Identification of natural images and computer-generated graphics based on statistical and textural features.

Science.gov (United States)

Peng, Fei; Li, Jiao-ting; Long, Min

2015-03-01

To discriminate the acquisition pipelines of digital images, a novel scheme for the identification of natural images and computer-generated graphics is proposed based on statistical and textural features. First, the differences between them are investigated from the view of statistics and texture, and 31 dimensions of feature are acquired for identification. Then, LIBSVM is used for the classification. Finally, the experimental results are presented. The results show that it can achieve an identification accuracy of 97.89% for computer-generated graphics, and an identification accuracy of 97.75% for natural images. The analyses also demonstrate the proposed method has excellent performance, compared with some existing methods based only on statistical features or other features. The method has a great potential to be implemented for the identification of natural images and computer-generated graphics. © 2014 American Academy of Forensic Sciences.

Biased discriminant euclidean embedding for content-based image retrieval.

Science.gov (United States)

Bian, Wei; Tao, Dacheng

2010-02-01

With many potential multimedia applications, content-based image retrieval (CBIR) has recently gained more attention for image management and web search. A wide variety of relevance feedback (RF) algorithms have been developed in recent years to improve the performance of CBIR systems. These RF algorithms capture user's preferences and bridge the semantic gap. However, there is still a big room to further the RF performance, because the popular RF algorithms ignore the manifold structure of image low-level visual features. In this paper, we propose the biased discriminative Euclidean embedding (BDEE) which parameterises samples in the original high-dimensional ambient space to discover the intrinsic coordinate of image low-level visual features. BDEE precisely models both the intraclass geometry and interclass discrimination and never meets the undersampled problem. To consider unlabelled samples, a manifold regularization-based item is introduced and combined with BDEE to form the semi-supervised BDEE, or semi-BDEE for short. To justify the effectiveness of the proposed BDEE and semi-BDEE, we compare them against the conventional RF algorithms and show a significant improvement in terms of accuracy and stability based on a subset of the Corel image gallery.

Real-time detection and discrimination of visual perception using electrocorticographic signals

Science.gov (United States)

Kapeller, C.; Ogawa, H.; Schalk, G.; Kunii, N.; Coon, W. G.; Scharinger, J.; Guger, C.; Kamada, K.

2018-06-01

Objective. Several neuroimaging studies have demonstrated that the ventral temporal cortex contains specialized regions that process visual stimuli. This study investigated the spatial and temporal dynamics of electrocorticographic (ECoG) responses to different types and colors of visual stimulation that were presented to four human participants, and demonstrated a real-time decoder that detects and discriminates responses to untrained natural images. Approach. ECoG signals from the participants were recorded while they were shown colored and greyscale versions of seven types of visual stimuli (images of faces, objects, bodies, line drawings, digits, and kanji and hiragana characters), resulting in 14 classes for discrimination (experiment I). Additionally, a real-time system asynchronously classified ECoG responses to faces, kanji and black screens presented via a monitor (experiment II), or to natural scenes (i.e. the face of an experimenter, natural images of faces and kanji, and a mirror) (experiment III). Outcome measures in all experiments included the discrimination performance across types based on broadband γ activity. Main results. Experiment I demonstrated an offline classification accuracy of 72.9% when discriminating among the seven types (without color separation). Further discrimination of grey versus colored images reached an accuracy of 67.1%. Discriminating all colors and types (14 classes) yielded an accuracy of 52.1%. In experiment II and III, the real-time decoder correctly detected 73.7% responses to face, kanji and black computer stimuli and 74.8% responses to presented natural scenes. Significance. Seven different types and their color information (either grey or color) could be detected and discriminated using broadband γ activity. Discrimination performance maximized for combined spatial-temporal information. The discrimination of stimulus color information provided the first ECoG-based evidence for color-related population

Fast Depiction Invariant Visual Similarity for Content Based Image Retrieval Based on Data-driven Visual Similarity using Linear Discriminant Analysis

Science.gov (United States)

Wihardi, Y.; Setiawan, W.; Nugraha, E.

2018-01-01

On this research we try to build CBIRS based on Learning Distance/Similarity Function using Linear Discriminant Analysis (LDA) and Histogram of Oriented Gradient (HoG) feature. Our method is invariant to depiction of image, such as similarity of image to image, sketch to image, and painting to image. LDA can decrease execution time compared to state of the art method, but it still needs an improvement in term of accuracy. Inaccuracy in our experiment happen because we did not perform sliding windows search and because of low number of negative samples as natural-world images.

Discriminative Projection Selection Based Face Image Hashing

Science.gov (United States)

Karabat, Cagatay; Erdogan, Hakan

Face image hashing is an emerging method used in biometric verification systems. In this paper, we propose a novel face image hashing method based on a new technique called discriminative projection selection. We apply the Fisher criterion for selecting the rows of a random projection matrix in a user-dependent fashion. Moreover, another contribution of this paper is to employ a bimodal Gaussian mixture model at the quantization step. Our simulation results on three different databases demonstrate that the proposed method has superior performance in comparison to previously proposed random projection based methods.

Multi spectral imaging analysis for meat spoilage discrimination

DEFF Research Database (Denmark)

Christiansen, Asger Nyman; Carstensen, Jens Michael; Papadopoulou, Olga

classification methods: Naive Bayes Classifier as a reference model, Canonical Discriminant Analysis (CDA) and Support Vector Classification (SVC). As the final step, generalization of the models was performed using k-fold validation (k=10). Results showed that image analysis provided good discrimination of meat......In the present study, fresh beef fillets were purchased from a local butcher shop and stored aerobically and in modified atmosphere packaging (MAP, CO2 40%/O2 30%/N2 30%) at six different temperatures (0, 4, 8, 12, 16 and 20°C). Microbiological analysis in terms of total viable counts (TVC......) was performed in parallel with videometer image snapshots and sensory analysis. Odour and colour characteristics of meat were determined by a test panel and attributed into three pre-characterized quality classes, namely Fresh; Semi Fresh and Spoiled during the days of its shelf life. So far, different...

Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN

OpenAIRE

Guo, Hao; Wu, Danni; An, Jubai

2017-01-01

Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred f...

Snapshot imaging Fraunhofer line discriminator for detection of plant fluorescence

Science.gov (United States)

Gupta Roy, S.; Kudenov, M. W.

2015-05-01

Non-invasive quantification of plant health is traditionally accomplished using reflectance based metrics, such as the normalized difference vegetative index (NDVI). However, measuring plant fluorescence (both active and passive) to determine photochemistry of plants has gained importance. Due to better cost efficiency, lower power requirements, and simpler scanning synchronization, detecting passive fluorescence is preferred over active fluorescence. In this paper, we propose a high speed imaging approach for measuring passive plant fluorescence, within the hydrogen alpha Fraunhofer line at ~656 nm, using a Snapshot Imaging Fraunhofer Line Discriminator (SIFOLD). For the first time, the advantage of snapshot imaging for high throughput Fraunhofer Line Discrimination (FLD) is cultivated by our system, which is based on a multiple-image Fourier transform spectrometer and a spatial heterodyne interferometer (SHI). The SHI is a Sagnac interferometer, which is dispersion compensated using blazed diffraction gratings. We present data and techniques for calibrating the SIFOLD to any particular wavelength. This technique can be applied to quantify plant fluorescence at low cost and reduced complexity of data collection.

Multi-level discriminative dictionary learning with application to large scale image classification.

Science.gov (United States)

Shen, Li; Sun, Gang; Huang, Qingming; Wang, Shuhui; Lin, Zhouchen; Wu, Enhua

2015-10-01

The sparse coding technique has shown flexibility and capability in image representation and analysis. It is a powerful tool in many visual applications. Some recent work has shown that incorporating the properties of task (such as discrimination for classification task) into dictionary learning is effective for improving the accuracy. However, the traditional supervised dictionary learning methods suffer from high computation complexity when dealing with large number of categories, making them less satisfactory in large scale applications. In this paper, we propose a novel multi-level discriminative dictionary learning method and apply it to large scale image classification. Our method takes advantage of hierarchical category correlation to encode multi-level discriminative information. Each internal node of the category hierarchy is associated with a discriminative dictionary and a classification model. The dictionaries at different layers are learnt to capture the information of different scales. Moreover, each node at lower layers also inherits the dictionary of its parent, so that the categories at lower layers can be described with multi-scale information. The learning of dictionaries and associated classification models is jointly conducted by minimizing an overall tree loss. The experimental results on challenging data sets demonstrate that our approach achieves excellent accuracy and competitive computation cost compared with other sparse coding methods for large scale image classification.

Hard and soft age discrimination: the dual nature of workplace discrimination.

Science.gov (United States)

Stypinska, Justyna; Turek, Konrad

2017-03-01

The paper concentrates on the problem of age discrimination in the labour market and the way it can be conceptualised and measured in a multi-disciplinary way. The approach proposed here combines two understandings of age discrimination-a sociological and legal one, what allows for a fuller and expanded understanding of ageism in the workplace. At the heart of the study is a survey carried out in Poland with a sample of 1000 men and women aged 45-65 years. The study takes a deeper and innovative look into the issue of age discrimination in employment. Confirmatory factor analysis with WLSMV estimation and logistic regressions were used to test the hypotheses. The study shows that age discrimination in labour market can take on different forms: hard and soft, where the hard type of age discrimination mirrors the legally prohibited types of behaviours and those which relate to the actual decisions of employers which can impact on the employee's career development. The soft discrimination corresponds with those occurrences, which are not inscribed in the legal system per se, are occurring predominantly in the interpersonal sphere, but can nevertheless have negative consequences. Soft discrimination was experienced more often (28.6% of respondents) than hard discrimination (15.7%) with higher occurrences among women, persons in precarious job situation or residents of urban areas. The role of education was not confirmed to influence the levels of perceived age discrimination.

On the Perceptual Organization of Image Databases Using Cognitive Discriminative Biplots

Directory of Open Access Journals (Sweden)

Spiros Fotopoulos

2007-01-01

Full Text Available A human-centered approach to image database organization is presented in this study. The management of a generic image database is pursued using a standard psychophysical experimental procedure followed by a well-suited data analysis methodology that is based on simple geometrical concepts. The end result is a cognitive discriminative biplot, which is a visualization of the intrinsic organization of the image database best reflecting the user's perception. The discriminating power of the introduced cognitive biplot constitutes an appealing tool for image retrieval and a flexible interface for visual data mining tasks. These ideas were evaluated in two ways. First, the separability of semantically distinct image classes was measured according to their reduced representations on the biplot. Then, a nearest-neighbor retrieval scheme was run on the emerged low-dimensional terrain to measure the suitability of the biplot for performing content-based image retrieval (CBIR. The achieved organization performance when compared with the performance of a contemporary system was found superior. This promoted the further discussion of packing these ideas into a realizable algorithmic procedure for an efficient and effective personalized CBIR system.

Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN.

Science.gov (United States)

Guo, Hao; Wu, Danni; An, Jubai

2017-08-09

Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred features subset. The features analyzed include entropy, alpha, and Single-bounce Eigenvalue Relative Difference (SERD) in the C-band polarimetric mode. We also propose a novel SAR image discrimination method for oil slicks and lookalikes based on Convolutional Neural Network (CNN). The regions of interest are selected as the training and testing samples for CNN on the three kinds of polarimetric feature images. The proposed method is applied to a training data set of 5400 samples, including 1800 crude oil, 1800 plant oil, and 1800 oil emulsion samples. In the end, the effectiveness of the method is demonstrated through the analysis of some experimental results. The classification accuracy obtained using 900 samples of test data is 91.33%. It is here observed that the proposed method not only can accurately identify the dark spots on SAR images but also verify the ability of the proposed algorithm to classify unstructured features.

Neighborhood Discriminant Hashing for Large-Scale Image Retrieval.

Science.gov (United States)

Tang, Jinhui; Li, Zechao; Wang, Meng; Zhao, Ruizhen

2015-09-01

With the proliferation of large-scale community-contributed images, hashing-based approximate nearest neighbor search in huge databases has aroused considerable interest from the fields of computer vision and multimedia in recent years because of its computational and memory efficiency. In this paper, we propose a novel hashing method named neighborhood discriminant hashing (NDH) (for short) to implement approximate similarity search. Different from the previous work, we propose to learn a discriminant hashing function by exploiting local discriminative information, i.e., the labels of a sample can be inherited from the neighbor samples it selects. The hashing function is expected to be orthogonal to avoid redundancy in the learned hashing bits as much as possible, while an information theoretic regularization is jointly exploited using maximum entropy principle. As a consequence, the learned hashing function is compact and nonredundant among bits, while each bit is highly informative. Extensive experiments are carried out on four publicly available data sets and the comparison results demonstrate the outperforming performance of the proposed NDH method over state-of-the-art hashing techniques.

Multiparametric Magnetic Resonance Imaging for Discriminating Low-Grade From High-Grade Prostate Cancer

NARCIS (Netherlands)

Vos, E.K.; Kobus, T.; Litjens, G.J.S.; Hambrock, T.; Hulsbergen-van de Kaa, C.A.; Barentsz, J.O.; Maas, M.C.; Scheenen, T.W.J.

2015-01-01

The aim of this study was to determine and validate the optimal combination of parameters derived from 3-T diffusion-weighted imaging, dynamic contrast-enhanced imaging, and magnetic resonance (MR) spectroscopic imaging for discriminating low-grade from high-grade prostate cancer (PCa).The study was

Soybean varieties discrimination using non-imaging hyperspectral sensor

Science.gov (United States)

da Silva Junior, Carlos Antonio; Nanni, Marcos Rafael; Shakir, Muhammad; Teodoro, Paulo Eduardo; de Oliveira-Júnior, José Francisco; Cezar, Everson; de Gois, Givanildo; Lima, Mendelson; Wojciechowski, Julio Cesar; Shiratsuchi, Luciano Shozo

2018-03-01

Infrared region of electromagnetic spectrum has remarkable applications in crop studies. Infrared along with Red band has been used to develop certain vegetation indices. These indices like NDVI, EVI provide important information on any crop physiological stages. The main objective of this research was to discriminate 4 different soybean varieties (BMX Potência, NA5909, FT Campo Mourão and Don Mario) using non-imaging hyperspectral sensor. The study was conducted in four agricultural areas in the municipality of Deodápolis (MS), Brazil. For spectral analysis, 2400 field samples were taken from soybean leaves by means of FieldSpec 3 JR spectroradiometer in the range from 350 to 2500 nm. The data were evaluated through multivariate analysis with the whole set of spectral curves isolated by blue, green, red and near infrared wavelengths along with the addition of vegetation indices like (Enhanced Vegetation Index - EVI, Normalized Difference Vegetation Index - NDVI, Green Normalized Difference Vegetation Index - GNDVI, Soil-adjusted Vegetation Index - SAVI, Transformed Vegetation Index - TVI and Optimized Soil-Adjusted Vegetation Index - OSAVI). A number of the analysis performed where, discriminant (60 and 80% of the data), simulated discriminant (40 and 20% of data), principal component (PC) and cluster analysis (CA). Discriminant and simulated discriminant analyze presented satisfactory results, with average global hit rates of 99.28 and 98.77%, respectively. The results obtained by PC and CA revealed considerable associations between the evaluated variables and the varieties, which indicated that each variety has a variable that discriminates it more effectively in relation to the others. There was great variation in the sample size (number of leaves) for estimating the mean of variables. However, it was possible to observe that 200 leaves allow to obtain a maximum error of 2% in relation to the mean.

