruction algorithm, is proposed in this work. The proposed LBP-PWLS-based algorithm adaptively encourages strong diffusion on the local spot/flat region around a voxel and less diffusion on edge/corner ones by adjusting the penalty for cost function, after the LBP is utilized to detect the region around the voxel as spot, flat and edge ones. The LBP-PWLS-based reconstruction algorithm was evaluated using the sinogram data acquired by a clinical CT scanner from the CatPhan® 600 phantom. Experimental results on the noiseresolution tradeoff measurement and other quantitative measurements demonstrated its feasibility and effectiveness in edge preserving and noise suppressing in comparison with a previous PWLS reconstruction algorithm.

Population-based birth weight reference percentiles for Chinese twins.

PubMed

Dai, Li; Deng, Changfei; Li, Yanhua; Yi, Ling; Li, Xiaohong; Mu, Yi; Li, Qi; Yao, Qiang; Wang, Yanping

2017-09-01

Birth weight percentiles by gestational age are important for assessing prenatal growth and predicting postnatal outcomes of newborns. Several countries have developed nation-specific birth weight references for twins, but China still lacks such references. Birth weight data for twins born between October 2006 and September 2015 were abstracted from the China National Population-based Birth Defects Surveillance System. A total of 54,786 live twin births aged ≥28 weeks of gestation without birth defects were included in the analysis. The LMS method was adopted to generate gestational age-specific birth weight percentiles and curves for male and female twins separately. Significant differences were observed between the current reference and other references developed for Chinese or non-Chinese twins. The neonatal mortality rate in this cohort was 12.3‰, and much higher rates at very early gestation weeks were identified in small-for-gestational-age twins grouped by the newly developed reference cutoffs. The established birth weight centiles represent the first birth weight norm for contemporary Chinese twins and can be a useful tool to assess growth of twins in clinical and research settings. Key Messages There have been no population-based birth weight percentiles for Chinese twins prior to this study. The established birth weight centiles for female and male twins are markedly lower than those for Chinese singletons. Twin-specific curves should be used for determining inappropriate for gestational age in twins rather than using existing singleton reference. The birth weight percentiles for twins differed significantly from those for non-Chinese twins. In addition to ethnic influences, the observed differences could be ascribed to variations in prenatal care, fetal or maternal nutrition status or other environmental factors. Neonatal mortality rates varied considerably among twins grouped by the newly developed reference percentiles. Small

Ship Detection from Ocean SAR Image Based on Local Contrast Variance Weighted Information Entropy

PubMed Central

Huang, Yulin; Pei, Jifang; Zhang, Qian; Gu, Qin; Yang, Jianyu

2018-01-01

Ship detection from synthetic aperture radar (SAR) images is one of the crucial issues in maritime surveillance. However, due to the varying ocean waves and the strong echo of the sea surface, it is very difficult to detect ships from heterogeneous and strong clutter backgrounds. In this paper, an innovative ship detection method is proposed to effectively distinguish the vessels from complex backgrounds from a SAR image. First, the input SAR image is pre-screened by the maximally-stable extremal region (MSER) method, which can obtain the ship candidate regions with low computational complexity. Then, the proposed local contrast variance weighted information entropy (LCVWIE) is adopted to evaluate the complexity of those candidate regions and the dissimilarity between the candidate regions with their neighborhoods. Finally, the LCVWIE values of the candidate regions are compared with an adaptive threshold to obtain the final detection result. Experimental results based on measured ocean SAR images have shown that the proposed method can obtain stable detection performance both in strong clutter and heterogeneous backgrounds. Meanwhile, it has a low computational complexity compared with some existing detection methods. PMID:29652863

Effects of early pregnancy BMI, mid-gestational weight gain, glucose and lipid levels in pregnancy on offspring's birth weight and subcutaneous fat: a population-based cohort study.

PubMed

Sommer, Christine; Sletner, Line; Mørkrid, Kjersti; Jenum, Anne Karen; Birkeland, Kåre Inge

2015-04-03

Maternal glucose and lipid levels are associated with neonatal anthropometry of the offspring, also independently of maternal body mass index (BMI). Gestational weight gain, however, is often not accounted for. The objective was to explore whether the effects of maternal glucose and lipid levels on offspring's birth weight and subcutaneous fat were independent of early pregnancy BMI and mid-gestational weight gain. In a population-based, multi-ethnic, prospective cohort of 699 women and their offspring, maternal anthropometrics were collected in gestational week 15 and 28. Maternal fasting plasma lipids, fasting and 2-hour glucose post 75 g glucose load, were collected in gestational week 28. Maternal risk factors were standardized using z-scores. Outcomes were neonatal birth weight and sum of skinfolds in four different regions. Mean (standard deviation) birth weight was 3491 ± 498 g and mean sum of skinfolds was 18.2 ± 3.9 mm. Maternal fasting glucose and HDL-cholesterol were predictors of birth weight, and fasting and 2-hour glucose were predictors of neonatal sum of skinfolds, independently of weight gain as well as early pregnancy BMI, gestational week at inclusion, maternal age, parity, smoking status, ethnic origin, gestational age and offspring's sex. However, weight gain was the strongest independent predictor of both birth weight and neonatal sum of skinfolds, with a 0.21 kg/week increased weight gain giving a 110.7 (95% confidence interval 76.6-144.9) g heavier neonate, and with 0.72 (0.38-1.06) mm larger sum of skinfolds. The effect size of mother's early pregnancy BMI on birth weight was higher in non-Europeans than in Europeans. Maternal fasting glucose and HDL-cholesterol were predictors of offspring's birth weight, and fasting and 2-hour glucose were predictors of neonatal sum of skinfolds, independently of weight gain. Mid-gestational weight gain was a stronger predictor of both birth weight and neonatal sum of skinfolds than early

Ordered weighted averaging with fuzzy quantifiers: GIS-based multicriteria evaluation for land-use suitability analysis

NASA Astrophysics Data System (ADS)

Malczewski, Jacek

2006-12-01

The objective of this paper is to incorporate the concept of fuzzy (linguistic) quantifiers into the GIS-based land suitability analysis via ordered weighted averaging (OWA). OWA is a multicriteria evaluation procedure (or combination operator). The nature of the OWA procedure depends on some parameters, which can be specified by means of fuzzy (linguistic) quantifiers. By changing the parameters, OWA can generate a wide range of decision strategies or scenarios. The quantifier-guided OWA procedure is illustrated using land-use suitability analysis in a region of Mexico.

"Guys, She's Humongous!": Gender and Weight-Based Teasing in Adolescence

ERIC Educational Resources Information Center

Taylor, Nicole L.

2011-01-01

Ethnographic research, including individual interviews, focus groups, and participant observation, was conducted to examine how adolescents defined and negotiated the boundaries between normal/acceptable weight and overweight through direct and indirect teasing. In particular, this article focuses on gender differences in weight-based teasing and…

Genome-wide association and regional heritability mapping to identify loci underlying variation in nematode resistance and body weight in Scottish Blackface lambs.

PubMed

Riggio, V; Matika, O; Pong-Wong, R; Stear, M J; Bishop, S C

2013-05-01

The genetic architecture underlying nematode resistance and body weight in Blackface lambs was evaluated comparing genome-wide association (GWA) and regional heritability mapping (RHM) approaches. The traits analysed were faecal egg count (FEC) and immunoglobulin A activity against third-stage larvae from Teladorsagia circumcincta, as indicators of nematode resistance, and body weight in a population of 752 Scottish Blackface lambs, genotyped with the 50k single-nucleotide polymorphism (SNP) chip. FEC for both Nematodirus and Strongyles nematodes (excluding Nematodirus), as well as body weight were collected at approximately 16, 20 and 24 weeks of age. In addition, a weighted average animal effect was estimated for both FEC and body weight traits. After quality control, 44 388 SNPs were available for the GWA analysis and 42 841 for the RHM, which utilises only mapped SNPs. The same fixed effects were used in both analyses: sex, year, management group, litter size and age of dam, with day of birth as covariate. Some genomic regions of interest for both nematode resistance and body weight traits were identified, using both GWA and RHM approaches. For both methods, strong evidence for association was found on chromosome 14 for Nematodirus average animal effect, chromosome 6 for Strongyles FEC at 16 weeks and chromosome 6 for body weight at 16 weeks. Across the entire data set, RHM identified more regions reaching the suggestive level than GWA, suggesting that RHM is capable of capturing some of the variation not detected by GWA analyses.

Relation of Trihalomethane Concentrations in Public Water Supplies to Stillbirth and Birth Weight in Three Water Regions in England

PubMed Central

Toledano, Mireille B.; Nieuwenhuijsen, Mark J.; Best, Nicky; Whitaker, Heather; Hambly, Peter; de Hoogh, Cornelis; Fawell, John; Jarup, Lars; Elliott, Paul

2005-01-01

We investigated the association between total trihalomethanes (TTHMs) and risk of stillbirth and low and very low birth weight in three water regions in England, 1992–1998; associations with individual trihalomethanes (THMs) were also examined. Modeled estimates of quarterly TTHM concentrations in water zones, categorized as low (< 30 μg/L), medium (30–59 μg/L), or high (≥60 μg/L), were linked to approximately 1 million routine birth and stillbirth records using maternal residence at time of birth. In one region, where there was a positive socioeconomic deprivation gradient across exposure categories, there was also a positive, significant association of TTHM with risk of stillbirth and low and very low birth weight. Overall summary estimates across the three regions using a random-effects model to allow for between-region heterogeneity in exposure effects showed small excess risks in areas with high TTHM concentrations for stillbirths [odds ratio (OR) = 1.11; 95% confidence interval (CI), 1.00–1.23), low birth weight (OR = 1.09; 95% CI, 0.93–1.27), and very low birth weight (OR = 1.05; 95% CI, 0.82–1.34). Among the individual THMs, chloroform showed a similar pattern of risk as TTHM, but no association was found with concentrations of bromodichloromethane or total brominated THMs. Our findings overall suggest a significant association of stillbirths with maternal residence in areas with high TTHM exposure. Further work is needed looking at cause-specific stillbirths and effects of other disinfection by-products and to help differentiate between alternative (noncausal) explanations and those that may derive from the water supply. PMID:15687062

GIS-Based Suitability Model for Assessment of Forest Biomass Energy Potential in a Region of Portugal

NASA Astrophysics Data System (ADS)

Quinta-Nova, Luis; Fernandez, Paulo; Pedro, Nuno

2017-12-01

This work focuses on developed a decision support system based on multicriteria spatial analysis to assess the potential for generation of biomass residues from forestry sources in a region of Portugal (Beira Baixa). A set of environmental, economic and social criteria was defined, evaluated and weighted in the context of Saaty’s analytic hierarchies. The best alternatives were obtained after applying Analytic Hierarchy Process (AHP). The model was applied to the central region of Portugal where forest and agriculture are the most representative land uses. Finally, sensitivity analysis of the set of factors and their associated weights was performed to test the robustness of the model. The proposed evaluation model provides a valuable reference for decision makers in establishing a standardized means of selecting the optimal location for new biomass plants.

Implications of weight-based stigma and self-bias on quality of life among individuals with Schizophrenia

PubMed Central

Barber, Jessica; Palmese, Laura; Reutenauer, Erin L.; Grilo, Carlos; Tek, Cenk

2011-01-01

Obesity has been associated with significant stigma and weight-related self-bias in community and clinical studies, but these issues have not been studied among individuals with schizophrenia. A consecutive series of 70 obese individuals with schizophrenia or schizoaffective disorder underwent assessment for perceptions of weight-based stigmatization, self-directed weight-bias, negative affect, medication compliance, and quality of life. Levels of weight-based stigmatization and self-bias were compared to levels reported for non-psychiatric overweight/obese samples. Weight measures were unrelated to stigma, self-bias, affect, and quality of life. Weight-based stigmatization was lower than published levels for non-psychiatric samples, whereas levels of weight-based self-bias did not differ. After controlling for negative affect, weight-based self-bias predicted an additional 11% of the variance in the quality of life measure. Individuals with schizophrenia and schizoaffective disorder reported weight-based self-bias to the same extent as non-psychiatric samples despite reporting less weight stigma. Weight-based self-bias was associated with poorer quality of life after controlling for negative affect. PMID:21716053

Censored quantile regression with recursive partitioning-based weights

PubMed Central

Wey, Andrew; Wang, Lan; Rudser, Kyle

2014-01-01

Censored quantile regression provides a useful alternative to the Cox proportional hazards model for analyzing survival data. It directly models the conditional quantile of the survival time and hence is easy to interpret. Moreover, it relaxes the proportionality constraint on the hazard function associated with the popular Cox model and is natural for modeling heterogeneity of the data. Recently, Wang and Wang (2009. Locally weighted censored quantile regression. Journal of the American Statistical Association 103, 1117–1128) proposed a locally weighted censored quantile regression approach that allows for covariate-dependent censoring and is less restrictive than other censored quantile regression methods. However, their kernel smoothing-based weighting scheme requires all covariates to be continuous and encounters practical difficulty with even a moderate number of covariates. We propose a new weighting approach that uses recursive partitioning, e.g. survival trees, that offers greater flexibility in handling covariate-dependent censoring in moderately high dimensions and can incorporate both continuous and discrete covariates. We prove that this new weighting scheme leads to consistent estimation of the quantile regression coefficients and demonstrate its effectiveness via Monte Carlo simulations. We also illustrate the new method using a widely recognized data set from a clinical trial on primary biliary cirrhosis. PMID:23975800

Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed.

PubMed

Martínez-Montes, Ángel M; Fernández, Almudena; Muñoz, María; Noguera, Jose Luis; Folch, Josep M; Fernández, Ana I

2018-01-01

One of the major limitation for the application of QTL results in pig breeding and QTN identification has been the limited number of QTL effects validated in different animal material. The aim of the current work was to validate QTL regions through joint and specific genome wide association and haplotype analyses for growth, fatness and premier cut weights in three different genetic backgrounds, backcrosses based on Iberian pigs, which has a major role in the analysis due to its high productive relevance. The results revealed nine common QTL regions, three segregating in all three backcrosses on SSC1, 0-3 Mb, for body weight, on SSC2, 3-9 Mb, for loin bone-in weight, and on SSC7, 3 Mb, for shoulder weight, and six segregating in two of the three backcrosses, on SSC2, SSC4, SSC6 and SSC10 for backfat thickness, shoulder and ham weights. Besides, 18 QTL regions were specifically identified in one of the three backcrosses, five identified only in BC_LD, seven in BC_DU and six in BC_PI. Beyond identifying and validating QTL, candidate genes and gene variants within the most interesting regions have been explored using functional annotation, gene expression data and SNP identification from RNA-Seq data. The results allowed us to propose a promising list of candidate mutations, those identified in PDE10A, DHCR7, MFN2 and CCNY genes located within the common QTL regions and those identified near ssc-mir-103-1 considered PANK3 regulators to be further analysed.

Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed

PubMed Central

Martínez-Montes, Ángel M.; Fernández, Almudena; Muñoz, María; Noguera, Jose Luis; Folch, Josep M.

2018-01-01

One of the major limitation for the application of QTL results in pig breeding and QTN identification has been the limited number of QTL effects validated in different animal material. The aim of the current work was to validate QTL regions through joint and specific genome wide association and haplotype analyses for growth, fatness and premier cut weights in three different genetic backgrounds, backcrosses based on Iberian pigs, which has a major role in the analysis due to its high productive relevance. The results revealed nine common QTL regions, three segregating in all three backcrosses on SSC1, 0–3 Mb, for body weight, on SSC2, 3–9 Mb, for loin bone-in weight, and on SSC7, 3 Mb, for shoulder weight, and six segregating in two of the three backcrosses, on SSC2, SSC4, SSC6 and SSC10 for backfat thickness, shoulder and ham weights. Besides, 18 QTL regions were specifically identified in one of the three backcrosses, five identified only in BC_LD, seven in BC_DU and six in BC_PI. Beyond identifying and validating QTL, candidate genes and gene variants within the most interesting regions have been explored using functional annotation, gene expression data and SNP identification from RNA-Seq data. The results allowed us to propose a promising list of candidate mutations, those identified in PDE10A, DHCR7, MFN2 and CCNY genes located within the common QTL regions and those identified near ssc-mir-103-1 considered PANK3 regulators to be further analysed. PMID:29522525

Weight-Based Victimization among Adolescents in the School Setting: Emotional Reactions and Coping Behaviors

ERIC Educational Resources Information Center

Puhl, Rebecca M.; Luedicke, Joerg

2012-01-01

Weight-based victimization is a frequent experience for adolescents, but little is known about their emotional reactions and coping strategies in response to weight-based teasing and bullying. The present study examined the ways that adolescents cope with experiences of weight-based victimization at school. An initial sample of 1,555 students from…

[Ecological security early-warning in Zhoushan Islands based on variable weight model].

PubMed

Zhou, Bin; Zhong, Lin-sheng; Chen, Tian; Zhou, Rui

2015-06-01

Ecological security early warning, as an important content of ecological security research, is of indicating significance in maintaining regional ecological security. Based on driving force, pressure, state, impact and response (D-P-S-I-R) framework model, this paper took Zhoushan Islands in Zhejiang Province as an example to construct the ecological security early warning index system, test degrees of ecological security early warning of Zhoushan Islands from 2000 to 2012 by using the method of variable weight model, and forecast ecological security state of 2013-2018 by Markov prediction method. The results showed that the variable weight model could meet the study needs of ecological security early warning of Zhoushan Islands. There was a fluctuant rising ecological security early warning index from 0.286 to 0.484 in Zhoushan Islands between year 2000 and 2012, in which the security grade turned from "serious alert" into " medium alert" and the indicator light turned from "orange" to "yellow". The degree of ecological security warning was "medium alert" with the light of "yellow" for Zhoushan Islands from 2013 to 2018. These findings could provide a reference for ecological security maintenance of Zhoushan Islands.

Local classifier weighting by quadratic programming.

PubMed

Cevikalp, Hakan; Polikar, Robi

2008-10-01

It has been widely accepted that the classification accuracy can be improved by combining outputs of multiple classifiers. However, how to combine multiple classifiers with various (potentially conflicting) decisions is still an open problem. A rich collection of classifier combination procedures -- many of which are heuristic in nature -- have been developed for this goal. In this brief, we describe a dynamic approach to combine classifiers that have expertise in different regions of the input space. To this end, we use local classifier accuracy estimates to weight classifier outputs. Specifically, we estimate local recognition accuracies of classifiers near a query sample by utilizing its nearest neighbors, and then use these estimates to find the best weights of classifiers to label the query. The problem is formulated as a convex quadratic optimization problem, which returns optimal nonnegative classifier weights with respect to the chosen objective function, and the weights ensure that locally most accurate classifiers are weighted more heavily for labeling the query sample. Experimental results on several data sets indicate that the proposed weighting scheme outperforms other popular classifier combination schemes, particularly on problems with complex decision boundaries. Hence, the results indicate that local classification-accuracy-based combination techniques are well suited for decision making when the classifiers are trained by focusing on different regions of the input space.

Epidemic spreading in weighted networks: an edge-based mean-field solution.

PubMed

Yang, Zimo; Zhou, Tao

2012-05-01

Weight distribution greatly impacts the epidemic spreading taking place on top of networks. This paper presents a study of a susceptible-infected-susceptible model on regular random networks with different kinds of weight distributions. Simulation results show that the more homogeneous weight distribution leads to higher epidemic prevalence, which, unfortunately, could not be captured by the traditional mean-field approximation. This paper gives an edge-based mean-field solution for general weight distribution, which can quantitatively reproduce the simulation results. This method could be applied to characterize the nonequilibrium steady states of dynamical processes on weighted networks.

Effectiveness of Social Media-based Interventions on Weight-related Behaviors and Body Weight Status: Review and Meta-analysis.

PubMed

An, Ruopeng; Ji, Mengmeng; Zhang, Sheng

2017-11-01

We reviewed scientific literature regarding the effectiveness of social media-based interventions about weight-related behaviors and body weight status. A keyword search were performed in May 2017 in the Clinical-Trials.gov, Cochrane Library, PsycINFO, PubMed, and Web of Science databases. We conducted a meta-analysis to estimate the pooled effect size of social media-based interventions on weight-related outcome measures. We identified 22 interventions from the keyword and reference search, including 12 randomized controlled trials, 6 pre-post studies and 3 cohort studies conducted in 9 countries during 2010-2016. The majority (N = 17) used Facebook, followed by Twitter (N = 4) and Instagram (N = 1). Intervention durations averaged 17.8 weeks with a mean sample size of 69. The meta-analysis showed that social media-based interventions were associated with a statistically significant, but clinically modest reduction of body weight by 1.01 kg, body mass index by 0.92 kg/m2, and waist circumstance by 2.65 cm, and an increase of daily number of steps taken by 1530. In the meta-regression there was no doseresponse effect with respect to intervention duration. The boom of social media provides an unprecedented opportunity to implement health promotion programs. Future interventions should make efforts to improve intervention scalability and effectiveness.

[Examination of upper abdominal region in high spatial resolution diffusion-weighted imaging using 3-Tesla MRI].

PubMed

Terada, Masaki; Matsushita, Hiroki; Oosugi, Masanori; Inoue, Kazuyasu; Yaegashi, Taku; Anma, Takeshi

2009-03-20

The advantage of the higher signal-to-noise ratio (SNR) of 3-Tesla magnetic resonance imaging (3-Tesla) has the possibility of contributing to the improvement of high spatial resolution without causing image deterioration. In this study, we compared SNR and the apparent diffusion coefficient (ADC) value with 3-Tesla as the condition in the diffusion-weighted image (DWI) parameter of the 1.5-Tesla magnetic resonance imaging (1.5-Tesla) and we examined the high spatial resolution images in the imaging method [respiratory-triggering (RT) method and breath free (BF) method] and artifact (motion and zebra) in the upper abdominal region of DWI at 3-Tesla. We have optimized scan parameters based on phantom and in vivo study. As a result, 3-Tesla was able to obtain about 1.5 times SNR in comparison with the 1.5-Tesla, ADC value had few differences. Moreover, the RT method was effective in correcting the influence of respiratory movement in comparison with the BF method, and image improvement by the effective acquisition of SNR and reduction of the artifact were provided. Thus, DWI of upper abdominal region was a useful sequence for the high spatial resolution in 3-Tesla.

Genome-wide association and regional heritability mapping to identify loci underlying variation in nematode resistance and body weight in Scottish Blackface lambs

PubMed Central

Riggio, V; Matika, O; Pong-Wong, R; Stear, M J; Bishop, S C

2013-01-01

The genetic architecture underlying nematode resistance and body weight in Blackface lambs was evaluated comparing genome-wide association (GWA) and regional heritability mapping (RHM) approaches. The traits analysed were faecal egg count (FEC) and immunoglobulin A activity against third-stage larvae from Teladorsagia circumcincta, as indicators of nematode resistance, and body weight in a population of 752 Scottish Blackface lambs, genotyped with the 50k single-nucleotide polymorphism (SNP) chip. FEC for both Nematodirus and Strongyles nematodes (excluding Nematodirus), as well as body weight were collected at approximately 16, 20 and 24 weeks of age. In addition, a weighted average animal effect was estimated for both FEC and body weight traits. After quality control, 44 388 SNPs were available for the GWA analysis and 42 841 for the RHM, which utilises only mapped SNPs. The same fixed effects were used in both analyses: sex, year, management group, litter size and age of dam, with day of birth as covariate. Some genomic regions of interest for both nematode resistance and body weight traits were identified, using both GWA and RHM approaches. For both methods, strong evidence for association was found on chromosome 14 for Nematodirus average animal effect, chromosome 6 for Strongyles FEC at 16 weeks and chromosome 6 for body weight at 16 weeks. Across the entire data set, RHM identified more regions reaching the suggestive level than GWA, suggesting that RHM is capable of capturing some of the variation not detected by GWA analyses. PMID:23512009

Brain function predictors and outcome of weight loss and weight loss maintenance.

PubMed

Szabo-Reed, Amanda N; Breslin, Florence J; Lynch, Anthony M; Patrician, Trisha M; Martin, Laura E; Lepping, Rebecca J; Powell, Joshua N; Yeh, Hung-Wen Henry; Befort, Christie A; Sullivan, Debra; Gibson, Cheryl; Washburn, Richard; Donnelly, Joseph E; Savage, Cary R

2015-01-01

Obesity rates are associated with public health consequences and rising health care costs. Weight loss interventions, while effective, do not work for everyone, and weight regain is a significant problem. Eating behavior is influenced by a convergence of processes in the brain, including homeostatic factors and motivational processing that are important contributors to overeating. Initial neuroimaging studies have identified brain regions that respond differently to visual food cues in obese and healthy weight individuals that are positively correlated with reports of hunger in obese participants. While these findings provide mechanisms of overeating, many important questions remain. It is not known whether brain activation patterns change after weight loss, or if they change differentially based on amount of weight lost. Also, little is understood regarding biological processes that contribute to long-term weight maintenance. This study will use neuroimaging in participants while viewing food and non-food images. Functional Magnetic Resonance Imaging will take place before and after completion of a twelve-week weight loss intervention. Obese participants will be followed though a 6-month maintenance period. The study will address three aims: 1. Characterize brain activation underlying food motivation and impulsive behaviors in obese individuals. 2. Identify brain activation changes and predictors of weight loss. 3. Identify brain activation predictors of weight loss maintenance. Findings from this study will have implications for understanding mechanisms of obesity, weight loss, and weight maintenance. Results will be significant to public health and could lead to a better understanding of how differences in brain activation relate to obesity. Copyright © 2014 Elsevier Inc. All rights reserved.

Brain function predictors and outcome of weight loss and weight loss maintenance

PubMed Central

Szabo-Reed, Amanda N.; Breslin, Florence J.; Lynch, Anthony M.; Patrician, Trisha M.; Martin, Laura E.; Lepping, Rebecca J.; Powell, Joshua N.; Yeh, Hung-Wen (Henry); Befort, Christie A.; Sullivan, Debra; Gibson, Cheryl; Washburn, Richard; Donnelly, Joseph E.; Savage, Cary R.

2015-01-01

Obesity rates are associated with public health consequences and rising health care costs. Weight loss interventions, while effective, do not work for everyone, and weight regain is a significant problem. Eating behavior is influenced by a convergence of processes in the brain, including homeostatic factors and motivational processing that are important contributors to overeating. Initial neuroimaging studies have identified brain regions that respond differently to visual food cues in obese and healthy weight individuals that are positively correlated with reports of hunger in obese participants. While these findings provide mechanisms of overeating, many important questions remain. It is not known whether brain activation patterns change after weight loss, or if they change differentially based on amount of weight lost. Also, little is understood regarding biological processes that contribute to long-term weight maintenance. This study will use neuroimaging in participants while viewing food and non-food images. Functional Magnetic Resonance Imaging will take place before and after completion of a twelve-week weight loss intervention. Obese participants will be followed though a 6-month maintenance period. The study will address three aims: 1. Characterize brain activation underlying food motivation and impulsive behaviors in obese individuals. 2. Identify brain activation changes and predictors of weight loss. 3. Identify brain activation predictors of weight loss maintenance. Findings from this study will have implications for understanding mechanisms of obesity, weight loss, and weight maintenance. Results will be significant to public health and could lead to a better understanding of how differences in brain activation relate to obesity. PMID:25533729

Point-based warping with optimized weighting factors of displacement vectors

NASA Astrophysics Data System (ADS)

Pielot, Ranier; Scholz, Michael; Obermayer, Klaus; Gundelfinger, Eckart D.; Hess, Andreas

2000-06-01

The accurate comparison of inter-individual 3D image brain datasets requires non-affine transformation techniques (warping) to reduce geometric variations. Constrained by the biological prerequisites we use in this study a landmark-based warping method with weighted sums of displacement vectors, which is enhanced by an optimization process. Furthermore, we investigate fast automatic procedures for determining landmarks to improve the practicability of 3D warping. This combined approach was tested on 3D autoradiographs of Gerbil brains. The autoradiographs were obtained after injecting a non-metabolized radioactive glucose derivative into the Gerbil thereby visualizing neuronal activity in the brain. Afterwards the brain was processed with standard autoradiographical methods. The landmark-generator computes corresponding reference points simultaneously within a given number of datasets by Monte-Carlo-techniques. The warping function is a distance weighted exponential function with a landmark- specific weighting factor. These weighting factors are optimized by a computational evolution strategy. The warping quality is quantified by several coefficients (correlation coefficient, overlap-index, and registration error). The described approach combines a highly suitable procedure to automatically detect landmarks in autoradiographical brain images and an enhanced point-based warping technique, optimizing the local weighting factors. This optimization process significantly improves the similarity between the warped and the target dataset.

Parent predictors of child weight change in family based behavioral obesity treatment.