The discriminating nature of dopamine transporter image in parkinsonism: the competency of dopaminergic transporter imaging in differential diagnosis of parkinsonism 123I-FP-CIT SPECT study

International Nuclear Information System (INIS)

Kim, Bom Sahn; Jang, Sung June; Eo, Jae Seon; Park, Eun Kyung; Kim, Yu Kyeong; Kim, Jong Min; Lee, Won Woo; Kim, Sang Eun

2007-01-01

The aim of this study was to evaluate the discriminating nature of 123 I-FP-CIT SPECT in patients with parkinsonism. 123 I-FP-CIT SPECT images acquired from the 18 normal controls; NC (60.4 ± 10.0 yr) and 237 patients with parkinsonism (65.9 ± 9.2 yr) were analyzed. From spatially normalized images, regional counts of the caudate, putamen, and occipital lobe were obtained using region of interest method. Binding potential (BP) was calculated with the ratio of specific to nonspecific binding activity at equilibrium. Additionally, the BP ratio of putamen to caudate (PCR) and asymmetric index (ASI) were measured. BPs of NC (3.37 ± 0.57, 3.10± 0.41, 3.23 ± 0.48 for caudate, putamen, whole striatum, respectively) had no significant difference with those of essential tremor; ET (3.31 ± 0.64, 3.06 ± 0.61, 3.14 ± 0.63) and Alzheimer's disease; AD (3.33 ± 0.60, 3.29 ± 0.79, 3.31 ± 0.70), but were higher than those of Parkinson's disease; PD (1.92 ± 0.74, 1.39 ±0.68, 1.64 ± 0.68), multiple system atrophy; MSA (2.36 ± 1.07, 2.16 ± 0.91, 2.26 ± 0.96), and dementia with Lewy body; DLB (1.95± 0.72, 1.64 ± 0.65, 1.79 ± 0.66)(ρ 123 I-FP-CIT SPECT was a good value in differential diagnosis of parkinsonism

Multispectral fluorescence imaging technique for discrimination of cucumber (Cucumis Sativus) seed viability

Science.gov (United States)

In this study, we developed a nondestructive method for discriminating viable cucumber (Cucumis sativus) seeds based on hyperspectral fluorescence imaging. The fluorescence spectra of cucumber seeds in the 420–700 nm range were extracted from hyperspectral fluorescence images obtained using 365 nm u...

Discrimination of Naturally Occurring Radioactive Material in Plastic Scintillator Material

International Nuclear Information System (INIS)

Ely, James H.; Kouzes, Richard T.; Geelhood, Bruce D.; Schweppe, John E.; Warner, Ray A.

2003-01-01

Plastic scintillator material is used in many applications for the detection of gamma-rays from radioactive material, primarily due to the sensitivity per unit cost compared to other detection materials. However, the resolution and lack of full-energy peaks in the plastic scintillator material prohibits detailed spectroscopy. Therefore, other materials such as doped sodium iodide are used for spectroscopic applications. The limited spectroscopic information can however be exploited in plastic scintillator materials to provide some discrimination. The discrimination between man-made and naturally occurring sources would be useful in reducing alarm screening for radiation detection applications which target man-made sources. The results of applying the limited energy information from plastic scintillator material for radiation portal monitors are discussed.

Naturalness and image quality : chroma and hue variation in color images of natural scenes

NARCIS (Netherlands)

Ridder, de H.; Blommaert, F.J.J.; Fedorovskaya, E.A.; Rogowitz, B.E.; Allebach, J.P.

1995-01-01

The relation between perceptual image quality and naturalness was investigated by varying the colorfulness and hue of color images of natural scenes. These variations were created by digitizing the images, subsequently determining their color point distributions in the CIELUV color space and finally

Naturalness and image quality: Chroma and hue variation in color images of natural scenes

NARCIS (Netherlands)

Ridder, de H.; Blommaert, F.J.J.; Fedorovskaya, E.A.; Eschbach, R.; Braun, K.

1997-01-01

The relation between perceptual image quality and natural ness was investigated by varying the colorfulness and hue of color images of natural scenes. These variations were created by digitizing the images, subsequently determining their color point distributions in the CIELUV color space and

Naturalness and image quality : saturation and lightness variation in color images of natural scenes

NARCIS (Netherlands)

Ridder, de H.

1996-01-01

The relation between perceived image quality and naturalness was investigated by varying the colorfulness of natural images at various lightness levels. At each lightness level, subjects assessed perceived colorfulness, naturalness, and quality as a function of average saturation by means of direct

Discriminating Projections for Estimating Face Age in Wild Images

Energy Technology Data Exchange (ETDEWEB)

Tokola, Ryan A [ORNL; Bolme, David S [ORNL; Ricanek, Karl [ORNL; Barstow, Del R [ORNL; Boehnen, Chris Bensing [ORNL

2014-01-01

We introduce a novel approach to estimating the age of a human from a single uncontrolled image. Current face age estimation algorithms work well in highly controlled images, and some are robust to changes in illumination, but it is usually assumed that images are close to frontal. This bias is clearly seen in the datasets that are commonly used to evaluate age estimation, which either entirely or mostly consist of frontal images. Using pose-specific projections, our algorithm maps image features into a pose-insensitive latent space that is discriminative with respect to age. Age estimation is then performed using a multi-class SVM. We show that our approach outperforms other published results on the Images of Groups dataset, which is the only age-related dataset with a non-trivial number of off-axis face images, and that we are competitive with recent age estimation algorithms on the mostly-frontal FG-NET dataset. We also experimentally demonstrate that our feature projections introduce insensitivity to pose.

The discriminating nature of dopamine transporter image in parkinsonism: the competency of dopaminergic transporter imaging in differential diagnosis of parkinsonism {sup 123}I-FP-CIT SPECT study

Energy Technology Data Exchange (ETDEWEB)

Kim, Bom Sahn; Jang, Sung June; Eo, Jae Seon; Park, Eun Kyung; Kim, Yu Kyeong; Kim, Jong Min; Lee, Won Woo; Kim, Sang Eun [Seoul National University College of Medicine, Seoul (Korea, Republic of)

2007-08-15

The aim of this study was to evaluate the discriminating nature of {sup 123}I-FP-CIT SPECT in patients with parkinsonism. {sup 123}I-FP-CIT SPECT images acquired from the 18 normal controls; NC (60.4 {+-} 10.0 yr) and 237 patients with parkinsonism (65.9 {+-} 9.2 yr) were analyzed. From spatially normalized images, regional counts of the caudate, putamen, and occipital lobe were obtained using region of interest method. Binding potential (BP) was calculated with the ratio of specific to nonspecific binding activity at equilibrium. Additionally, the BP ratio of putamen to caudate (PCR) and asymmetric index (ASI) were measured. BPs of NC (3.37 {+-} 0.57, 3.10{+-} 0.41, 3.23 {+-} 0.48 for caudate, putamen, whole striatum, respectively) had no significant difference with those of essential tremor; ET (3.31 {+-} 0.64, 3.06 {+-} 0.61, 3.14 {+-} 0.63) and Alzheimer's disease; AD (3.33 {+-} 0.60, 3.29 {+-} 0.79, 3.31 {+-} 0.70), but were higher than those of Parkinson's disease; PD (1.92 {+-} 0.74, 1.39 {+-}0.68, 1.64 {+-} 0.68), multiple system atrophy; MSA (2.36 {+-} 1.07, 2.16 {+-} 0.91, 2.26 {+-} 0.96), and dementia with Lewy body; DLB (1.95{+-} 0.72, 1.64 {+-} 0.65, 1.79 {+-} 0.66)({rho} < 0.005). PD had statistically lower values of PCR and higher values of ASI than those of NC ({rho} < 0.005). And PD had significantly lower value of PCR, higher ASI and lower BP in the putamen and whole striatum than MSA ({rho} < 0.05). Dopamine transporter image of {sup 123}I-FP-CIT SPECT was a good value in differential diagnosis of parkinsonism.

Target discrimination method for SAR images based on semisupervised co-training

Science.gov (United States)

Wang, Yan; Du, Lan; Dai, Hui

2018-01-01

Synthetic aperture radar (SAR) target discrimination is usually performed in a supervised manner. However, supervised methods for SAR target discrimination may need lots of labeled training samples, whose acquirement is costly, time consuming, and sometimes impossible. This paper proposes an SAR target discrimination method based on semisupervised co-training, which utilizes a limited number of labeled samples and an abundant number of unlabeled samples. First, Lincoln features, widely used in SAR target discrimination, are extracted from the training samples and partitioned into two sets according to their physical meanings. Second, two support vector machine classifiers are iteratively co-trained with the extracted two feature sets based on the co-training algorithm. Finally, the trained classifiers are exploited to classify the test data. The experimental results on real SAR images data not only validate the effectiveness of the proposed method compared with the traditional supervised methods, but also demonstrate the superiority of co-training over self-training, which only uses one feature set.

Discriminative Hierarchical K-Means Tree for Large-Scale Image Classification.

Science.gov (United States)

Chen, Shizhi; Yang, Xiaodong; Tian, Yingli

2015-09-01

A key challenge in large-scale image classification is how to achieve efficiency in terms of both computation and memory without compromising classification accuracy. The learning-based classifiers achieve the state-of-the-art accuracies, but have been criticized for the computational complexity that grows linearly with the number of classes. The nonparametric nearest neighbor (NN)-based classifiers naturally handle large numbers of categories, but incur prohibitively expensive computation and memory costs. In this brief, we present a novel classification scheme, i.e., discriminative hierarchical K-means tree (D-HKTree), which combines the advantages of both learning-based and NN-based classifiers. The complexity of the D-HKTree only grows sublinearly with the number of categories, which is much better than the recent hierarchical support vector machines-based methods. The memory requirement is the order of magnitude less than the recent Naïve Bayesian NN-based approaches. The proposed D-HKTree classification scheme is evaluated on several challenging benchmark databases and achieves the state-of-the-art accuracies, while with significantly lower computation cost and memory requirement.

An information-theoretical approach to image resolution applied to neutron imaging detectors based upon individual discriminator signals

International Nuclear Information System (INIS)

Clergeau, Jean-Francois; Ferraton, Matthieu; Guerard, Bruno; Khaplanov, Anton; Piscitelli, Francesco; Platz, Martin; Rigal, Jean-Marie; Van Esch, Patrick; Daulle, Thibault

2013-06-01

1D or 2D neutron imaging detectors with individual wire or strip readout using discriminators have the advantage of being able to treat several neutron impacts partially overlapping in time, hence reducing global dead time. A single neutron impact usually gives rise to several discriminator signals. In this paper, we introduce an information-theoretical definition of image resolution. Two point-like spots of neutron impacts with a given distance between them act as a source of information (each neutron hit belongs to one spot or the other), and the detector plus signal treatment is regarded as an imperfect communication channel that transmits this information. The maximal mutual information obtained from this channel as a function of the distance between the spots allows to define a calibration-independent measure of resolution. We then apply this measure to quantify the power of resolution of different algorithms treating these individual discriminator signals which can be implemented in firmware. The method is then applied to different detectors existing at the ILL. Center-of-gravity methods usually improve the resolution over best-wire algorithms which are the standard way of treating these signals. (authors)

An information-theoretical approach to image resolution applied to neutron imaging detectors based upon individual discriminator signals

Energy Technology Data Exchange (ETDEWEB)

Clergeau, Jean-Francois; Ferraton, Matthieu; Guerard, Bruno; Khaplanov, Anton; Piscitelli, Francesco; Platz, Martin; Rigal, Jean-Marie; Van Esch, Patrick [Institut Laue Langevin, Neutron Detector Service, Grenoble (France); Daulle, Thibault [PHELMA Grenoble - INP Grenoble (France)

2013-06-15

1D or 2D neutron imaging detectors with individual wire or strip readout using discriminators have the advantage of being able to treat several neutron impacts partially overlapping in time, hence reducing global dead time. A single neutron impact usually gives rise to several discriminator signals. In this paper, we introduce an information-theoretical definition of image resolution. Two point-like spots of neutron impacts with a given distance between them act as a source of information (each neutron hit belongs to one spot or the other), and the detector plus signal treatment is regarded as an imperfect communication channel that transmits this information. The maximal mutual information obtained from this channel as a function of the distance between the spots allows to define a calibration-independent measure of resolution. We then apply this measure to quantify the power of resolution of different algorithms treating these individual discriminator signals which can be implemented in firmware. The method is then applied to different detectors existing at the ILL. Center-of-gravity methods usually improve the resolution over best-wire algorithms which are the standard way of treating these signals. (authors)

Optimizing color reproduction of natural images

NARCIS (Netherlands)

Yendrikhovskij, S.N.; Blommaert, F.J.J.; Ridder, de H.

1998-01-01

The paper elaborates on understanding, measuring and optimizing perceived color quality of natural images. We introduce a model for optimal color reproduction of natural scenes which is based on the assumption that color quality of natural images is constrained by perceived naturalness and

Tile-Level Annotation of Satellite Images Using Multi-Level Max-Margin Discriminative Random Field

Directory of Open Access Journals (Sweden)

Hong Sun

2013-05-01

Full Text Available This paper proposes a multi-level max-margin discriminative analysis (M3DA framework, which takes both coarse and fine semantics into consideration, for the annotation of high-resolution satellite images. In order to generate more discriminative topic-level features, the M3DA uses the maximum entropy discrimination latent Dirichlet Allocation (MedLDA model. Moreover, for improving the spatial coherence of visual words neglected by M3DA, conditional random field (CRF is employed to optimize the soft label field composed of multiple label posteriors. The framework of M3DA enables one to combine word-level features (generated by support vector machines and topic-level features (generated by MedLDA via the bag-of-words representation. The experimental results on high-resolution satellite images have demonstrated that, using the proposed method can not only obtain suitable semantic interpretation, but also improve the annotation performance by taking into account the multi-level semantics and the contextual information.

Amide proton transfer imaging to discriminate between low- and high-grade gliomas: added value to apparent diffusion coefficient and relative cerebral blood volume

Energy Technology Data Exchange (ETDEWEB)

Choi, Yoon Seong; Ahn, Sung Soo; Lee, Seung-Koo [Yonsei University College of Medicine, Department of Radiology and Research Institute of Radiological Science, College of Medicine, Seoul (Korea, Republic of); Chang, Jong Hee; Kang, Seok-Gu [Yonsei University College of Medicine, Department of Neurosurgery, Seoul (Korea, Republic of); Kim, Se Hoon [Yonsei University College of Medicine, Department of Pathology, Seoul (Korea, Republic of); Zhou, Jinyuan [Johns Hopkins University School of Medicine, Division of MRI Research, Department of Radiology, Baltimore, MD (United States)

2017-08-15

To evaluate the added value of amide proton transfer (APT) imaging to the apparent diffusion coefficient (ADC) from diffusion tensor imaging (DTI) and the relative cerebral blood volume (rCBV) from perfusion magnetic resonance imaging (MRI) for discriminating between high- and low-grade gliomas. Forty-six consecutive adult patients with diffuse gliomas who underwent preoperative APT imaging, DTI and perfusion MRI were enrolled. APT signals were compared according to the World Health Organization grade. The diagnostic ability and added value of the APT signal to the ADC and rCBV for discriminating between low- and high-grade gliomas were evaluated using receiver operating characteristic (ROC) analyses and integrated discrimination improvement. The APT signal increased as the glioma grade increased. The discrimination abilities of the APT, ADC and rCBV values were not significantly different. Using both the APT signal and ADC significantly improved discrimination vs. the ADC alone (area under the ROC curve [AUC], 0.888 vs. 0.910; P = 0.007), whereas using both the APT signal and rCBV did not improve discrimination vs. the rCBV alone (AUC, 0.927 vs. 0.923; P = 0.222). APT imaging may be a useful imaging biomarker that adds value to the ADC for discriminating between low- and high-grade gliomas. (orig.)

Electrostatic X-ray image recording device with mesh-base photocathode photoelectron discriminator means

International Nuclear Information System (INIS)

1977-01-01

An electrostatic X-ray image recording device having a pair of spaced electrodes with a gas-filled gap therebetween, and including discrimination means, having a conductive mesh supporting a photocathodic material, positioned in the gas-filled gap between a first electrode having a layer of ultraviolet-emitting fluorescent material and a second electrode having a plastic sheet adjacent thereto for receiving photoelectrons emitted by the photocathodic material and accelerated to the second electrode by an applied field. The photoconductor-mesh element discriminates against fast electrons, produced by direct impingement of X-rays upon the photocathode to substantially reduce secondary electron production and amplification, thereby increasing both the signal-to-noise and contrast ratios. The electrostatic image formed on the plastic sheet is developed by zerographic techniques after exposure. (Auth.)

Discriminating image textures with the multiscale two-dimensional complexity-entropy causality plane

International Nuclear Information System (INIS)

Zunino, Luciano; Ribeiro, Haroldo V.

2016-01-01

The aim of this paper is to further explore the usefulness of the two-dimensional complexity-entropy causality plane as a texture image descriptor. A multiscale generalization is introduced in order to distinguish between different roughness features of images at small and large spatial scales. Numerically generated two-dimensional structures are initially considered for illustrating basic concepts in a controlled framework. Then, more realistic situations are studied. Obtained results allow us to confirm that intrinsic spatial correlations of images are successfully unveiled by implementing this multiscale symbolic information-theory approach. Consequently, we conclude that the proposed representation space is a versatile and practical tool for identifying, characterizing and discriminating image textures.

Animal Detection in Natural Images: Effects of Color and Image Database

Science.gov (United States)

Zhu, Weina; Drewes, Jan; Gegenfurtner, Karl R.

2013-01-01

The visual system has a remarkable ability to extract categorical information from complex natural scenes. In order to elucidate the role of low-level image features for the recognition of objects in natural scenes, we recorded saccadic eye movements and event-related potentials (ERPs) in two experiments, in which human subjects had to detect animals in previously unseen natural images. We used a new natural image database (ANID) that is free of some of the potential artifacts that have plagued the widely used COREL images. Color and grayscale images picked from the ANID and COREL databases were used. In all experiments, color images induced a greater N1 EEG component at earlier time points than grayscale images. We suggest that this influence of color in animal detection may be masked by later processes when measuring reation times. The ERP results of go/nogo and forced choice tasks were similar to those reported earlier. The non-animal stimuli induced bigger N1 than animal stimuli both in the COREL and ANID databases. This result indicates ultra-fast processing of animal images is possible irrespective of the particular database. With the ANID images, the difference between color and grayscale images is more pronounced than with the COREL images. The earlier use of the COREL images might have led to an underestimation of the contribution of color. Therefore, we conclude that the ANID image database is better suited for the investigation of the processing of natural scenes than other databases commonly used. PMID:24130744

Animal detection in natural images: effects of color and image database.

Directory of Open Access Journals (Sweden)

Weina Zhu

Full Text Available The visual system has a remarkable ability to extract categorical information from complex natural scenes. In order to elucidate the role of low-level image features for the recognition of objects in natural scenes, we recorded saccadic eye movements and event-related potentials (ERPs in two experiments, in which human subjects had to detect animals in previously unseen natural images. We used a new natural image database (ANID that is free of some of the potential artifacts that have plagued the widely used COREL images. Color and grayscale images picked from the ANID and COREL databases were used. In all experiments, color images induced a greater N1 EEG component at earlier time points than grayscale images. We suggest that this influence of color in animal detection may be masked by later processes when measuring reation times. The ERP results of go/nogo and forced choice tasks were similar to those reported earlier. The non-animal stimuli induced bigger N1 than animal stimuli both in the COREL and ANID databases. This result indicates ultra-fast processing of animal images is possible irrespective of the particular database. With the ANID images, the difference between color and grayscale images is more pronounced than with the COREL images. The earlier use of the COREL images might have led to an underestimation of the contribution of color. Therefore, we conclude that the ANID image database is better suited for the investigation of the processing of natural scenes than other databases commonly used.

Classification of Error-Diffused Halftone Images Based on Spectral Regression Kernel Discriminant Analysis

Directory of Open Access Journals (Sweden)

Zhigao Zeng

2016-01-01

Full Text Available This paper proposes a novel algorithm to solve the challenging problem of classifying error-diffused halftone images. We firstly design the class feature matrices, after extracting the image patches according to their statistics characteristics, to classify the error-diffused halftone images. Then, the spectral regression kernel discriminant analysis is used for feature dimension reduction. The error-diffused halftone images are finally classified using an idea similar to the nearest centroids classifier. As demonstrated by the experimental results, our method is fast and can achieve a high classification accuracy rate with an added benefit of robustness in tackling noise.

New Region-Scalable Discriminant and Fitting Energy Functional for Driving Geometric Active Contours in Medical Image Segmentation

Directory of Open Access Journals (Sweden)

Xuchu Wang

2014-01-01

that uses region-scalable discriminant and fitting energy functional for handling the intensity inhomogeneity and weak boundary problems in medical image segmentation. The region-scalable discriminant and fitting energy functional is defined to capture the image intensity characteristics in local and global regions for driving the evolution of active contour. The discriminant term in the model aims at separating background and foreground in scalable regions while the fitting term tends to fit the intensity in these regions. This model is then transformed into a variational level set formulation with a level set regularization term for accurate computation. The new model utilizes intensity information in the local and global regions as much as possible; so it not only handles better intensity inhomogeneity, but also allows more robustness to noise and more flexible initialization in comparison to the original global region and regional-scalable based models. Experimental results for synthetic and real medical image segmentation show the advantages of the proposed method in terms of accuracy and robustness.

Exploring coherent phenomena and energy discrimination in X-ray imaging

Energy Technology Data Exchange (ETDEWEB)

Koenig, Thomas

2011-05-04

Conventional X-ray imaging is based on the generation of photons in materials that are selected for different applications according to their densities, dimensions, and atomic numbers. The photons produced in these targets are commonly detected by measuring the integrated amount of energy released in films or digital imaging systems. This thesis aims at extending these two paradigms. First, it is shown that the use of single-crystalline, i.e. well-ordered targets, can significantly soften photon spectra created by megavoltage electrons when compared to usual targets. The reason for this is an effect called ''coherent bremsstrahlung''. It is shown that this type of radiation bears the potential of increasing the quality of megavoltage images and reducing radiation dose for image guided radiotherapy. Second, new spectroscopic pixel detectors of the Medipix2 family operated with cadmium telluride sensors are characterised and thus potential benefits and difficulties for X-ray imaging are investigated. Besides describing in detail how to calibrate these detectors, emphasis is placed on determining their energy responses, modulation transfer functions, and detective quantum efficiencies. Requirements for photon counting megavoltage imaging are discussed. The detector systems studied are finally used to perform spectral computed tomography and to illustrate the benefits of energy discrimination for coherent scatter imaging. (orig.)

Exploring coherent phenomena and energy discrimination in X-ray imaging

International Nuclear Information System (INIS)

Koenig, Thomas

2011-01-01

Conventional X-ray imaging is based on the generation of photons in materials that are selected for different applications according to their densities, dimensions, and atomic numbers. The photons produced in these targets are commonly detected by measuring the integrated amount of energy released in films or digital imaging systems. This thesis aims at extending these two paradigms. First, it is shown that the use of single-crystalline, i.e. well-ordered targets, can significantly soften photon spectra created by megavoltage electrons when compared to usual targets. The reason for this is an effect called ''coherent bremsstrahlung''. It is shown that this type of radiation bears the potential of increasing the quality of megavoltage images and reducing radiation dose for image guided radiotherapy. Second, new spectroscopic pixel detectors of the Medipix2 family operated with cadmium telluride sensors are characterised and thus potential benefits and difficulties for X-ray imaging are investigated. Besides describing in detail how to calibrate these detectors, emphasis is placed on determining their energy responses, modulation transfer functions, and detective quantum efficiencies. Requirements for photon counting megavoltage imaging are discussed. The detector systems studied are finally used to perform spectral computed tomography and to illustrate the benefits of energy discrimination for coherent scatter imaging. (orig.)

Comparison of simultaneous and sequential SPECT imaging for discrimination tasks in assessment of cardiac defects.

Science.gov (United States)

Trott, C M; Ouyang, J; El Fakhri, G

2010-11-21

Simultaneous rest perfusion/fatty-acid metabolism studies have the potential to replace sequential rest/stress perfusion studies for the assessment of cardiac function. Simultaneous acquisition has the benefits of increased signal and lack of need for patient stress, but is complicated by cross-talk between the two radionuclide signals. We consider a simultaneous rest (99m)Tc-sestamibi/(123)I-BMIPP imaging protocol in place of the commonly used sequential rest/stress (99m)Tc-sestamibi protocol. The theoretical precision with which the severity of a cardiac defect and the transmural extent of infarct can be measured is computed for simultaneous and sequential SPECT imaging, and their performance is compared for discriminating (1) degrees of defect severity and (2) sub-endocardial from transmural defects. We consider cardiac infarcts for which reduced perfusion and metabolism are observed. From an information perspective, simultaneous imaging is found to yield comparable or improved performance compared with sequential imaging for discriminating both severity of defect and transmural extent of infarct, for three defects of differing location and size.

Comparison of simultaneous and sequential SPECT imaging for discrimination tasks in assessment of cardiac defects

International Nuclear Information System (INIS)

Trott, C M; Ouyang, J; El Fakhri, G

2010-01-01

Simultaneous rest perfusion/fatty-acid metabolism studies have the potential to replace sequential rest/stress perfusion studies for the assessment of cardiac function. Simultaneous acquisition has the benefits of increased signal and lack of need for patient stress, but is complicated by cross-talk between the two radionuclide signals. We consider a simultaneous rest 99m Tc-sestamibi/ 123 I-BMIPP imaging protocol in place of the commonly used sequential rest/stress 99m Tc-sestamibi protocol. The theoretical precision with which the severity of a cardiac defect and the transmural extent of infarct can be measured is computed for simultaneous and sequential SPECT imaging, and their performance is compared for discriminating (1) degrees of defect severity and (2) sub-endocardial from transmural defects. We consider cardiac infarcts for which reduced perfusion and metabolism are observed. From an information perspective, simultaneous imaging is found to yield comparable or improved performance compared with sequential imaging for discriminating both severity of defect and transmural extent of infarct, for three defects of differing location and size.

Discrimination of Breast Tumors in Ultrasonic Images by Classifier Ensemble Trained with AdaBoost

Science.gov (United States)

Takemura, Atsushi; Shimizu, Akinobu; Hamamoto, Kazuhiko

In this paper, we propose a novel method for acurate automated discrimination of breast tumors (carcinoma, fibroadenoma, and cyst). We defined 199 features related to diagnositic observations noticed when a doctor judges breast tumors, such as internal echo, shape, and boundary echo. These features included novel features based on a parameter of log-compressed K distribution, which reflect physical characteristics of ultrasonic B-mode imaging. Furthermore, we propose a discrimination method of breast tumors by using an ensemble classifier based on the multi-class AdaBoost algorithm with effective features selection. Verification by analyzing 200 carcinomas, 30 fibroadenomas and 30 cycts showed the usefulness of the newly defined features and the effectiveness of the discrimination by using an ensemble classifier trained by AdaBoost.

Discrimination of nitrogen fertilizer levels of tea plant (Camellia sinensis) based on hyperspectral imaging.