PubMed

Boutelle, Kerri N; Cafri, Guy; Crow, Scott J

2012-07-01

Family based behavioral treatment for overweight and obese children includes parenting skills targeting the modification of child eating and activity change. The purpose of this study was to examine parenting skills and parent weight change as predictors of child weight change in a sample of 80 parent/child dyads who were enrolled in a family based behavioral weight loss program for childhood obesity. Eighty overweight and obese children and their parents who enrolled in treatment in two sites were included in the study. Variables included those related to parent modeling (parent BMI), home food environment, parenting (parent and child report), and demographics. Results suggested that parent BMI change was a significant predictor of child weight, in that a reduction of 1 BMI unit in the parent was associated with a 0.255 reduction in child BMI. None of the other variables were significant in the final model. This study is consistent with other research showing that parent weight change is a key contributor to child weight change in behavioral treatment for childhood obesity. Researchers and clinicians should focus on encouraging parents to lose weight to assist their overweight and obese child in weight management.

Image fusion method based on regional feature and improved bidimensional empirical mode decomposition

NASA Astrophysics Data System (ADS)

Qin, Xinqiang; Hu, Gang; Hu, Kai

2018-01-01

The decomposition of multiple source images using bidimensional empirical mode decomposition (BEMD) often produces mismatched bidimensional intrinsic mode functions, either by their number or their frequency, making image fusion difficult. A solution to this problem is proposed using a fixed number of iterations and a union operation in the sifting process. By combining the local regional features of the images, an image fusion method has been developed. First, the source images are decomposed using the proposed BEMD to produce the first intrinsic mode function (IMF) and residue component. Second, for the IMF component, a selection and weighted average strategy based on local area energy is used to obtain a high-frequency fusion component. Third, for the residue component, a selection and weighted average strategy based on local average gray difference is used to obtain a low-frequency fusion component. Finally, the fused image is obtained by applying the inverse BEMD transform. Experimental results show that the proposed algorithm provides superior performance over methods based on wavelet transform, line and column-based EMD, and complex empirical mode decomposition, both in terms of visual quality and objective evaluation criteria.

Weight and volume equations and tables for red maple in the Lake States.

Treesearch

Thomas R. Crow; G.G. Erdmann

1983-01-01

Weight and volume information based on regional sampling are provided for red maple in the Lake States. Both green weight and dry weight values are presented for biomass. Volume equations predict total stem volume, volume to 8-inch top, and volume to 4-inch top, inside and outside bark.

Enhanced Weight based DSR for Mobile Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Verma, Samant; Jain, Sweta

2011-12-01

Routing in ad hoc network is a great problematic, since a good routing protocol must ensure fast and efficient packet forwarding, which isn't evident in ad hoc networks. In literature there exists lot of routing protocols however they don't include all the aspects of ad hoc networks as mobility, device and medium constraints which make these protocols not efficient for some configuration and categories of ad hoc networks. Thus in this paper we propose an improvement of Weight Based DSR in order to include some of the aspects of ad hoc networks as stability, remaining battery power, load and trust factor and proposing a new approach Enhanced Weight Based DSR.

Overestimation and Underestimation: Adolescents' Weight Perception in Comparison to BMI-Based Weight Status and How It Varies across Socio-Demographic Factors

ERIC Educational Resources Information Center

Park, Eunkyung

2011-01-01

Background: Weight perception has been studied with a limited focus on "feeling overweight." This study, using a more inclusive definition of overestimation and underestimation, examines adolescents' weight perception focusing on how accurate it is in relation to body mass index (BMI)-based weight status and how it varies across socio-demographic…

Brief report: Weight dissatisfaction, weight status, and weight loss in Mexican-American children

USDA-ARS?s Scientific Manuscript database

The study objectives were to assess the association between weight dissatisfaction, weight status, and weight loss in Mexican-American children participating in a weight management program. Participants included 265 Mexican American children recruited for a school-based weight management program. Al...

Psychological well-being, health behaviors, and weight loss among participants in a residential, Kripalu yoga-based weight loss program.

PubMed

Braun, Tosca D; Park, Crystal L; Conboy, Lisa Ann

2012-01-01

The increasing prevalence of overweight and obesity in humans is a growing public health concern in the United States. Concomitants include poor health behaviors and reduced psychological well-being. Preliminary evidence suggests yoga and treatment paradigms incorporating mindfulness, self-compassion (SC), acceptance, non-dieting, and intuitive eating may improve these ancillary correlates, which may promote long-term weight loss. We explored the impact of a 5-day residential weight loss program, which was multifaceted and based on Kripalu yoga, on health behaviors, weight loss, and psychological well-being in overweight/obese individuals. Thirty-seven overweight/obese program participants (age 32-65, BMI<25) completed validated mind-fulness, SC, lifestyle behavior, and mood questionnaires at baseline, post-program, and 3-month follow-up and reported their weight 1 year after program completion. Significant improvements in nutrition behaviors, SC, mindfulness, stress management, and spiritual growth were observed immediately post-program (n = 31, 84% retention), with medium to large effect sizes. At 3-month follow-up (n = 18, 49% retention), most changes persisted. Physical activity and mood disturbance had improved significantly post-program but failed to reach significance at 3-month follow-up. Self-report weight loss at 1 year (n = 19, 51% retention) was significant. These findings suggest a Kripalu yoga-based, residential weight loss program may foster psychological well-being, improved nutrition behaviors, and weight loss. Given the exploratory nature of this investigation, more rigorous work in this area is warranted.

Dynamic intensity-weighted region of interest imaging for conebeam CT

PubMed Central

Pearson, Erik; Pan, Xiaochuan; Pelizzari, Charles

2017-01-01

BACKGROUND Patient dose from image guidance in radiotherapy is small compared to the treatment dose. However, the imaging beam is untargeted and deposits dose equally in tumor and healthy tissues. It is desirable to minimize imaging dose while maintaining efficacy. OBJECTIVE Image guidance typically does not require full image quality throughout the patient. Dynamic filtration of the kV beam allows local control of CT image noise for high quality around the target volume and lower quality elsewhere, with substantial dose sparing and reduced scatter fluence on the detector. METHODS The dynamic Intensity-Weighted Region of Interest (dIWROI) technique spatially varies beam intensity during acquisition with copper filter collimation. Fluence is reduced by 95% under the filters with the aperture conformed dynamically to the ROI during cone-beam CT scanning. Preprocessing to account for physical effects of the collimator before reconstruction is described. RESULTS Reconstructions show image quality comparable to a standard scan in the ROI, with higher noise and streak artifacts in the outer region but still adequate quality for patient localization. Monte Carlo modeling shows dose reduction by 10–15% in the ROI due to reduced scatter, and up to 75% outside. CONCLUSIONS The presented technique offers a method to reduce imaging dose by accepting increased image noise outside the ROI, while maintaining full image quality inside the ROI. PMID:27257875

Regional brain injury on conventional and diffusion weighted MRI is associated with outcome after pediatric cardiac arrest.

PubMed

Fink, Ericka L; Panigrahy, A; Clark, R S B; Fitz, C R; Landsittel, D; Kochanek, P M; Zuccoli, G

2013-08-01

To assess regional brain injury on magnetic resonance imaging (MRI) after pediatric cardiac arrest (CA) and to associate regional injury with patient outcome and effects of hypothermia therapy for neuroprotection. We performed a retrospective chart review with prospective imaging analysis. Children between 1 week and 17 years of age who had a brain MRI in the first 2 weeks after CA without other acute brain injury between 2002 and 2008 were included. Brain MRI (1.5 T General Electric, Milwaukee, WI, USA) images were analyzed by 2 blinded neuroradiologists with adjudication; images were visually graded. Brain lobes, basal ganglia, thalamus, brain stem, and cerebellum were analyzed using T1, T2, and diffusion-weighted images (DWI). We examined 28 subjects with median age 1.9 years (IQR 0.4-13.0) and 19 (68 %) males. Increased intensity on T2 in the basal ganglia and restricted diffusion in the brain lobes were associated with unfavorable outcome (all P < 0.05). Therapeutic hypothermia had no effect on regional brain injury. Repeat brain MRI was infrequently performed but demonstrated evolution of lesions. Children with lesions in the basal ganglia on conventional MRI and brain lobes on DWI within the first 2 weeks after CA represent a group with increased risk of poor outcome. These findings may be important for developing neuroprotective strategies based on regional brain injury and for evaluating response to therapy in interventional clinical trials.

Lifestyle behaviours and weight among hospital-based nurses.

PubMed

Zapka, Jane M; Lemon, Stephenie C; Magner, Robert P; Hale, Janet

2009-11-01

The purpose of this study was to (i) describe the weight, weight-related perceptions and lifestyle behaviours of hospital-based nurses, and (ii) explore the relationship of demographic, health, weight and job characteristics with lifestyle behaviours. The obesity epidemic is widely documented. Worksite initiatives have been advocated. Nurses represent an important part of the hospital workforce and serve as role models when caring for patients. A sample of 194 nurses from six hospitals participated in anthropometric measurements and self-administered surveys. The majority of nurses were overweight and obese, and some were not actively involved in weight management behaviours. Self-reported health, diet and physical activity behaviours were low, although variable by gender, age and shift. Reports of co-worker norms supported low levels of healthy behaviours. Findings reinforce the need to address the hospital environment and culture as well as individual behaviours for obesity control. Nurse managers have an opportunity to consider interventions that promote a climate favourable to improved health habits by facilitating and supporting healthy lifestyle choices (nutrition and physical activity) and environmental changes. Such efforts have the potential to increase productivity and morale and decrease work-related disabilities and improve quality of life.

Child Health in Peru: Importance of Regional Variation and Community Effects on Children's Height and Weight

ERIC Educational Resources Information Center

Shin, Heeju

2007-01-01

In developing countries, height and weight are good indicators of children's health and nutritional status. Maternal education has been accepted as one of the most important influences on child health. Using the 2000 Demographic and Health Survey of Peru, however, I find that the effect of maternal education varies as a function of region. In the…

Spatial feature analysis of a cosmic-ray sensor for measuring the soil water content: Comparison of four weighting methods

NASA Astrophysics Data System (ADS)

Cai, Jingya; Pang, Zhiguo; Fu, Jun'e.

2018-04-01

To quantitatively analyze the spatial features of a cosmic-ray sensor (CRS) (i.e., the measurement support volume of the CRS and the weight of the in situ point-scale soil water content (SWC) in terms of the regionally averaged SWC derived from the CRS) in measuring the SWC, cooperative observations based on CRS, oven drying and frequency domain reflectometry (FDR) methods are performed at the point and regional scales in a desert steppe area of the Inner Mongolia Autonomous Region. This region is flat with sparse vegetation cover consisting of only grass, thereby minimizing the effects of terrain and vegetation. Considering the two possibilities of the measurement support volume of the CRS, the results of four weighting methods are compared with the SWC monitored by FDR within an appropriate measurement support volume. The weighted average calculated using the neutron intensity-based weighting method (Ni weighting method) best fits the regionally averaged SWC measured by the CRS. Therefore, we conclude that the gyroscopic support volume and the weights determined by the Ni weighting method are the closest to the actual spatial features of the CRS when measuring the SWC. Based on these findings, a scale transformation model of the SWC from the point scale to the scale of the CRS measurement support volume is established. In addition, the spatial features simulated using the Ni weighting method are visualized by developing a software system.

Literature-based concept profiles for gene annotation: the issue of weighting.

PubMed

Jelier, Rob; Schuemie, Martijn J; Roes, Peter-Jan; van Mulligen, Erik M; Kors, Jan A

2008-05-01

Text-mining has been used to link biomedical concepts, such as genes or biological processes, to each other for annotation purposes or the generation of new hypotheses. To relate two concepts to each other several authors have used the vector space model, as vectors can be compared efficiently and transparently. Using this model, a concept is characterized by a list of associated concepts, together with weights that indicate the strength of the association. The associated concepts in the vectors and their weights are derived from a set of documents linked to the concept of interest. An important issue with this approach is the determination of the weights of the associated concepts. Various schemes have been proposed to determine these weights, but no comparative studies of the different approaches are available. Here we compare several weighting approaches in a large scale classification experiment. Three different techniques were evaluated: (1) weighting based on averaging, an empirical approach; (2) the log likelihood ratio, a test-based measure; (3) the uncertainty coefficient, an information-theory based measure. The weighting schemes were applied in a system that annotates genes with Gene Ontology codes. As the gold standard for our study we used the annotations provided by the Gene Ontology Annotation project. Classification performance was evaluated by means of the receiver operating characteristics (ROC) curve using the area under the curve (AUC) as the measure of performance. All methods performed well with median AUC scores greater than 0.84, and scored considerably higher than a binary approach without any weighting. Especially for the more specific Gene Ontology codes excellent performance was observed. The differences between the methods were small when considering the whole experiment. However, the number of documents that were linked to a concept proved to be an important variable. When larger amounts of texts were available for the generation of

Regional Brain Biometrics at Term-Equivalent Age and Developmental Outcome in Extremely Low-Birth-Weight Infants.

PubMed

Melbourne, Launice; Murnick, Jonathan; Chang, Taeun; Glass, Penny; Massaro, An N

2015-10-01

This study aims to evaluate individual regional brain biometrics and their association with developmental outcome in extremely low-birth-weight (ELBW) infants. This is a retrospective study evaluating term-equivalent magnetic resonance imaging (TE-MRI) from 27 ELBW infants with known developmental outcomes beyond 12 months corrected age. Regional biometric measurements were performed by a pediatric neuroradiologist blinded to outcome data. Measures included biparietal width, transcerebellar diameter (TCD), deep gray matter area (DGMA), ventricular dilatation, corpus callosum, and interhemispheric distance. The relationship between regional biometrics and Bayley-II developmental scores were evaluated with linear regression models. The study cohort had an average±standard deviation birth weight of 684±150 g, gestational age of 24.6±2 weeks and 48% males. DGMA was significantly associated with both cognitive and motor outcomes. Significant associations were also observed between TCD and corpus callosum splenium with cognitive and motor outcomes, respectively. Other biometric measures were not associated with outcome (p>0.05). DGMA<10.26 cm2 was highly specific for poor motor and cognitive outcome. TE-MRI biometrics reflecting impaired deep gray matter, callosal, and cerebellar size is associated with worse early childhood cognitive and motor outcomes. DGMA may be the most robust single biometric measure to predict adverse developmental outcome in preterm survivors. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

School-Based Obesity-Prevention Policies and Practices and Weight-Control Behaviors among Adolescents.

PubMed

Larson, Nicole; Davey, Cynthia S; Caspi, Caitlin E; Kubik, Martha Y; Nanney, Marilyn S

2017-02-01

The promotion of healthy eating and physical activity within school settings is an important component of population-based strategies to prevent obesity; however, adolescents may be vulnerable to weight-related messages, as rapid development during this life stage often leads to preoccupation with body size and shape. This study examines secular trends in secondary school curricula topics relevant to the prevention of unhealthy weight-control behaviors; describes cross-sectional associations between weight-related curricula content and students' use of weight-control behaviors; and assesses whether implementation of school-based obesity-prevention policies/practices is longitudinally related to students' weight-control behaviors. The Minnesota School Health Profiles and Minnesota Student Survey (grades 9 and 12) data were used along with National Center for Education Statistics data to examine secular trends, cross-sectional associations (n=141 schools), and longitudinal associations (n=42 schools). Students self-reported their height and weight along with past-year use of healthy (eg, exercise), unhealthy (eg, fasting), and extreme (eg, use laxatives) weight-control behaviors. Descriptive statistics, generalized estimating equations, and generalized linear regression models accounting for school-level demographics. There was no observable pattern during the years 2008 to 2014 in the mean number of curricula topics addressing unhealthy weight-control behaviors, despite an increase in the prevalence of curricula addressing acceptance of body-size differences. Including three vs fewer weight-control topics and specifically including the topic of eating disorders in the curricula was related to a lower school-level percent of students using any extreme weight-control behaviors. In contrast, an overall measure of implementing school-based obesity-prevention policies/practices (eg, prohibited advertising) was unrelated to use of unhealthy or extreme behaviors

School-based obesity prevention policies and practices and weight-control behaviors among adolescents

PubMed Central

Davey, Cynthia S.; Caspi, Caitlin E.; Kubik, Martha Y.; Nanney, Marilyn S.

2016-01-01

Background The promotion of healthy eating and physical activity within school settings is an important component of population-based strategies to prevent obesity; however, adolescents may be vulnerable to weight-related messages as rapid development during this lifestage often leads to preoccupation with body size and shape. Objective This study (1) examines secular trends in secondary school curricula topics relevant to the prevention of unhealthy weight-control behaviors; (2) describes cross-sectional associations between weight-related curricula content and students’ use of weight-control behaviors; and (3) assesses whether implementation of school-based obesity prevention policies/practices are longitudinally related to students’ weight-control behaviors. Design/participants The Minnesota School Health Profiles and Minnesota Student Survey (grades 9 and 12) data were used along with National Center for Education Statistics data to examine secular trends; cross-sectional associations (n=141 schools); and longitudinal associations (n=42 schools). Main Outcome Measures Students self-reported their height and weight along with past-year use of healthy (e.g., exercise), unhealthy (e.g., fasting), and extreme (e.g., use laxatives) weight-control behaviors. Statistical analyses performed Descriptive statistics, generalized estimating equations, and generalized linear regression models accounting for school-level demographics. Results There was no observable pattern over the years 2008 to 2014 in the mean number of curricula topics addressing unhealthy weight-control behaviors despite an increase in the prevalence of curricula addressing acceptance of body size differences. Including three versus fewer weight-control topics and specifically including the topic of eating disorders in the curricula were related to a lower school-level percent of students using any extreme weight-control behaviors. In contrast, an overall measure of implementing school-based obesity

Convergence analyses on on-line weight noise injection-based training algorithms for MLPs.

PubMed

Sum, John; Leung, Chi-Sing; Ho, Kevin

2012-11-01

Injecting weight noise during training is a simple technique that has been proposed for almost two decades. However, little is known about its convergence behavior. This paper studies the convergence of two weight noise injection-based training algorithms, multiplicative weight noise injection with weight decay and additive weight noise injection with weight decay. We consider that they are applied to multilayer perceptrons either with linear or sigmoid output nodes. Let w(t) be the weight vector, let V(w) be the corresponding objective function of the training algorithm, let α >; 0 be the weight decay constant, and let μ(t) be the step size. We show that if μ(t)→ 0, then with probability one E[||w(t)||2(2)] is bound and lim(t) → ∞ ||w(t)||2 exists. Based on these two properties, we show that if μ(t)→ 0, Σtμ(t)=∞, and Σtμ(t)(2) <; ∞, then with probability one these algorithms converge. Moreover, w(t) converges with probability one to a point where ∇wV(w)=0.

Region-based automatic building and forest change detection on Cartosat-1 stereo imagery

NASA Astrophysics Data System (ADS)

Tian, J.; Reinartz, P.; d'Angelo, P.; Ehlers, M.

2013-05-01

In this paper a novel region-based method is proposed for change detection using space borne panchromatic Cartosat-1 stereo imagery. In the first step, Digital Surface Models (DSMs) from two dates are generated by semi-global matching. The geometric lateral resolution of the DSMs is 5 m × 5 m and the height accuracy is in the range of approximately 3 m (RMSE). In the second step, mean-shift segmentation is applied on the orthorectified images of two dates to obtain initial regions. A region intersection following a merging strategy is proposed to get minimum change regions and multi-level change vectors are extracted for these regions. Finally change detection is achieved by combining these features with weighted change vector analysis. The result evaluations demonstrate that the applied DSM generation method is well suited for Cartosat-1 imagery, and the extracted height values can largely improve the change detection accuracy, moreover it is shown that the proposed change detection method can be used robustly for both forest and industrial areas.

Application of Entropy Method in River Health Evaluation Based on Aquatic Ecological Function Regionalization

NASA Astrophysics Data System (ADS)

Shi, Yan-ting; Liu, Jie; Wang, Peng; Zhang, Xu-nuo; Wang, Jun-qiang; Guo, Liang

2017-05-01

With the implementation of water environment management in key basins in China, the monitoring and evaluation system of basins are in urgent need of innovation and upgrading. In view of the heavy workload of existing evaluation methods and the cumbersome calculation of multi-factor weighting method, the idea of using entroy method to assess river health based on aquatic ecological function regionalization was put forward. According to the monitoring data of songhua river in the year of 2011-2015, the entropy weight method was used to calculate the weight of 9 evaluation factors of 29 monitoring sections, and the river health assessment was carried out. In the study area, the river health status of the biodiversity conservation function area (4.111 point) was good, the water conservation function area (3.371 point), the habitat maintenance functional area (3.262 point), the agricultural production maintenance functional area (3.695 point) and the urban supporting functional area (3.399 point) was light pollution.

Infrared target tracking via weighted correlation filter

NASA Astrophysics Data System (ADS)

He, Yu-Jie; Li, Min; Zhang, JinLi; Yao, Jun-Ping

2015-11-01

Design of an effective target tracker is an important and challenging task for many applications due to multiple factors which can cause disturbance in infrared video sequences. In this paper, an infrared target tracking method under tracking by detection framework based on a weighted correlation filter is presented. This method consists of two parts: detection and filtering. For the detection stage, we propose a sequential detection method for the infrared target based on low-rank representation. For the filtering stage, a new multi-feature weighted function which fuses different target features is proposed, which takes the importance of the different regions into consideration. The weighted function is then incorporated into a correlation filter to compute a confidence map more accurately, in order to indicate the best target location based on the detection results obtained from the first stage. Extensive experimental results on different video sequences demonstrate that the proposed method performs favorably for detection and tracking compared with baseline methods in terms of efficiency and accuracy.

Organizational- and employee-level recruitment into a worksite-based weight loss study.

PubMed

Linnan, Laura; Tate, Deborah F; Harrington, Cherise B; Brooks-Russell, Ashley; Finkelstein, Eric; Bangdiwala, Shrikant; Birken, Ben; Britt, Ashley

2012-04-01

Based on national estimates, the majority of working adults are overweight or obese. Overweight and obesity are associated with diminished health, productivity, and increased medical costs for employers. Worksite-based weight loss interventions are desirable from both employee and employer perspectives. To investigate organizational- and employee-level participation in a group-randomized controlled worksite-based weight loss trial. Using a set of inclusion criteria and pre-established procedures, we recruited worksites (and overweight/obese employees from enrolled worksites) from the North Carolina Community College System to participate in a weight loss study. Recruitment results at the worksite (organization) and employee levels are described, along with an assessment of representativeness. Eighty-one percent (48/59) of community colleges indicated initial interest in participating in the weight loss study, and of those, 17 colleges were enrolled. Few characteristics distinguished enrolled community colleges from unenrolled colleges in the overall system. Eligible employees (n = 1004) at participating colleges were enrolled in the weight loss study. On average, participants were aged 46.9 years (SD = 12.1 years), had a body mass index (BMI) of 33.6 kg/m(2) (SD = 7.9 kg/m(2)), 83.2% were White, 13.3% African American, 82.2% female, and 41.8% reported holding an advanced degree (master's or doctoral degree). Compared with the larger North Carolina Community College employee population, participants most often were women, but few other differences were observed. Employees with reduced computer access may have been less likely to participate, and limited data on unenrolled individuals or colleges were available. Community colleges are willing partners for weight loss intervention studies, and overweight/obese employees were receptive to joining a weight loss study offered in the workplace. The results from this study are useful for planning future worksite-based

Risk-based prioritization method for the classification of groundwater pesticide pollution from agricultural regions.

PubMed

Yang, Yu; Lian, Xin-Ying; Jiang, Yong-Hai; Xi, Bei-Dou; He, Xiao-Song

2017-11-01

Agricultural regions are a significant source of groundwater pesticide pollution. To ensure that agricultural regions with a significantly high risk of groundwater pesticide contamination are properly managed, a risk-based ranking method related to groundwater pesticide contamination is needed. In the present paper, a risk-based prioritization method for the classification of groundwater pesticide pollution from agricultural regions was established. The method encompasses 3 phases, including indicator selection, characterization, and classification. In the risk ranking index system employed here, 17 indicators involving the physicochemical properties, environmental behavior characteristics, pesticide application methods, and inherent vulnerability of groundwater in the agricultural region were selected. The boundary of each indicator was determined using K-means cluster analysis based on a survey of a typical agricultural region and the physical and chemical properties of 300 typical pesticides. The total risk characterization was calculated by multiplying the risk value of each indicator, which could effectively avoid the subjectivity of index weight calculation and identify the main factors associated with the risk. The results indicated that the risk for groundwater pesticide contamination from agriculture in a region could be ranked into 4 classes from low to high risk. This method was applied to an agricultural region in Jiangsu Province, China, and it showed that this region had a relatively high risk for groundwater contamination from pesticides, and that the pesticide application method was the primary factor contributing to the relatively high risk. The risk ranking method was determined to be feasible, valid, and able to provide reference data related to the risk management of groundwater pesticide pollution from agricultural regions. Integr Environ Assess Manag 2017;13:1052-1059. © 2017 SETAC. © 2017 SETAC.

Automatic Feature Selection and Weighting for the Formation of Homogeneous Groups for Regional Intensity-Duration-Frequency (IDF) Curve Estimation

NASA Astrophysics Data System (ADS)

Yang, Z.; Burn, D. H.

2017-12-01

Extreme rainfall events can have devastating impacts on society. To quantify the associated risk, the IDF curve has been used to provide the essential rainfall-related information for urban planning. However, the recent changes in the rainfall climatology caused by climate change and urbanization have made the estimates provided by the traditional regional IDF approach increasingly inaccurate. This inaccuracy is mainly caused by two problems: 1) The ineffective choice of similarity indicators for the formation of a homogeneous group at different regions; and 2) An inadequate number of stations in the pooling group that does not adequately reflect the optimal balance between group size and group homogeneity or achieve the lowest uncertainty in the rainfall quantiles estimates. For the first issue, to consider the temporal difference among different meteorological and topographic indicators, a three-layer design is proposed based on three stages in the extreme rainfall formation: cloud formation, rainfall generation and change of rainfall intensity above urban surface. During the process, the impacts from climate change and urbanization are considered through the inclusion of potential relevant features at each layer. Then to consider spatial difference of similarity indicators for the homogeneous group formation at various regions, an automatic feature selection and weighting algorithm, specifically the hybrid searching algorithm of Tabu search, Lagrange Multiplier and Fuzzy C-means Clustering, is used to select the optimal combination of features for the potential optimal homogenous groups formation at a specific region. For the second issue, to compare the uncertainty of rainfall quantile estimates among potential groups, the two sample Kolmogorov-Smirnov test-based sample ranking process is used. During the process, linear programming is used to rank these groups based on the confidence intervals of the quantile estimates. The proposed methodology fills the gap

Disability weights based on patient-reported data from a multinational injury cohort

PubMed Central

Lyons, Ronan A; Simpson, Pamela M; Rivara, Frederick P; Ameratunga, Shanthi; Polinder, Suzanne; Derrett, Sarah; Harrison, James E

2016-01-01

Abstract Objective To create patient-based disability weights for individual injury diagnosis codes and nature-of-injury classifications, for use, as an alternative to panel-based weights, in studies on the burden of disease. Methods Self-reported data based on the EQ-5D standardized measure of health status were collected from 29 770 participants in the Injury-VIBES injury cohort study, which covered Australia, the Netherlands, New Zealand, the United Kingdom of Great Britain and Northern Ireland and the United States of America. The data were combined to calculate new disability weights for each common injury classification and for each type of diagnosis covered by the 10th revision of the International statistical classification of diseases and related health problems. Weights were calculated separately for hospital admissions and presentations confined to emergency departments. Findings There were 29 770 injury cases with at least one EQ-5D score. The mean age of the participants providing data was 51 years. Most participants were male and almost a third had road traffic injuries. The new disability weights were higher for admitted cases than for cases confined to emergency departments and higher than the corresponding weights used by the Global Burden of Disease 2013 study. Long-term disability was common in most categories of injuries. Conclusion Injury is often a chronic disorder and burden of disease estimates should reflect this. Application of the new weights to burden studies would substantially increase estimates of disability-adjusted life-years and provide a more accurate reflection of the impact of injuries on peoples’ lives. PMID:27821883

Child health in Peru: importance of regional variation and community effects on children's height and weight.

PubMed

Shin, Heeju

2007-12-01

In developing countries, height and weight are good indicators of children's health and nutritional status. Maternal education has been accepted as one of the most important influences on child health. Using the 2000 Demographic and Health Survey of Peru, however, I find that the effect of maternal education varies as a function of region. In the most prosperous urban region, maternal education is less important for child health than in poor rural areas, and a higher level of education has a greater effect in rural areas. Multilevel analysis shows that a significant part of the observed correlation between maternal education and child health is moderated by regional differences and community characteristics. The finding suggests that Peruvian public policy should emphasize resource redistribution as well as women's education, and that investment in maternal education should be considered within regional contexts to enhance child health in rural areas.