Science.gov (United States)

Wang, Yujie; Hu, Xin; Hou, Zhiwei; Ning, Jingming; Zhang, Zhengzhu

2018-04-01

Nitrogen (N) fertilizer plays an important role in tea plantation management, with significant impacts on the photosynthetic capacity, productivity and nutrition status of tea plants. The present study aimed to establish a method for the discrimination of N fertilizer levels using hyperspectral imaging technique. Spectral data were extracted from the region of interest, followed by the first derivative to reduce background noise. Five optimal wavelengths were selected by principal component analysis. Texture features were extracted from the images at optimal wavelengths by gray-level gradient co-occurrence matrix. Support vector machine (SVM) and extreme learning machine were used to build classification models based on spectral data, optimal wavelengths, texture features and data fusion, respectively. The SVM model using fused data gave the best performance with highest correct classification rate of 100% for prediction set. The overall results indicated that visible and near-infrared hyperspectral imaging combined with SVM were effective in discriminating N fertilizer levels of tea plants. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Segmentation of MR images via discriminative dictionary learning and sparse coding: Application to hippocampus labeling

OpenAIRE

Tong, Tong; Wolz, Robin; Coupe, Pierrick; Hajnal, Joseph V.; Rueckert, Daniel

2013-01-01

International audience; We propose a novel method for the automatic segmentation of brain MRI images by using discriminative dictionary learning and sparse coding techniques. In the proposed method, dictionaries and classifiers are learned simultaneously from a set of brain atlases, which can then be used for the reconstruction and segmentation of an unseen target image. The proposed segmentation strategy is based on image reconstruction, which is in contrast to most existing atlas-based labe...

Binocular contrast-gain control for natural scenes: Image structure and phase alignment.

Science.gov (United States)

Huang, Pi-Chun; Dai, Yu-Ming

2018-05-01

In the context of natural scenes, we applied the pattern-masking paradigm to investigate how image structure and phase alignment affect contrast-gain control in binocular vision. We measured the discrimination thresholds of bandpass-filtered natural-scene images (targets) under various types of pedestals. Our first experiment had four pedestal types: bandpass-filtered pedestals, unfiltered pedestals, notch-filtered pedestals (which enabled removal of the spatial frequency), and misaligned pedestals (which involved rotation of unfiltered pedestals). Our second experiment featured six types of pedestals: bandpass-filtered, unfiltered, and notch-filtered pedestals, and the corresponding phase-scrambled pedestals. The thresholds were compared for monocular, binocular, and dichoptic viewing configurations. The bandpass-filtered pedestal and unfiltered pedestals showed classic dipper shapes; the dipper shapes of the notch-filtered, misaligned, and phase-scrambled pedestals were weak. We adopted a two-stage binocular contrast-gain control model to describe our results. We deduced that the phase-alignment information influenced the contrast-gain control mechanism before the binocular summation stage and that the phase-alignment information and structural misalignment information caused relatively strong divisive inhibition in the monocular and interocular suppression stages. When the pedestals were phase-scrambled, the elimination of the interocular suppression processing was the most convincing explanation of the results. Thus, our results indicated that both phase-alignment information and similar image structures cause strong interocular suppression. Copyright © 2018 Elsevier Ltd. All rights reserved.

Adaptable pattern recognition system for discriminating Melanocytic Nevi from Malignant Melanomas using plain photography images from different image databases.

Science.gov (United States)

Kostopoulos, Spiros A; Asvestas, Pantelis A; Kalatzis, Ioannis K; Sakellaropoulos, George C; Sakkis, Theofilos H; Cavouras, Dionisis A; Glotsos, Dimitris T

2017-09-01

The aim of this study was to propose features that evaluate pictorial differences between melanocytic nevus (mole) and melanoma lesions by computer-based analysis of plain photography images and to design a cross-platform, tunable, decision support system to discriminate with high accuracy moles from melanomas in different publicly available image databases. Digital plain photography images of verified mole and melanoma lesions were downloaded from (i) Edinburgh University Hospital, UK, (Dermofit, 330moles/70 melanomas, under signed agreement), from 5 different centers (Multicenter, 63moles/25 melanomas, publicly available), and from the Groningen University, Netherlands (Groningen, 100moles/70 melanomas, publicly available). Images were processed for outlining the lesion-border and isolating the lesion from the surrounding background. Fourteen features were generated from each lesion evaluating texture (4), structure (5), shape (4) and color (1). Features were subjected to statistical analysis for determining differences in pictorial properties between moles and melanomas. The Probabilistic Neural Network (PNN) classifier, the exhaustive search features selection, the leave-one-out (LOO), and the external cross-validation (ECV) methods were used to design the PR-system for discriminating between moles and melanomas. Statistical analysis revealed that melanomas as compared to moles were of lower intensity, of less homogenous surface, had more dark pixels with intensities spanning larger spectra of gray-values, contained more objects of different sizes and gray-levels, had more asymmetrical shapes and irregular outlines, had abrupt intensity transitions from lesion to background tissue, and had more distinct colors. The PR-system designed by the Dermofit images scored on the Dermofit images, using the ECV, 94.1%, 82.9%, 96.5% for overall accuracy, sensitivity, specificity, on the Multicenter Images 92.0%, 88%, 93.7% and on the Groningen Images 76.2%, 73.9%, 77

Natural radioactivity distribution images and their educational uses

International Nuclear Information System (INIS)

Mori, Chizuo; Sumi, Tetsuo; Miyahara, Hiroshi; Uritani, Akira; Nishina, Kojiro

1999-01-01

Distribution images of natural radioactivities in vegetables, meat and porcelain works were obtained by use of Imaging Plate with very high sensitivity to radiations. A brochure titled 'Natural Radiations through Naked Eyes' was published in both Japanese and English which included the images mentioned above. In this paper, the method to obtain the distribution images of extremely low level natural radioactivity, the content of the brochure and the effect of it to the public are described. (author)

Natural radioactivity distribution images and their educational uses

Energy Technology Data Exchange (ETDEWEB)

Mori, Chizuo; Sumi, Tetsuo [Aichi Institute of Technology, Toyota, Aichi (Japan); Miyahara, Hiroshi; Uritani, Akira; Nishina, Kojiro

1999-09-01

Distribution images of natural radioactivities in vegetables, meat and porcelain works were obtained by use of Imaging Plate with very high sensitivity to radiations. A brochure titled 'Natural Radiations through Naked Eyes' was published in both Japanese and English which included the images mentioned above. In this paper, the method to obtain the distribution images of extremely low level natural radioactivity, the content of the brochure and the effect of it to the public are described. (author)

Enhanced EDX images by fusion of multimodal SEM images using pansharpening techniques.

Science.gov (United States)

Franchi, G; Angulo, J; Moreaud, M; Sorbier, L

2018-01-01

The goal of this paper is to explore the potential interest of image fusion in the context of multimodal scanning electron microscope (SEM) imaging. In particular, we aim at merging the backscattered electron images that usually have a high spatial resolution but do not provide enough discriminative information to physically classify the nature of the sample, with energy-dispersive X-ray spectroscopy (EDX) images that have discriminative information but a lower spatial resolution. The produced images are named enhanced EDX. To achieve this goal, we have compared the results obtained with classical pansharpening techniques for image fusion with an original approach tailored for multimodal SEM fusion of information. Quantitative assessment is obtained by means of two SEM images and a simulated dataset produced by a software based on PENELOPE. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

Hip fracture discrimination by the Achilles Insight QUS imaging device

International Nuclear Information System (INIS)

Damilakis, John; Papadokostakis, George; Perisinakis, Kostas; Maris, Thomas G.; Karantanas, Apostolos H.

2007-01-01

The importance of osteoporosis as a major health problem is well recognized. Its major clinical manifestation is low energy fractures. Considerable effort has been directed towards search of noninvasive methods for assessing osteoporotic fracture risk. The aim of this study was to evaluate the ability of quantitative ultrasound (QUS) variables measured by a new heel QUS imaging device to discriminate between postmenopausal women with and without hip fracture. The subjects included 30 postmenopausal female patients with hip fracture and 30 age-matched healthy women. Measurements were acquired using the Achilles Insight QUS imaging device. Bone mineral density (BMD) measurements were carried out using the Lunar Prodigy DXA scanner. Achilles Insight provides images of the heel bone and measures broadband ultrasound attenuation (BUA) and speed of sound (SOS) values in a circular region of interest. A third QUS variable, the stiffness index (SI) was also determined. The short-term precision for healthy subjects was 2.05%, 0.17% and 1.91% for BUA, SOS and SI, respectively. Corresponding values for patients with fractures were 1.80%, 0.16% and 2.04%. All QUS variables measured using the Achilles Insight were significant discriminators of hip fractures (area under ROC curve = 0.77, 0.74 and 0.77 for BUA, SOS and SI, respectively). BMD measurements of the hip had the greatest discriminatory ability (area under ROC curve = 0.88). Statistically significant differences were found between the area under the ROC curve of BMD and the corresponding curves of the QUS variables (P < 0.05 for each of the three comparisons). QUS variables measured by Achilles Insight can be expected to be useful as indicators of the risk of hip fracture in postmenopausal women

Comparison of model and human observer performance for detection and discrimination tasks using dual-energy x-ray images

International Nuclear Information System (INIS)

Richard, Samuel; Siewerdsen, Jeffrey H.

2008-01-01

Model observer performance, computed theoretically using cascaded systems analysis (CSA), was compared to the performance of human observers in detection and discrimination tasks. Dual-energy (DE) imaging provided a wide range of acquisition and decomposition parameters for which observer performance could be predicted and measured. This work combined previously derived observer models (e.g., Fisher-Hotelling and non-prewhitening) with CSA modeling of the DE image noise-equivalent quanta (NEQ) and imaging task (e.g., sphere detection, shape discrimination, and texture discrimination) to yield theoretical predictions of detectability index (d ' ) and area under the receiver operating characteristic (A Z ). Theoretical predictions were compared to human observer performance assessed using 9-alternative forced-choice tests to yield measurement of A Z as a function of DE image acquisition parameters (viz., allocation of dose between the low- and high-energy images) and decomposition technique [viz., three DE image decomposition algorithms: standard log subtraction (SLS), simple-smoothing of the high-energy image (SSH), and anti-correlated noise reduction (ACNR)]. Results showed good agreement between theory and measurements over a broad range of imaging conditions. The incorporation of an eye filter and internal noise in the observer models demonstrated improved correspondence with human observer performance. Optimal acquisition and decomposition parameters were shown to depend on the imaging task; for example, ACNR and SSH yielded the greatest performance in the detection of soft-tissue and bony lesions, respectively. This study provides encouraging evidence that Fourier-based modeling of NEQ computed via CSA and imaging task provides a good approximation to human observer performance for simple imaging tasks, helping to bridge the gap between Fourier metrics of detector performance (e.g., NEQ) and human observer performance.

Using digital images to measure and discriminate small particles in cotton

Science.gov (United States)

Taylor, Robert A.; Godbey, Luther C.

1991-02-01

Inages from conventional video systems are being digitized in coraputers for the analysis of small trash particles in cotton. The method has been developed to automate particle counting and area measurements for bales of cotton prepared for market. Because the video output is linearly proportional to the amount of light reflected the best spectral band for optimum particle discrimination should be centered at the wavelength of maximum difference between particles and their surroundings. However due to the spectral distribution of the illumination energy and the detector sensitivity peak image performance bands were altered. Reflectance from seven mechanically cleaned cotton lint samples and trash removed were examined for spectral contrast in the wavelength range of camera sensitivity. Pixel intensity histograms from the video systent are reported for simulated trashmeter area reference samples (painted dots on panels) and for cotton containing trash to demonstrate the particle discrimination mechanism. 2.

Learning discriminant face descriptor.

Science.gov (United States)

Lei, Zhen; Pietikäinen, Matti; Li, Stan Z

2014-02-01

Local feature descriptor is an important module for face recognition and those like Gabor and local binary patterns (LBP) have proven effective face descriptors. Traditionally, the form of such local descriptors is predefined in a handcrafted way. In this paper, we propose a method to learn a discriminant face descriptor (DFD) in a data-driven way. The idea is to learn the most discriminant local features that minimize the difference of the features between images of the same person and maximize that between images from different people. In particular, we propose to enhance the discriminative ability of face representation in three aspects. First, the discriminant image filters are learned. Second, the optimal neighborhood sampling strategy is soft determined. Third, the dominant patterns are statistically constructed. Discriminative learning is incorporated to extract effective and robust features. We further apply the proposed method to the heterogeneous (cross-modality) face recognition problem and learn DFD in a coupled way (coupled DFD or C-DFD) to reduce the gap between features of heterogeneous face images to improve the performance of this challenging problem. Extensive experiments on FERET, CAS-PEAL-R1, LFW, and HFB face databases validate the effectiveness of the proposed DFD learning on both homogeneous and heterogeneous face recognition problems. The DFD improves POEM and LQP by about 4.5 percent on LFW database and the C-DFD enhances the heterogeneous face recognition performance of LBP by over 25 percent.

Hyperspectral image analysis for rapid and accurate discrimination of bacterial infections: A benchmark study.

Science.gov (United States)

Arrigoni, Simone; Turra, Giovanni; Signoroni, Alberto

2017-09-01

With the rapid diffusion of Full Laboratory Automation systems, Clinical Microbiology is currently experiencing a new digital revolution. The ability to capture and process large amounts of visual data from microbiological specimen processing enables the definition of completely new objectives. These include the direct identification of pathogens growing on culturing plates, with expected improvements in rapid definition of the right treatment for patients affected by bacterial infections. In this framework, the synergies between light spectroscopy and image analysis, offered by hyperspectral imaging, are of prominent interest. This leads us to assess the feasibility of a reliable and rapid discrimination of pathogens through the classification of their spectral signatures extracted from hyperspectral image acquisitions of bacteria colonies growing on blood agar plates. We designed and implemented the whole data acquisition and processing pipeline and performed a comprehensive comparison among 40 combinations of different data preprocessing and classification techniques. High discrimination performance has been achieved also thanks to improved colony segmentation and spectral signature extraction. Experimental results reveal the high accuracy and suitability of the proposed approach, driving the selection of most suitable and scalable classification pipelines and stimulating clinical validations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Aster images for discrimination of agricultural use areas in Colombia

International Nuclear Information System (INIS)

Ortiz L, Nidia E; Perez G Uriel

2009-01-01

The advance of geographical information technology has led to the placement of new sensors for earth observation. ASTER (Advanced Space borne Thermal Emission and Reflection Radiometer) is considered as a latest generation sensor. It has special characteristics that places it as an alternative for studies of vegetation cover on earth. This work is based on its spatial, spectral and radiometric features to discriminate agricultural areas in the irrigation district of USOCOELLO in Colombia. We used a level 1B image from 2006, geometrically corrected, re sampled and its radiance values transformed into reflectance values allowing us to make two compositions: original images (VNIR-SWIR) and fusion images in IHS transformation. The thematic legend was established from the classification scheme C orine Land Cover - Colombia , defining 10 representative coverage categories in the image. The maximum likelihood classifier was used in the allocation phase. In the process of verifying and quantifying the level of accuracy, it was used, as ground truth, the database of geographical area at the site in the same date that the image was taken, obtaining an estimating a global reliability of 75 % for VNIR - SWIR images; if the variability of phenological stages of crops (rice, maize and sorghum) in the area and an important space contrast in the fusion image are taken into account, the obtained Kappa index was 0,75, which means that there is a substantial degree of agreement.

Comparison between ultrasonography and MR imaging for discriminating squamous cell carcinoma nodes with extranodal spread in the neck

International Nuclear Information System (INIS)

Katayama, Ikuo; Sasaki, Miho; Kimura, Yasuo; Hotokezaka, Yuka; Eida, Sato; Tashiro, Shigeki; Sumi, Misa; Nakamura, Takashi

2012-01-01

Objective: To compare the diagnostic ability of ultrasonography (US) and MR imaging for discriminating squamous cell carcinoma (SCC) nodes with extranodal spread (ENS) in the neck. Methods: US and MR imaging was retrospectively evaluated for differentiating ENS-positive (n = 28) from ENS-negative (n = 26) SCC nodes (>10 mm short-axis diameter) in 50 patients with head and neck SCCs. We assessed nodal size on US and MR images; irregular nodal margin on US; and vanishing nodal border, flare, and shaggy nodal margin signs on T1-, fat-suppressed T2-, and contrast-enhanced T1-weighted MR images, respectively. US and MR images were analyzed by 3 radiologists in consensus and the results were compared between ENS-positive and ENS-negative SCC nodes. Results: The nodal sizes of ENS-positive nodes (21 ± 9 mm) were significantly larger than those of ENS-negative SCC nodes (14 ± 4 mm) (p < 0.001). Irregular nodal margins were more frequently observed in ENS-positive SCC nodes (75%) than in ENS-negative SCC nodes (12%). The vanishing nodal margin, flare, and shaggy nodal margin signs were more frequently observed in ENS-positive SCC nodes (93%, 89%, and 82%, respectively) than in ENS-negative nodes (46%, 19%, and 19%, respectively). A combination of size (≥22 mm) and imaging criteria (irregular margin or flare sign) best discriminated ENS-positive SCC nodes with 82% sensitivity, 89% specificity, and 85% accuracy for US and 89% sensitivity, 81% specificity, and 85% accuracy for MR imaging. Conclusion: US discriminated ENS-positive from ENS-negative SCC nodes with comparable accuracy and higher specificity than MR imaging.

Mnemonic discrimination relates to perforant path integrity: An ultra-high resolution diffusion tensor imaging study.

Science.gov (United States)

Bennett, Ilana J; Stark, Craig E L

2016-03-01

Pattern separation describes the orthogonalization of similar inputs into unique, non-overlapping representations. This computational process is thought to serve memory by reducing interference and to be mediated by the dentate gyrus of the hippocampus. Using ultra-high in-plane resolution diffusion tensor imaging (hrDTI) in older adults, we previously demonstrated that integrity of the perforant path, which provides input to the dentate gyrus from entorhinal cortex, was associated with mnemonic discrimination, a behavioral outcome designed to load on pattern separation. The current hrDTI study assessed the specificity of this perforant path integrity-mnemonic discrimination relationship relative to other cognitive constructs (identified using a factor analysis) and white matter tracts (hippocampal cingulum, fornix, corpus callosum) in 112 healthy adults (20-87 years). Results revealed age-related declines in integrity of the perforant path and other medial temporal lobe (MTL) tracts (hippocampal cingulum, fornix). Controlling for global effects of brain aging, perforant path integrity related only to the factor that captured mnemonic discrimination performance. Comparable integrity-mnemonic discrimination relationships were also observed for the hippocampal cingulum and fornix. Thus, whereas perforant path integrity specifically relates to mnemonic discrimination, mnemonic discrimination may be mediated by a broader MTL network. Copyright © 2015 Elsevier Inc. All rights reserved.

Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification.

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Wen, Zaidao; Hou, Biao; Jiao, Licheng

2017-05-03

Linear synthesis model based dictionary learning framework has achieved remarkable performances in image classification in the last decade. Behaved as a generative feature model, it however suffers from some intrinsic deficiencies. In this paper, we propose a novel parametric nonlinear analysis cosparse model (NACM) with which a unique feature vector will be much more efficiently extracted. Additionally, we derive a deep insight to demonstrate that NACM is capable of simultaneously learning the task adapted feature transformation and regularization to encode our preferences, domain prior knowledge and task oriented supervised information into the features. The proposed NACM is devoted to the classification task as a discriminative feature model and yield a novel discriminative nonlinear analysis operator learning framework (DNAOL). The theoretical analysis and experimental performances clearly demonstrate that DNAOL will not only achieve the better or at least competitive classification accuracies than the state-of-the-art algorithms but it can also dramatically reduce the time complexities in both training and testing phases.

[Correlation of diffusion tensor imaging between the cerebral cortex and speech discrimination in presbycusis].

Science.gov (United States)

Peng, Lu; Yu, Shuilian; Chen, Ruichun; Jing, Yan; Liang, Jianping

2015-09-01

To investigate the relationship between pure-tone average (PTA), the fractional anisotropy (FA) of the auditory pathway, cognitive cortex and auditory cortex in presbycusis. Twenty-five elderly subjects with presbycusis were participated in the study. PTA, speech discrimination abilities were evaluated in each subject. Diffusion tensor imaging (DTI) was applied to access the FA of the IC, the superior frontal gyrus and the Heschl's gyrus. Compare the difference between two sides of the values of FA in the three areas. Bivariate correlation analysis was performed to evaluate the effects of PTA and FA of the inferior colliculus (IC), the superior frontal gyrus and the Heschl's gyrus on speech discrimination abilities. There were no significant differences between the left and right side of the inferior colliculus (P > 0.05). Higher FA values were recorded at the left side of the Heschl's gyrus and the superior frontal gyrus (P < 0.05). Both PTA and the FA of the superior frontal gyrus have a negative association with speech discrimination abilities (P < 0.01, P < 0.05), while the FA of the Heschl's gyrus has a positive association with speech discrimination abilities (P < 0.05). Our findings indicated that the speech discrimination abilities of the elderly is not only related to the peripheral auditory function, but also to the central auditory and cognitive function.

Multiscale Region-Level VHR Image Change Detection via Sparse Change Descriptor and Robust Discriminative Dictionary Learning

Directory of Open Access Journals (Sweden)

Yuan Xu

2015-01-01

Full Text Available Very high resolution (VHR image change detection is challenging due to the low discriminative ability of change feature and the difficulty of change decision in utilizing the multilevel contextual information. Most change feature extraction techniques put emphasis on the change degree description (i.e., in what degree the changes have happened, while they ignore the change pattern description (i.e., how the changes changed, which is of equal importance in characterizing the change signatures. Moreover, the simultaneous consideration of the classification robust to the registration noise and the multiscale region-consistent fusion is often neglected in change decision. To overcome such drawbacks, in this paper, a novel VHR image change detection method is proposed based on sparse change descriptor and robust discriminative dictionary learning. Sparse change descriptor combines the change degree component and the change pattern component, which are encoded by the sparse representation error and the morphological profile feature, respectively. Robust change decision is conducted by multiscale region-consistent fusion, which is implemented by the superpixel-level cosparse representation with robust discriminative dictionary and the conditional random field model. Experimental results confirm the effectiveness of the proposed change detection technique.

CARS hyperspectral imaging of cartilage aiming for state discrimination of cell

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Shiozawa, Manabu; Shirai, Masataka; Izumisawa, Junko; Tanabe, Maiko; Watanabe, Koichi

2016-03-01

Non-invasive cell analyses are increasingly important for medical field. A CARS microscope is one of the non-invasive imaging equipments and enables to obtain images indicating molecular distribution. Some studies on discrimination of cell state by using CARS images of lipid are reported. However, due to low signal intensity, it is still challenging to obtain images of the fingerprint region (800~1800 cm-1), in which many spectrum peaks correspond to compositions of a cell. Here, to identify cell differentiation by using multiplex CARS, we investigated hyperspectral imaging of fingerprint region of living cells. To perform multiplex CARS, we used a prototype of a compact light source, which consists of a microchip laser, a single-mode fiber, and a photonic crystal fiber to generate supercontinuum light. Assuming application to regenerative medicine, we chose a cartilage cell, whose differentiation is difficult to be identified by change of the cell morphology. Because one of the major components of cartilage is collagen, we focused on distribution of proline, which accounts for approximately 20% of collagen in general. The spectrum quality was improved by optical adjustments about power branching ratio and divergence of broadband Stokes light. Hyperspectral images were successfully obtained by the improvement. Periphery of a cartilage cell was highlighted in CARS image of proline, and this result suggests correspondence with collagen generated as extracellular matrix. A possibility of cell analyses by using CARS hyperspectral imaging was indicated.

Some distinguishing characteristics of contour and texture phenomena in images

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Jobson, Daniel J.

1992-01-01

The development of generalized contour/texture discrimination techniques is a central element necessary for machine vision recognition and interpretation of arbitrary images. Here, the visual perception of texture, selected studies of texture analysis in machine vision, and diverse small samples of contour and texture are all used to provide insights into the fundamental characteristics of contour and texture. From these, an experimental discrimination scheme is developed and tested on a battery of natural images. The visual perception of texture defined fine texture as a subclass which is interpreted as shading and is distinct from coarse figural similarity textures. Also, perception defined the smallest scale for contour/texture discrimination as eight to nine visual acuity units. Three contour/texture discrimination parameters were found to be moderately successful for this scale discrimination: (1) lightness change in a blurred version of the image, (2) change in lightness change in the original image, and (3) percent change in edge counts relative to local maximum.

Optical redox imaging indices discriminate human breast cancer from normal tissues

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Xu, He N.; Tchou, Julia; Feng, Min; Zhao, Huaqing; Li, Lin Z.

2016-01-01

Abstract. Our long-term goal was to investigate the potential of incorporating redox imaging technique as a breast cancer (BC) diagnosis component to increase the positive predictive value of suspicious imaging finding and to reduce unnecessary biopsies and overdiagnosis. We previously found that precancer and cancer tissues in animal models displayed abnormal mitochondrial redox state. We also revealed abnormal mitochondrial redox state in cancerous specimens from three BC patients. Here, we extend our study to include biopsies of 16 patients. Tissue aliquots were collected from both apparently normal and cancerous tissues from the affected cancer-bearing breasts shortly after surgical resection. All specimens were snap-frozen and scanned with the Chance redox scanner, i.e., the three-dimensional cryogenic NADH/Fp (reduced nicotinamide adenine dinucleotide/oxidized flavoproteins) fluorescence imager. We found both Fp and NADH in the cancerous tissues roughly tripled that in the normal tissues (predox ratio Fp/(NADH + Fp) was ∼27% higher in the cancerous tissues (predox ratio alone could predict cancer with reasonable sensitivity and specificity. Our findings suggest that the optical redox imaging technique can provide parameters independent of clinical factors for discriminating cancer from noncancer breast tissues in human patients. PMID:27896360

Dimensionality Reduction of Hyperspectral Image with Graph-Based Discriminant Analysis Considering Spectral Similarity

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Fubiao Feng

2017-03-01

Full Text Available Recently, graph embedding has drawn great attention for dimensionality reduction in hyperspectral imagery. For example, locality preserving projection (LPP utilizes typical Euclidean distance in a heat kernel to create an affinity matrix and projects the high-dimensional data into a lower-dimensional space. However, the Euclidean distance is not sufficiently correlated with intrinsic spectral variation of a material, which may result in inappropriate graph representation. In this work, a graph-based discriminant analysis with spectral similarity (denoted as GDA-SS measurement is proposed, which fully considers curves changing description among spectral bands. Experimental results based on real hyperspectral images demonstrate that the proposed method is superior to traditional methods, such as supervised LPP, and the state-of-the-art sparse graph-based discriminant analysis (SGDA.

Dominant color and texture feature extraction for banknote discrimination

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Wang, Junmin; Fan, Yangyu; Li, Ning

2017-07-01

Banknote discrimination with image recognition technology is significant in many applications. The traditional methods based on image recognition only recognize the banknote denomination without discriminating the counterfeit banknote. To solve this problem, we propose a systematical banknote discrimination approach with the dominant color and texture features. After capturing the visible and infrared images of the test banknote, we first implement the tilt correction based on the principal component analysis (PCA) algorithm. Second, we extract the dominant color feature of the visible banknote image to recognize the denomination. Third, we propose an adaptively weighted local binary pattern with "delta" tolerance algorithm to extract the texture features of the infrared banknote image. At last, we discriminate the genuine or counterfeit banknote by comparing the texture features between the test banknote and the benchmark banknote. The proposed approach is tested using 14,000 banknotes of six different denominations from Chinese yuan (CNY). The experimental results show 100% accuracy for denomination recognition and 99.92% accuracy for counterfeit banknote discrimination.

Natural color image segmentation using integrated mechanism

Institute of Scientific and Technical Information of China (English)

Jie Xu (徐杰); Pengfei Shi (施鹏飞)

2003-01-01

A new method for natural color image segmentation using integrated mechanism is proposed in this paper.Edges are first detected in term of the high phase congruency in the gray-level image. K-mean cluster is used to label long edge lines based on the global color information to estimate roughly the distribution of objects in the image, while short ones are merged based on their positions and local color differences to eliminate the negative affection caused by texture or other trivial features in image. Region growing technique is employed to achieve final segmentation results. The proposed method unifies edges, whole and local color distributions, as well as spatial information to solve the natural image segmentation problem.The feasibility and effectiveness of this method have been demonstrated by various experiments.