12 CFR 567.6 - Risk-based capital credit risk-weight categories.

Code of Federal Regulations, 2013 CFR

2013-01-01

...) [Reserved] (vi) Indirect ownership interests in pools of assets. Assets representing an indirect holding of a pool of assets, e.g., mutual funds, are assigned to risk-weight categories under this section based upon the risk weight that would be assigned to the assets in the portfolio of the pool. An...

12 CFR 167.6 - Risk-based capital credit risk-weight categories.

Code of Federal Regulations, 2013 CFR

2013-01-01

...) [Reserved] (vi) Indirect ownership interests in pools of assets. Assets representing an indirect holding of a pool of assets, e.g., mutual funds, are assigned to risk-weight categories under this section based upon the risk weight that would be assigned to the assets in the portfolio of the pool. An...

12 CFR 567.6 - Risk-based capital credit risk-weight categories.

Code of Federal Regulations, 2014 CFR

2014-01-01

...) [Reserved] (vi) Indirect ownership interests in pools of assets. Assets representing an indirect holding of a pool of assets, e.g., mutual funds, are assigned to risk-weight categories under this section based upon the risk weight that would be assigned to the assets in the portfolio of the pool. An...

Enhancing Community Detection By Affinity-based Edge Weighting Scheme

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoo, Andy; Sanders, Geoffrey; Henson, Van

Community detection refers to an important graph analytics problem of finding a set of densely-connected subgraphs in a graph and has gained a great deal of interest recently. The performance of current community detection algorithms is limited by an inherent constraint of unweighted graphs that offer very little information on their internal community structures. In this paper, we propose a new scheme to address this issue that weights the edges in a given graph based on recently proposed vertex affinity. The vertex affinity quantifies the proximity between two vertices in terms of their clustering strength, and therefore, it is idealmore » for graph analytics applications such as community detection. We also demonstrate that the affinity-based edge weighting scheme can improve the performance of community detection algorithms significantly.« less

Serotonin transporter gene-linked polymorphic region: allele distributions in relationship to body weight and in anorexia nervosa.

PubMed

Hinney, A; Barth, N; Ziegler, A; von Prittwitz, S; Hamann, A; Hennighausen, K; Pirke, K M; Heils, A; Rosenkranz, K; Roth, H; Coners, H; Mayer, H; Herzog, W; Siegfried, A; Lehmkuhl, G; Poustka, F; Schmidt, M H; Schäfer, H; Grzeschik, K H; Lesch, K P; Lentes, K U; Remschmidt, H; Hebebrand, J

1997-01-01

Several lines of evidence implicate a role for the serotonergic system in body weight regulation and eating disorders. The magnitude and duration of postsynaptic responses to serotonin (5-HT) is directed by the transport into and release from the presynaptic neuron. Recently, a common polymorphism of a repetitive element in the region of the serotonin transporter (5-HTT) gene-linked polymorphic region (5-HTTLPR) was identified that results in a system of two common alleles. The activity of the 5-HTT, as measured in in vitro assays and in human lymphoblastoid cell lines, is dependent on the respective genotype. We thus hypothesized that this polymorphism is relevant for weight regulation in general and is possibly involved in the etiology of anorexia nervosa (AN). Allele frequencies and genotypes were determined in a total of 385 unrelated obese children, adolescents and adults, 112 underweight subjects and 96 patients with AN. Furthermore, both parents of 98 obese children and adolescents and of 55 patients with AN, respectively, were genotyped, thus allowing to test for both association and linkage. The comparison of allele frequencies between obese and underweight probands provided no evidence for a major role of the 5-HTTLPR in weight regulation. Patients with AN had allele frequencies not significantly different to those observed for obese and underweight individuals.

Probabilistic Near and Far-Future Climate Scenarios of Precipitation and Surface Temperature for the North American Monsoon Region Under a Weighted CMIP5-GCM Ensemble Approach.

NASA Astrophysics Data System (ADS)

Montero-Martinez, M. J.; Colorado, G.; Diaz-Gutierrez, D. E.; Salinas-Prieto, J. A.

2017-12-01

It is well known the North American Monsoon (NAM) region is already a very dry region which is under a lot of stress due to the lack of water resources on multiple locations of the area. However, it is very interesting that even under those conditions, the Mexican part of the NAM region is certainly the most productive in Mexico from the agricultural point of view. Thus, it is very important to have realistic climate scenarios for climate variables such as temperature, precipitation, relative humidity, radiation, etc. This study tries to tackle that problem by generating probabilistic climate scenarios using a weighted CMIP5-GCM ensemble approach based on the Xu et al. (2010) technique which is on itself an improved method from the better known Reliability Ensemble Averaging algorithm of Giorgi and Mearns (2002). In addition, it is compared the 20-plus GCMs individual performances and the weighted ensemble versus observed data (CRU TS2.1) by using different metrics and Taylor diagrams. This study focuses on probabilistic results reaching a certain threshold given the fact that those types of products could be of potential use for agricultural applications.

Genome-wide association study of body weight in Australian Merino sheep reveals an orthologous region on OAR6 to human and bovine genomic regions affecting height and weight.

PubMed

Al-Mamun, Hawlader A; Kwan, Paul; Clark, Samuel A; Ferdosi, Mohammad H; Tellam, Ross; Gondro, Cedric

2015-08-14

Body weight (BW) is an important trait for meat production in sheep. Although over the past few years, numerous quantitative trait loci (QTL) have been detected for production traits in cattle, few QTL studies have been reported for sheep, with even fewer on meat production traits. Our objective was to perform a genome-wide association study (GWAS) with the medium-density Illumina Ovine SNP50 BeadChip to identify genomic regions and corresponding haplotypes associated with BW in Australian Merino sheep. A total of 1781 Australian Merino sheep were genotyped using the medium-density Illumina Ovine SNP50 BeadChip. Among the 53 862 single nucleotide polymorphisms (SNPs) on this array, 48 640 were used to perform a GWAS using a linear mixed model approach. Genotypes were phased with hsphase; to estimate SNP haplotype effects, linkage disequilibrium blocks were identified in the detected QTL region. Thirty-nine SNPs were associated with BW at a Bonferroni-corrected genome-wide significance threshold of 1 %. One region on sheep (Ovis aries) chromosome 6 (OAR6) between 36.15 and 38.56 Mb, included 13 significant SNPs that were associated with BW; the most significant SNP was OAR6_41936490.1 (P = 2.37 × 10(-16)) at 37.69 Mb with an allele substitution effect of 2.12 kg, which corresponds to 0.248 phenotypic standard deviations for BW. The region that surrounds this association signal on OAR6 contains three genes: leucine aminopeptidase 3 (LAP3), which is involved in the processing of the oxytocin precursor; NCAPG non-SMC condensin I complex, subunit G (NCAPG), which is associated with foetal growth and carcass size in cattle; and ligand dependent nuclear receptor corepressor-like (LCORL), which is associated with height in humans and cattle. The GWAS analysis detected 39 SNPs associated with BW in sheep and a major QTL region was identified on OAR6. In several other mammalian species, regions that are syntenic with this region have been found to be associated with body

Developing and testing evidence-based weight management in Australian pharmacies: A Healthier Life Program.

PubMed

Um, Irene S; Krass, Ines; Armour, Carol; Gill, Timothy; Chaar, Betty B

2015-10-01

Pharmacies represent a valuable opportunity to deliver weight management services, rather than just the routine supply of weight-loss products. In order to provide optimal services and translation of evidence-based weight management in community pharmacy, a best practice model program was designed and pilot tested to facilitate implementation of such services in pharmacies in Australia. To develop and pilot a pharmacist-delivered, evidence-based, non-product-centred weight management service for community pharmacy in Australia. Setting Sydney, New South Wales, Australia. A pharmacy-based weight management service called the A Healthier Life Program (AHLP), for overweight and obese individuals, was developed based on current Australian weight management guidelines and recommendations made by key stakeholders. The pharmacist undertook training to acquire specific competencies to deliver the program. The AHLP involved six individual face-to-face sessions with the pharmacist over 3 months. The intervention targeted three areas: diet, physical activity and behavioural change. Weight, BMI, waist circumference, blood pressure, dietary intake, and physical activity levels at 3 months were compared with values at baseline. Qualitative feedback on participants' satisfaction and willingness to pay were also analysed. Eight pharmacies provided the AHLP between February and December 2013. Thirty-four participants were enrolled in the AHLP; mean age 50.7 years (SD 15.7) and mean BMI 34.3 kg/m(2) (SD 5.3). Of the 22 (65%) participants who completed the program, six had achieved the target weight loss of ≥5%. The mean change in weight was -3.5 kg (95% CI -4.8, -2.2) and waist circumference -2.0 cm (95% CI -2.8, -1.3) for program completers at 3 months. Furthermore, participants reported overall positive experiences of the program, and identified accessibility of the pharmacy and high comfort level with the pharmacist, as the major advantages. The AHLP was well received and

Learning to predict where human gaze is using quaternion DCT based regional saliency detection

NASA Astrophysics Data System (ADS)

Li, Ting; Xu, Yi; Zhang, Chongyang

2014-09-01

Many current visual attention approaches used semantic features to accurately capture human gaze. However, these approaches demand high computational cost and can hardly be applied to daily use. Recently, some quaternion-based saliency detection models, such as PQFT (phase spectrum of Quaternion Fourier Transform), QDCT (Quaternion Discrete Cosine Transform), have been proposed to meet real-time requirement of human gaze tracking tasks. However, current saliency detection methods used global PQFT and QDCT to locate jump edges of the input, which can hardly detect the object boundaries accurately. To address the problem, we improved QDCT-based saliency detection model by introducing superpixel-wised regional saliency detection mechanism. The local smoothness of saliency value distribution is emphasized to distinguish noises of background from salient regions. Our algorithm called saliency confidence can distinguish the patches belonging to the salient object and those of the background. It decides whether the image patches belong to the same region. When an image patch belongs to a region consisting of other salient patches, this patch should be salient as well. Therefore, we use saliency confidence map to get background weight and foreground weight to do the optimization on saliency map obtained by QDCT. The optimization is accomplished by least square method. The optimization approach we proposed unifies local and global saliency by combination of QDCT and measuring the similarity between each image superpixel. We evaluate our model on four commonly-used datasets (Toronto, MIT, OSIE and ASD) using standard precision-recall curves (PR curves), the mean absolute error (MAE) and area under curve (AUC) measures. In comparison with most state-of-art models, our approach can achieve higher consistency with human perception without training. It can get accurate human gaze even in cluttered background. Furthermore, it achieves better compromise between speed and accuracy.

A genome-wide association study for body weight in Japanese Thoroughbred racehorses clarifies candidate regions on chromosomes 3, 9, 15, and 18

PubMed Central

TOZAKI, Teruaki; KIKUCHI, Mio; KAKOI, Hironaga; HIROTA, Kei-ichi; NAGATA, Shun-ichi

2017-01-01

ABSTRACT Body weight is an important trait to confirm growth and development in humans and animals. In Thoroughbred racehorses, it is measured in the postnatal, training, and racing periods to evaluate growth and training degrees. The body weight of mature Thoroughbred racehorses generally ranges from 400 to 600 kg, and this broad range is likely influenced by environmental and genetic factors. Therefore, a genome-wide association study (GWAS) using the Equine SNP70 BeadChip was performed to identify the genomic regions associated with body weight in Japanese Thoroughbred racehorses using 851 individuals. The average body weight of these horses was 473.9 kg (standard deviation: 28.0) at the age of 3, and GWAS identified statistically significant SNPs on chromosomes 3 (BIEC2_808466, P=2.32E-14), 9 (BIEC2_1105503, P=1.03E-7), 15 (BIEC2_322669, P=9.50E-6), and 18 (BIEC2_417274, P=1.44E-14), which were associated with body weight as a quantitative trait. The genomic regions on chromosomes 3, 9, 15, and 18 included ligand-dependent nuclear receptor compressor-like protein (LCORL), zinc finger and AT hook domain containing (ZFAT), tribbles pseudokinase 2 (TRIB2), and myostatin (MSTN), respectively, as candidate genes. LCORL and ZFAT are associated with withers height in horses, whereas MSTN affects muscle mass. Thus, the genomic regions identified in this study seem to affect the body weight of Thoroughbred racehorses. Although this information is useful for breeding and growth management of the horses, the production of genetically modified animals and gene doping (abuse/misuse of gene therapy) should be prohibited to maintain horse racing integrity. PMID:29270069

Truncation-based energy weighting string method for efficiently resolving small energy barriers

NASA Astrophysics Data System (ADS)

Carilli, Michael F.; Delaney, Kris T.; Fredrickson, Glenn H.

2015-08-01

The string method is a useful numerical technique for resolving minimum energy paths in rare-event barrier-crossing problems. However, when applied to systems with relatively small energy barriers, the string method becomes inconvenient since many images trace out physically uninteresting regions where the barrier has already been crossed and recrossing is unlikely. Energy weighting alleviates this difficulty to an extent, but typical implementations still require the string's endpoints to evolve to stable states that may be far from the barrier, and deciding upon a suitable energy weighting scheme can be an iterative process dependent on both the application and the number of images used. A second difficulty arises when treating nucleation problems: for later images along the string, the nucleus grows to fill the computational domain. These later images are unphysical due to confinement effects and must be discarded. In both cases, computational resources associated with unphysical or uninteresting images are wasted. We present a new energy weighting scheme that eliminates all of the above difficulties by actively truncating the string as it evolves and forcing all images, including the endpoints, to remain within and cover uniformly a desired barrier region. The calculation can proceed in one step without iterating on strategy, requiring only an estimate of an energy value below which images become uninteresting.

New Internet search volume-based weighting method for integrating various environmental impacts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ji, Changyoon, E-mail: changyoon@yonsei.ac.kr; Hong, Taehoon, E-mail: hong7@yonsei.ac.kr

Weighting is one of the steps in life cycle impact assessment that integrates various characterized environmental impacts as a single index. Weighting factors should be based on the society's preferences. However, most previous studies consider only the opinion of some people. Thus, this research proposes a new weighting method that determines the weighting factors of environmental impact categories by considering public opinion on environmental impacts using the Internet search volumes for relevant terms. To validate the new weighting method, the weighting factors for six environmental impacts calculated by the new weighting method were compared with the existing weighting factors. Themore » resulting Pearson's correlation coefficient between the new and existing weighting factors was from 0.8743 to 0.9889. It turned out that the new weighting method presents reasonable weighting factors. It also requires less time and lower cost compared to existing methods and likewise meets the main requirements of weighting methods such as simplicity, transparency, and reproducibility. The new weighting method is expected to be a good alternative for determining the weighting factor. - Highlight: • A new weighting method using Internet search volume is proposed in this research. • The new weighting method reflects the public opinion using Internet search volume. • The correlation coefficient between new and existing weighting factors is over 0.87. • The new weighting method can present the reasonable weighting factors. • The proposed method can be a good alternative for determining the weighting factors.« less

Lifestyle Intervention for Weight Loss: a group-based program for Emiratis in Ajman, United Arab Emirates

PubMed Central

Sadiya, Amena; Abdi, Sarah; Abusnana, Salah

2016-01-01

Background Lifestyle Intervention for Weight Loss (LIFE-8) is developed as a structured, group-based weight management program for Emiratis with obesity and type 2 diabetes. It is a 3-month program followed by a 1-year follow-up. The results from the first 2 years are presented here to indicate the possibility of its further adaptation and implementation in this region. Methodology We recruited 45 participants with obesity and/or type 2 diabetes based on inclusion/exclusion criteria. The LIFE-8 program was executed by incorporating dietary modification, physical activity, and behavioral therapy, aiming to achieve up to 5% weight loss. The outcomes included body weight, fat mass, waist circumference, blood pressure, fasting blood glucose (FBG), hemoglobin A1c (HbA1c), and nutritional knowledge at 3 months and 12 months. Results We observed a reduction of 5.0% in body weight (4.8±2.8 kg; 95% CI 3.7–5.8), fat mass (−7.8%, P<0.01), and waist circumference (Δ=4±4 cm, P<0.01) in the completed participants (n=28). An improvement (P<0.05) in HbA1c (7.1%±1.0% vs 6.6%±0.7%) and FBG (8.2±2.0 mmol/L vs 6.8±0.8 mmol/L) was observed in participants with obesity and type 2 diabetes after the program. Increase in nutritional knowledge (<0.01) and overall evaluation of the program (9/10) was favorable. On 1-year follow-up, we found that the participants could sustain weight loss (−4.0%), while obese, type 2 diabetic participants sustained HbA1c (6.6%±0.7% vs 6.4%±0.7%) and further improved (P<0.05) the level of FBG (6.8±0.8 mmol/L vs 6.7±0.4 mmol/L). Conclusion LIFE-8 could be an effective, affordable, acceptable, and adaptable lifestyle intervention program for the prevention and management of diabetes in Emiratis. It was successful not only in delivering a modest weight loss but also in improving glycemic control in diabetic participants. PMID:27051310

Replication fidelity improvement of PMMA microlens array based on weight evaluation and optimization

NASA Astrophysics Data System (ADS)

Jiang, Bing-yan; Shen, Long-jiang; Peng, Hua-jiang; Yin, Xiang-lin

2007-12-01

High replication fidelity is a prerequisite of high quality plastic microlens array in injection molding. But, there's not an economical and practical method to evaluate and improve the replication fidelity until now. Based on part weight evaluation and optimization, this paper presents a new method of replication fidelity improvement. Firstly, a simplified analysis model of PMMA micro columns arrays (5×16) with 200μm diameter was set up. And then, Flow (3D) module of Moldflow MPI6.0 based on Navier-Stokes equations was used to calculate the weight of the micro columns arrays in injection molding. The effects of processing parameters (melt temperature, mold temperature, injection time, packing pressure and packing time) on the part weight were investigated in the simulations. The simulation results showed that the mold temperature and the injection time have important effects on the filling of micro columns; the optimal mold temperature and injection time for better replication fidelity could be determined by the curves of mold temperature vs part weight and injection time vs part weight. At last, the effects of processing parameters on part weight of micro columns array were studied experimentally. The experimental results showed that the increase of melt temperature and mold temperature can make the packing pressure transfer to micro cavity more effectively through runner system, and increase the part weight. From the observation results of the image measuring apparatus, it was discovered that the higher the part weight, the better the filling of the microstructures. In conclusion, part weight can be used to evaluate the replication fidelity of micro-feature structured parts primarily; which is an economical and practical method to improve the replication fidelity of microlens arrays based on weight evaluation and optimization.

An Efficient Seam Elimination Method for UAV Images Based on Wallis Dodging and Gaussian Distance Weight Enhancement

PubMed Central

Tian, Jinyan; Li, Xiaojuan; Duan, Fuzhou; Wang, Junqian; Ou, Yang

2016-01-01

The rapid development of Unmanned Aerial Vehicle (UAV) remote sensing conforms to the increasing demand for the low-altitude very high resolution (VHR) image data. However, high processing speed of massive UAV data has become an indispensable prerequisite for its applications in various industry sectors. In this paper, we developed an effective and efficient seam elimination approach for UAV images based on Wallis dodging and Gaussian distance weight enhancement (WD-GDWE). The method encompasses two major steps: first, Wallis dodging was introduced to adjust the difference of brightness between the two matched images, and the parameters in the algorithm were derived in this study. Second, a Gaussian distance weight distribution method was proposed to fuse the two matched images in the overlap region based on the theory of the First Law of Geography, which can share the partial dislocation in the seam to the whole overlap region with an effect of smooth transition. This method was validated at a study site located in Hanwang (Sichuan, China) which was a seriously damaged area in the 12 May 2008 enchuan Earthquake. Then, a performance comparison between WD-GDWE and the other five classical seam elimination algorithms in the aspect of efficiency and effectiveness was conducted. Results showed that WD-GDWE is not only efficient, but also has a satisfactory effectiveness. This method is promising in advancing the applications in UAV industry especially in emergency situations. PMID:27171091

An Efficient Seam Elimination Method for UAV Images Based on Wallis Dodging and Gaussian Distance Weight Enhancement.

PubMed

Tian, Jinyan; Li, Xiaojuan; Duan, Fuzhou; Wang, Junqian; Ou, Yang

2016-05-10

The rapid development of Unmanned Aerial Vehicle (UAV) remote sensing conforms to the increasing demand for the low-altitude very high resolution (VHR) image data. However, high processing speed of massive UAV data has become an indispensable prerequisite for its applications in various industry sectors. In this paper, we developed an effective and efficient seam elimination approach for UAV images based on Wallis dodging and Gaussian distance weight enhancement (WD-GDWE). The method encompasses two major steps: first, Wallis dodging was introduced to adjust the difference of brightness between the two matched images, and the parameters in the algorithm were derived in this study. Second, a Gaussian distance weight distribution method was proposed to fuse the two matched images in the overlap region based on the theory of the First Law of Geography, which can share the partial dislocation in the seam to the whole overlap region with an effect of smooth transition. This method was validated at a study site located in Hanwang (Sichuan, China) which was a seriously damaged area in the 12 May 2008 enchuan Earthquake. Then, a performance comparison between WD-GDWE and the other five classical seam elimination algorithms in the aspect of efficiency and effectiveness was conducted. Results showed that WD-GDWE is not only efficient, but also has a satisfactory effectiveness. This method is promising in advancing the applications in UAV industry especially in emergency situations.

Impact of region contouring variability on image-based focal therapy evaluation

NASA Astrophysics Data System (ADS)

Gibson, Eli; Donaldson, Ian A.; Shah, Taimur T.; Hu, Yipeng; Ahmed, Hashim U.; Barratt, Dean C.

2016-03-01

Motivation: Focal therapy is an emerging low-morbidity treatment option for low-intermediate risk prostate cancer; however, challenges remain in accurately delivering treatment to specified targets and determining treatment success. Registered multi-parametric magnetic resonance imaging (MPMRI) acquired before and after treatment can support focal therapy evaluation and optimization; however, contouring variability, when defining the prostate, the clinical target volume (CTV) and the ablation region in images, reduces the precision of quantitative image-based focal therapy evaluation metrics. To inform the interpretation and clarify the limitations of such metrics, we investigated inter-observer contouring variability and its impact on four metrics. Methods: Pre-therapy and 2-week-post-therapy standard-of-care MPMRI were acquired from 5 focal cryotherapy patients. Two clinicians independently contoured, on each slice, the prostate (pre- and post-treatment) and the dominant index lesion CTV (pre-treatment) in the T2-weighted MRI, and the ablated region (post-treatment) in the dynamic-contrast- enhanced MRI. For each combination of clinician contours, post-treatment images were registered to pre-treatment images using a 3D biomechanical-model-based registration of prostate surfaces, and four metrics were computed: the proportion of the target tissue region that was ablated and the target:ablated region volume ratio for each of two targets (the CTV and an expanded planning target volume). Variance components analysis was used to measure the contribution of each type of contour to the variance in the therapy evaluation metrics. Conclusions: 14-23% of evaluation metric variance was attributable to contouring variability (including 6-12% from ablation region contouring); reducing this variability could improve the precision of focal therapy evaluation metrics.

Eligibility for medical thromboprophylaxis based on risk-factor weights, and clinical thrombotic event rates.

PubMed

Millar, J Alasdair; Lett, Joanne E; Bagley, Leonard J; Densie, Ian K

2012-04-16

To measure eligibility for medical thromboprophylaxis using two Australasian guidelines - the Australia and New Zealand Working Party Guidelines [WPG] and the National Health and Medical Research Council Guidelines [NHMRCG]) - and proposed new guidelines based on risk-factor weights; and to measure the incidence of clinical venous thromboembolism (VTE) events in medical patients ("ensuing VTE"). Prospective case-note audit in an acute medical ward of Southland Hospital, a regional hospital in Invercargill, New Zealand, among all 595 patients who were discharged consecutively from 21 November 2010 to 7 March 2011. Of these, 245 were excluded on clinical grounds or because they were under the care of the authors. The primary outcome was eligibility for prophylaxis under each guideline. Secondary outcomes included incidence of ensuing VTEs, use of thromboprophylaxis, drug acquisition costs with each guideline, and bedside practicability of a guideline based on risk-factor weights. Nineteen per cent of patients were eligible under the new guidelines, compared with 80%, 88% and 36% under the WPG and two interpetations of the NHMRCG, respectively. One patient had an ensuing VTE. The new guideline had lower drug acquisition costs and was suitable for bedside use. Clinical VTE events are rare in medical patients, and medical VTE thromboprophylaxis needs to be more focused. The new guideline has performance characteristics th@satisfy this need.

Randomised controlled trial and economic analysis of an internet-based weight management programme: POWeR+ (Positive Online Weight Reduction).

PubMed

Little, Paul; Stuart, Beth; Hobbs, Fd Richard; Kelly, Jo; Smith, Emily R; Bradbury, Katherine J; Hughes, Stephanie; Smith, Peter Wf; Moore, Michael V; Lean, Mike Ej; Margetts, Barrie M; Byrne, Christopher D; Griffin, Simon; Davoudianfar, Mina; Hooper, Julie; Yao, Guiqing; Zhu, Shihua; Raftery, James; Yardley, Lucy

2017-01-01

Behavioural counselling with intensive follow-up for obesity is effective, but in resource-constrained primary care settings briefer approaches are needed. To estimate the clinical effectiveness and cost-effectiveness of an internet-based behavioural intervention with regular face-to-face or remote support in primary care, compared with brief advice. Individually randomised three-arm parallel trial with health economic evaluation and nested qualitative interviews. Primary care general practices in the UK. Patients with a body mass index of ≥ 30 kg/m 2 (or ≥ 28 kg/m 2 with risk factors) identified from general practice records, recruited by postal invitation. Positive Online Weight Reduction (POWeR+) is a 24-session, web-based weight management intervention completed over 6 months. Following online registration, the website randomly allocated participants using computer-generated random numbers to (1) the control intervention ( n  = 279), which had previously been demonstrated to be clinically effective (brief web-based information that minimised pressure to cut down foods, instead encouraging swaps to healthier choices and increasing fruit and vegetables, plus 6-monthly nurse weighing); (2) POWeR+F ( n  = 269), POWeR+ supplemented by face-to-face nurse support (up to seven contacts); or (3) POWeR+R ( n  = 270), POWeR+ supplemented by remote nurse support (up to five e-mails or brief telephone calls). The primary outcome was a modelled estimate of average weight reduction over 12 months, assessed blind to group where possible, using multiple imputation for missing data. The secondary outcome was the number of participants maintaining a 5% weight reduction at 12 months. A total of 818 eligible individuals were randomised using computer-generated random numbers. Weight change, averaged over 12 months, was documented in 666 out of 818 participants (81%; control, n  = 227; POWeR+F, n  = 221; POWeR+R, n  = 218). The control group

Randomised controlled trial and economic analysis of an internet-based weight management programme: POWeR+ (Positive Online Weight Reduction).

PubMed Central

Little, Paul; Stuart, Beth; Hobbs, Fd Richard; Kelly, Jo; Smith, Emily R; Bradbury, Katherine J; Hughes, Stephanie; Smith, Peter Wf; Moore, Michael V; Lean, Mike Ej; Margetts, Barrie M; Byrne, Christopher D; Griffin, Simon; Davoudianfar, Mina; Hooper, Julie; Yao, Guiqing; Zhu, Shihua; Raftery, James; Yardley, Lucy

2017-01-01

BACKGROUND Behavioural counselling with intensive follow-up for obesity is effective, but in resource-constrained primary care settings briefer approaches are needed. OBJECTIVES To estimate the clinical effectiveness and cost-effectiveness of an internet-based behavioural intervention with regular face-to-face or remote support in primary care, compared with brief advice. DESIGN Individually randomised three-arm parallel trial with health economic evaluation and nested qualitative interviews. SETTING Primary care general practices in the UK. PARTICIPANTS Patients with a body mass index of ≥ 30 kg/m(2) (or ≥ 28 kg/m(2) with risk factors) identified from general practice records, recruited by postal invitation. INTERVENTIONS Positive Online Weight Reduction (POWeR+) is a 24-session, web-based weight management intervention completed over 6 months. Following online registration, the website randomly allocated participants using computer-generated random numbers to (1) the control intervention (n = 279), which had previously been demonstrated to be clinically effective (brief web-based information that minimised pressure to cut down foods, instead encouraging swaps to healthier choices and increasing fruit and vegetables, plus 6-monthly nurse weighing); (2) POWeR+F (n = 269), POWeR+ supplemented by face-to-face nurse support (up to seven contacts); or (3) POWeR+R (n = 270), POWeR+ supplemented by remote nurse support (up to five e-mails or brief telephone calls). MAIN OUTCOME MEASURES The primary outcome was a modelled estimate of average weight reduction over 12 months, assessed blind to group where possible, using multiple imputation for missing data. The secondary outcome was the number of participants maintaining a 5% weight reduction at 12 months. RESULTS A total of 818 eligible individuals were randomised using computer-generated random numbers. Weight change, averaged over 12 months, was documented in 666 out of 818 participants (81

Mothers' birth weight and survival of their offspring: population based study.

PubMed

Skjaerven, R; Wilcox, A J; Oyen, N; Magnus, P

1997-05-10

To test the hypothesis that a baby's survival is related to the mother's birth weight. Population based dataset for two generations. Population registry in Norway. All birth records for women born in Norway since 1967 were linked to births during 1981-94, thereby forming 105104 mother-offspring units. Perinatal mortality specific for weight for offspring in groups of maternal birth weight (with 500 g categories in both). A mother's birth weight was strongly associated with the weight of her baby. Maternal birth weight was associated with perinatal survival of her baby only for mothers with birth weights under 2000 g. These mothers were more likely to lose a baby in the perinatal period (odds ratio 2.3, 95% confidence interval 1.4 to 3.7). Among mothers with a birth weight over 2000 g there was no overall association between mother's weight and infant survival. There was, however, a strong interaction between mother's birth weight, infant birth weight, and infant survival. Mortality among small babies was much higher for those whose mothers had been large at birth. For example, babies weighing 2500-2999 g had a threefold higher mortality if their mother's birth weight had been high (> or = 4000 g) than if the mother had been small (2500-2999 g). Mothers who weighed less than 2000 g at birth have a higher risk of losing their own babies. For mothers who weighed > or = 2000 g their birth weight provides a benchmark for judging the growth of their offspring. Babies who are small relative to their mother's birth weight are at increased risk of mortality.

Modeling the relationship between body weight and energy intake: A molecular diffusion-based approach

PubMed Central

2012-01-01

Background Body weight is at least partly controlled by the choices made by a human in response to external stimuli. Changes in body weight are mainly caused by energy intake. By analyzing the mechanisms involved in food intake, we considered that molecular diffusion plays an important role in body weight changes. We propose a model based on Fick's second law of diffusion to simulate the relationship between energy intake and body weight. Results This model was applied to food intake and body weight data recorded in humans; the model showed a good fit to the experimental data. This model was also effective in predicting future body weight. Conclusions In conclusion, this model based on molecular diffusion provides a new insight into the body weight mechanisms. Reviewers This article was reviewed by Dr. Cabral Balreira (nominated by Dr. Peter Olofsson), Prof. Yang Kuang and Dr. Chao Chen. PMID:22742862

Birth weight and infant growth: optimal infant weight gain versus optimal infant weight.

PubMed

Xiong, Xu; Wightkin, Joan; Magnus, Jeanette H; Pridjian, Gabriella; Acuna, Juan M; Buekens, Pierre

2007-01-01

Infant growth assessment often focuses on "optimal" infant weights and lengths at specific ages, while de-emphasizing infant weight gain. Objective of this study was to examine infant growth patterns by measuring infant weight gain relative to birth weight. We conducted this study based on data collected in a prospective cohort study including 3,302 births with follow up examinations of infants between the ages of 8 and 18 months. All infants were participants in the Louisiana State Women, Infant and Children Supplemental Food Program between 1999 and 2001. Growth was assessed by infant weight gain percentage (IWG%, defined as infant weight gain divided by birth weight) as well as by mean z-scores and percentiles for weight-for-age, length-for-age, and weight-for-length calculated based on growth charts published by the U.S. Centers for Disease Control (CDC). An inverse relationship was noted between birth weight category and IWG% (from 613.9% for infants with birth weights <1500 g to 151.3% for infants with birth weights of 4000 g or more). In contrast, low birth weight infants had lower weight-for-age, weight-for-length z-scores and percentiles compared to normal birth weight infants according to CDC growth charts. Although low birth weight infants had lower anthropometric measures compared to a national reference population, they had significant catch-up growth; High birth weight infants had significant slow-down growth. We suggest that growth assessments should compare infants' anthropometric data to their own previous growth measures as well as to a reference population. Further studies are needed to identify optimal ranges of infant weight gain.

Weighted spline based integration for reconstruction of freeform wavefront.

PubMed

Pant, Kamal K; Burada, Dali R; Bichra, Mohamed; Ghosh, Amitava; Khan, Gufran S; Sinzinger, Stefan; Shakher, Chandra

2018-02-10

In the present work, a spline-based integration technique for the reconstruction of a freeform wavefront from the slope data has been implemented. The slope data of a freeform surface contain noise due to their machining process and that introduces reconstruction error. We have proposed a weighted cubic spline based least square integration method (WCSLI) for the faithful reconstruction of a wavefront from noisy slope data. In the proposed method, the measured slope data are fitted into a piecewise polynomial. The fitted coefficients are determined by using a smoothing cubic spline fitting method. The smoothing parameter locally assigns relative weight to the fitted slope data. The fitted slope data are then integrated using the standard least squares technique to reconstruct the freeform wavefront. Simulation studies show the improved result using the proposed technique as compared to the existing cubic spline-based integration (CSLI) and the Southwell methods. The proposed reconstruction method has been experimentally implemented to a subaperture stitching-based measurement of a freeform wavefront using a scanning Shack-Hartmann sensor. The boundary artifacts are minimal in WCSLI which improves the subaperture stitching accuracy and demonstrates an improved Shack-Hartmann sensor for freeform metrology application.

A Multi-Scale Algorithm for Graffito Advertisement Detection from Images of Real Estate

NASA Astrophysics Data System (ADS)

Yang, Jun; Zhu, Shi-Jiao

There is a significant need to detect and extract the graffito advertisement embedded in the housing images automatically. However, it is a hard job to separate the advertisement region well since housing images generally have complex background. In this paper, a detecting algorithm which uses multi-scale Gabor filters to identify graffito regions is proposed. Firstly, multi-scale Gabor filters with different directions are applied to housing images, then the approach uses these frequency data to find likely graffito regions using the relationship of different channels, it exploits the ability of different filters technique to solve the detection problem with low computational efforts. Lastly, the method is tested on several real estate images which are embedded graffito advertisement to verify its robustness and efficiency. The experiments demonstrate graffito regions can be detected quite well.

Investigating local network interactions underlying first- and second-order processing.

PubMed

Ellemberg, Dave; Allen, Harriet A; Hess, Robert F

2004-01-01

We compared the spatial lateral interactions for first-order cues to those for second-order cues, and investigated spatial interactions between these two types of cues. We measured the apparent modulation depth of a target Gabor at fixation, in the presence and the absence of horizontally flanking Gabors. The Gabors' gratings were either added to (first-order) or multiplied with (second-order) binary 2-D noise. Apparent "contrast" or modulation depth (i.e., the perceived difference between the high and low luminance regions for the first-order stimulus, or between the high and low contrast regions for the second-order stimulus) was measured with a modulation depth-matching paradigm. For each observer, the first- and second-order Gabors were equated for apparent modulation depth without the flankers. Our results indicate that at the smallest inter-element spacing, the perceived reduction in modulation depth is significantly smaller for the second-order than for the first-order stimuli. Further, lateral interactions operate over shorter distances and the spatial frequency and orientation tuning of the suppression effect are broader for second- than first-order stimuli. Finally, first- and second-order information interact in an asymmetrical fashion; second-order flankers do not reduce the apparent modulation depth of the first-order target, whilst first-order flankers reduce the apparent modulation depth of the second-order target.

Maternal vitamin D, DNA methylation at imprint regulatory regions, and offspring weight at birth, 1 year, and 3 years

PubMed Central

Neelon, Sara E Benjamin; White, Alexandra J; Vidal, Adriana C; Schildkraut, Joellen M; Murtha, Amy P; Murphy, Susan K; Kullman, Seth W; Hoyo, Cathrine

2017-01-01

Background/Objective Vitamin D deficiency during pregnancy is associated with poor birth outcomes in some studies, but few have examined weight beyond birth. Additionally, little is known about how vitamin D influences DNA methylation of regulatory regions known to be involved in growth, as possible mediators to weight status in offspring. Subjects/Methods We conducted linear regressions to assess maternal plasma 25-hydroxyvitamin D (25(OH)D) by quartile and birth weight for gestational age z-score, 1-year weight-for-length z-score, and 3-year body mass index (BMI) z-score among 476 mother/infant dyads from a prospective cohort. We assessed maternal 25(OH)D and infant DNA methylation at 9 differentially methylated regions (DMRs) of genomically imprinted genes with known functions in fetal growth, including H19, IGF2, MEG3, MEG3-IG, MEST, NNAT, PEG3, PLAGL1, and SGCE/PEG10. Results Mean (standard deviation, SD) maternal 25(OH)D was 41.1 (14.2) nmol/L at a mean (SD) of 13.2 (5.5) weeks gestation. After adjustment for potential confounders, the first (Q1) and second (Q2) quartiles of 25(OH)D, compared to the fourth (Q4), were associated with lower birth weight for gestational age z-scores (−0.43 units; CI −0.79, −0.07; p=0.02 for Q1 and −0.56 units; CI −0.89, −0.23; p=0.001 for Q2). Q1 compared to Q4 was associated with higher 1-year weight-for-length z-scores (0.78 units; 0.08, 1.54; p=0.04) and higher 3-year BMI z-scores (0.83 units; 0.11, 0.93; p=0.02). We did not observe associations between maternal 25(OH)D and methylation for any of the 9 DMRs after correcting for multiple testing. Conclusions Reduced maternal 25(OH)D was associated with lower birth weight for gestational age z-scores but higher 1-year weight-for-length and 3-year BMI z-scores in offspring. However, 25(OH)D does not appear to be operating through the regulatory sequences of the genomically imprinted genes we examined. PMID:28676681

Image-based Analysis of Emotional Facial Expressions in Full Face Transplants.

PubMed

Bedeloglu, Merve; Topcu, Çagdas; Akgul, Arzu; Döger, Ela Naz; Sever, Refik; Ozkan, Ozlenen; Ozkan, Omer; Uysal, Hilmi; Polat, Ovunc; Çolak, Omer Halil

2018-01-20

In this study, it is aimed to determine the degree of the development in emotional expression of full face transplant patients from photographs. Hence, a rehabilitation process can be planned according to the determination of degrees as a later work. As envisaged, in full face transplant cases, the determination of expressions can be confused or cannot be achieved as the healthy control group. In order to perform image-based analysis, a control group consist of 9 healthy males and 2 full-face transplant patients participated in the study. Appearance-based Gabor Wavelet Transform (GWT) and Local Binary Pattern (LBP) methods are adopted for recognizing neutral and 6 emotional expressions which consist of angry, scared, happy, hate, confused and sad. Feature extraction was carried out by using both methods and combination of these methods serially. In the performed expressions, the extracted features of the most distinct zones in the facial area where the eye and mouth region, have been used to classify the emotions. Also, the combination of these region features has been used to improve classifier performance. Control subjects and transplant patients' ability to perform emotional expressions have been determined with K-nearest neighbor (KNN) classifier with region-specific and method-specific decision stages. The results have been compared with healthy group. It has been observed that transplant patients don't reflect some emotional expressions. Also, there were confusions among expressions.

Quantitative DLA-based compressed sensing for T1-weighted acquisitions

NASA Astrophysics Data System (ADS)

Svehla, Pavel; Nguyen, Khieu-Van; Li, Jing-Rebecca; Ciobanu, Luisa

2017-08-01

High resolution Manganese Enhanced Magnetic Resonance Imaging (MEMRI), which uses manganese as a T1 contrast agent, has great potential for functional imaging of live neuronal tissue at single neuron scale. However, reaching high resolutions often requires long acquisition times which can lead to reduced image quality due to sample deterioration and hardware instability. Compressed Sensing (CS) techniques offer the opportunity to significantly reduce the imaging time. The purpose of this work is to test the feasibility of CS acquisitions based on Diffusion Limited Aggregation (DLA) sampling patterns for high resolution quantitative T1-weighted imaging. Fully encoded and DLA-CS T1-weighted images of Aplysia californica neural tissue were acquired on a 17.2T MRI system. The MR signal corresponding to single, identified neurons was quantified for both versions of the T1 weighted images. For a 50% undersampling, DLA-CS can accurately quantify signal intensities in T1-weighted acquisitions leading to only 1.37% differences when compared to the fully encoded data, with minimal impact on image spatial resolution. In addition, we compared the conventional polynomial undersampling scheme with the DLA and showed that, for the data at hand, the latter performs better. Depending on the image signal to noise ratio, higher undersampling ratios can be used to further reduce the acquisition time in MEMRI based functional studies of living tissues.

High-molecular-weight polymers for protein crystallization: poly-γ-glutamic acid-based precipitants

PubMed Central

Hu, Ting-Chou; Korczyńska, Justyna; Smith, David K.; Brzozowski, Andrzej Marek

2008-01-01

Protein crystallization has been revolutionized by the intro­duction of high-throughput technologies, which have led to a speeding up of the process while simultaneously reducing the amount of protein sample necessary. Nonetheless, the chemistry dimension of protein crystallization has remained relatively undeveloped. Most crystallization screens are based on the same set of precipitants. To address this shortcoming, the development of new protein precipitants based on poly-γ-­glutamic acid (PGA) polymers with different molecular-weight ranges is reported here: PGA-LM (low molecular weight) of ∼400 kDa and PGA-HM (high molecular weight) of >1000 kDa. It is also demonstrated that protein precipitants can be expanded further to polymers with much higher molecular weight than those that are currently in use. Furthermore, the modification of PGA-like polymers by covalent attachments of glucosamine substantially improved their solubility without affecting their crystallization properties. Some preliminary PGA-based screens are presented here. PMID:18703844

Weighted Discriminative Dictionary Learning based on Low-rank Representation

NASA Astrophysics Data System (ADS)

Chang, Heyou; Zheng, Hao

2017-01-01

Low-rank representation has been widely used in the field of pattern classification, especially when both training and testing images are corrupted with large noise. Dictionary plays an important role in low-rank representation. With respect to the semantic dictionary, the optimal representation matrix should be block-diagonal. However, traditional low-rank representation based dictionary learning methods cannot effectively exploit the discriminative information between data and dictionary. To address this problem, this paper proposed weighted discriminative dictionary learning based on low-rank representation, where a weighted representation regularization term is constructed. The regularization associates label information of both training samples and dictionary atoms, and encourages to generate a discriminative representation with class-wise block-diagonal structure, which can further improve the classification performance where both training and testing images are corrupted with large noise. Experimental results demonstrate advantages of the proposed method over the state-of-the-art methods.

A motivation-focused weight loss maintenance program is an effective alternative to a skill-based approach.

PubMed

West, D S; Gorin, A A; Subak, L L; Foster, G; Bragg, C; Hecht, J; Schembri, M; Wing, R R

2011-02-01

Maintaining weight loss is a major challenge in obesity treatment. Individuals often indicate that waning motivation prompts cessation of effective weight management behaviors. Therefore, a novel weight loss maintenance program that specifically targets motivational factors was evaluated. Overweight women (N=338; 19% African American) with urinary incontinence were randomized to lifestyle obesity treatment or control and followed for 18 months. All participants in lifestyle (N=226) received the same initial 6-month group behavioral obesity treatment and were then randomized to (1) a novel motivation-focused maintenance program (N=113) or (2) a standard skill-based maintenance approach (N=113). Weight assessed at baseline, 6 and 18 months. Both treatment groups (motivation-focused and skill-based) achieved comparable 18-month weight losses (-5.48% for motivation-focused vs -5.55% in skill-based, P=0.98), and both groups lost significantly more than controls (-1.51%; P=0.0012 in motivation-focused and P=0.0021 in skill-based). A motivation-focused maintenance program offers an alternative, effective approach to weight maintenance expanding available evidence-based interventions beyond traditional skill-based programs.

Estimating regional centile curves from mixed data sources and countries.

PubMed

van Buuren, Stef; Hayes, Daniel J; Stasinopoulos, D Mikis; Rigby, Robert A; ter Kuile, Feiko O; Terlouw, Dianne J

2009-10-15

Regional or national growth distributions can provide vital information on the health status of populations. In most resource poor countries, however, the required anthropometric data from purpose-designed growth surveys are not readily available. We propose a practical method for estimating regional (multi-country) age-conditional weight distributions based on existing survey data from different countries. We developed a two-step method by which one is able to model data with widely different age ranges and sample sizes. The method produces references both at the country level and at the regional (multi-country) level. The first step models country-specific centile curves by Box-Cox t and Box-Cox power exponential distributions implemented in generalized additive model for location, scale and shape through a common model. Individual countries may vary in location and spread. The second step defines the regional reference from a finite mixture of the country distributions, weighted by population size. To demonstrate the method we fitted the weight-for-age distribution of 12 countries in South East Asia and the Western Pacific, based on 273 270 observations. We modeled both the raw body weight and the corresponding Z score, and obtained a good fit between the final models and the original data for both solutions. We briefly discuss an application of the generated regional references to obtain appropriate, region specific, age-based dosing regimens of drugs used in the tropics. The method is an affordable and efficient strategy to estimate regional growth distributions where the standard costly alternatives are not an option. Copyright (c) 2009 John Wiley & Sons, Ltd.

Multi-objective optimization for generating a weighted multi-model ensemble

NASA Astrophysics Data System (ADS)

Lee, H.

2017-12-01

Many studies have demonstrated that multi-model ensembles generally show better skill than each ensemble member. When generating weighted multi-model ensembles, the first step is measuring the performance of individual model simulations using observations. There is a consensus on the assignment of weighting factors based on a single evaluation metric. When considering only one evaluation metric, the weighting factor for each model is proportional to a performance score or inversely proportional to an error for the model. While this conventional approach can provide appropriate combinations of multiple models, the approach confronts a big challenge when there are multiple metrics under consideration. When considering multiple evaluation metrics, it is obvious that a simple averaging of multiple performance scores or model ranks does not address the trade-off problem between conflicting metrics. So far, there seems to be no best method to generate weighted multi-model ensembles based on multiple performance metrics. The current study applies the multi-objective optimization, a mathematical process that provides a set of optimal trade-off solutions based on a range of evaluation metrics, to combining multiple performance metrics for the global climate models and their dynamically downscaled regional climate simulations over North America and generating a weighted multi-model ensemble. NASA satellite data and the Regional Climate Model Evaluation System (RCMES) software toolkit are used for assessment of the climate simulations. Overall, the performance of each model differs markedly with strong seasonal dependence. Because of the considerable variability across the climate simulations, it is important to evaluate models systematically and make future projections by assigning optimized weighting factors to the models with relatively good performance. Our results indicate that the optimally weighted multi-model ensemble always shows better performance than an arithmetic

Contrast sensitivity function in stereoscopic viewing of Gabor patches on a medical polarized three-dimensional stereoscopic display

NASA Astrophysics Data System (ADS)

Rousson, Johanna; Haar, Jérémy; Santal, Sarah; Kumcu, Asli; Platiša, Ljiljana; Piepers, Bastian; Kimpe, Tom; Philips, Wilfried

2016-03-01

While three-dimensional (3-D) imaging systems are entering hospitals, no study to date has explored the luminance calibration needs of 3-D stereoscopic diagnostic displays and if they differ from two-dimensional (2-D) displays. Since medical display calibration incorporates the human contrast sensitivity function (CSF), we first assessed the 2-D CSF for benchmarking and then examined the impact of two image parameters on the 3-D stereoscopic CSF: (1) five depth plane (DP) positions (between DP: -171 and DP: 2853 mm), and (2) three 3-D inclinations (0 deg, 45 deg, and 60 deg around the horizontal axis of a DP). Stimuli were stereoscopic images of a vertically oriented 2-D Gabor patch at one of seven frequencies ranging from 0.4 to 10 cycles/deg. CSFs were measured for seven to nine human observers with a staircase procedure. The results indicate that the 2-D CSF model remains valid for a 3-D stereoscopic display regardless of the amount of disparity between the stereo images. We also found that the 3-D CSF at DP≠0 does not differ from the 3-D CSF at DP=0 for DPs and disparities which allow effortless binocular fusion. Therefore, the existing 2-D medical luminance calibration algorithm remains an appropriate tool for calibrating polarized stereoscopic medical displays.

Male sex, height, weight, and body mass index can increase external pressure to calf region using knee-crutch-type leg holder system in lithotomy position.

PubMed

Mizuno, Ju; Takahashi, Toru

2016-01-01

Well-leg compartment syndrome (WLCS) is one of the catastrophic complications related to prolonged surgical procedures performed in the lithotomy position, using a knee-crutch-type leg holder (KCLH) system, to support the popliteal fossae and calf regions. Obesity has been implicated as a risk factor in the lithotomy position-related WLCS during surgery. In the present study, we investigated the relationship between the external pressure (EP) applied to the calf region using a KCLH system in the lithotomy position and selected physical characteristics. Twenty-one young, healthy volunteers (21.4±0.5 years of age, eleven males and ten females) participated in this study. The KCLH system used was Knee Crutch(®). We assessed four types of EPs applied to the calf region: box pressure, peak box pressure, contact pressure, and peak contact pressure, using pressure-distribution measurement system (BIG-MAT(®)). Relationships between these four EPs to the calf regions of both lower legs and a series of physical characteristics (sex, height, weight, and body mass index [BMI]) were analyzed. All four EPs applied to the bilateral calf regions were higher in males than in females. For all subjects, significant positive correlations were observed between all four EPs and height, weight, and BMI. EP applied to the calf region is higher in males than in females when the subject is supported by a KCLH system in the lithotomy position. In addition, EP increases with the increase in height, weight, and BMI. Therefore, male sex, height, weight, and BMI may contribute to the risk of inducing WLCS.

Effects of Weight Loss with and without Exercise on Regional Body Fat Distribution in Postmenopausal Women.

PubMed

Serra, Monica C; Blumenthal, Jacob B; Addison, Odessa R; Miller, Ann J; Goldberg, Andrew P; Ryan, Alice S

2017-01-01

The purpose was to determine whether lifestyle interventions have different effects on regional fat in women with normal glucose tolerance vs. impaired glucose tolerance (NGT vs. IGT). Changes in glucose metabolism (2-h oral glucose-tolerance tests), android to gynoid fat mass ratio (dual energy X-ray absorptiometry [DXA]), visceral to subcutaneous abdominal fat area ratio (CT), and abdominal to gluteal subcutaneous fat cell weight (FCW; adipose tissue biopsies) were determined in 60 overweight postmenopausal women (45-80 years) following 6 months of weight loss alone (WL; n = 28) or with aerobic exercise (AEX + WL; n = 32). The interventions led to ∼8% decrease in weight, but only the AEX + WL group improved fitness (↑11% in VO2max) and reduced the android-to-gynoid fat mass ratio (↓5%; p < 0.05). Both NGT and IGT groups reduced visceral and subcutaneous abdominal fat areas and abdominal and gluteal FCWs, which related to improvements in homeostatic model assessment (r = 0.34-0.42) and 2-h glucose (r = 0.34-0.35), respectively (p < 0.05). The decline in FCW was 2× greater in women with IGT following WL (p < 0.05). The ratios of abdominal-to-gluteal FCW did not change following either intervention. The mechanisms by which WL with and without exercise impact regional fat loss should be explored as reductions in abdominal fat area and subcutaneous FCW appear to influence glucose metabolism. This is a work of the U.S. Government and is not subject to copyright protection in the United States. Foreign copyrights may apply. Published by S. Karger AG, Basel.

Energy Efficient and Stable Weight Based Clustering for Mobile Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Bouk, Safdar H.; Sasase, Iwao

Recently several weighted clustering algorithms have been proposed, however, to the best of our knowledge; there is none that propagates weights to other nodes without weight message for leader election, normalizes node parameters and considers neighboring node parameters to calculate node weights. In this paper, we propose an Energy Efficient and Stable Weight Based Clustering (EE-SWBC) algorithm that elects cluster heads without sending any additional weight message. It propagates node parameters to its neighbors through neighbor discovery message (HELLO Message) and stores these parameters in neighborhood list. Each node normalizes parameters and efficiently calculates its own weight and the weights of neighboring nodes from that neighborhood table using Grey Decision Method (GDM). GDM finds the ideal solution (best node parameters in neighborhood list) and calculates node weights in comparison to the ideal solution. The node(s) with maximum weight (parameters closer to the ideal solution) are elected as cluster heads. In result, EE-SWBC fairly selects potential nodes with parameters closer to ideal solution with less overhead. Different performance metrics of EE-SWBC and Distributed Weighted Clustering Algorithm (DWCA) are compared through simulations. The simulation results show that EE-SWBC maintains fewer average numbers of stable clusters with minimum overhead, less energy consumption and fewer changes in cluster structure within network compared to DWCA.

Body Weight Perception and Weight Control Practices among Teenagers

PubMed Central

Jeewon, Rajesh

2013-01-01

Background. Weight-loss behaviours are highly prevalent among adolescents, and body weight perception motivates weight control practices. However, little is known about the association of body weight perception, and weight control practices among teenagers in Mauritius. The aim of this study is to investigate the relationships between actual body weight, body weight perception, and weight control practices among teenagers. Methods. A questionnaire-based survey was used to collect data on anthropometric measurements, weight perception and weight control practices from a sample of 180 male and female students (90 boys and 90 girls) aged between 13 and 18 years old. Results. Based on BMI, 11.7% of students were overweight. Overall, 43.3% of respondents reported trying to lose weight (61.1% girls and 25.6% boys). Weight-loss behaviours were more prevalent among girls. Among the weight-loss teens, 88.5% students perceived themselves as overweight even though only 19.2% were overweight. Reducing fat intake (84.6%), exercising (80.8%), and increasing intake of fruits and vegetables (73.1%) and decreasing intake of sugar (66.7%) were the most commonly reported methods to lose weight. Conclusion. Body weight perception was poorly associated with actual weight status. Gender difference was observed in body weight perception. PMID:24967256

Mindless Eating Challenge: Retention, Weight Outcomes, and Barriers for Changes in a Public Web-Based Healthy Eating and Weight Loss Program

PubMed Central

Payne, Collin R; Wansink, Brian

2012-01-01

Background Most dietary programs fail to produce lasting outcomes because participants soon return to their old habits. Small behavioral and environmental changes based on simple heuristics may have the best chance to lead to sustainable habit changes over time. Objective To evaluate participant retention, weight outcomes, and barriers for changes in a publicly available web-based healthy eating and weight loss program. Methods The National Mindless Eating Challenge (NMEC) was a publicly available, online healthy eating and weight loss program with ongoing recruitment of participants. This volunteer sample consisted of 2053 participants (mean age 39.8 years, 89% female, 90% white/Caucasian, BMI mean 28.14). Participants completed an initial profiling survey and were assigned three targeted habit change suggestions (tips). After each month, participants were asked to complete a follow-up survey and then receive new suggestions for the subsequent month. Results In terms of overall attrition, 75% (1549/2053) of participants who completed the intake survey never returned to follow up. Overall mean weight loss among returning participants was 0.4% of initial weight (P=.019). Participants who stayed in the program at least three calendar months and completed at least two follow-up surveys (38%, 189/504) lost on average 1.8 lbs (1.0%) of their initial weight over the course of the program (P=.009). Furthermore, participants who reported consistent adherence (25+ days/month) to the suggested changes reported an average monthly weight loss of 2.0 lbs (P<.001). Weight loss was less for those who discontinued after 1-2 months or who did not adhere to the suggested changes. Participants who reported having lost weight reported higher monthly adherence to suggestions (mean 14.9 days, SD 7.92) than participants who maintained (mean 12.4 days, SD 7.63) or gained weight (mean 12.0 days, SD 7.50; F=14.17, P<.001). Common reported barriers for changes included personally unsuitable

Mindless eating challenge: retention, weight outcomes, and barriers for changes in a public web-based healthy eating and weight loss program.

PubMed

Kaipainen, Kirsikka; Payne, Collin R; Wansink, Brian

2012-12-17

Most dietary programs fail to produce lasting outcomes because participants soon return to their old habits. Small behavioral and environmental changes based on simple heuristics may have the best chance to lead to sustainable habit changes over time. To evaluate participant retention, weight outcomes, and barriers for changes in a publicly available web-based healthy eating and weight loss program. The National Mindless Eating Challenge (NMEC) was a publicly available, online healthy eating and weight loss program with ongoing recruitment of participants. This volunteer sample consisted of 2053 participants (mean age 39.8 years, 89% female, 90% white/Caucasian, BMI mean 28.14). Participants completed an initial profiling survey and were assigned three targeted habit change suggestions (tips). After each month, participants were asked to complete a follow-up survey and then receive new suggestions for the subsequent month. In terms of overall attrition, 75% (1549/2053) of participants who completed the intake survey never returned to follow up. Overall mean weight loss among returning participants was 0.4% of initial weight (P=.019). Participants who stayed in the program at least three calendar months and completed at least two follow-up surveys (38%, 189/504) lost on average 1.8 lbs (1.0%) of their initial weight over the course of the program (P=.009). Furthermore, participants who reported consistent adherence (25+ days/month) to the suggested changes reported an average monthly weight loss of 2.0 lbs (P<.001). Weight loss was less for those who discontinued after 1-2 months or who did not adhere to the suggested changes. Participants who reported having lost weight reported higher monthly adherence to suggestions (mean 14.9 days, SD 7.92) than participants who maintained (mean 12.4 days, SD 7.63) or gained weight (mean 12.0 days, SD 7.50; F=14.17, P<.001). Common reported barriers for changes included personally unsuitable or inapplicable suggestions

Enrichment of low molecular weight serum proteins using acetonitrile precipitation for mass spectrometry based proteomic analysis.