Generalized image contrast enhancement technique based on Heinemann contrast discrimination model

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Liu, Hong; Nodine, Calvin F.

1994-03-01

This paper presents a generalized image contrast enhancement technique which equalizes perceived brightness based on the Heinemann contrast discrimination model. This is a modified algorithm which presents an improvement over the previous study by Mokrane in its mathematically proven existence of a unique solution and in its easily tunable parameterization. The model uses a log-log representation of contrast luminosity between targets and the surround in a fixed luminosity background setting. The algorithm consists of two nonlinear gray-scale mapping functions which have seven parameters, two of which are adjustable Heinemann constants. Another parameter is the background gray level. The remaining four parameters are nonlinear functions of gray scale distribution of the image, and can be uniquely determined once the previous three are given. Tests have been carried out to examine the effectiveness of the algorithm for increasing the overall contrast of images. It can be demonstrated that the generalized algorithm provides better contrast enhancement than histogram equalization. In fact, the histogram equalization technique is a special case of the proposed mapping.

Generalized image contrast enhancement technique based on the Heinemann contrast discrimination model

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Liu, Hong; Nodine, Calvin F.

1996-07-01

This paper presents a generalized image contrast enhancement technique, which equalizes the perceived brightness distribution based on the Heinemann contrast discrimination model. It is based on the mathematically proven existence of a unique solution to a nonlinear equation, and is formulated with easily tunable parameters. The model uses a two-step log-log representation of luminance contrast between targets and surround in a luminous background setting. The algorithm consists of two nonlinear gray scale mapping functions that have seven parameters, two of which are adjustable Heinemann constants. Another parameter is the background gray level. The remaining four parameters are nonlinear functions of the gray-level distribution of the given image, and can be uniquely determined once the previous three are set. Tests have been carried out to demonstrate the effectiveness of the algorithm for increasing the overall contrast of radiology images. The traditional histogram equalization can be reinterpreted as an image enhancement technique based on the knowledge of human contrast perception. In fact, it is a special case of the proposed algorithm.

Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning.

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Guo, Yanrong; Gao, Yaozong; Shao, Yeqin; Price, True; Oto, Aytekin; Shen, Dinggang

2014-07-01

Automatic prostate segmentation from MR images is an important task in various clinical applications such as prostate cancer staging and MR-guided radiotherapy planning. However, the large appearance and shape variations of the prostate in MR images make the segmentation problem difficult to solve. Traditional Active Shape/Appearance Model (ASM/AAM) has limited accuracy on this problem, since its basic assumption, i.e., both shape and appearance of the targeted organ follow Gaussian distributions, is invalid in prostate MR images. To this end, the authors propose a sparse dictionary learning method to model the image appearance in a nonparametric fashion and further integrate the appearance model into a deformable segmentation framework for prostate MR segmentation. To drive the deformable model for prostate segmentation, the authors propose nonparametric appearance and shape models. The nonparametric appearance model is based on a novel dictionary learning method, namely distributed discriminative dictionary (DDD) learning, which is able to capture fine distinctions in image appearance. To increase the differential power of traditional dictionary-based classification methods, the authors' DDD learning approach takes three strategies. First, two dictionaries for prostate and nonprostate tissues are built, respectively, using the discriminative features obtained from minimum redundancy maximum relevance feature selection. Second, linear discriminant analysis is employed as a linear classifier to boost the optimal separation between prostate and nonprostate tissues, based on the representation residuals from sparse representation. Third, to enhance the robustness of the authors' classification method, multiple local dictionaries are learned for local regions along the prostate boundary (each with small appearance variations), instead of learning one global classifier for the entire prostate. These discriminative dictionaries are located on different patches of the

Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning

Science.gov (United States)

Guo, Yanrong; Gao, Yaozong; Shao, Yeqin; Price, True; Oto, Aytekin; Shen, Dinggang

2014-01-01

Purpose: Automatic prostate segmentation from MR images is an important task in various clinical applications such as prostate cancer staging and MR-guided radiotherapy planning. However, the large appearance and shape variations of the prostate in MR images make the segmentation problem difficult to solve. Traditional Active Shape/Appearance Model (ASM/AAM) has limited accuracy on this problem, since its basic assumption, i.e., both shape and appearance of the targeted organ follow Gaussian distributions, is invalid in prostate MR images. To this end, the authors propose a sparse dictionary learning method to model the image appearance in a nonparametric fashion and further integrate the appearance model into a deformable segmentation framework for prostate MR segmentation. Methods: To drive the deformable model for prostate segmentation, the authors propose nonparametric appearance and shape models. The nonparametric appearance model is based on a novel dictionary learning method, namely distributed discriminative dictionary (DDD) learning, which is able to capture fine distinctions in image appearance. To increase the differential power of traditional dictionary-based classification methods, the authors' DDD learning approach takes three strategies. First, two dictionaries for prostate and nonprostate tissues are built, respectively, using the discriminative features obtained from minimum redundancy maximum relevance feature selection. Second, linear discriminant analysis is employed as a linear classifier to boost the optimal separation between prostate and nonprostate tissues, based on the representation residuals from sparse representation. Third, to enhance the robustness of the authors' classification method, multiple local dictionaries are learned for local regions along the prostate boundary (each with small appearance variations), instead of learning one global classifier for the entire prostate. These discriminative dictionaries are located on different

Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning

International Nuclear Information System (INIS)

Guo, Yanrong; Shao, Yeqin; Gao, Yaozong; Price, True; Oto, Aytekin; Shen, Dinggang

2014-01-01

Purpose: Automatic prostate segmentation from MR images is an important task in various clinical applications such as prostate cancer staging and MR-guided radiotherapy planning. However, the large appearance and shape variations of the prostate in MR images make the segmentation problem difficult to solve. Traditional Active Shape/Appearance Model (ASM/AAM) has limited accuracy on this problem, since its basic assumption, i.e., both shape and appearance of the targeted organ follow Gaussian distributions, is invalid in prostate MR images. To this end, the authors propose a sparse dictionary learning method to model the image appearance in a nonparametric fashion and further integrate the appearance model into a deformable segmentation framework for prostate MR segmentation. Methods: To drive the deformable model for prostate segmentation, the authors propose nonparametric appearance and shape models. The nonparametric appearance model is based on a novel dictionary learning method, namely distributed discriminative dictionary (DDD) learning, which is able to capture fine distinctions in image appearance. To increase the differential power of traditional dictionary-based classification methods, the authors' DDD learning approach takes three strategies. First, two dictionaries for prostate and nonprostate tissues are built, respectively, using the discriminative features obtained from minimum redundancy maximum relevance feature selection. Second, linear discriminant analysis is employed as a linear classifier to boost the optimal separation between prostate and nonprostate tissues, based on the representation residuals from sparse representation. Third, to enhance the robustness of the authors' classification method, multiple local dictionaries are learned for local regions along the prostate boundary (each with small appearance variations), instead of learning one global classifier for the entire prostate. These discriminative dictionaries are located on

Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning

Energy Technology Data Exchange (ETDEWEB)

Guo, Yanrong; Shao, Yeqin [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 (United States); Gao, Yaozong; Price, True [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 and Department of Computer Science, University of North Carolina at Chapel Hill, North Carolina 27599 (United States); Oto, Aytekin [Department of Radiology, Section of Urology, University of Chicago, Illinois 60637 (United States); Shen, Dinggang, E-mail: dgshen@med.unc.edu [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 and Department of Brain and Cognitive Engineering, Korea University, Seoul 136-713 (Korea, Republic of)

2014-07-15

Purpose: Automatic prostate segmentation from MR images is an important task in various clinical applications such as prostate cancer staging and MR-guided radiotherapy planning. However, the large appearance and shape variations of the prostate in MR images make the segmentation problem difficult to solve. Traditional Active Shape/Appearance Model (ASM/AAM) has limited accuracy on this problem, since its basic assumption, i.e., both shape and appearance of the targeted organ follow Gaussian distributions, is invalid in prostate MR images. To this end, the authors propose a sparse dictionary learning method to model the image appearance in a nonparametric fashion and further integrate the appearance model into a deformable segmentation framework for prostate MR segmentation. Methods: To drive the deformable model for prostate segmentation, the authors propose nonparametric appearance and shape models. The nonparametric appearance model is based on a novel dictionary learning method, namely distributed discriminative dictionary (DDD) learning, which is able to capture fine distinctions in image appearance. To increase the differential power of traditional dictionary-based classification methods, the authors' DDD learning approach takes three strategies. First, two dictionaries for prostate and nonprostate tissues are built, respectively, using the discriminative features obtained from minimum redundancy maximum relevance feature selection. Second, linear discriminant analysis is employed as a linear classifier to boost the optimal separation between prostate and nonprostate tissues, based on the representation residuals from sparse representation. Third, to enhance the robustness of the authors' classification method, multiple local dictionaries are learned for local regions along the prostate boundary (each with small appearance variations), instead of learning one global classifier for the entire prostate. These discriminative dictionaries are located on

Radar image and data fusion for natural hazards characterisation

Science.gov (United States)

Lu, Zhong; Dzurisin, Daniel; Jung, Hyung-Sup; Zhang, Jixian; Zhang, Yonghong

2010-01-01

Fusion of synthetic aperture radar (SAR) images through interferometric, polarimetric and tomographic processing provides an all - weather imaging capability to characterise and monitor various natural hazards. This article outlines interferometric synthetic aperture radar (InSAR) processing and products and their utility for natural hazards characterisation, provides an overview of the techniques and applications related to fusion of SAR/InSAR images with optical and other images and highlights the emerging SAR fusion technologies. In addition to providing precise land - surface digital elevation maps, SAR - derived imaging products can map millimetre - scale elevation changes driven by volcanic, seismic and hydrogeologic processes, by landslides and wildfires and other natural hazards. With products derived from the fusion of SAR and other images, scientists can monitor the progress of flooding, estimate water storage changes in wetlands for improved hydrological modelling predictions and assessments of future flood impacts and map vegetation structure on a global scale and monitor its changes due to such processes as fire, volcanic eruption and deforestation. With the availability of SAR images in near real - time from multiple satellites in the near future, the fusion of SAR images with other images and data is playing an increasingly important role in understanding and forecasting natural hazards.

Potential for observing and discriminating impact craters and comparable volcanic landforms on Magellan radar images

International Nuclear Information System (INIS)

Ford, J.P.

1989-01-01

Observations of small terrestrial craters by Seasat synthetic aperture radar (SAR) at high resolution (approx. 25 m) and of comparatively large Venusian craters by Venera 15/16 images at low resolution (1000 to 2000 m) and shorter wavelength show similarities in the radar responses to crater morphology. At low incidence angles, the responses are dominated by large scale slope effects on the order of meters; consequently it is difficult to locate the precise position of crater rims on the images. Abrupt contrasts in radar response to changing slope (hence incidence angle) across a crater produce sharp tonal boundaries normal to the illumination. Crater morphology that is radially symmetrical appears on images to have bilateral symmetry parallel to the illumination vector. Craters are compressed in the distal sector and drawn out in the proximal sector. At higher incidence angles obtained with the viewing geometry of SIR-A, crater morphology appears less compressed on the images. At any radar incidence angle, the distortion of a crater outline is minimal across the medial sector, in a direction normal to the illumination. Radar bright halos surround some craters imaged by SIR-A and Venera 15 and 16. The brightness probably denotes the radar response to small scale surface roughness of the surrounding ejecta blankets. Similarities in the radar responses of small terrestrial impact craters and volcanic craters of comparable dimensions emphasize the difficulties in discriminating an impact origin from a volcanic origin in the images. Similar difficulties will probably apply in discriminating the origin of small Venusian craters, if they exist. Because of orbital considerations, the nominal incidence angel of Magellan radar at the center of the imaging swath will vary from about 45 deg at 10 deg N latitude to about 16 deg at the north pole and at 70 deg S latitude. Impact craters and comparable volcanic landforms will show bilateral symmetry

Boosting bonsai trees for handwritten/printed text discrimination

Science.gov (United States)

Ricquebourg, Yann; Raymond, Christian; Poirriez, Baptiste; Lemaitre, Aurélie; Coüasnon, Bertrand

2013-12-01

Boosting over decision-stumps proved its efficiency in Natural Language Processing essentially with symbolic features, and its good properties (fast, few and not critical parameters, not sensitive to over-fitting) could be of great interest in the numeric world of pixel images. In this article we investigated the use of boosting over small decision trees, in image classification processing, for the discrimination of handwritten/printed text. Then, we conducted experiments to compare it to usual SVM-based classification revealing convincing results with very close performance, but with faster predictions and behaving far less as a black-box. Those promising results tend to make use of this classifier in more complex recognition tasks like multiclass problems.

The self-nonself discrimination and the nature and acquisition of the antibody repertoire.

Science.gov (United States)

Coutinho, A

1980-01-01

Network ideas are confronted with current hypotheses for the origin of antibody diversity and self-nonself discrimination. The difficulties of reconciling the promethean evolution of the antibody system with "germ line" theories are discussed, as well as the problems of "somatic" hypotheses to explain the completeness of the antibody repertoire. The formal incompatibility of the network theory with ideas basing self-nonself discrimination on the elimination of self-reactive cells is demonstrated, as well as the difficulties of these and other environment-dependent hypotheses for lymphocyte activation, to encompass the internal activity in the immune system. It is argued, on the other hand, that the limitations of the network theory in providing a functional basis for the idiotypic network and in accounting for self-nonself discrimination, can be solved by finding in a complete repertoire of antibody-combining sites the complementary structures to growth receptors on B lymphocytes, and by using these as internal mitogens in the expansion of the precursor cell pools and in the maintenance of the mature steady states. Letting self-nonself discrimination be accounted for by such growth receptors, both the integrity of the antibody repertoire and the internal activity in the system can also be ensured. Moreover, by postulating a germ line origin for the antireceptor antibodies and by accepting idiotypic cross-reactivity between growth receptors and other germ line antibodies, the possibilities are set for a phylogenetically and ontogenically autonomous immune system embodied with the capabilities for self-expansion, diversification and selection of available repertoires. Its promethean characteristics are explained by its completeness, and this is achieved by idiotypic interactions between growth receptors and a limited number of complementary or cross-reactive germ line antibodies, naturally selected on the basis of their structural relationships with growth receptors.