PubMed

Kay, Richard; Barton, Chris; Ratcliffe, Lucy; Matharoo-Ball, Balwir; Brown, Pamela; Roberts, Jane; Teale, Phil; Creaser, Colin

2008-10-01

A rapid acetonitrile (ACN)-based extraction method has been developed that reproducibly depletes high abundance and high molecular weight proteins from serum prior to mass spectrometric analysis. A nanoflow liquid chromatography/tandem mass spectrometry (nano-LC/MS/MS) multiple reaction monitoring (MRM) method for 57 high to medium abundance serum proteins was used to characterise the ACN-depleted fraction after tryptic digestion. Of the 57 targeted proteins 29 were detected and albumin, the most abundant protein in serum and plasma, was identified as the 20th most abundant protein in the extract. The combination of ACN depletion and one-dimensional nano-LC/MS/MS enabled the detection of the low abundance serum protein, insulin-like growth factor-I (IGF-I), which has a serum concentration in the region of 100 ng/mL. One-dimensional sodium dodecyl sulfate/polyacrylamide gel electrophoresis (SDS-PAGE) analysis of the depleted serum showed no bands corresponding to proteins of molecular mass over 75 kDa after extraction, demonstrating the efficiency of the method for the depletion of high molecular weight proteins. Total protein analysis of the ACN extracts showed that approximately 99.6% of all protein is removed from the serum. The ACN-depletion strategy offers a viable alternative to the immunochemistry-based protein-depletion techniques commonly used for removing high abundance proteins from serum prior to MS-based proteomic analyses.

A preliminary structural analysis of space-base living quarters modules to verify a weight-estimating technique

NASA Technical Reports Server (NTRS)

Grissom, D. S.; Schneider, W. C.

1971-01-01

The determination of a base line (minimum weight) design for the primary structure of the living quarters modules in an earth-orbiting space base was investigated. Although the design is preliminary in nature, the supporting analysis is sufficiently thorough to provide a reasonably accurate weight estimate of the major components that are considered to comprise the structural weight of the space base.

A Novel Weighted Kernel PCA-Based Method for Optimization and Uncertainty Quantification

NASA Astrophysics Data System (ADS)

Thimmisetty, C.; Talbot, C.; Chen, X.; Tong, C. H.

2016-12-01

It has been demonstrated that machine learning methods can be successfully applied to uncertainty quantification for geophysical systems through the use of the adjoint method coupled with kernel PCA-based optimization. In addition, it has been shown through weighted linear PCA how optimization with respect to both observation weights and feature space control variables can accelerate convergence of such methods. Linear machine learning methods, however, are inherently limited in their ability to represent features of non-Gaussian stochastic random fields, as they are based on only the first two statistical moments of the original data. Nonlinear spatial relationships and multipoint statistics leading to the tortuosity characteristic of channelized media, for example, are captured only to a limited extent by linear PCA. With the aim of coupling the kernel-based and weighted methods discussed, we present a novel mathematical formulation of kernel PCA, Weighted Kernel Principal Component Analysis (WKPCA), that both captures nonlinear relationships and incorporates the attribution of significance levels to different realizations of the stochastic random field of interest. We also demonstrate how new instantiations retaining defining characteristics of the random field can be generated using Bayesian methods. In particular, we present a novel WKPCA-based optimization method that minimizes a given objective function with respect to both feature space random variables and observation weights through which optimal snapshot significance levels and optimal features are learned. We showcase how WKPCA can be applied to nonlinear optimal control problems involving channelized media, and in particular demonstrate an application of the method to learning the spatial distribution of material parameter values in the context of linear elasticity, and discuss further extensions of the method to stochastic inversion.

A Multi-Modal Face Recognition Method Using Complete Local Derivative Patterns and Depth Maps

PubMed Central

Yin, Shouyi; Dai, Xu; Ouyang, Peng; Liu, Leibo; Wei, Shaojun

2014-01-01

In this paper, we propose a multi-modal 2D + 3D face recognition method for a smart city application based on a Wireless Sensor Network (WSN) and various kinds of sensors. Depth maps are exploited for the 3D face representation. As for feature extraction, we propose a new feature called Complete Local Derivative Pattern (CLDP). It adopts the idea of layering and has four layers. In the whole system, we apply CLDP separately on Gabor features extracted from a 2D image and depth map. Then, we obtain two features: CLDP-Gabor and CLDP-Depth. The two features weighted by the corresponding coefficients are combined together in the decision level to compute the total classification distance. At last, the probe face is assigned the identity with the smallest classification distance. Extensive experiments are conducted on three different databases. The results demonstrate the robustness and superiority of the new approach. The experimental results also prove that the proposed multi-modal 2D + 3D method is superior to other multi-modal ones and CLDP performs better than other Local Binary Pattern (LBP) based features. PMID:25333290

Equivalent charge source model based iterative maximum neighbor weight for sparse EEG source localization.

PubMed

Xu, Peng; Tian, Yin; Lei, Xu; Hu, Xiao; Yao, Dezhong

2008-12-01

How to localize the neural electric activities within brain effectively and precisely from the scalp electroencephalogram (EEG) recordings is a critical issue for current study in clinical neurology and cognitive neuroscience. In this paper, based on the charge source model and the iterative re-weighted strategy, proposed is a new maximum neighbor weight based iterative sparse source imaging method, termed as CMOSS (Charge source model based Maximum neighbOr weight Sparse Solution). Different from the weight used in focal underdetermined system solver (FOCUSS) where the weight for each point in the discrete solution space is independently updated in iterations, the new designed weight for each point in each iteration is determined by the source solution of the last iteration at both the point and its neighbors. Using such a new weight, the next iteration may have a bigger chance to rectify the local source location bias existed in the previous iteration solution. The simulation studies with comparison to FOCUSS and LORETA for various source configurations were conducted on a realistic 3-shell head model, and the results confirmed the validation of CMOSS for sparse EEG source localization. Finally, CMOSS was applied to localize sources elicited in a visual stimuli experiment, and the result was consistent with those source areas involved in visual processing reported in previous studies.

An evaluation of a primary care-based weight management initiative.

PubMed

Muckle, Sarah

2007-07-01

Obesity is a significant issue in public health. There is a wealth of research that will be discussed as part of this article that identifies what has been effective in helping obese people reach a healthy weight. Health visitors and practice nurses are ideally situated to provide evidence-based support and monitoring to those living with obesity who want to improve their health and well-being. This article evaluates a primary-care-based weight management programme that was devised from the research evidence available. A total of nine women were offered a combination of interactive group education sessions, monitoring and supoort over a period of six months. Success was measured using quantitative and qualitative measures. The intervention effectively reduced the BMI of participants and demonstrated the adverse effects obesity has on individual quality of life.

A method for determining customer requirement weights based on TFMF and TLR

NASA Astrophysics Data System (ADS)

Ai, Qingsong; Shu, Ting; Liu, Quan; Zhou, Zude; Xiao, Zheng

2013-11-01

'Customer requirements' (CRs) management plays an important role in enterprise systems (ESs) by processing customer-focused information. Quality function deployment (QFD) is one of the main CRs analysis methods. Because CR weights are crucial for the input of QFD, we developed a method for determining CR weights based on trapezoidal fuzzy membership function (TFMF) and 2-tuple linguistic representation (TLR). To improve the accuracy of CR weights, we propose to apply TFMF to describe CR weights so that they can be appropriately represented. Because the fuzzy logic is not capable of aggregating information without loss, TLR model is adopted as well. We first describe the basic concepts of TFMF and TLR and then introduce an approach to compute CR weights. Finally, an example is provided to explain and verify the proposed method.

Mobile Visual Search Based on Histogram Matching and Zone Weight Learning

NASA Astrophysics Data System (ADS)

Zhu, Chuang; Tao, Li; Yang, Fan; Lu, Tao; Jia, Huizhu; Xie, Xiaodong

2018-01-01

In this paper, we propose a novel image retrieval algorithm for mobile visual search. At first, a short visual codebook is generated based on the descriptor database to represent the statistical information of the dataset. Then, an accurate local descriptor similarity score is computed by merging the tf-idf weighted histogram matching and the weighting strategy in compact descriptors for visual search (CDVS). At last, both the global descriptor matching score and the local descriptor similarity score are summed up to rerank the retrieval results according to the learned zone weights. The results show that the proposed approach outperforms the state-of-the-art image retrieval method in CDVS.

Exploring weight loss services in primary care and staff views on using a web-based programme.

PubMed

Ware, Lisa J; Williams, Sarah; Bradbury, Katherine; Brant, Catherine; Little, Paul; Hobbs, F D Richard; Yardley, Lucy

2012-01-01

Demand is increasing for primary care to deliver effective weight management services to patients, but research suggests that staff feel inadequately resourced for such a role. Supporting service delivery with a free and effective web-based weight management programme could maximise primary care resource and provide cost-effective support for patients. However, integration of e-health into primary care may face challenges. To explore primary care staff experiences of delivering weight management services and their perceptions of a web-based weight management programme to aid service delivery. Focus groups were conducted with primary care physicians, nurses and healthcare assistants (n = 36) involved in delivering weight loss services. Data were analysed using inductive thematic analysis. Participants thought that primary care should be involved in delivering weight management, especially when weight was aggravating health problems. However, they felt under-resourced to deliver these services and unsure as to the effectiveness of their input, as routine services were not evaluated. Beliefs that current services were ineffective resulted in staff reluctance to allocate more resources. Participants were hopeful that supplementing practice with a web-based weight management programme would enhance patient services and promote service evaluation. Although primary care staff felt they should deliver weight loss services, low levels of faith in the efficacy of current treatments resulted in provision of under-resourced and 'ad hoc' services. Integration of a web-based weight loss programme that promotes service evaluation and provides a cost-effective option for supporting patients may encourage practices to invest more in weight management services.

Similarity indices based on link weight assignment for link prediction of unweighted complex networks

NASA Astrophysics Data System (ADS)

Liu, Shuxin; Ji, Xinsheng; Liu, Caixia; Bai, Yi

2017-01-01

Many link prediction methods have been proposed for predicting the likelihood that a link exists between two nodes in complex networks. Among these methods, similarity indices are receiving close attention. Most similarity-based methods assume that the contribution of links with different topological structures is the same in the similarity calculations. This paper proposes a local weighted method, which weights the strength of connection between each pair of nodes. Based on the local weighted method, six local weighted similarity indices extended from unweighted similarity indices (including Common Neighbor (CN), Adamic-Adar (AA), Resource Allocation (RA), Salton, Jaccard and Local Path (LP) index) are proposed. Empirical study has shown that the local weighted method can significantly improve the prediction accuracy of these unweighted similarity indices and that in sparse and weakly clustered networks, the indices perform even better.

Weight-based nutritional diagnosis of Mexican children and adolescents with neuromotor disabilities.

PubMed

Vega-Sanchez, Rodrigo; de la Luz Gomez-Aguilar, Maria; Haua, Karime; Rozada, Guadalupe

2012-07-04

Nutrition related problems are increasing worldwide but they have scarcely been evaluated in people with neuromotor disabilities, particularly in developing countries. In this study our aim was to describe the weight-based nutritional diagnoses of children and adolescents with neuromotor disabilities who attended a private rehabilitation center in Mexico City. Data from the first visit's clinical records of 410 patients who attended the Nutrition department at the Teleton Center for Children Rehabilitation, between 1999 and 2008, were analyzed. Sex, age, weight and height, length or segmental length data were collected and used to obtain the nutritional diagnosis based on international growth charts, as well as disability-specific charts. Weight for height was considered the main indicator. Cerebral palsy was the most frequent diagnosis, followed by spina bifida, muscular dystrophy, and Down's syndrome. Children with cerebral palsy showed a higher risk of presenting low weight/undernutrition (LW/UN) than children with other disabilities, which was three times higher in females. In contrast, children with spina bifida, particularly males, were more likely to be overweight/obese (OW/OB), especially after the age of 6 and even more after 11. Patients with muscular dystrophy showed a significantly lower risk of LW/UN than patients with other disabilities. In patients with Down's syndrome neither LW/UN nor OW/OB were different between age and sex. This is the first study that provides evidence of the nutritional situation of children and adolescents with neuromotor disabilities in Mexico, based on their weight status. Low weight and obesity affect a large number of these patients due to their disability, age and sex. Early nutritional diagnosis must be considered an essential component in the treatment of these patients to prevent obesity and malnutrition, and improve their quality of life.

Effect of Web-based lifestyle modification on weight control: a meta-analysis.

PubMed

Kodama, S; Saito, K; Tanaka, S; Horikawa, C; Fujiwara, K; Hirasawa, R; Yachi, Y; Iida, K T; Shimano, H; Ohashi, Y; Yamada, N; Sone, H

2012-05-01

Web-based treatment programs are attractive in primary care because of their ability to reach numerous individuals at low cost. Our aim of this meta-analysis is to systematically review the weight loss or maintenance effect of the Internet component in obesity treatment programs. MEDLINE and EMBASE literature searches were conducted to identify studies investigating the effect of Web-based individualized advice on lifestyle modification on weight loss. Randomized controlled trials that consisted of a Web-user experimental and non-Web user control group were included. Weight changes in the experimental group in comparison with the control group were pooled with a random-effects model. A total of 23 studies comprising 8697 participants were included. Overall, using the Internet had a modest but significant additional weight-loss effect compared with non-Web user control groups (-0.68 kg, P=0.03). In comparison with the control group, stratified analysis indicated that using the Internet as an adjunct to obesity care was effective (-1.00 kg, P<0.001), but that using it as a substitute for face-to-face support was unfavorable (+1.27 kg, P=0.01). An additional effect on weight control was observed when the aim of using the Internet was initial weight loss (-1.01 kg; P=0.03), but was not observed when the aim was weight maintenance (+0.68 kg; P=0.26). The relative effect was diminished with longer educational periods (P-trend=0.04) and was insignificant (-0.20 kg; P=0.75) in studies with educational periods of 12 months or more. The current meta-analysis indicates that the Internet component in obesity treatment programs has a modest effect on weight control. However, the effect was inconsistent, largely depending on the type of usage of the Internet or the period of its use.

A Comparison of Weights Matrices on Computation of Dengue Spatial Autocorrelation

NASA Astrophysics Data System (ADS)

Suryowati, K.; Bekti, R. D.; Faradila, A.

2018-04-01

Spatial autocorrelation is one of spatial analysis to identify patterns of relationship or correlation between locations. This method is very important to get information on the dispersal patterns characteristic of a region and linkages between locations. In this study, it applied on the incidence of Dengue Hemorrhagic Fever (DHF) in 17 sub districts in Sleman, Daerah Istimewa Yogyakarta Province. The link among location indicated by a spatial weight matrix. It describe the structure of neighbouring and reflects the spatial influence. According to the spatial data, type of weighting matrix can be divided into two types: point type (distance) and the neighbourhood area (contiguity). Selection weighting function is one determinant of the results of the spatial analysis. This study use queen contiguity based on first order neighbour weights, queen contiguity based on second order neighbour weights, and inverse distance weights. Queen contiguity first order and inverse distance weights shows that there is the significance spatial autocorrelation in DHF, but not by queen contiguity second order. Queen contiguity first and second order compute 68 and 86 neighbour list

Spatially weighted mutual information image registration for image guided radiation therapy.

PubMed

Park, Samuel B; Rhee, Frank C; Monroe, James I; Sohn, Jason W

2010-09-01

To develop a new metric for image registration that incorporates the (sub)pixelwise differential importance along spatial location and to demonstrate its application for image guided radiation therapy (IGRT). It is well known that rigid-body image registration with mutual information is dependent on the size and location of the image subset on which the alignment analysis is based [the designated region of interest (ROI)]. Therefore, careful review and manual adjustments of the resulting registration are frequently necessary. Although there were some investigations of weighted mutual information (WMI), these efforts could not apply the differential importance to a particular spatial location since WMI only applies the weight to the joint histogram space. The authors developed the spatially weighted mutual information (SWMI) metric by incorporating an adaptable weight function with spatial localization into mutual information. SWMI enables the user to apply the selected transform to medically "important" areas such as tumors and critical structures, so SWMI is neither dominated by, nor neglects the neighboring structures. Since SWMI can be utilized with any weight function form, the authors presented two examples of weight functions for IGRT application: A Gaussian-shaped weight function (GW) applied to a user-defined location and a structures-of-interest (SOI) based weight function. An image registration example using a synthesized 2D image is presented to illustrate the efficacy of SWMI. The convergence and feasibility of the registration method as applied to clinical imaging is illustrated by fusing a prostate treatment planning CT with a clinical cone beam CT (CBCT) image set acquired for patient alignment. Forty-one trials are run to test the speed of convergence. The authors also applied SWMI registration using two types of weight functions to two head and neck cases and a prostate case with clinically acquired CBCT/ MVCT image sets. The SWMI registration with

Anthropometric surrogates for screening of low birth weight newborns: a community-based study.

PubMed

Rustagi, Neeti; Prasuna, J G; Taneja, D K

2012-03-01

In developing countries, where about 75% of births occur at home or in the community, logistic problems prevent the weighing of every newborn child. This study compares various anthropometric surrogates for identification of low birth weight neonates. A longitudinal community based study was done in an urban resettlement colony and 283 singleton neonates within 7 days of birth were examined for the anthropometric measurements such as head, chest, mid upper arm circumference and foot length as a screening tool for low birth weight. Chest circumference measured within 7 days of birth appeared to be the most appropriate surrogate of low birth weight with highest sensitivity (75.4%), specificity (78.4%), and positive predictive value (48.9%) as compared with other anthropometric parameters. Low birth weight neonates in absence of weighing scales can be early identified by using simple anthropometric measurements for enhanced home-based care and timely referral.

Task-based evaluation of segmentation algorithms for diffusion-weighted MRI without using a gold standard

PubMed Central

Jha, Abhinav K.; Kupinski, Matthew A.; Rodríguez, Jeffrey J.; Stephen, Renu M.; Stopeck, Alison T.

2012-01-01

In many studies, the estimation of the apparent diffusion coefficient (ADC) of lesions in visceral organs in diffusion-weighted (DW) magnetic resonance images requires an accurate lesion-segmentation algorithm. To evaluate these lesion-segmentation algorithms, region-overlap measures are used currently. However, the end task from the DW images is accurate ADC estimation, and the region-overlap measures do not evaluate the segmentation algorithms on this task. Moreover, these measures rely on the existence of gold-standard segmentation of the lesion, which is typically unavailable. In this paper, we study the problem of task-based evaluation of segmentation algorithms in DW imaging in the absence of a gold standard. We first show that using manual segmentations instead of gold-standard segmentations for this task-based evaluation is unreliable. We then propose a method to compare the segmentation algorithms that does not require gold-standard or manual segmentation results. The no-gold-standard method estimates the bias and the variance of the error between the true ADC values and the ADC values estimated using the automated segmentation algorithm. The method can be used to rank the segmentation algorithms on the basis of both accuracy and precision. We also propose consistency checks for this evaluation technique. PMID:22713231

Mobile applications for weight management: theory-based content analysis.

PubMed

Azar, Kristen M J; Lesser, Lenard I; Laing, Brian Y; Stephens, Janna; Aurora, Magi S; Burke, Lora E; Palaniappan, Latha P

2013-11-01

The use of smartphone applications (apps) to assist with weight management is increasingly prevalent, but the quality of these apps is not well characterized. The goal of the study was to evaluate diet/nutrition and anthropometric tracking apps based on incorporation of features consistent with theories of behavior change. A comparative, descriptive assessment was conducted of the top-rated free apps in the Health and Fitness category available in the iTunes App Store. Health and Fitness apps (N=200) were evaluated using predetermined inclusion/exclusion criteria and categorized based on commonality in functionality, features, and developer description. Four researchers then evaluated the two most popular apps in each category using two instruments: one based on traditional behavioral theory (score range: 0-100) and the other on the Fogg Behavioral Model (score range: 0-6). Data collection and analysis occurred in November 2012. Eligible apps (n=23) were divided into five categories: (1) diet tracking; (2) healthy cooking; (3) weight/anthropometric tracking; (4) grocery decision making; and (5) restaurant decision making. The mean behavioral theory score was 8.1 (SD=4.2); the mean persuasive technology score was 1.9 (SD=1.7). The top-rated app on both scales was Lose It! by Fitnow Inc. All apps received low overall scores for inclusion of behavioral theory-based strategies. © 2013 American Journal of Preventive Medicine.

Older members perform better in an internet-based behavioral weight loss program compared to younger members.

PubMed

van der Mark, Marianne; Jonasson, Josefine; Svensson, Madeleine; Linné, Yvonne; Rossner, Stephan; Lagerros, Ylva Trolle

2009-01-01

New technology offers increased opportunities for weight control. However, it is not clear whether older people with less computer training can make use of this tool. Our objective was to examine how members above the age of 65 years performed in an internet-based behavioral weight loss program, compared to younger members. Data from members (n = 23,233) of an internet-based behavioral weight loss program were analyzed. We restricted our study to active participants accessing the weight club, during a 6-month period (n = 4,440). The number of logins, food intake, and weight records were examined. Participants were divided into age tertiles separately for men and women. The oldest tertile was further subdivided into two groups: above and below the age of 65 years. Participants aged 65 or older were more likely to remain active in the weight club for at least 6 months compared to younger age groups. They had the highest frequency of recordings of food intake and current weight. Among women, those older than 65 years had on average the highest percentage of weight loss (5.6 kg, 6.8%). Men above 65 years of age had the highest number of logins, on average 161 times during the 6-month period. Older participants are performing equally well or even better in an internet-based behavioral weight loss program than younger participants. Internet-based programs could be a promising and attractive option for older adults requiring assistance in losing weight. 2009 S. Karger AG, Basel.

Does Successful Weight Loss in an Internet-Based Worksite Weight Loss Program Improve Employee Presenteeism and Absenteeism?

ERIC Educational Resources Information Center

Harden, Samantha M.; You, Wen; Almeida, Fabio A.; Hill, Jennie L.; Linnan, Laura A.; Allen, Kacie C.; Estabrooks, Paul A.

2015-01-01

Certain risk factors associated with overweight and obesity may lead to reduced productivity in the workforce (i.e., increased absenteeism and presenteeism). Participants in a large, Internet-based worksite weight loss intervention, who were present at follow-up (N = 1,030), completed a self-reported productivity measure (World Health…

Adjudicating between face-coding models with individual-face fMRI responses

PubMed Central

Kriegeskorte, Nikolaus

2017-01-01

The perceptual representation of individual faces is often explained with reference to a norm-based face space. In such spaces, individuals are encoded as vectors where identity is primarily conveyed by direction and distinctiveness by eccentricity. Here we measured human fMRI responses and psychophysical similarity judgments of individual face exemplars, which were generated as realistic 3D animations using a computer-graphics model. We developed and evaluated multiple neurobiologically plausible computational models, each of which predicts a representational distance matrix and a regional-mean activation profile for 24 face stimuli. In the fusiform face area, a face-space coding model with sigmoidal ramp tuning provided a better account of the data than one based on exemplar tuning. However, an image-processing model with weighted banks of Gabor filters performed similarly. Accounting for the data required the inclusion of a measurement-level population averaging mechanism that approximates how fMRI voxels locally average distinct neuronal tunings. Our study demonstrates the importance of comparing multiple models and of modeling the measurement process in computational neuroimaging. PMID:28746335

Research on HDR image fusion algorithm based on Laplace pyramid weight transform with extreme low-light CMOS

NASA Astrophysics Data System (ADS)

Guan, Wen; Li, Li; Jin, Weiqi; Qiu, Su; Zou, Yan

2015-10-01

Extreme-Low-Light CMOS has been widely applied in the field of night-vision as a new type of solid image sensor. But if the illumination in the scene has drastic changes or the illumination is too strong, Extreme-Low-Light CMOS can't both clearly present the high-light scene and low-light region. According to the partial saturation problem in the field of night-vision, a HDR image fusion algorithm based on the Laplace Pyramid was researched. The overall gray value and the contrast of the low light image is very low. We choose the fusion strategy based on regional average gradient for the top layer of the long exposure image and short exposure image, which has rich brightness and textural features. The remained layers which represent the edge feature information of the target are based on the fusion strategy based on regional energy. In the process of source image reconstruction with Laplacian pyramid image, we compare the fusion results with four kinds of basal images. The algorithm is tested using Matlab and compared with the different fusion strategies. We use information entropy, average gradient and standard deviation these three objective evaluation parameters for the further analysis of the fusion result. Different low illumination environment experiments show that the algorithm in this paper can rapidly get wide dynamic range while keeping high entropy. Through the verification of this algorithm features, there is a further application prospect of the optimized algorithm. Keywords: high dynamic range imaging, image fusion, multi-exposure image, weight coefficient, information fusion, Laplacian pyramid transform.

A Case Study on a Combination NDVI Forecasting Model Based on the Entropy Weight Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Shengzhi; Ming, Bo; Huang, Qiang

It is critically meaningful to accurately predict NDVI (Normalized Difference Vegetation Index), which helps guide regional ecological remediation and environmental managements. In this study, a combination forecasting model (CFM) was proposed to improve the performance of NDVI predictions in the Yellow River Basin (YRB) based on three individual forecasting models, i.e., the Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Support Vector Machine (SVM) models. The entropy weight method was employed to determine the weight coefficient for each individual model depending on its predictive performance. Results showed that: (1) ANN exhibits the highest fitting capability among the four orecastingmore » models in the calibration period, whilst its generalization ability becomes weak in the validation period; MLR has a poor performance in both calibration and validation periods; the predicted results of CFM in the calibration period have the highest stability; (2) CFM generally outperforms all individual models in the validation period, and can improve the reliability and stability of predicted results through combining the strengths while reducing the weaknesses of individual models; (3) the performances of all forecasting models are better in dense vegetation areas than in sparse vegetation areas.« less

Model-based inference for small area estimation with sampling weights

PubMed Central

Vandendijck, Y.; Faes, C.; Kirby, R.S.; Lawson, A.; Hens, N.

2017-01-01

Obtaining reliable estimates about health outcomes for areas or domains where only few to no samples are available is the goal of small area estimation (SAE). Often, we rely on health surveys to obtain information about health outcomes. Such surveys are often characterised by a complex design, stratification, and unequal sampling weights as common features. Hierarchical Bayesian models are well recognised in SAE as a spatial smoothing method, but often ignore the sampling weights that reflect the complex sampling design. In this paper, we focus on data obtained from a health survey where the sampling weights of the sampled individuals are the only information available about the design. We develop a predictive model-based approach to estimate the prevalence of a binary outcome for both the sampled and non-sampled individuals, using hierarchical Bayesian models that take into account the sampling weights. A simulation study is carried out to compare the performance of our proposed method with other established methods. The results indicate that our proposed method achieves great reductions in mean squared error when compared with standard approaches. It performs equally well or better when compared with more elaborate methods when there is a relationship between the responses and the sampling weights. The proposed method is applied to estimate asthma prevalence across districts. PMID:28989860

RANWAR: rank-based weighted association rule mining from gene expression and methylation data.

PubMed

Mallik, Saurav; Mukhopadhyay, Anirban; Maulik, Ujjwal

2015-01-01

Ranking of association rules is currently an interesting topic in data mining and bioinformatics. The huge number of evolved rules of items (or, genes) by association rule mining (ARM) algorithms makes confusion to the decision maker. In this article, we propose a weighted rule-mining technique (say, RANWAR or rank-based weighted association rule-mining) to rank the rules using two novel rule-interestingness measures, viz., rank-based weighted condensed support (wcs) and weighted condensed confidence (wcc) measures to bypass the problem. These measures are basically depended on the rank of items (genes). Using the rank, we assign weight to each item. RANWAR generates much less number of frequent itemsets than the state-of-the-art association rule mining algorithms. Thus, it saves time of execution of the algorithm. We run RANWAR on gene expression and methylation datasets. The genes of the top rules are biologically validated by Gene Ontologies (GOs) and KEGG pathway analyses. Many top ranked rules extracted from RANWAR that hold poor ranks in traditional Apriori, are highly biologically significant to the related diseases. Finally, the top rules evolved from RANWAR, that are not in Apriori, are reported.

Soft learning vector quantization and clustering algorithms based on ordered weighted aggregation operators.

PubMed

Karayiannis, N B

2000-01-01

This paper presents the development and investigates the properties of ordered weighted learning vector quantization (LVQ) and clustering algorithms. These algorithms are developed by using gradient descent to minimize reformulation functions based on aggregation operators. An axiomatic approach provides conditions for selecting aggregation operators that lead to admissible reformulation functions. Minimization of admissible reformulation functions based on ordered weighted aggregation operators produces a family of soft LVQ and clustering algorithms, which includes fuzzy LVQ and clustering algorithms as special cases. The proposed LVQ and clustering algorithms are used to perform segmentation of magnetic resonance (MR) images of the brain. The diagnostic value of the segmented MR images provides the basis for evaluating a variety of ordered weighted LVQ and clustering algorithms.

Regional Differences in Adipose Tissue Hormone/Cytokine Production Before and After Weight Loss in Abdominally Obese Women

PubMed Central

You, Tongjian; Wang, Xuewen; Murphy, Karin M.; Lyles, Mary F.; Demons, Jamehl L.; Yang, Rongze; Gong, Da-Wei; Nicklas, Barbara J.

2014-01-01

Objective To compare the regional differences in subcutaneous adipose tissue hormone/cytokine production in abdominally obese women during weight loss. Design and Methods Forty-two abdominally obese, older women underwent a 20-week weight loss intervention composed of hypocaloric diet with or without aerobic exercise (total energy expenditure: ~2800 kcal/week). Subcutaneous (gluteal and abdominal) adipose tissue biopsies were conducted before and after the intervention. Results Adipose tissue gene expression and release of leptin, adiponectin, and interleukin 6 (IL-6) were determined. The intervention resulted in significant weight loss (−10.1 ±0.7 kg, P<0.001). At baseline, gene expression of adiponectin were higher (P<0.01), and gene expression and release of IL-6 were lower (both P<0.05) in abdominal than in gluteal adipose tissue. After intervention, leptin gene expression and release were lower in both gluteal and abdominal adipose tissue compared to baseline (P<0.05 to P<0.01). Abdominal, but not gluteal, adipose tissue adiponectin gene expression and release increased after intervention (both P<0.05). Conclusion A 20-week weight loss program decreased leptin production in both gluteal and abdominal adipose tissue, but only increased adiponectin production from abdominal adipose tissue in obese women. This depot-specific effect may be of importance for the treatment of health complications associated with abdominal adiposity. PMID:24634403

Toward semantic-based retrieval of visual information: a model-based approach

NASA Astrophysics Data System (ADS)

Park, Youngchoon; Golshani, Forouzan; Panchanathan, Sethuraman

2002-07-01

This paper center around the problem of automated visual content classification. To enable classification based image or visual object retrieval, we propose a new image representation scheme called visual context descriptor (VCD) that is a multidimensional vector in which each element represents the frequency of a unique visual property of an image or a region. VCD utilizes the predetermined quality dimensions (i.e., types of features and quantization level) and semantic model templates mined in priori. Not only observed visual cues, but also contextually relevant visual features are proportionally incorporated in VCD. Contextual relevance of a visual cue to a semantic class is determined by using correlation analysis of ground truth samples. Such co-occurrence analysis of visual cues requires transformation of a real-valued visual feature vector (e.g., color histogram, Gabor texture, etc.,) into a discrete event (e.g., terms in text). Good-feature to track, rule of thirds, iterative k-means clustering and TSVQ are involved in transformation of feature vectors into unified symbolic representations called visual terms. Similarity-based visual cue frequency estimation is also proposed and used for ensuring the correctness of model learning and matching since sparseness of sample data causes the unstable results of frequency estimation of visual cues. The proposed method naturally allows integration of heterogeneous visual or temporal or spatial cues in a single classification or matching framework, and can be easily integrated into a semantic knowledge base such as thesaurus, and ontology. Robust semantic visual model template creation and object based image retrieval are demonstrated based on the proposed content description scheme.

Is School-Based Height and Weight Screening of Elementary Students Private and Reliable?

ERIC Educational Resources Information Center

Stoddard, Sarah A.; Kubik, Martha Y.; Skay, Carol

2008-01-01

The Institute of Medicine recommends school-based body mass index (BMI) screening as an obesity prevention strategy. While school nurses have provided height/weight screening for years, little has been published describing measurement reliability or process. This study evaluated the reliability of height/weight measures collected by school nurses…

A voxel based comparative analysis using magnetization transfer imaging and T1-weighted magnetic resonance imaging in progressive supranuclear palsy

PubMed Central

Sandhya, Mangalore; Saini, Jitender; Pasha, Shaik Afsar; Yadav, Ravi; Pal, Pramod Kumar

2014-01-01

Aims: In progressive supranuclear palsy (PSP) tissue damage occurs in specific cortical and subcortical regions. Voxel based analysis using T1-weighted images depict quantitative gray matter (GM) atrophy changes. Magnetization transfer (MT) imaging depicts qualitative changes in the brain parenchyma. The purpose of our study was to investigate whether MT imaging could indicate abnormalities in PSP. Settings and Design: A total of 10 patients with PSP (9 men and 1 woman) and 8 controls (5 men and 3 women) were studied with T1-weighted magnetic resonance imaging (MRI) and 3DMT imaging. Voxel based analysis of T1-weighted MRI was performed to investigate brain atrophy while MT was used to study qualitative abnormalities in the brain tissue. We used SPM8 to investigate group differences (with two sample t-test) using the GM and white matter (WM) segmented data. Results: T1-weighted imaging and MT are equally sensitive to detect changes in GM and WM in PSP. Magnetization transfer ratio images and magnetization-prepared rapid acquisition of gradient echo revealed extensive bilateral volume and qualitative changes in the orbitofrontal, prefrontal cortex and limbic lobe and sub cortical GM. The prefrontal structures involved were the rectal gyrus, medial, inferior frontal gyrus (IFG) and middle frontal gyrus (MFG). The anterior cingulate, cingulate gyrus and lingual gyrus of limbic lobe and subcortical structures such as caudate, thalamus, insula and claustrum were also involved. Cerebellar involvement mainly of anterior lobe was also noted. Conclusions: The findings suggest that voxel based MT imaging permits a whole brain unbiased investigation of central nervous system structural integrity in PSP. PMID:25024571

Satellite-based high-resolution PM2.5 estimation over the Beijing-Tianjin-Hebei region of China using an improved geographically and temporally weighted regression model.

PubMed

He, Qingqing; Huang, Bo

2018-05-01

Ground fine particulate matter (PM2.5) concentrations at high spatial resolution are substantially required for determining the population exposure to PM2.5 over densely populated urban areas. However, most studies for China have generated PM2.5 estimations at a coarse resolution (≥10 km) due to the limitation of satellite aerosol optical depth (AOD) product in spatial resolution. In this study, the 3 km AOD data fused using the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 AOD products were employed to estimate the ground PM2.5 concentrations over the Beijing-Tianjin-Hebei (BTH) region of China from January 2013 to December 2015. An improved geographically and temporally weighted regression (iGTWR) model incorporating seasonal characteristics within the data was developed, which achieved comparable performance to the standard GTWR model for the days with paired PM 2.5 - AOD samples (Cross-validation (CV) R 2  = 0.82) and showed better predictive power for the days without PM 2.5 - AOD pairs (the R 2 increased from 0.24 to 0.46 in CV). Both iGTWR and GTWR (CV R 2  = 0.84) significantly outperformed the daily geographically weighted regression model (CV R 2  = 0.66). Also, the fused 3 km AODs improved data availability and presented more spatial gradients, thereby enhancing model performance compared with the MODIS original 3/10 km AOD product. As a result, ground PM2.5 concentrations at higher resolution were well represented, allowing, e.g., short-term pollution events and long-term PM2.5 trend to be identified, which, in turn, indicated that concerns about air pollution in the BTH region are justified despite its decreasing trend from 2013 to 2015. Copyright © 2018 Elsevier Ltd. All rights reserved.

Validation of the physical and RBE-weighted dose estimator based on PHITS coupled with a microdosimetric kinetic model for proton therapy

PubMed Central

Sato, Tatsuhiko; Kumada, Hiroaki; Koketsu, Junichi; Takei, Hideyuki; Sakurai, Hideyuki; Sakae, Takeji

2018-01-01

Abstract The microdosimetric kinetic model (MKM) is widely used for estimating relative biological effectiveness (RBE)-weighted doses for various radiotherapies because it can determine the surviving fraction of irradiated cells based on only the lineal energy distribution, and it is independent of the radiation type and ion species. However, the applicability of the method to proton therapy has not yet been investigated thoroughly. In this study, we validated the RBE-weighted dose calculated by the MKM in tandem with the Monte Carlo code PHITS for proton therapy by considering the complete simulation geometry of the clinical proton beam line. The physical dose, lineal energy distribution, and RBE-weighted dose for a 155 MeV mono-energetic and spread-out Bragg peak (SOBP) beam of 60 mm width were evaluated. In estimating the physical dose, the calculated depth dose distribution by irradiating the mono-energetic beam using PHITS was consistent with the data measured by a diode detector. A maximum difference of 3.1% in the depth distribution was observed for the SOBP beam. In the RBE-weighted dose validation, the calculated lineal energy distributions generally agreed well with the published measurement data. The calculated and measured RBE-weighted doses were in excellent agreement, except at the Bragg peak region of the mono-energetic beam, where the calculation overestimated the measured data by ~15%. This research has provided a computational microdosimetric approach based on a combination of PHITS and MKM for typical clinical proton beams. The developed RBE-estimator function has potential application in the treatment planning system for various radiotherapies. PMID:29087492

Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

2017-09-11

Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

Breast Histopathological Image Retrieval Based on Latent Dirichlet Allocation.

PubMed

Ma, Yibing; Jiang, Zhiguo; Zhang, Haopeng; Xie, Fengying; Zheng, Yushan; Shi, Huaqiang; Zhao, Yu

2017-07-01

In the field of pathology, whole slide image (WSI) has become the major carrier of visual and diagnostic information. Content-based image retrieval among WSIs can aid the diagnosis of an unknown pathological image by finding its similar regions in WSIs with diagnostic information. However, the huge size and complex content of WSI pose several challenges for retrieval. In this paper, we propose an unsupervised, accurate, and fast retrieval method for a breast histopathological image. Specifically, the method presents a local statistical feature of nuclei for morphology and distribution of nuclei, and employs the Gabor feature to describe the texture information. The latent Dirichlet allocation model is utilized for high-level semantic mining. Locality-sensitive hashing is used to speed up the search. Experiments on a WSI database with more than 8000 images from 15 types of breast histopathology demonstrate that our method achieves about 0.9 retrieval precision as well as promising efficiency. Based on the proposed framework, we are developing a search engine for an online digital slide browsing and retrieval platform, which can be applied in computer-aided diagnosis, pathology education, and WSI archiving and management.

Weight-based stigmatization, psychological distress, & binge eating behavior among obese treatment-seeking adults.

PubMed

Ashmore, Jamile A; Friedman, Kelli E; Reichmann, Simona K; Musante, Gerard J

2008-04-01

To evaluate the associations between weight-based stigmatization, psychological distress, and binge eating behavior in a treatment-seeking obese sample. Ninety-three obese adults completed three questionnaires: 1) Stigmatizing Situations Inventory, 2) Brief Symptoms Inventory, and 3) Binge Eating Questionnaire. Correlational analyses were used to evaluate the association between stigmatizing experiences, psychological distress and binge eating behavior. Stigmatizing experiences predicted both binge eating behavior (R(2)=.20, p<.001) and overall psychological distress (R(2)=.18, p<.001). A substantial amount of the variance in binge eating predicted by weight-based stigmatization was due to the effect of psychological distress. Specifically, of the 20% of the variance in binge eating accounted for by stigmatizing experiences, between 7% and 34% (p<.01) was due to the effects of various indicators of psychological distress. These data suggest that weight-based stigmatization predicts binge eating behavior and that psychological distress associated with stigmatizing experiences may be an important mediating factor.

Web-Based Interventions Alone or Supplemented with Peer-Led Support or Professional Email Counseling for Weight Loss and Weight Maintenance in Women from Rural Communities: Results of a Clinical Trial

PubMed Central

Pullen, Carol H.; Pozehl, Bunny; Eisenhauer, Christine; Boeckner, Linda S.

2017-01-01

Objective. This trial compared the effectiveness of a web-based only (WO) intervention with web-based supplemented by peer-led discussion (WD) or professional email counseling (WE) across 3 phases to achieve weight loss and weight maintenance in women from underserved rural communities. Methods. 301 women (BMI of 28–45 kg/m2) randomly assigned to groups participated in guided weight loss (baseline to 6 months), guided weight loss and maintenance (6 to 18 months), and self-managed weight maintenance (18 to 30 months). Results. Retention was 88.7%, 76.5%, and 71.8% at 6, 18, and 30 months, respectively. Intent-to-treat analyses demonstrated no group differences in change in weight within any phases. At 6 months, observed mean (SD) weight loss was 5.1 (6.0) kg in WO, 4.1 (5.6) kg in WD, and 6.0 (6.3) kg in WE, with 42%, 38%, and 51%, respectively, meeting ≥ 5% weight loss. These proportions dropped by a third after phase 2 with no further change during phase 3. Conclusion. Web-based interventions assisted women from rural communities in achieving 6-month weight loss, with weight regain by half at 30 months. No group differences were potentially due to the robust nature of the web-based intervention. Trial Registration. This trial is registered with ClinicalTrials.gov NCT01307644. PMID:28480078

Weight-based enoxaparin dosing and deep vein thrombosis in hospitalized trauma patients: A double-blind, randomized, pilot study.

PubMed

Kay, Annika Bickford; Majercik, Sarah; Sorensen, Jeffrey; Woller, Scott C; Stevens, Scott M; White, Thomas W; Morris, David S; Baldwin, Margaret; Bledsoe, Joseph R

2018-04-23

Venous thromboembolism is a cause of morbidity and mortality in trauma patients. Chemoprophylaxis with low-molecular-weight heparin at a standardized dose is recommended. Conventional chemoprophylaxis may be inadequate. We hypothesized that a weight-adjusted enoxaparin prophylaxis regimen would reduce the frequency of venous thromboembolism in hospitalized trauma patients and at 90-day follow-up. This prospective, randomized pilot study enrolled adult patients admitted to a level 1 trauma center between July 2013 and January 2015. Subjects were randomized to receive either standard (30 mg subcutaneously every 12 hours) or weight-based (0.5mg/kg subcutaneously every 12 hours) enoxaparin. Surveillance duplex ultrasound for lower extremity deep vein thrombosis was performed on hospital days 1, 3, and 7, and weekly thereafter. The primary outcome was deep vein thrombosis during hospitalization. Secondary outcomes included venous thromboembolism at 90 days and significant bleeding events. Two hundred thirty-four (124 standard, 110 weight-based) subjects were enrolled. There was no difference between standard and weight-based regarding age, body mass index, percentage female gender, injury severity score, or percentage that had surgery. There was a trend toward less in-hospital deep vein thrombosis in weight-based (12 [9.7%] standard vs 4 [3.6%] weight-based, P = .075). At 90 days, there was no difference in venous thromboembolism (12 [9.7%] standard vs 6 [5.5%] weight-based, P =.34). There was 1 bleeding event, which occurred in a standard subject. Weight-based enoxaparin dosing for venous thromboembolism chemoprophylaxis in trauma patients may provide better protection against venous thromboembolism than standard. A definitive study is necessary to determine whether weight-based dosing is superior to standard. Copyright © 2018 Elsevier Inc. All rights reserved.

Are early first trimester weights valid proxies for preconception weight?

USDA-ARS?s Scientific Manuscript database

An accurate estimate of preconception weight is necessary for providing a gestational weight gain range based on the Institute of Medicine’s guidelines; however, an accurate and proximal preconception weight is not available for most women. We examined the validity of first trimester weights for est...

Challenging body weight: evidence from a community-based intervention on weight, behaviour and motivation.

PubMed

Blais, Louise T; Mack, Diane E; Wilson, Philip M; Blanchard, Chris M

2017-08-01

The objective of this study was to examine the effectiveness of a 12 week weight loss intervention within a commercial fitness centre on body weight, moderate to vigorous physical activity (MVPA), dietary intake, and behavioural regulations for exercise and healthy eating. Using a quasi-experimental design, the intervention group received weekly coaching sessions and bi-weekly seminars designed to increase MVPA and improve dietary intake. Outcome variables were assessed at three time points over a six month period. Results showed a significant interaction for body weight (p = .04) and dietary changes (p < .05) following the weight loss challenge but were not maintained across the six month period. Changes in behavioural regulations favoured the intervention condition. Results imply that a 12 week weight loss challenge within a commercial fitness centre may be effective at prompting short-term weight loss and support the internalization of behavioural regulations specific to healthy eating and exercise.

Weight loss and lipid changes with low-energy diets: comparator study of milk-based versus soy-based liquid meal replacement interventions.

PubMed

Anderson, James W; Hoie, Lars H

2005-06-01

Soy protein intake has favorable effects on body weight and fat distribution in experimental animals but these effects have not been demonstrated in humans. To compare effects of soy- vs. milk-based meal replacements (MR) we assessed weight loss and serum lipoproteins changes for obese subjects who consumed low-energy diets (LED) including either milk-based or soy-based MR. Overweight or obese women and men (body mass indices 27-40 kg/m(2)) were randomly assigned to LED providing 1200 kcal/day, with consumption of five soy-based or two milk-based liquid MR for a 12-week weight loss trial. Serum lipoprotein measurements were obtained at baseline, 6 and 12 weeks. For soy and milk MR groups, subject numbers were, respectively, 51 and 39 randomized and 30 and 22 completers. MR use averaged: soy, 3.7/day; and milk, 1.9/day. Weight losses for completers at 12 weeks were: soy MR, 9.0% of initial body weight (95% confidence intervals, 7.3-10.6%); and milk MR, 7.9% (5.8-8.8%) with no significant differences. Reductions from baseline in serum cholesterol and LDL-cholesterol values, respectively, at six weeks were significantly greater (P < 0.015) with soy MR (15.2% and 17.4%) than with milk MR (7.9% and 7.7%). Soy MR use was associated with significant reductions in serum triglycerides at 6 and 12 weeks while milk MR use was not. Soy MR use, as part of a low-energy diet, was associated with slightly but not significantly greater weight loss over a 12-week period than milk MR use. These observations confirm previous studies documenting the effectiveness of MR use for weight loss.

Improving anti-bullying laws and policies to protect youth from weight-based victimization: parental support for action.

PubMed

Puhl, R M; Suh, Y; Li, X

2017-04-01

Weight-based bullying is a prevalent problem among youth with overweight and obesity, but remains neglected in existing policy-level strategies to address youth bullying. Parental support is an influential catalyst motivating political will for policy decisions affecting youth, but has received limited research attention. To assess levels of, and predictors of, parental support for school-based policies and state/federal legal measures to address weight-based bullying in 2014 and 2015. Identical online questionnaires were completed by two independent national samples of parents in 2014 and 2015 (N = 1804). Parental support for all policy actions was high (at least 81%) and significantly increased from 2014 to 2015 for legal measures that would a) require state anti-bullying laws to add protections against weight-based bullying, and b) enact a federal anti-bullying law that includes weight-based bullying. These findings can inform policy discourse about remedies for youth bullying, and suggest that parental support for improved legal protections against weight-based bullying is present, consistent, and strong. © 2016 World Obesity Federation.

Combating weight-based bullying in schools: is there public support for the use of litigation?

PubMed

Puhl, Rebecca; Luedicke, Joerg; King, Kelly M

2015-06-01

Bullying litigation is an emerging area of law that has increased in response to serious cases of bullying at school. Weight-based bullying is prevalent at school, but no research has examined the use of litigation to address this problem. We assessed public support for litigation approaches to address weight-based bullying at school, and whether support for litigation varies according to the reason why a student is bullied. A national sample of 994 adults (49% parents) completed an online questionnaire assessing their support for litigation approaches in response to hypothetical incidents of youth bullying. As many as two thirds of participants supported litigation against schools for failing to intervene and protect students from weight-based bullying. Litigation remedies received slightly higher support in response to bullying due to race or sexual orientation compared to body weight. Participants favored litigation approaches that target schools for inadequate intervention or a bully's parents on behalf of their child's actions. Our study offers novel findings about public and parental views of litigation as a potential approach to address weight-based (and other forms of) bullying, and introduces considerations about the potential role of litigation as part of broader remedies to address youth bullying. © 2015, American School Health Association.

Weight-based Teasing and Bullying in Children: How Parents Can Help

MedlinePlus

... Size Email Print Share Weight-based Teasing and Bullying in Children: How Parents Can Help Page Content ... Parents & Children Should Respond to This Type of Bullying Emphasize that no one deserves to be teased . ...

Optimising product advice based on age when design criteria are based on weight: child restraints in vehicles.

PubMed

Anderson, R W G; Hutchinson, T P

2009-03-01

The motivation for this paper is the high rate of inappropriate child restraint selection in cars that is apparent in published surveys of child restraint use and how the public health messages promoting child restraints might respond. Advice has increasingly been given solely according to the child's weight, while many parents do not know the weight of their children. A common objection to promoting restraint use based on the age of the child is the imprecision of such advice, given the variation in the size of children, but the magnitude of the misclassification such advice would produce has never been estimated. This paper presents a method for estimating the misclassification of children by weight, when advice is posed in terms of age, and applies it to detailed child growth data published by the Centers for Disease Control and Prevention. In Australia, guidelines instructing all parents to promote their children from an infant restraint to a forward-facing child seat at 6 months, and then to a belt-positioning booster at 4 years, would mean that 5% of all children under the age of 6 years would be using a restraint not suited to their weight. Coordination of aged-based advice and the weight ranges chosen for the Australian Standard on child restraints could reduce this level of misclassification to less than 1%. The general method developed may also be applied to other aspects of restraint design that are more directly relevant to good restraint fit.

a Weighted Local-World Evolving Network Model Based on the Edge Weights Preferential Selection

NASA Astrophysics Data System (ADS)

Li, Ping; Zhao, Qingzhen; Wang, Haitang

2013-05-01

In this paper, we use the edge weights preferential attachment mechanism to build a new local-world evolutionary model for weighted networks. It is different from previous papers that the local-world of our model consists of edges instead of nodes. Each time step, we connect a new node to two existing nodes in the local-world through the edge weights preferential selection. Theoretical analysis and numerical simulations show that the scale of the local-world affect on the weight distribution, the strength distribution and the degree distribution. We give the simulations about the clustering coefficient and the dynamics of infectious diseases spreading. The weight dynamics of our network model can portray the structure of realistic networks such as neural network of the nematode C. elegans and Online Social Network.

A Multi-level Fuzzy Evaluation Method for Smart Distribution Network Based on Entropy Weight

NASA Astrophysics Data System (ADS)

Li, Jianfang; Song, Xiaohui; Gao, Fei; Zhang, Yu

2017-05-01

Smart distribution network is considered as the future trend of distribution network. In order to comprehensive evaluate smart distribution construction level and give guidance to the practice of smart distribution construction, a multi-level fuzzy evaluation method based on entropy weight is proposed. Firstly, focus on both the conventional characteristics of distribution network and new characteristics of smart distribution network such as self-healing and interaction, a multi-level evaluation index system which contains power supply capability, power quality, economy, reliability and interaction is established. Then, a combination weighting method based on Delphi method and entropy weight method is put forward, which take into account not only the importance of the evaluation index in the experts’ subjective view, but also the objective and different information from the index values. Thirdly, a multi-level evaluation method based on fuzzy theory is put forward. Lastly, an example is conducted based on the statistical data of some cites’ distribution network and the evaluation method is proved effective and rational.

Changes of dietary patterns during participation in a web-based weight-reduction programme.

PubMed

Luger, Eva; Aspalter, Rosa; Luger, Maria; Longin, Rita; Rieder, Anita; Dorner, Thomas Ernst

2016-05-01

To examine the weight-loss success associated with distinct dietary patterns and to determine changes of these dietary patterns during participation in a web-based weight-reduction programme. Factor analysis was used to identify the dietary patterns of twenty-two food groups that were administered in 14 d dietary protocols at baseline and after 3 months. Successful weight loss (≥5% of initial weight) and BMI were calculated. Logistic regression analyses were used to assess the rates of weight-loss success from each dietary pattern and changing or remaining in the initial dietary pattern. A generalised linear mixed model was used to estimate the effects of changing or staying in a dietary pattern on change in BMI. Adults (n 1635) aged 18-81 years. Users of a web-based weight-reduction programme (2006-2012). Participants who aligned to a healthful dietary pattern at baseline (OR=1·8; 95% CI 1·5, 2·3) and after 3 months (OR=1·5; 95% CI 1·2, 1·9) had a greater chance of successfully losing weight. After adjusting for age, sex, initial dietary pattern and BMI, participants who started with or changed to the healthful dietary pattern had a greater chance of being successful (OR=1·4; 95% CI 1·1, 1·7) and a higher BMI reduction of 0·30 (95% CI 0·2, 0·5) kg/m(2) compared with those who started with or changed to the energy-dense or high-carbohydrate dietary pattern. A favourable healthful dietary pattern at the beginning and after 3 months was positively associated with anthropometry. However, successful weight loss was feasible in each dietary pattern.

Efficacy of a Pilot Internet-Based Weight Management Program (H.E.A.L.T.H.) and Longitudinal Physical Fitness Data in Army Reserve Soldiers

PubMed Central

Newton, Robert L; Han, Hongmei; Stewart, Tiffany M; Ryan, Donna H; Williamson, Donald A

2011-01-01

Background The primary aims of this article are to describe the utilization of an Internet-based weight management Web site [Healthy Eating, Activity, and Lifestyle Training Headquarters (H.E.A.L.T.H.)] over a 12–27 month period and to describe concurrent weight and fitness changes in Army Reserve soldiers. Methods The H.E.A.L.T.H. Web site was marketed to Army Reserve soldiers via a Web site promotion program for 27 months (phase I) and its continued usage was observed over a subsequent 12-month period (phase II). Web site usage was obtained from the H.E.A.L.T.H. Web site. Weight and fitness data were extracted from the Regional Level Application Software (RLAS). Results A total of 1499 Army Reserve soldiers registered on the H.E.A.L.T.H. Web site. There were 118 soldiers who returned to the H.E.A.L.T.H. Web site more than once. Registration rate reduced significantly following the removal of the Web site promotion program. During phase I, 778 Army Reserve soldiers had longitudinal weight and fitness data in RLAS. Men exceeding the screening table weight gained less weight compared with men below it (p < .007). Percentage change in body weight was inversely associated with change in fitness scores. Conclusions The Web site promotion program resulted in 52% of available Army Reserve soldiers registering onto the H.E.A.L.T.H. Web site, and 7.9% used the Web site more than once. The H.E.A.L.T.H. Web site may be a viable population-based weight and fitness management tool for soldier use. PMID:22027327

Safe semi-supervised learning based on weighted likelihood.

PubMed

Kawakita, Masanori; Takeuchi, Jun'ichi

2014-05-01

We are interested in developing a safe semi-supervised learning that works in any situation. Semi-supervised learning postulates that n(') unlabeled data are available in addition to n labeled data. However, almost all of the previous semi-supervised methods require additional assumptions (not only unlabeled data) to make improvements on supervised learning. If such assumptions are not met, then the methods possibly perform worse than supervised learning. Sokolovska, Cappé, and Yvon (2008) proposed a semi-supervised method based on a weighted likelihood approach. They proved that this method asymptotically never performs worse than supervised learning (i.e., it is safe) without any assumption. Their method is attractive because it is easy to implement and is potentially general. Moreover, it is deeply related to a certain statistical paradox. However, the method of Sokolovska et al. (2008) assumes a very limited situation, i.e., classification, discrete covariates, n(')→∞ and a maximum likelihood estimator. In this paper, we extend their method by modifying the weight. We prove that our proposal is safe in a significantly wide range of situations as long as n≤n('). Further, we give a geometrical interpretation of the proof of safety through the relationship with the above-mentioned statistical paradox. Finally, we show that the above proposal is asymptotically safe even when n(')weight. Numerical experiments illustrate the performance of these methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

Combating Weight-Based Bullying in Schools: Is There Public Support for the Use of Litigation?

ERIC Educational Resources Information Center

Puhl, Rebecca; Luedicke, Joerg; King, Kelly M.