43 CFR 34.4 - Discrimination prohibited.

Science.gov (United States)

2010-10-01

... 43 Public Lands: Interior 1 2010-10-01 2010-10-01 false Discrimination prohibited. 34.4 Section 34... DURING CONSTRUCTION AND OPERATION OF THE ALASKA NATURAL GAS TRANSPORTATION SYSTEM § 34.4 Discrimination... part applies. (b) Specific actions in which discrimination is prohibited. No person shall directly or...

Automated discrimination of lower and higher grade gliomas based on histopathological image analysis

Directory of Open Access Journals (Sweden)

Hojjat Seyed Mousavi

2015-01-01

Full Text Available Introduction: Histopathological images have rich structural information, are multi-channel in nature and contain meaningful pathological information at various scales. Sophisticated image analysis tools that can automatically extract discriminative information from the histopathology image slides for diagnosis remain an area of significant research activity. In this work, we focus on automated brain cancer grading, specifically glioma grading. Grading of a glioma is a highly important problem in pathology and is largely done manually by medical experts based on an examination of pathology slides (images. To complement the efforts of clinicians engaged in brain cancer diagnosis, we develop novel image processing algorithms and systems to automatically grade glioma tumor into two categories: Low-grade glioma (LGG and high-grade glioma (HGG which represent a more advanced stage of the disease. Results: We propose novel image processing algorithms based on spatial domain analysis for glioma tumor grading that will complement the clinical interpretation of the tissue. The image processing techniques are developed in close collaboration with medical experts to mimic the visual cues that a clinician looks for in judging of the grade of the disease. Specifically, two algorithmic techniques are developed: (1 A cell segmentation and cell-count profile creation for identification of Pseudopalisading Necrosis, and (2 a customized operation of spatial and morphological filters to accurately identify microvascular proliferation (MVP. In both techniques, a hierarchical decision is made via a decision tree mechanism. If either Pseudopalisading Necrosis or MVP is found present in any part of the histopathology slide, the whole slide is identified as HGG, which is consistent with World Health Organization guidelines. Experimental results on the Cancer Genome Atlas database are presented in the form of: (1 Successful detection rates of pseudopalisading necrosis

The neural network involved in a bimanual tactile-tactile matching discrimination task: a functional imaging study at 3 T

Energy Technology Data Exchange (ETDEWEB)

Habas, Christophe; Cabanis, Emmanuel A. [UPMC Paris 6, Service de NeuroImagerie, Hopital des Quinze-Vingts, Paris (France)

2007-08-15

The cerebral and cerebellar network involved in a bimanual object recognition was studied in blood oxygenation dependent level functional magnetic resonance imaging (fMRI). Nine healthy right-handed volunteers were scanned (1) while performing bilateral finger movements (nondiscrimination motor task), and (2) while performing a bimanual tactile-tactile matching discrimination task using small chess pieces (tactile discrimination task). Extensive activations were specifically observed in the parietal (SII, superior lateral lobule), insular, prefrontal, cingulate and neocerebellar cortices (HVIII), with a left predominance in motor areas, during the tactile discrimination task in contrast to the findings during the nondiscrimination motor task. Bimanual tactile-tactile matching discrimination recruits multiple sensorimotor and associative cerebral and neocerebellar networks (including the cerebellar second homunculus, HVIII), comparable to the neural circuits involved in unimanual tactile object recognition. (orig.)

MALDI imaging mass spectrometry: discrimination of pathophysiological regions in traumatized skeletal muscle by characteristic peptide signatures.

Science.gov (United States)

Klein, Oliver; Strohschein, Kristin; Nebrich, Grit; Oetjen, Janina; Trede, Dennis; Thiele, Herbert; Alexandrov, Theodore; Giavalisco, Patrick; Duda, Georg N; von Roth, Philipp; Geissler, Sven; Klose, Joachim; Winkler, Tobias

2014-10-01

Due to formation of fibrosis and the loss of contractile muscle tissue, severe muscle injuries often result in insufficient healing marked by a significant reduction of muscle force and motor activity. Our previous studies demonstrated that the local transplantation of mesenchymal stromal cells into an injured skeletal muscle of the rat improves the functional outcome of the healing process. Since, due to the lack of sufficient markers, the accurate discrimination of pathophysiological regions in injured skeletal muscle is inadequate, underlying mechanisms of the beneficial effects of mesenchymal stromal cell transplantation on primary trauma and trauma adjacent muscle area remain elusive. For discrimination of these pathophysiological regions, formalin-fixed injured skeletal muscle tissue was analyzed by MALDI imaging MS. By using two computational evaluation strategies, a supervised approach (ClinProTools) and unsupervised segmentation (SCiLS Lab), characteristic m/z species could be assigned to primary trauma and trauma adjacent muscle regions. Using "bottom-up" MS for protein identification and validation of results by immunohistochemistry, we could identify two proteins, skeletal muscle alpha actin and carbonic anhydrase III, which discriminate between the secondary damage on adjacent tissue and the primary traumatized muscle area. Our results underscore the high potential of MALDI imaging MS to describe the spatial characteristics of pathophysiological changes in muscle. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Device for the track useful signal discrimination during the image scanning form bubble chambers

International Nuclear Information System (INIS)

Osipov, E.A.; Uvarov, V.A.

1976-01-01

A device for the image processing from the bubble chambers, developed to increase the reliability of the track useful signal discrimination at the image scanning from the background component is described. The device consists of a low-pass filter, repetition and memory circuit and subtraction circuit. Besides a delay line and extra channel consisting of a differentiating circuit in series with the selective shaping circuit are introduced into the device. The output signal of the selective shaping is the controlling signal of the repetition and memory circuit, at the output of which a signal corresponding the background component is formed. The functional diagram of the device operation is presented

Bloodstain detection and discrimination impacted by spectral shift when using an interference filter-based visible and near-infrared multispectral crime scene imaging system

Science.gov (United States)

Yang, Jie; Messinger, David W.; Dube, Roger R.

2018-03-01

Bloodstain detection and discrimination from nonblood substances on various substrates are critical in forensic science as bloodstains are a critical source for confirmatory DNA tests. Conventional bloodstain detection methods often involve time-consuming sample preparation, a chance of harm to investigators, the possibility of destruction of blood samples, and acquisition of too little data at crime scenes either in the field or in the laboratory. An imaging method has the advantages of being nondestructive, noncontact, real-time, and covering a large field-of-view. The abundant spectral information provided by multispectral imaging makes it a potential presumptive bloodstain detection and discrimination method. This article proposes an interference filter (IF) based area scanning three-spectral-band crime scene imaging system used for forensic bloodstain detection and discrimination. The impact of large angle of views on the spectral shift of calibrated IFs is determined, for both detecting and discriminating bloodstains from visually similar substances on multiple substrates. Spectral features in the visible and near-infrared portion employed by the relative band depth method are used. This study shows that 1 ml bloodstain on black felt, gray felt, red felt, white cotton, white polyester, and raw wood can be detected. Bloodstains on the above substrates can be discriminated from cola, coffee, ketchup, orange juice, red wine, and green tea.

Cell nuclei segmentation in fluorescence microscopy images using inter- and intra-region discriminative information.

Science.gov (United States)

Song, Yang; Cai, Weidong; Feng, David Dagan; Chen, Mei

2013-01-01

Automated segmentation of cell nuclei in microscopic images is critical to high throughput analysis of the ever increasing amount of data. Although cell nuclei are generally visually distinguishable for human, automated segmentation faces challenges when there is significant intensity inhomogeneity among cell nuclei or in the background. In this paper, we propose an effective method for automated cell nucleus segmentation using a three-step approach. It first obtains an initial segmentation by extracting salient regions in the image, then reduces false positives using inter-region feature discrimination, and finally refines the boundary of the cell nuclei using intra-region contrast information. This method has been evaluated on two publicly available datasets of fluorescence microscopic images with 4009 cells, and has achieved superior performance compared to popular state of the art methods using established metrics.

Discriminative Structured Dictionary Learning on Grassmann Manifolds and Its Application on Image Restoration.

Science.gov (United States)

Pan, Han; Jing, Zhongliang; Qiao, Lingfeng; Li, Minzhe

2017-09-25

Image restoration is a difficult and challenging problem in various imaging applications. However, despite of the benefits of a single overcomplete dictionary, there are still several challenges for capturing the geometric structure of image of interest. To more accurately represent the local structures of the underlying signals, we propose a new problem formulation for sparse representation with block-orthogonal constraint. There are three contributions. First, a framework for discriminative structured dictionary learning is proposed, which leads to a smooth manifold structure and quotient search spaces. Second, an alternating minimization scheme is proposed after taking both the cost function and the constraints into account. This is achieved by iteratively alternating between updating the block structure of the dictionary defined on Grassmann manifold and sparsifying the dictionary atoms automatically. Third, Riemannian conjugate gradient is considered to track local subspaces efficiently with a convergence guarantee. Extensive experiments on various datasets demonstrate that the proposed method outperforms the state-of-the-art methods on the removal of mixed Gaussian-impulse noise.

On the nature of the mental image

NARCIS (Netherlands)

Janssen, Wiel

1976-01-01

The present study investigates the nature of the so-called visual mental image. Specifically it is examined to what degree there is a correspondence between the structures of visual images and visual percepts. After introducing the general problem in Chapter 1 the functional significance of mental

Pseudo natural colour aerial imagery for urban and suburban mapping

DEFF Research Database (Denmark)

Knudsen, Thomas

2005-01-01

Due to their near-infrared data channel, digital airborne four-channel imagers provide a potentially good discrimination between vegetation and human-made materials, which is very useful in automated mapping. Due to their red, green and blue data channels, they also provide natural colour images......, which are very useful in traditional (manual) mapping. In this paper, an algorithm is described which provides an approximation to the spectral capabilities of the four-channel imagers by using a colour-infrared aerial photo as input. The algorithm is tailored to urban/suburban surroundings, where...... the quality of the generated (pseudo) natural colour images are fully acceptable for manual mapping. This brings the combined availability of near-infrared and (pseudo) natural colours within reach for mapping projects based on traditional photogrammetry, which is valuable since traditional analytical cameras...

Is the preference of natural versus man-made scenes driven by bottom-up processing of the visual features of nature?

Directory of Open Access Journals (Sweden)

Omid eKardan

2015-04-01

Full Text Available Previous research has shown that viewing images of nature scenes can have a beneficial effect on memory, attention and mood. In this study we aimed to determine whether the preference of natural versus man-made scenes is driven by bottom-up processing of the low-level visual features of nature. We used participants’ ratings of perceived naturalness as well as aesthetic preference for 307 images with varied natural and urban content. We then quantified ten low-level image features for each image (a combination of spatial and color properties. These features were used to predict aesthetic preference in the images, as well as to decompose perceived naturalness to its predictable (modelled by the low-level visual features and non-modelled aspects. Interactions of these separate aspects of naturalness with the time it took to make a preference judgment showed that naturalness based on low-level features related more to preference when the judgment was faster (bottom-up. On the other hand perceived naturalness that was not modelled by low-level features was related more to preference when the judgment was slower. A quadratic discriminant classification analysis showed how relevant each aspect of naturalness (modelled and non-modelled was to predicting preference ratings, as well as the image features on their own. Finally, we compared the effect of color-related and structure-related modelled naturalness, and the remaining unmodelled naturalness in predicting aesthetic preference. In summary bottom-up (color and spatial properties of natural images captured by our features and the non-modelled naturalness are important to aesthetic judgments of natural and man-made scenes, with each predicting unique variance.

Sub-pattern based multi-manifold discriminant analysis for face recognition

Science.gov (United States)

Dai, Jiangyan; Guo, Changlu; Zhou, Wei; Shi, Yanjiao; Cong, Lin; Yi, Yugen

2018-04-01

In this paper, we present a Sub-pattern based Multi-manifold Discriminant Analysis (SpMMDA) algorithm for face recognition. Unlike existing Multi-manifold Discriminant Analysis (MMDA) approach which is based on holistic information of face image for recognition, SpMMDA operates on sub-images partitioned from the original face image and then extracts the discriminative local feature from the sub-images separately. Moreover, the structure information of different sub-images from the same face image is considered in the proposed method with the aim of further improve the recognition performance. Extensive experiments on three standard face databases (Extended YaleB, CMU PIE and AR) demonstrate that the proposed method is effective and outperforms some other sub-pattern based face recognition methods.

Excitation-scanning hyperspectral imaging as a means to discriminate various tissues types

Science.gov (United States)

Deal, Joshua; Favreau, Peter F.; Lopez, Carmen; Lall, Malvika; Weber, David S.; Rich, Thomas C.; Leavesley, Silas J.

2017-02-01

Little is currently known about the fluorescence excitation spectra of disparate tissues and how these spectra change with pathological state. Current imaging diagnostic techniques have limited capacity to investigate fluorescence excitation spectral characteristics. This study utilized excitation-scanning hyperspectral imaging to perform a comprehensive assessment of fluorescence spectral signatures of various tissues. Immediately following tissue harvest, a custom inverted microscope (TE-2000, Nikon Instruments) with Xe arc lamp and thin film tunable filter array (VersaChrome, Semrock, Inc.) were used to acquire hyperspectral image data from each sample. Scans utilized excitation wavelengths from 340 nm to 550 nm in 5 nm increments. Hyperspectral images were analyzed with custom Matlab scripts including linear spectral unmixing (LSU), principal component analysis (PCA), and Gaussian mixture modeling (GMM). Spectra were examined for potential characteristic features such as consistent intensity peaks at specific wavelengths or intensity ratios among significant wavelengths. The resultant spectral features were conserved among tissues of similar molecular composition. Additionally, excitation spectra appear to be a mixture of pure endmembers with commonalities across tissues of varied molecular composition, potentially identifiable through GMM. These results suggest the presence of common autofluorescent molecules in most tissues and that excitationscanning hyperspectral imaging may serve as an approach for characterizing tissue composition as well as pathologic state. Future work will test the feasibility of excitation-scanning hyperspectral imaging as a contrast mode for discriminating normal and pathological tissues.

Discriminating Phytoplankton Functional Types (PFTs) in the Coastal Ocean Using the Inversion Algorithm Phydotax and Airborne Imaging Spectrometer Data

Science.gov (United States)

Palacios, Sherry L.; Schafer, Chris; Broughton, Jennifer; Guild, Liane S.; Kudela, Raphael M.