2015-01-01

Background: Bullying litigation is an emerging area of law that has increased in response to serious cases of bullying at school. Weight-based bullying is prevalent at school, but no research has examined the use of litigation to address this problem. We assessed public support for litigation approaches to address weight-based bullying at school,…

Weighted south-wide average pulpwood prices

Treesearch

James E. Granskog; Kevin D. Growther

1991-01-01

Weighted average prices provide a more accurate representation of regional pulpwood price trends when production volumes valy widely by state. Unweighted South-wide average delivered prices for pulpwood, as reported by Timber Mart-South, were compared to average annual prices weighted by each state's pulpwood production from 1977 to 1986. Weighted average prices...

Normal gray and white matter volume after weight restoration in adolescents with anorexia nervosa.

PubMed

Lázaro, Luisa; Andrés, Susana; Calvo, Anna; Cullell, Clàudia; Moreno, Elena; Plana, M Teresa; Falcón, Carles; Bargalló, Núria; Castro-Fornieles, Josefina

2013-12-01

The aim of this study was to determine whether treated, weight-stabilized adolescents with anorexia nervosa (AN) present brain volume differences in comparison with healthy controls. Thirty-five adolescents with weight-recovered AN and 17 healthy controls were assessed by means of psychopathology scales and magnetic resonance imaging. Axial three-dimensional T1-weighted images were obtained in a 1.5 Tesla scanner and analyzed using optimized voxel-based morphometry (VBM). There were no significant differences between controls and weight-stabilized AN patients with regard to global volumes of either gray or white brain matter, or in the regional VBM study. Differences were not significant between patients with psychopharmacological treatment and without, between those with amenorrhea and without, as well as between patients with restrictive versus purgative AN. The present findings reveal no global or regional gray or white matter abnormalities in this sample of adolescents following weight restoration. Copyright © 2013 Wiley Periodicals, Inc.

Dissonance-Based Eating Disorder Prevention Program Reduces Reward Region Response to Thin Models; How Actions Shape Valuation

PubMed Central

Stice, Eric; Yokum, Sonja; Waters, Allison

2015-01-01

Research supports the effectiveness of a dissonance-based eating disorder prevention program wherein high-risk young women with body dissatisfaction critique the thin ideal, which reduces pursuit of this ideal, and the theory that dissonance induction contributes to these effects. Based on evidence that dissonance produces attitudinal change by altering neural representation of valuation, we tested whether completing the Body Project would reduce response of brain regions implicated in reward valuation to thin models. Young women with body dissatisfaction were randomized to this intervention or an educational control condition, completing assessments and fMRI scans while viewing images of thin versus average-weight female models at pre and post. Whole brain analyses indicated that, compared to controls, Body Project participants showed greater reductions in caudate response to images of thin versus average-weight models, though participants in the two conditions showed pretest differences in responsivity of other brain regions that might have contributed to this effect. Greater pre-post reductions in caudate and putamen response to thin models correlated with greater reductions in body dissatisfaction. The finding that the Body Project reduces caudate response to thin models provides novel preliminary evidence that this intervention reduces valuation of media images thought to contribute to body dissatisfaction and eating disorders, providing support for the intervention theory by documenting that this intervention alters an objective biological outcome. PMID:26641854

Dissonance-Based Eating Disorder Prevention Program Reduces Reward Region Response to Thin Models; How Actions Shape Valuation.

PubMed

Stice, Eric; Yokum, Sonja; Waters, Allison

2015-01-01

Research supports the effectiveness of a dissonance-based eating disorder prevention program wherein high-risk young women with body dissatisfaction critique the thin ideal, which reduces pursuit of this ideal, and the theory that dissonance induction contributes to these effects. Based on evidence that dissonance produces attitudinal change by altering neural representation of valuation, we tested whether completing the Body Project would reduce response of brain regions implicated in reward valuation to thin models. Young women with body dissatisfaction were randomized to this intervention or an educational control condition, completing assessments and fMRI scans while viewing images of thin versus average-weight female models at pre and post. Whole brain analyses indicated that, compared to controls, Body Project participants showed greater reductions in caudate response to images of thin versus average-weight models, though participants in the two conditions showed pretest differences in responsivity of other brain regions that might have contributed to this effect. Greater pre-post reductions in caudate and putamen response to thin models correlated with greater reductions in body dissatisfaction. The finding that the Body Project reduces caudate response to thin models provides novel preliminary evidence that this intervention reduces valuation of media images thought to contribute to body dissatisfaction and eating disorders, providing support for the intervention theory by documenting that this intervention alters an objective biological outcome.

Texture analysis of intermediate-advanced hepatocellular carcinoma: prognosis and patients' selection of transcatheter arterial chemoembolization and sorafenib

PubMed Central

Fu, Sirui; Chen, Shuting; Liang, Changhong; Liu, Zaiyi; Zhu, Yanjie; Li, Yong; Lu, Ligong

2017-01-01

Transcatheter arterial chemoembolization (TACE) and sorafenib combination treatment for unselected hepatocellular carcinoma (HCC) is controversial. We explored the potential of texture analysis for appropriate patient selection. There were 261 HCCs included (TACE group: n = 197; TACE plus sorafenib (TACE+Sorafenib) group n = 64). We applied a Gabor filter and wavelet transform with 3 band-width responses (filter 0, 1.0, and 1.5) to portal-phase computed tomography (CT) images of the TACE group. Twenty-one textural parameters per filter were extracted from the region of interests delineated around tumor outline. After testing survival correlations, the TACE group was subdivided according to parameter thresholds in receiver operating characteristic curves and compared to TACE+Sorafenib group survival. The Gabor-1-90 (filter 0) was most significantly correlated with TTP. The TACE group was accordingly divided into the TACE-1 (Gabor-1-90 ≤ 3.6190) and TACE-2 (Gabor-1-90 > 3.6190) subgroups; TTP was similar in the TACE-1 subgroup and TACE+Sorafenib group, but shorter in the TACE-2 subgroup. Only wavelet-3-D (filter 1.0) correlated with overall survival (OS), and was used for subgrouping. The TACE-5 (wavelet-3-D ≤ 12.2620) subgroup and the TACE+Sorafenib group showed similar OS, while the TACE-6 (wavelet-3-D > 12.2620) subgroup had shorter OS. Gabor-1-90 and wavelet-3-D were consistent. In dependent of tumor number or size, CT textural parameters are correlated with TTP and OS. Patients with lower Gabor-1-90 (filter 0) and wavelet-3-D (filter 1.0) should be treated with TACE and sorafenib. Texture analysis holds promise for appropriate selection of HCCs for this combination therapy. PMID:27911268

Recovery of a spectrum based on a compressive-sensing algorithm with weighted principal component analysis

NASA Astrophysics Data System (ADS)

Dafu, Shen; Leihong, Zhang; Dong, Liang; Bei, Li; Yi, Kang

2017-07-01

The purpose of this study is to improve the reconstruction precision and better copy the color of spectral image surfaces. A new spectral reflectance reconstruction algorithm based on an iterative threshold combined with weighted principal component space is presented in this paper, and the principal component with weighted visual features is the sparse basis. Different numbers of color cards are selected as the training samples, a multispectral image is the testing sample, and the color differences in the reconstructions are compared. The channel response value is obtained by a Mega Vision high-accuracy, multi-channel imaging system. The results show that spectral reconstruction based on weighted principal component space is superior in performance to that based on traditional principal component space. Therefore, the color difference obtained using the compressive-sensing algorithm with weighted principal component analysis is less than that obtained using the algorithm with traditional principal component analysis, and better reconstructed color consistency with human eye vision is achieved.

An 8-week web-based weight loss challenge with celebrity endorsement and enhanced social support: observational study.

PubMed

Hutchesson, Melinda J; Collins, Clare E; Morgan, Philip J; Callister, Robin

2013-07-04

Initial engagement and weight loss within Web-based weight loss programs may predict long-term success. The integration of persuasive Web-based features may boost engagement and therefore weight loss. To determine whether an 8-week challenge within a commercial Web-based weight loss program influenced weight loss, website use, and attrition in the short term, when compared to the standard program. De-identified data for participants (mean age 36.7±10.3 years; 86% female) who enrolled in the Biggest Loser Club (BLC) (n=952) and the BLC's Shannan Ponton Fast Track Challenge (SC) for 8 weeks (n=381) were compared. The BLC program used standard evidence-based website features, with individualized calorie and exercise targets to facilitate a weight loss of 0.5-1 kg per week (-500kcal/day less than estimated energy expenditure). SC used the same website features but in addition promoted greater initial weight loss using a 1200 kcal/day energy intake target and physical activity energy expenditure of 600 kcal/day. SC used persuasive features to facilitate greater user engagement, including offering additional opportunities for social support (eg, webinar meetings with a celebrity personal trainer and social networking) endorsed by a celebrity personal trainer. Self-reported weekly weight records were used to determine weight change after 8 weeks. A primary analysis was undertaken using a generalized linear mixed model (GLMM) with all available weight records for all participants included. Dropout (participants who cancelled their subscription) and nonusage (participants who stopped using the Web-based features) attrition rates at 8 weeks were calculated. The number of participants who accessed each website feature and the total number of days each feature was used were calculated. The difference between attrition rates and website use for the two programs were tested using chi-square and Wilcoxon Rank Sum tests, respectively. Using GLMM, including weight data for all

Hierarchical clustering of EMD based interest points for road sign detection

NASA Astrophysics Data System (ADS)

Khan, Jesmin; Bhuiyan, Sharif; Adhami, Reza

2014-04-01

This paper presents an automatic road traffic signs detection and recognition system based on hierarchical clustering of interest points and joint transform correlation. The proposed algorithm consists of the three following stages: interest points detection, clustering of those points and similarity search. At the first stage, good discriminative, rotation and scale invariant interest points are selected from the image edges based on the 1-D empirical mode decomposition (EMD). We propose a two-step unsupervised clustering technique, which is adaptive and based on two criterion. In this context, the detected points are initially clustered based on the stable local features related to the brightness and color, which are extracted using Gabor filter. Then points belonging to each partition are reclustered depending on the dispersion of the points in the initial cluster using position feature. This two-step hierarchical clustering yields the possible candidate road signs or the region of interests (ROIs). Finally, a fringe-adjusted joint transform correlation (JTC) technique is used for matching the unknown signs with the existing known reference road signs stored in the database. The presented framework provides a novel way to detect a road sign from the natural scenes and the results demonstrate the efficacy of the proposed technique, which yields a very low false hit rate.

Aberrant Global and Regional Topological Organization of the Fractional Anisotropy-weighted Brain Structural Networks in Major Depressive Disorder

PubMed Central

Chen, Jian-Huai; Yao, Zhi-Jian; Qin, Jiao-Long; Yan, Rui; Hua, Ling-Ling; Lu, Qing

2016-01-01

Background: Most previous neuroimaging studies have focused on the structural and functional abnormalities of local brain regions in major depressive disorder (MDD). Moreover, the exactly topological organization of networks underlying MDD remains unclear. This study examined the aberrant global and regional topological patterns of the brain white matter networks in MDD patients. Methods: The diffusion tensor imaging data were obtained from 27 patients with MDD and 40 healthy controls. The brain fractional anisotropy-weighted structural networks were constructed, and the global network and regional nodal metrics of the networks were explored by the complex network theory. Results: Compared with the healthy controls, the brain structural network of MDD patients showed an intact small-world topology, but significantly abnormal global network topological organization and regional nodal characteristic of the network in MDD were found. Our findings also indicated that the brain structural networks in MDD patients become a less strongly integrated network with a reduced central role of some key brain regions. Conclusions: All these resulted in a less optimal topological organization of networks underlying MDD patients, including an impaired capability of local information processing, reduced centrality of some brain regions and limited capacity to integrate information across different regions. Thus, these global network and regional node-level aberrations might contribute to understanding the pathogenesis of MDD from the view of the brain network. PMID:26960371

An economic analysis of traditional and technology-based approaches to weight loss.

PubMed

Archer, Edward; Groessl, Erik J; Sui, Xuemei; McClain, Amanda C; Wilcox, Sara; Hand, Gregory A; Meriwether, Rebecca A; Blair, Steven N

2012-08-01

The financial burden and human losses associated with noncommunicable diseases necessitate cost-effective and efficacious interventions. An economic analysis of the Lifestyle Education for Activity and Nutrition (LEAN) Study; an RCT that examined the efficacy of traditional and technology-based approaches to weight loss. Economic analyses from an organizational perspective were conducted for four approaches: standard care control (SC); group weight-loss education (GWL); a multisensor armband (SWA); and the armband in combination with group weight-loss education (GWL+SWA). Data were collected in 2008-2009. Weight loss was the primary outcome. Total costs, costs per participant, costs per kilogram lost, and incremental cost-effectiveness ratios (ICERs) were calculated in 2010-2011. All costs are the actual expenses (i.e., staff time and materials) incurred by the LEAN study (except where noted) and reported in 2010 U.S. dollars. In the sample population of 197 sedentary, overweight, and obese adults (mean [±SD] age=46.9 ± 0.8 years, BMI=33.3 ± 5.2, weight=92.8 ± 18.4 kg), the GWL+SWA was the most expensive intervention in costs/participant ($365/partic) while yielding the greatest weight loss/partic (6.59 kg). The GWL was next in cost/partic ($240), but the SWA was less expensive in cost/partic ($183) and more efficacious (3.55 vs 1.86 kg/partic). The SC did not achieve significant weight loss. The SWA was the most cost effective ($51/partic/kg lost), followed by the GWL+SWA ($55) and GWL alone ($129). The ICER suggests that for each additional kilogram lost, the GWL+SWA cost $60 more than the SWA alone. The SWA was the most cost-effective intervention ($51/partic/kg lost). The addition of the GWL increased the efficacy of the SWA intervention but increased costs by $60/partic for each additional kilogram lost. The technology-based approaches were more cost effective and efficacious than traditional approaches in promoting weight loss via lifestyle changes in

Participant experiences of two successful habit-based weight-loss interventions in Australia: a qualitative study

PubMed Central

2018-01-01

Objectives Habit-based weight-loss interventions have shown clinically important weight loss and weight-loss maintenance. Understanding why habit-based interventions work is therefore of great value, but there is little qualitative evidence about the experiences of participants in such programmes. We explored the perspectives of individuals who completed two habit-based weight-management programmes, Ten Top Tips and Do Something Different. Design One-on-one, face-to-face, semistructured interviews were conducted and analysed thematically. Setting Participants from the community were interviewed at Bond University, Australia. Participants Using a maximum variation design, we recruited 15 participants (eight men, seven women) aged 39–69 years (mean 53.3 years, SD 10.3) with a range of education levels (no high school to university degree) and percentage weight change on the programmes (+4.0% to −10.4%). Main outcome measures (1) The general experience of participants who completed the Ten Top Tips or Do Something Different intervention, (2) whether and how the interventions affected the participants’ lifestyle postintervention, and (3) participants’ views regarding the acceptability and practical application of Ten Top Tips and Do Something Different. Results Participants reported positive experiences of the two programmes, both during and after the interventions. Participants particularly enjoyed the novelty of the interventions as they shifted focus from diet and exercise, to practical everyday habit changes. They also reported indirect health benefits such as increased energy levels, increased confidence and improved self-awareness. Accountability throughout the programmes and convenience of the interventions were identified as key themes and facilitators for weight-loss success. Conclusions This study offers insight into how and why habit-based interventions might work. Overall, Ten Top Tips and Do Something Different are practical and convenient to

Family Food Providers’ Perceptions of the Causes of Obesity and Effectiveness of Weight Control Strategies in Five Countries in the Asia Pacific Region: A Cross-Sectional Survey

PubMed Central

Worsley, Anthony; Wang, Wei; Sarmugam, Rani; Pham, Quynh; Februhartanty, Judhiastuty; Ridley, Stacey

2017-01-01

The rise of the middle classes in developing countries and the associated epidemiological transition raises the importance of assessing this population group’s awareness of the causes of obesity and effective weight control strategies in order to develop effective health promotion strategies. The study aimed to examine the perceptions of the causes of obesity and weight control strategies held by middle class household food providers in Melbourne, Singapore, Shanghai, Indonesia and Vietnam. An online survey was conducted in late 2013, early 2014 among 3945 respondents. Information about body weight concerns, perceived causes of obesity, effectiveness of weight control methods, demographics, self-reported height and weight, and personal values was elicited. Confirmatory factor analyses (CFA) derived nine reliable factors which were used in structural equation modelling (SEM). Two thirds of respondents were trying to change their body weight, of them, 71% were trying to lose weight. The CFA and SEM showed that demographics, region of residence, personal values and perceptions of the causes of obesity (Unhealthy food behaviours, influences Beyond personal control and Environmental influences) had direct and indirect associations with three weight control methods factors, named: Healthy habits, Eat less, sit less, and Dieting. Middle class food providers in the study regions share public health views of obesity causation and personal weight control. These findings could inform public health and food policies, and the design of public health interventions and communications. Further research is required among lower socio economic status (SES) populations. PMID:28106781

Brain structural correlates of reward sensitivity and impulsivity in adolescents with normal and excess weight.

PubMed

Moreno-López, Laura; Soriano-Mas, Carles; Delgado-Rico, Elena; Rio-Valle, Jacqueline S; Verdejo-García, Antonio

2012-01-01

Neuroscience evidence suggests that adolescent obesity is linked to brain dysfunctions associated with enhanced reward and somatosensory processing and reduced impulse control during food processing. Comparatively less is known about the role of more stable brain structural measures and their link to personality traits and neuropsychological factors on the presentation of adolescent obesity. Here we aimed to investigate regional brain anatomy in adolescents with excess weight vs. lean controls. We also aimed to contrast the associations between brain structure and personality and cognitive measures in both groups. Fifty-two adolescents (16 with normal weight and 36 with excess weight) were scanned using magnetic resonance imaging and completed the Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ), the UPPS-P scale, and the Stroop task. Voxel-based morphometry (VBM) was used to assess possible between-group differences in regional gray matter (GM) and to measure the putative differences in the way reward and punishment sensitivity, impulsivity and inhibitory control relate to regional GM volumes, which were analyzed using both region of interest (ROI) and whole brain analyses. The ROIs included areas involved in reward/somatosensory processing (striatum, somatosensory cortices) and motivation/impulse control (hippocampus, prefrontal cortex). Excess weight adolescents showed increased GM volume in the right hippocampus. Voxel-wise volumes of the second somatosensory cortex (SII) were correlated with reward sensitivity and positive urgency in lean controls, but this association was missed in excess weight adolescents. Moreover, Stroop performance correlated with dorsolateral prefrontal cortex volumes in controls but not in excess weight adolescents. Adolescents with excess weight have structural abnormalities in brain regions associated with somatosensory processing and motivation.

A Divergence Median-based Geometric Detector with A Weighted Averaging Filter

NASA Astrophysics Data System (ADS)

Hua, Xiaoqiang; Cheng, Yongqiang; Li, Yubo; Wang, Hongqiang; Qin, Yuliang

2018-01-01

To overcome the performance degradation of the classical fast Fourier transform (FFT)-based constant false alarm rate detector with the limited sample data, a divergence median-based geometric detector on the Riemannian manifold of Heimitian positive definite matrices is proposed in this paper. In particular, an autocorrelation matrix is used to model the correlation of sample data. This method of the modeling can avoid the poor Doppler resolution as well as the energy spread of the Doppler filter banks result from the FFT. Moreover, a weighted averaging filter, conceived from the philosophy of the bilateral filtering in image denoising, is proposed and combined within the geometric detection framework. As the weighted averaging filter acts as the clutter suppression, the performance of the geometric detector is improved. Numerical experiments are given to validate the effectiveness of our proposed method.

Weighted compactness function based label propagation algorithm for community detection

NASA Astrophysics Data System (ADS)

Zhang, Weitong; Zhang, Rui; Shang, Ronghua; Jiao, Licheng

2018-02-01

Community detection in complex networks, is to detect the community structure with the internal structure relatively compact and the external structure relatively sparse, according to the topological relationship among nodes in the network. In this paper, we propose a compactness function which combines the weight of nodes, and use it as the objective function to carry out the node label propagation. Firstly, according to the node degree, we find the sets of core nodes which have great influence on the network. The more the connections between the core nodes and the other nodes are, the larger the amount of the information these kernel nodes receive and transform. Then, according to the similarity of the nodes between the core nodes sets and the nodes degree, we assign weights to the nodes in the network. So the label of the nodes with great influence will be the priority in the label propagation process, which effectively improves the accuracy of the label propagation. The compactness function between nodes and communities in this paper is based on the nodes influence. It combines the connections between nodes and communities with the degree of the node belongs to its neighbor communities based on calculating the node weight. The function effectively uses the information of nodes and connections in the network. The experimental results show that the proposed algorithm can achieve good results in the artificial network and large-scale real networks compared with the 8 contrast algorithms.

Weight- and race-based bullying: health associations among urban adolescents.

PubMed

Rosenthal, Lisa; Earnshaw, Valerie A; Carroll-Scott, Amy; Henderson, Kathryn E; Peters, Susan M; McCaslin, Catherine; Ickovics, Jeannette R

2015-04-01

Stigma-based bullying is associated with negative mental and physical health outcomes. In a longitudinal study, surveys and physical assessments were conducted with mostly Black and Latino, socioeconomically disadvantaged, urban students. As hypothesized, greater weight- and race-based bullying each was significantly indirectly associated with increased blood pressure and body mass index, as well as decreased overall self-rated health across 2 years, through the mechanism of more negative emotional symptoms. Results support important avenues for future research on mechanisms and longitudinal associations of stigma-based bullying with health. Interventions are needed to reduce stigma-based bullying and buffer adolescents from adverse health effects. © The Author(s) 2013.

Weight- and race-based bullying: Health associations among urban adolescents

PubMed Central

Rosenthal, Lisa; Earnshaw, Valerie A; Carroll-Scott, Amy; Henderson, Kathryn E; Peters, Susan M; McCaslin, Catherine; Ickovics, Jeannette R

2014-01-01

Stigma-based bullying is associated with negative mental and physical health outcomes. In a longitudinal study, surveys and physical assessments were conducted with mostly Black and Latino, socioeconomically disadvantaged, urban students. As hypothesized, greater weight- and race-based bullying each was significantly indirectly associated with increased blood pressure and body mass index, as well as decreased overall self-rated health across 2 years, through the mechanism of more negative emotional symptoms. Results support important avenues for future research on mechanisms and longitudinal associations of stigma-based bullying with health. Interventions are needed to reduce stigma-based bullying and buffer adolescents from adverse health effects. PMID:24155192

Light-weight reference-based compression of FASTQ data.

PubMed

Zhang, Yongpeng; Li, Linsen; Yang, Yanli; Yang, Xiao; He, Shan; Zhu, Zexuan

2015-06-09

The exponential growth of next generation sequencing (NGS) data has posed big challenges to data storage, management and archive. Data compression is one of the effective solutions, where reference-based compression strategies can typically achieve superior compression ratios compared to the ones not relying on any reference. This paper presents a lossless light-weight reference-based compression algorithm namely LW-FQZip to compress FASTQ data. The three components of any given input, i.e., metadata, short reads and quality score strings, are first parsed into three data streams in which the redundancy information are identified and eliminated independently. Particularly, well-designed incremental and run-length-limited encoding schemes are utilized to compress the metadata and quality score streams, respectively. To handle the short reads, LW-FQZip uses a novel light-weight mapping model to fast map them against external reference sequence(s) and produce concise alignment results for storage. The three processed data streams are then packed together with some general purpose compression algorithms like LZMA. LW-FQZip was evaluated on eight real-world NGS data sets and achieved compression ratios in the range of 0.111-0.201. This is comparable or superior to other state-of-the-art lossless NGS data compression algorithms. LW-FQZip is a program that enables efficient lossless FASTQ data compression. It contributes to the state of art applications for NGS data storage and transmission. LW-FQZip is freely available online at: http://csse.szu.edu.cn/staff/zhuzx/LWFQZip.

Healthy habits: efficacy of simple advice on weight control based on a habit-formation model.

PubMed

Lally, P; Chipperfield, A; Wardle, J

2008-04-01

To evaluate the efficacy of a simple weight loss intervention, based on principles of habit formation. An exploratory trial in which overweight and obese adults were randomized either to a habit-based intervention condition (with two subgroups given weekly vs monthly weighing; n=33, n=36) or to a waiting-list control condition (n=35) over 8 weeks. Intervention participants were followed up for 8 months. A total of 104 adults (35 men, 69 women) with an average BMI of 30.9 kg m(-2). Intervention participants were given a leaflet containing advice on habit formation and simple recommendations for eating and activity behaviours promoting negative energy balance, together with a self-monitoring checklist. Weight change over 8 weeks in the intervention condition compared with the control condition and weight loss maintenance over 32 weeks in the intervention condition. At 8 weeks, people in the intervention condition had lost significantly more weight (mean=2.0 kg) than those in the control condition (0.4 kg), with no difference between weekly and monthly weighing subgroups. At 32 weeks, those who remained in the study had lost an average of 3.8 kg, with 54% losing 5% or more of their body weight. An intention-to-treat analysis (based on last-observation-carried-forward) reduced this to 2.6 kg, with 26% achieving a 5% weight loss. This easily disseminable, low-cost, simple intervention produced clinically significant weight loss. In limited resource settings it has potential as a tool for obesity management.

Self-similarity analysis of eubacteria genome based on weighted graph.

PubMed

Qi, Zhao-Hui; Li, Ling; Zhang, Zhi-Meng; Qi, Xiao-Qin

2011-07-07

We introduce a weighted graph model to investigate the self-similarity characteristics of eubacteria genomes. The regular treating in similarity comparison about genome is to discover the evolution distance among different genomes. Few people focus their attention on the overall statistical characteristics of each gene compared with other genes in the same genome. In our model, each genome is attributed to a weighted graph, whose topology describes the similarity relationship among genes in the same genome. Based on the related weighted graph theory, we extract some quantified statistical variables from the topology, and give the distribution of some variables derived from the largest social structure in the topology. The 23 eubacteria recently studied by Sorimachi and Okayasu are markedly classified into two different groups by their double logarithmic point-plots describing the similarity relationship among genes of the largest social structure in genome. The results show that the proposed model may provide us with some new sights to understand the structures and evolution patterns determined from the complete genomes. Copyright © 2011 Elsevier Ltd. All rights reserved.

Mediators of weight loss in a family-based intervention presented over the internet.

PubMed

White, Marney A; Martin, Pamela D; Newton, Robert L; Walden, Heather M; York-Crowe, Emily E; Gordon, Stewart T; Ryan, Donna H; Williamson, Donald A

2004-07-01

To assess the process variables involved in a weight loss program for African-American adolescent girls. Several process variables have been identified as affecting success in in vivo weight loss programs for adults and children, including program adherence, self-efficacy, and social support. The current study sought to broaden the understanding of these process variables as they pertain to an intervention program that is presented using the Internet. It was hypothesized that variables such as program adherence, dietary self-efficacy, psychological factors, and family environment factors would mediate the effect of the experimental condition on weight loss. Participants were 57 adolescent African-American girls who joined the program with one obese parent; family pairs were randomized to either a behavioral or control condition in an Internet-based weight loss program. Outcome data (weight loss) are reported for the first 6 months of the intervention. Results partially supported the hypotheses. For weight loss among adolescents, parent variables pertaining to life and family satisfaction were the strongest mediating variables. For parental weight loss, changes in dietary practices over the course of 6 months were the strongest mediators. The identification of factors that enhance or impede weight loss for adolescents is an important step in improving weight loss programs for this group. The current findings suggest that family/parental variables exert a strong influence on weight loss efforts for adolescents and should be considered in developing future programs. Copyright 2004 NAASO

Parent Interest in a School-Based, School Nurse-Led Weight Management Program

ERIC Educational Resources Information Center

Kubik, Martha Y.; Lee, Jiwoo

2014-01-01

Because one in three children is already overweight or obese, school-based interventions targeting secondary obesity prevention merit consideration. This study assessed parent interest in participating in a school-based, school nurse-led weight management program for young school-aged children. A random sample of parents ("n" = 122) of…

A Precise Drunk Driving Detection Using Weighted Kernel Based on Electrocardiogram.

PubMed

Wu, Chung Kit; Tsang, Kim Fung; Chi, Hao Ran; Hung, Faan Hei

2016-05-09

Globally, 1.2 million people die and 50 million people are injured annually due to traffic accidents. These traffic accidents cost $500 billion dollars. Drunk drivers are found in 40% of the traffic crashes. Existing drunk driving detection (DDD) systems do not provide accurate detection and pre-warning concurrently. Electrocardiogram (ECG) is a proven biosignal that accurately and simultaneously reflects human's biological status. In this letter, a classifier for DDD based on ECG is investigated in an attempt to reduce traffic accidents caused by drunk drivers. At this point, it appears that there is no known research or literature found on ECG classifier for DDD. To identify drunk syndromes, the ECG signals from drunk drivers are studied and analyzed. As such, a precise ECG-based DDD (ECG-DDD) using a weighted kernel is developed. From the measurements, 10 key features of ECG signals were identified. To incorporate the important features, the feature vectors are weighted in the customization of kernel functions. Four commonly adopted kernel functions are studied. Results reveal that weighted feature vectors improve the accuracy by 11% compared to the computation using the prime kernel. Evaluation shows that ECG-DDD improved the accuracy by 8% to 18% compared to prevailing methods.

A global weighted mean temperature model based on empirical orthogonal function analysis

NASA Astrophysics Data System (ADS)

Li, Qinzheng; Chen, Peng; Sun, Langlang; Ma, Xiaping

2018-03-01

A global empirical orthogonal function (EOF) model of the tropospheric weighted mean temperature called GEOFM_Tm was developed using high-precision Global Geodetic Observing System (GGOS) Atmosphere Tm data during the years 2008-2014. Due to the quick convergence of EOF decomposition, it is possible to use the first four EOF series, which consists base functions Uk and associated coefficients Pk, to represent 99.99% of the overall variance of the original data sets and its spatial-temporal variations. Results show that U1 displays a prominent latitude distribution profile with positive peaks located at low latitude region. U2 manifests an asymmetric pattern that positive values occurred over 30° in the Northern Hemisphere, and negative values were observed at other regions. U3 and U4 displayed significant anomalies in Tibet and North America, respectively. Annual variation is the major component of the first and second associated coefficients P1 and P2, whereas P3 and P4 mainly reflects both annual and semi-annual variation components. Furthermore, the performance of constructed GEOFM_Tm was validated by comparison with GTm_III and GTm_N with different kinds of data including GGOS Atmosphere Tm data in 2015 and radiosonde data from Integrated Global Radiosonde Archive (IGRA) in 2014. Generally speaking, GEOFM_Tm can achieve the same accuracy and reliability as GTm_III and GTm_N models in a global scale, even has improved in the Antarctic and Greenland regions. The MAE and RMS of GEOFM_Tm tend to be 2.49 K and 3.14 K with respect to GGOS Tm data, respectively; and 3.38 K and 4.23 K with respect to IGRA sounding data, respectively. In addition, those three models have higher precision at low latitude than middle and high latitude regions. The magnitude of Tm remains at the range of 220-300 K, presented a high correlation with geographic latitude. In the Northern Hemisphere, there was a significant enhancement at high latitude region reaching 270 K during summer

Impact of newer self-monitoring technology and brief phone-based intervention on weight loss: A randomized pilot study.

PubMed

Ross, Kathryn M; Wing, Rena R

2016-08-01

Despite the proliferation of newer self-monitoring technology (e.g., activity monitors and smartphone apps), their impact on weight loss outside of structured in-person behavioral intervention is unknown. A randomized, controlled pilot study was conducted to examine efficacy of self-monitoring technology, with and without phone-based intervention, on 6-month weight loss in adults with overweight and obesity. Eighty participants were randomized to receive standard self-monitoring tools (ST, n = 26), technology-based self-monitoring tools (TECH, n = 27), or technology-based tools combined with phone-based intervention (TECH + PHONE, n = 27). All participants attended one introductory weight loss session and completed assessments at baseline, 3 months, and 6 months. Weight loss from baseline to 6 months differed significantly between groups P = 0.042; there was a trend for TECH + PHONE (-6.4 ± 1.2 kg) to lose more weight than ST (-1.3 ± 1.2 kg); weight loss in TECH (-4.1 ± 1.4 kg) was between ST and TECH + PHONE. Fewer ST (15%) achieved ≥5% weight losses compared with TECH and TECH + PHONE (44%), P = 0.039. Adherence to self-monitoring caloric intake was higher in TECH + PHONE than TECH or ST, Ps < 0.05. These results suggest use of newer self-monitoring technology plus brief phone-based intervention improves adherence and weight loss compared with traditional self-monitoring tools. Further research should determine cost-effectiveness of adding phone-based intervention when providing self-monitoring technology. © 2016 The Obesity Society.

Impact of newer self-monitoring technology and brief phone-based intervention on weight loss: a randomized pilot study

PubMed Central

Ross, Kathryn M.; Wing, Rena R.

2016-01-01

Objective Despite the proliferation of newer self-monitoring technology (e.g., activity monitors and smartphone apps), their impact on weight loss outside of structured in-person behavioral intervention is unknown. Methods A randomized, controlled pilot study was conducted to examine efficacy of self-monitoring technology, with and without phone-based intervention, on 6-month weight loss in adults with overweight and obesity. Eighty participants were randomized to receive standard self-monitoring tools (ST, n=26), technology-based self-monitoring tools (TECH, n=27), or technology-based tools combined with phone-based intervention (TECH+PHONE, n=27). All participants attended one introductory weight loss session and completed assessments at baseline, 3 months, and 6 months. Results Weight loss from baseline to 6 months differed significantly between groups p=.042; there was a trend for TECH+PHONE (−6.4±1.2kg) to lose more weight than ST (−1.3±1.2kg); weight loss in TECH (−4.1±1.4kg) was between ST and TECH+PHONE. Fewer ST (15%) achieved ≥5% weight losses compared to TECH and TECH+PHONE (44%), p=.039. Adherence to self-monitoring caloric intake was higher in TECH+PHONE than TECH or ST, ps<.05. Conclusion These results suggest use of newer self-monitoring technology plus brief phone-based intervention improves adherence and weight loss compared to traditional self-monitoring tools. Further research should determine cost-effectiveness of adding phone-based intervention when providing self-monitoring technology. PMID:27367614

Combating weight-based cyberbullying on Facebook with the dissenter effect.

PubMed

Anderson, Jenn; Bresnahan, Mary; Musatics, Catherine

2014-05-01

Weight-based cyberbullying is prevalent among youth and adolescents and can have lasting negative psychological effects on the victims. One way to combat these negative effects is through modeling dissenting behavior. When a bystander challenges the bully or supports the victim, this models dissenting behavior. In this study, 181 participants were exposed to message manipulations posted on a Facebook page aimed at testing the conformity effect, the dissenter effect, and the bystander effect in response to enactment of weight-based bullying. Facebook is a common social media site where cyberbullying is reported. Results indicate that in the dissenting condition, participants' comments were significantly more positive or supporting for the victim, as compared to other conditions. This effect was more pronounced for men than for women. In addition, in the dissenting condition, men were less likely to consider the victim unhealthy than women and men in other conditions. These results support the effectiveness of efforts to model dissenting behavior in the face of bullies and extend them to online contexts. Implications are discussed.

Differential functional magnetic resonance imaging response to food pictures in successful weight-loss maintainers relative to normal-weight and obese controls1234

PubMed Central

Haley, Andreana P; Sweet, Lawrence H; Phelan, Suzanne; Raynor, Hollie A; Del Parigi, Angelo; Cohen, Ron; Wing, Rena R

2009-01-01

Background: Prior research indicates that successful weight-loss maintainers (SWLs) work harder than people of normal weight to maintain their weight loss, including greater dietary restriction of fat and higher physical activity levels. However, little work to date has examined how SWLs differ biologically from normal-weight (NW) and obese controls. Objective: The objective was to compare the brain responses of SWLs to food pictures with those of NW and obese controls. Design: Blood oxygen level–dependent responses to high- and low-energy food pictures were measured in 18 NW controls, 16 obese controls, and 17 SWLs. Results: Group differences were identified in 4 regions, which indicated significant change in activation in response to the food pictures. SWLs showed greater activation in the left superior frontal region and right middle temporal region than did NW and obese controls—a pattern of results confirmed in exploratory voxel-wise analyses. Obese controls also showed greater activation in a bilateral precentral region. Conclusions: These results suggest that SWLs show greater activation in frontal regions and primary and secondary visual cortices—a pattern consistent with greater inhibitory control in response to food cues and greater visual attention to the food cues. A greater engagement of inhibitory control regions in response to food cues as well as a greater monitoring of foods may promote control of food intake and successful weight-loss maintenance. PMID:19675107

An 8-Week Web-Based Weight Loss Challenge With Celebrity Endorsement and Enhanced Social Support: Observational Study

PubMed Central

Collins, Clare E; Morgan, Philip J; Callister, Robin

2013-01-01

Background Initial engagement and weight loss within Web-based weight loss programs may predict long-term success. The integration of persuasive Web-based features may boost engagement and therefore weight loss. Objective To determine whether an 8-week challenge within a commercial Web-based weight loss program influenced weight loss, website use, and attrition in the short term, when compared to the standard program. Methods De-identified data for participants (mean age 36.7±10.3 years; 86% female) who enrolled in the Biggest Loser Club (BLC) (n=952) and the BLC’s Shannan Ponton Fast Track Challenge (SC) for 8 weeks (n=381) were compared. The BLC program used standard evidence-based website features, with individualized calorie and exercise targets to facilitate a weight loss of 0.5-1 kg per week (–500kcal/day less than estimated energy expenditure). SC used the same website features but in addition promoted greater initial weight loss using a 1200 kcal/day energy intake target and physical activity energy expenditure of 600 kcal/day. SC used persuasive features to facilitate greater user engagement, including offering additional opportunities for social support (eg, webinar meetings with a celebrity personal trainer and social networking) endorsed by a celebrity personal trainer. Self-reported weekly weight records were used to determine weight change after 8 weeks. A primary analysis was undertaken using a generalized linear mixed model (GLMM) with all available weight records for all participants included. Dropout (participants who cancelled their subscription) and nonusage (participants who stopped using the Web-based features) attrition rates at 8 weeks were calculated. The number of participants who accessed each website feature and the total number of days each feature was used were calculated. The difference between attrition rates and website use for the two programs were tested using chi-square and Wilcoxon Rank Sum tests, respectively. Results

Perceived weight discrimination in England: a population-based study of adults aged ⩾50 years

PubMed Central

Jackson, S E; Steptoe, A; Beeken, R J; Croker, H; Wardle, J

2015-01-01

Background: Despite a wealth of experimental studies on weight bias, little is known about weight discrimination at the population level. This study examined the prevalence and socio-demographic correlates of perceived weight discrimination in a large population-based sample of older adults. Methods: Data were from 5307 adults in the English Longitudinal Study of Ageing; a population-based cohort of men and women aged ⩾50 years. Weight discrimination was reported for five domains (less respect/courtesy; treated as less clever; poorer treatment in medical settings; poorer service in restaurants/stores; threatened/harassed) at wave 5 (2010–2011). Height and weight were measured at wave 4 (2008–2009). We used logistic regression to test the odds of weight discrimination in relation to weight status, age, sex, wealth, education and marital status. Results: Perceived weight discrimination in any domain was reported by 4.6% of participants, ranging from 0.8% in the normal-weight participants through 0.9, 6.7, 24.2 and 35.1% in individuals who were overweight or met criteria for class I, II and III obesity. Overall, and in each situation, odds of perceived weight discrimination were higher in younger and less wealthy individuals. There was no interaction between weight status and any socio-demographic variable. Relative to normal-weight participants, odds ratios for any perceived weight discrimination were 1.13 (95% confidence interval 0.53–2.40) in those who were overweight, 8.86 (4.65–16.88) in those with class I obesity, 35.06 (18.30–67.16) in class II obese and 56.43 (27.72–114.87) in class III obese. Conclusions: Our results indicate that rates of perceived weight discrimination are comparatively low in individuals who are overweight or have class I obesity, but for those with class II/III obesity, >10% had experienced discrimination in each domain, and >20% had been treated with less respect or courtesy. These findings have implications for public

Perceived weight discrimination in England: a population-based study of adults aged ⩾50 years.

PubMed

Jackson, S E; Steptoe, A; Beeken, R J; Croker, H; Wardle, J

2015-05-01

Despite a wealth of experimental studies on weight bias, little is known about weight discrimination at the population level. This study examined the prevalence and socio-demographic correlates of perceived weight discrimination in a large population-based sample of older adults. Data were from 5307 adults in the English Longitudinal Study of Ageing; a population-based cohort of men and women aged ⩾50 years. Weight discrimination was reported for five domains (less respect/courtesy; treated as less clever; poorer treatment in medical settings; poorer service in restaurants/stores; threatened/harassed) at wave 5 (2010-2011). Height and weight were measured at wave 4 (2008-2009). We used logistic regression to test the odds of weight discrimination in relation to weight status, age, sex, wealth, education and marital status. Perceived weight discrimination in any domain was reported by 4.6% of participants, ranging from 0.8% in the normal-weight participants through 0.9, 6.7, 24.2 and 35.1% in individuals who were overweight or met criteria for class I, II and III obesity. Overall, and in each situation, odds of perceived weight discrimination were higher in younger and less wealthy individuals. There was no interaction between weight status and any socio-demographic variable. Relative to normal-weight participants, odds ratios for any perceived weight discrimination were 1.13 (95% confidence interval 0.53-2.40) in those who were overweight, 8.86 (4.65-16.88) in those with class I obesity, 35.06 (18.30-67.16) in class II obese and 56.43 (27.72-114.87) in class III obese. Our results indicate that rates of perceived weight discrimination are comparatively low in individuals who are overweight or have class I obesity, but for those with class II/III obesity, >10% had experienced discrimination in each domain, and >20% had been treated with less respect or courtesy. These findings have implications for public policy and highlight the need for effective interventions

Detergent-dispersant additives based on high-molecular-weight alkylphenols

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kulieva, K.N.; Namazova, I.I.; Ismailova, N.D.

1988-09-01

This article describes the synthesis and investigation of Mannich bases produced for alkylphenols, obtained in turn from ethylene oligomers. These oligomers are the still bottoms from distillation products of high-temperature oligomerization of ethylene in the presence of triethylaluminum. Two narrow cuts obtained from the distillation of oligomer fraction were used to study the influence of ethylene oligomer molecular weight on the properties of the additives. The additives were blended in DS-11 oil to evaluate their detergency-dispersancy and other properties. Comparison blends were made with succinimide additives based on the same ethylene oligomers. The Mannich bases give improvements in the oxidationmore » resistance, anticorrosion properties, and detergency-dispersancy of the DS-11 diesel oil.« less

Attribute Weighting Based K-Nearest Neighbor Using Gain Ratio

NASA Astrophysics Data System (ADS)

Nababan, A. A.; Sitompul, O. S.; Tulus

2018-04-01

K- Nearest Neighbor (KNN) is a good classifier, but from several studies, the result performance accuracy of KNN still lower than other methods. One of the causes of the low accuracy produced, because each attribute has the same effect on the classification process, while some less relevant characteristics lead to miss-classification of the class assignment for new data. In this research, we proposed Attribute Weighting Based K-Nearest Neighbor Using Gain Ratio as a parameter to see the correlation between each attribute in the data and the Gain Ratio also will be used as the basis for weighting each attribute of the dataset. The accuracy of results is compared to the accuracy acquired from the original KNN method using 10-fold Cross-Validation with several datasets from the UCI Machine Learning repository and KEEL-Dataset Repository, such as abalone, glass identification, haberman, hayes-roth and water quality status. Based on the result of the test, the proposed method was able to increase the classification accuracy of KNN, where the highest difference of accuracy obtained hayes-roth dataset is worth 12.73%, and the lowest difference of accuracy obtained in the abalone dataset of 0.07%. The average result of the accuracy of all dataset increases the accuracy by 5.33%.

A new age-based formula for estimating weight of Korean children.

PubMed

Park, Jungho; Kwak, Young Ho; Kim, Do Kyun; Jung, Jae Yun; Lee, Jin Hee; Jang, Hye Young; Kim, Hahn Bom; Hong, Ki Jeong

2012-09-01

The objective of this study was to develop and validate a new age-based formula for estimating body weights of Korean children. We obtained body weight and age data from a survey conducted in 2005 by the Korean Pediatric Society that was performed to establish normative values for Korean children. Children aged 0-14 were enrolled, and they were divided into three groups according to age: infants (<12 months), preschool-aged (1-4 years) and school-aged children (5-14 years). Seventy-five percent of all subjects were randomly selected to make a derivation set. Regression analysis was performed in order to produce equations that predict the weight from the age for each group. The linear equations derived from this analysis were simplified to create a weight estimating formula for Korean children. This formula was then validated using the remaining 25% of the study subjects with mean percentage error and absolute error. To determine whether a new formula accurately predicts actual weights of Korean children, we also compared this new formula to other weight estimation methods (APLS, Shann formula, Leffler formula, Nelson formula and Broselow tape). A total of 124,095 children's data were enrolled, and 19,854 (16.0%), 40,612 (32.7%) and 63,629 (51.3%) were classified as infants, preschool-aged and school-aged groups, respectively. Three equations, (age in months+9)/2, 2×(age in years)+9 and 4×(age in years)-1 were derived for infants, pre-school and school-aged groups, respectively. When these equations were applied to the validation set, the actual average weight of those children was 0.4kg heavier than our estimated weight (95% CI=0.37-0.43, p<0.001). The mean percentage error of our model (+0.9%) was lower than APLS (-11.5%), Shann formula (-8.6%), Leffler formula (-1.7%), Nelson formula (-10.0%), Best Guess formula (+5.0%) and Broselow tape (-4.8%) for all age groups. We developed and validated a simple formula to estimate body weight from the age of Korean

Bag-of-features based medical image retrieval via multiple assignment and visual words weighting.

PubMed

Wang, Jingyan; Li, Yongping; Zhang, Ying; Wang, Chao; Xie, Honglan; Chen, Guoling; Gao, Xin

2011-11-01

Bag-of-features based approaches have become prominent for image retrieval and image classification tasks in the past decade. Such methods represent an image as a collection of local features, such as image patches and key points with scale invariant feature transform (SIFT) descriptors. To improve the bag-of-features methods, we first model the assignments of local descriptors as contribution functions, and then propose a novel multiple assignment strategy. Assuming the local features can be reconstructed by their neighboring visual words in a vocabulary, reconstruction weights can be solved by quadratic programming. The weights are then used to build contribution functions, resulting in a novel assignment method, called quadratic programming (QP) assignment. We further propose a novel visual word weighting method. The discriminative power of each visual word is analyzed by the sub-similarity function in the bin that corresponds to the visual word. Each sub-similarity function is then treated as a weak classifier. A strong classifier is learned by boosting methods that combine those weak classifiers. The weighting factors of the visual words are learned accordingly. We evaluate the proposed methods on medical image retrieval tasks. The methods are tested on three well-known data sets, i.e., the ImageCLEFmed data set, the 304 CT Set, and the basal-cell carcinoma image set. Experimental results demonstrate that the proposed QP assignment outperforms the traditional nearest neighbor assignment, the multiple assignment, and the soft assignment, whereas the proposed boosting based weighting strategy outperforms the state-of-the-art weighting methods, such as the term frequency weights and the term frequency-inverse document frequency weights.

Relationship of weight-based teasing and adolescents' psychological well-being and physical health.

PubMed

Greenleaf, Christy; Petrie, Trent A; Martin, Scott B

2014-01-01

To date, research has focused primarily on psychological correlates of weight-based teasing. In this study, we extended previous work by also examining physical health-related variables (eg, physical self-concept and physical fitness [PF]). Participants included 1419 middle school students (637 boys and 782 girls). Of these, 245 (17.3%) reported being teased about being overweight. Participants completed measures of self-esteem, depression, physical self-concept, physical activity (PA) self-efficacy, and self-report physical and sedentary activities. Participants also completed PF testing. After controlling for demographic characteristics, participants who were teased about being overweight had higher scores on depression and lower scores on self-esteem, physical self-concept, PA self-efficacy, and health-related measures of PF in comparison to participants who were not teased. The results of this study support previous research indicating relationships between teasing and low levels of psychological well-being, physical self-concept, and PA self-efficacy, and establishes one between weight-based teasing and different types of PF. Research is needed to determine the potential causal nature of the relationships between teasing and fitness and evidence-based interventions are needed to reduce weight-based teasing and its potential effects on health and well-being. © 2013, American School Health Association.

Financial incentive strategies for maintenance of weight loss: results from an internet-based randomized controlled trial.

PubMed

Yancy, William S; Shaw, Pamela A; Wesby, Lisa; Hilbert, Victoria; Yang, Lin; Zhu, Jingsan; Troxel, Andrea; Huffman, David; Foster, Gary D; Wojtanowski, Alexis C; Volpp, Kevin G

2018-05-25

Financial incentives can improve initial weight loss; we examined whether financial incentives can improve weight loss maintenance. Participants aged 30-80 years who lost at least 5 kg during the first 4-6 months in a nationally available commercial weight loss program were recruited via the internet into a three-arm randomized trial of two types of financial incentives versus active control during months 1-6 (Phase I) followed by passive monitoring during months 7-12 (Phase II). Interventions were daily self-weighing and text messaging feedback alone (control) or combined with a lottery-based incentive or a direct incentive. The primary outcome was weight change 6 months after initial weight loss. Secondary outcomes included weight change 12 months after initial weight loss (6 months after cessation of maintenance intervention), and self-reported physical activity and eating behaviors. Of 191 participants randomized, the mean age was 49.0 (SD = 10.5) years and weight loss prior to randomization was 11.4 (4.7) kg; 92% were women and 89% were White. Mean weight changes during the next 6 months (Phase I) were: lottery -3.0 (5.8) kg; direct -2.8 (5.8) kg; and control -1.4 (5.8) kg (all pairwise comparisons p > 0.1). Weight changes through the end of 12 months post-weight loss (Phase II) were: lottery -1.8 (10.5) kg; direct -0.7 (10.7) kg; and control -0.3 (9.4) kg (all pairwise comparisons p > 0.1). The percentages of participants who maintained their weight loss (defined as gaining ≤1.36 kg) were: lottery 79%, direct 76%, and control 67% at 6 months and lottery 66%, direct 62%, and control 59% at 12 months (all pairwise comparisons p > 0.1). At 6 and 12 months after initial weight loss, changes in self-reported physical activity or eating behaviors did not differ across arms. Compared with the active control of daily texting based on daily home weighing, lottery-based and direct monetary incentives provided no additional benefit

An AHP-Based Weighted Analysis of Network Knowledge Management Platforms for Elementary School Students

ERIC Educational Resources Information Center

Lee, Chung-Ping; Lou, Shi-Jer; Shih, Ru-Chu; Tseng, Kuo-Hung

2011-01-01

This study uses the analytical hierarchy process (AHP) to quantify important knowledge management behaviors and to analyze the weight scores of elementary school students' behaviors in knowledge transfer, sharing, and creation. Based on the analysis of Expert Choice and tests for validity and reliability, this study identified the weight scores of…

Benchmarking of state-of-the-art needle detection algorithms in 3D ultrasound data volumes

NASA Astrophysics Data System (ADS)

Pourtaherian, Arash; Zinger, Svitlana; de With, Peter H. N.; Korsten, Hendrikus H. M.; Mihajlovic, Nenad

2015-03-01

Ultrasound-guided needle interventions are widely practiced in medical diagnostics and therapy, i.e. for biopsy guidance, regional anesthesia or for brachytherapy. Needle guidance using 2D ultrasound can be very challenging due to the poor needle visibility and the limited field of view. Since 3D ultrasound transducers are becoming more widely used, needle guidance can be improved and simplified with appropriate computer-aided analyses. In this paper, we compare two state-of-the-art 3D needle detection techniques: a technique based on line filtering from literature and a system employing Gabor transformation. Both algorithms utilize supervised classification to pre-select candidate needle voxels in the volume and then fit a model of the needle on the selected voxels. The major differences between the two approaches are in extracting the feature vectors for classification and selecting the criterion for fitting. We evaluate the performance of the two techniques using manually-annotated ground truth in several ex-vivo situations of different complexities, containing three different needle types with various insertion angles. This extensive evaluation provides better understanding on the limitations and advantages of each technique under different acquisition conditions, which is leading to the development of improved techniques for more reliable and accurate localization. Benchmarking results that the Gabor features are better capable of distinguishing the needle voxels in all datasets. Moreover, it is shown that the complete processing chain of the Gabor-based method outperforms the line filtering in accuracy and stability of the detection results.

Novel method to predict body weight in children based on age and morphological facial features.

PubMed

Huang, Ziyin; Barrett, Jeffrey S; Barrett, Kyle; Barrett, Ryan; Ng, Chee M

2015-04-01

A new and novel approach of predicting the body weight of children based on age and morphological facial features using a three-layer feed-forward artificial neural network (ANN) model is reported. The model takes in four parameters, including age-based CDC-inferred median body weight and three facial feature distances measured from digital facial images. In this study, thirty-nine volunteer subjects with age ranging from 6-18 years old and BW ranging from 18.6-96.4 kg were used for model development and validation. The final model has a mean prediction error of 0.48, a mean squared error of 18.43, and a coefficient of correlation of 0.94. The model shows significant improvement in prediction accuracy over several age-based body weight prediction methods. Combining with a facial recognition algorithm that can detect, extract and measure the facial features used in this study, mobile applications that incorporate this body weight prediction method may be developed for clinical investigations where access to scales is limited. © 2014, The American College of Clinical Pharmacology.

An extensive analysis of various texture feature extractors to detect Diabetes Mellitus using facial specific regions.

PubMed

Shu, Ting; Zhang, Bob; Yan Tang, Yuan

2017-04-01

Researchers have recently discovered that Diabetes Mellitus can be detected through non-invasive computerized method. However, the focus has been on facial block color features. In this paper, we extensively study the effects of texture features extracted from facial specific regions at detecting Diabetes Mellitus using eight texture extractors. The eight methods are from four texture feature families: (1) statistical texture feature family: Image Gray-scale Histogram, Gray-level Co-occurance Matrix, and Local Binary Pattern, (2) structural texture feature family: Voronoi Tessellation, (3) signal processing based texture feature family: Gaussian, Steerable, and Gabor filters, and (4) model based texture feature family: Markov Random Field. In order to determine the most appropriate extractor with optimal parameter(s), various parameter(s) of each extractor are experimented. For each extractor, the same dataset (284 Diabetes Mellitus and 231 Healthy samples), classifiers (k-Nearest Neighbors and Support Vector Machines), and validation method (10-fold cross validation) are used. According to the experiments, the first and third families achieved a better outcome at detecting Diabetes Mellitus than the other two. The best texture feature extractor for Diabetes Mellitus detection is the Image Gray-scale Histogram with bin number=256, obtaining an accuracy of 99.02%, a sensitivity of 99.64%, and a specificity of 98.26% by using SVM. Copyright © 2017 Elsevier Ltd. All rights reserved.

Contrast, size, and orientation-invariant target detection in infrared imagery

NASA Astrophysics Data System (ADS)

Zhou, Yi-Tong; Crawshaw, Richard D.

1991-08-01

Automatic target detection in IR imagery is a very difficult task due to variations in target brightness, shape, size, and orientation. In this paper, the authors present a contrast, size, and orientation invariant algorithm based on Gabor functions for detecting targets from a single IR image frame. The algorithms consists of three steps. First, it locates potential targets by using low-resolution Gabor functions which resist noise and background clutter effects, then, it removes false targets and eliminates redundant target points based on a similarity measure. These two steps mimic human vision processing but are different from Zeevi's Foveating Vision System. Finally, it uses both low- and high-resolution Gabor functions to verify target existence. This algorithm has been successfully tested on several IR images that contain multiple examples of military vehicles with different size and brightness in various background scenes and orientations.

A new evidence-based model for weight management in primary care: the Counterweight Programme.

PubMed

Laws, Rachel

2004-06-01

Obesity has become a global epidemic, and a major preventable cause of morbidity and mortality. Management strategies and treatment protocols are however poorly developed and evaluated. The aim of the Counterweight Programme is to develop an evidence-based model for the management of obesity in primary care. The Counterweight Programme is based on the theoretical model of Evidence-Based Quality Assessment aimed at improving the management of obese adults (18-75 years) in primary care. The model consists of four phases: (1) practice audit and needs assessment, (2) practice support and training, (3) practice nurse-led patient intervention, and (4) evaluation. Patient intervention consisted of screening and treatment pathways incorporating evidence-based approaches, including patient-centred goal setting, prescribed eating plans, a group programme, physical activity and behavioural approaches, anti-obesity medication and weight maintenance strategies. Weight Management Advisers who are specialist obesity dietitians facilitated programme implementation. Eighty practices were recruited of which 18 practices were randomized to act as controls and receive deferred intervention 2 years after the initial audit. By February 2004, 58 of the 62 (93.5%) intervention practices had been trained to run the intervention programme, 47 (75.8%) practices were active in implementing the model and 1256 patients had been recruited (74% female, 26% male, mean age 50.6 years, SD 14). At baseline, 75% of patients had at one or more co-morbidity, and the mean body mass index (BMI) was 36.9 kg/m(2) (SD 5.4). Of the 1256 patients recruited, 91% received one of the core lifestyle interventions in the first 12 months. For all patients followed up at 12 months, 34% achieved a clinical meaningful weight loss of 5% or more. A total of 51% of patients were classed as compliant in that they attended the required level of appointments in 3, 6, and 12 months. For fully compliant patients, weight loss