2013-01-01

There is a need in the Biological Oceanography community to discriminate among phytoplankton groups within the bulk chlorophyll pool to understand energy flow through ecosystems, to track the fate of carbon in the ocean, and to detect and monitor-for harmful algal blooms (HABs). The ocean color community has responded to this demand with the development of phytoplankton functional type (PFT) discrimination algorithms. These PFT algorithms fall into one of three categories depending on the science application: size-based, biogeochemical function, and taxonomy. The new PFT algorithm Phytoplankton Detection with Optics (PHYDOTax) is an inversion algorithm that discriminates taxon-specific biomass to differentiate among six taxa found in the California Current System: diatoms, dinoflagellates, haptophytes, chlorophytes, cryptophytes, and cyanophytes. PHYDOTax was developed and validated in Monterey Bay, CA for the high resolution imaging spectrometer, Spectroscopic Aerial Mapping System with On-board Navigation (SAMSON - 3.5 nm resolution). PHYDOTax exploits the high spectral resolution of an imaging spectrometer and the improved spatial resolution that airborne data provides for coastal areas. The objective of this study was to apply PHYDOTax to a relatively lower resolution imaging spectrometer to test the algorithm's sensitivity to atmospheric correction, to evaluate capability with other sensors, and to determine if down-sampling spectral resolution would degrade its ability to discriminate among phytoplankton taxa. This study is a part of the larger Hyperspectral Infrared Imager (HyspIRI) airborne simulation campaign which is collecting Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery aboard NASA's ER-2 aircraft during three seasons in each of two years over terrestrial and marine targets in California. Our aquatic component seeks to develop and test algorithms to retrieve water quality properties (e.g. HABs and river plumes) in both marine and in

How daylight influences high-order chromatic descriptors in natural images.

Science.gov (United States)

Ojeda, Juan; Nieves, Juan Luis; Romero, Javier

2017-07-01

Despite the global and local daylight changes naturally occurring in natural scenes, the human visual system usually adapts quite well to those changes, developing a stable color perception. Nevertheless, the influence of daylight in modeling natural image statistics is not fully understood and has received little attention. The aim of this work was to analyze the influence of daylight changes in different high-order chromatic descriptors (i.e., color volume, color gamut, and number of discernible colors) derived from 350 color images, which were rendered under 108 natural illuminants with Correlated Color Temperatures (CCT) from 2735 to 25,889 K. Results suggest that chromatic and luminance information is almost constant and does not depend on the CCT of the illuminant for values above 14,000 K. Nevertheless, differences between the red-green and blue-yellow image components were found below that CCT, with most of the statistical descriptors analyzed showing local extremes in the range 2950 K-6300 K. Uniform regions and areas of the images attracting observers' attention were also considered in this analysis and were characterized by their patchiness index and their saliency maps. Meanwhile, the results of the patchiness index do not show a clear dependence on CCT, and it is remarkable that a significant reduction in the number of discernible colors (58% on average) was found when the images were masked with their corresponding saliency maps. Our results suggest that chromatic diversity, as defined in terms of the discernible colors, can be strongly reduced when an observer scans a natural scene. These findings support the idea that a reduction in the number of discernible colors will guide visual saliency and attention. Whatever the modeling is mediating the neural representation of natural images, natural image statistics, it is clear that natural image statistics should take into account those local maxima and minima depending on the daylight illumination and

MR PROSTATE SEGMENTATION VIA DISTRIBUTED DISCRIMINATIVE DICTIONARY (DDD) LEARNING.

Science.gov (United States)

Guo, Yanrong; Zhan, Yiqiang; Gao, Yaozong; Jiang, Jianguo; Shen, Dinggang

2013-01-01

Segmenting prostate from MR images is important yet challenging. Due to non-Gaussian distribution of prostate appearances in MR images, the popular active appearance model (AAM) has its limited performance. Although the newly developed sparse dictionary learning method[1, 2] can model the image appearance in a non-parametric fashion, the learned dictionaries still lack the discriminative power between prostate and non-prostate tissues, which is critical for accurate prostate segmentation. In this paper, we propose to integrate deformable model with a novel learning scheme, namely the Distributed Discriminative Dictionary ( DDD ) learning, which can capture image appearance in a non-parametric and discriminative fashion. In particular, three strategies are designed to boost the tissue discriminative power of DDD. First , minimum Redundancy Maximum Relevance (mRMR) feature selection is performed to constrain the dictionary learning in a discriminative feature space. Second , linear discriminant analysis (LDA) is employed to assemble residuals from different dictionaries for optimal separation between prostate and non-prostate tissues. Third , instead of learning the global dictionaries, we learn a set of local dictionaries for the local regions (each with small appearance variations) along prostate boundary, thus achieving better tissue differentiation locally. In the application stage, DDDs will provide the appearance cues to robustly drive the deformable model onto the prostate boundary. Experiments on 50 MR prostate images show that our method can yield a Dice Ratio of 88% compared to the manual segmentations, and have 7% improvement over the conventional AAM.

Discrimination of legal entities: Phenomenological characteristics and legal protection

Directory of Open Access Journals (Sweden)

Petrušić Nevena

2017-01-01

Full Text Available Their social nature encourages people to associate and jointly achieve the goals that they would not be able to achieve individually. Legal entities are created as one of the legal modalities of that association, as separate entities that have their own legal personality independent of the subjectivity of their members. Legal entities are holders of some human rights, depending on the nature of the right, including the right to non-discrimination. All mechanisms envisaged for legal protection against discrimination in the national legislation are available to legal persons. On the other hand, the situation is quite different in terms of access to international forums competent to deal with cases of discrimination. Legal entities do not have access to some international forums, while they may have access to others under the same conditions prescribed for natural persons. Legal entities may be exposed to various forms of direct and indirect discrimination both in the private and in the public sphere of social relations. Phenomenological characteristics of discrimination against legal persons are not substantially different from discrimination against individuals. There are no significant differences regarding the application of discrimination test in cases of discrimination of legal entities as compared to the use of this test in cases involving discrimination of natural persons or groups of persons. Legal entities may be discriminated against on the basis of characteristics of their legal personality, such as those which are objective elements of the legal entity and part of its legal identity. Discrimination of legal entities may be based on personal characteristics of its members (i.e. people who make a personal essence of a legal entity because their characteristics can be 'transferred' to the legal entity and become part of its identity. Legal entities should also be protected from this special form of transferred (associative discrimination.

Explaining the Timing of Natural Scene Understanding with a Computational Model of Perceptual Categorization

Science.gov (United States)

Sofer, Imri; Crouzet, Sébastien M.; Serre, Thomas

2015-01-01

Observers can rapidly perform a variety of visual tasks such as categorizing a scene as open, as outdoor, or as a beach. Although we know that different tasks are typically associated with systematic differences in behavioral responses, to date, little is known about the underlying mechanisms. Here, we implemented a single integrated paradigm that links perceptual processes with categorization processes. Using a large image database of natural scenes, we trained machine-learning classifiers to derive quantitative measures of task-specific perceptual discriminability based on the distance between individual images and different categorization boundaries. We showed that the resulting discriminability measure accurately predicts variations in behavioral responses across categorization tasks and stimulus sets. We further used the model to design an experiment, which challenged previous interpretations of the so-called “superordinate advantage.” Overall, our study suggests that observed differences in behavioral responses across rapid categorization tasks reflect natural variations in perceptual discriminability. PMID:26335683

Chiral discrimination in nuclear magnetic resonance spectroscopy

Science.gov (United States)

Lazzeretti, Paolo

2017-11-01

Chirality is a fundamental property of molecules whose spatial symmetry is characterized by the absence of improper rotations, making them not superimposable to their mirror image. Chiral molecules constitute the elementary building blocks of living species and one enantiomer is favoured in general (e.g. L-aminoacids and D-sugars pervade terrestrial homochiral biochemistry) because most chemical reactions producing natural substances are enantioselective. Since the effect of chiral chemicals and drugs on living beings can be markedly different between enantiomers, the quest for practical spectroscopical methods to scrutinize chirality is an issue of great importance and interest. Nuclear magnetic resonance (NMR) is a topmost analytical technique, but spectrometers currently used are ‘blind’ to chirality, i.e. unable to discriminate the two mirror-image forms of a chiral molecule, because, in the absence of a chiral solvent, the spectral parameters, chemical shifts and spin-spin coupling constants are identical for enantiomers. Therefore, the development of new procedures for routine chiral recognition would offer basic support to scientists. However, in the presence of magnetic fields, a distinction between true and false chirality is mandatory. The former epitomizes natural optical activity, which is rationalized by a time-even pseudoscalar, i.e. the trace of a second-rank tensor, the mixed electric dipole/magnetic dipole polarizability. The Faraday effect, magnetic circular dichroism and magnetic optical activity are instead related to a time-odd axial vector. The present review summarizes recent theoretical and experimental efforts to discriminate enantiomers via NMR spectroscopy, with the focus on the deep connection between chirality and symmetry properties under the combined set of fundamental discrete operations, namely charge conjugation, parity (space inversion) and time (motion) reversal.

Discrimination of Different Water Layers with TerraSAR X Images in "La Albufera de Valencia"

Science.gov (United States)

García Fernández, M. A.; Miguelsanz Muñoz, P.

2009-04-01

To analyze the capabilities of TerraSAR X Strip Map images in order to discriminate different water layers in the "Parque de la Albufera de Valencia", Spain, a test project was carried out. This place is a rice crop area under European and National Agro environmental regulation which obliges to preserve the habitat and to keep the rice plots flooded out of crop season, from October to January

Tensor Rank Preserving Discriminant Analysis for Facial Recognition.

Science.gov (United States)

Tao, Dapeng; Guo, Yanan; Li, Yaotang; Gao, Xinbo

2017-10-12

Facial recognition, one of the basic topics in computer vision and pattern recognition, has received substantial attention in recent years. However, for those traditional facial recognition algorithms, the facial images are reshaped to a long vector, thereby losing part of the original spatial constraints of each pixel. In this paper, a new tensor-based feature extraction algorithm termed tensor rank preserving discriminant analysis (TRPDA) for facial image recognition is proposed; the proposed method involves two stages: in the first stage, the low-dimensional tensor subspace of the original input tensor samples was obtained; in the second stage, discriminative locality alignment was utilized to obtain the ultimate vector feature representation for subsequent facial recognition. On the one hand, the proposed TRPDA algorithm fully utilizes the natural structure of the input samples, and it applies an optimization criterion that can directly handle the tensor spectral analysis problem, thereby decreasing the computation cost compared those traditional tensor-based feature selection algorithms. On the other hand, the proposed TRPDA algorithm extracts feature by finding a tensor subspace that preserves most of the rank order information of the intra-class input samples. Experiments on the three facial databases are performed here to determine the effectiveness of the proposed TRPDA algorithm.

Luminance cues constrain chromatic blur discrimination in natural scene stimuli.

Science.gov (United States)

Sharman, Rebecca J; McGraw, Paul V; Peirce, Jonathan W

2013-03-22

Introducing blur into the color components of a natural scene has very little effect on its percept, whereas blur introduced into the luminance component is very noticeable. Here we quantify the dominance of luminance information in blur detection and examine a number of potential causes. We show that the interaction between chromatic and luminance information is not explained by reduced acuity or spatial resolution limitations for chromatic cues, the effective contrast of the luminance cue, or chromatic and achromatic statistical regularities in the images. Regardless of the quality of chromatic information, the visual system gives primacy to luminance signals when determining edge location. In natural viewing, luminance information appears to be specialized for detecting object boundaries while chromatic information may be used to determine surface properties.

Direct Imaging of Natural Fractures and Stress Compartments Stimulated by Hydraulic Fracturing

Science.gov (United States)

Lacazette, A.; Vermilye, J. M.

2014-12-01

This contribution will present results from passive seismic studies of hydraulic fracture treatments in North American and Asian basins. One of the key data types is a comparatively new surface-based seismic imaging product - "Tomographic Fracture Images®" (TFI®). The procedure is an extension of Seismic Emission Tomography (SET), which is well-established and widely used. Conventional microseismic results - microearthquake hypocenter locations, magnitudes, and focal mechanism solutions - are also obtained from the data via a branch of the processing workflow. TFI is accomplished by summing the individual time steps in a multidimensional SET hypervolume over extended periods of time, such as an entire frac stage. The dimensions of a SET hypervolume are the X, Y, and Z coordinates of the voxels, the time step (typically on the order of 100 milliseconds), and the seismic activity value. The resulting summed volume is skeletonized to produce images of the main fracture surfaces, which are known to occupy the maximum activity surfaces of the high activity clouds from theory, field studies, and experiments. The orientation vs. area of the resulting TFIs can be analyzed in detail and compared with independent data sets such as volumetric structural attributes from reflection seismic data and borehole fracture data. We find that the primary effect of hydraulic fracturing is to stimulate preexisting natural fracture networks and faults. The combination of TFIs with hypocenter distributions and microearthquake focal mechanisms provides detailed information on subsurface stress compartmentalization. Faults are directly imaged which allows discrimination of fault planes from auxiliary planes of focal mechanism solutions. Examples that will be shown include simultaneous movement on a thrust fault and tear fault and examples of radically different stress compartments (e.g. extensional vs. wrench faulting) stimulated during a single hydraulic fracture treatment. The figure

Growth Simulation and Discrimination of Botrytis cinerea, Rhizopus stolonifer and Colletotrichum acutatum Using Hyperspectral Reflectance Imaging.

Directory of Open Access Journals (Sweden)

Ye Sun

Full Text Available This research aimed to develop a rapid and nondestructive method to model the growth and discrimination of spoilage fungi, like Botrytis cinerea, Rhizopus stolonifer and Colletotrichum acutatum, based on hyperspectral imaging system (HIS. A hyperspectral imaging system was used to measure the spectral response of fungi inoculated on potato dextrose agar plates and stored at 28°C and 85% RH. The fungi were analyzed every 12 h over two days during growth, and optimal simulation models were built based on HIS parameters. The results showed that the coefficients of determination (R2 of simulation models for testing datasets were 0.7223 to 0.9914, and the sum square error (SSE and root mean square error (RMSE were in a range of 2.03-53.40×10(-4 and 0.011-0.756, respectively. The correlation coefficients between the HIS parameters and colony forming units of fungi were high from 0.887 to 0.957. In addition, fungi species was discriminated by partial least squares discrimination analysis (PLSDA, with the classification accuracy of 97.5% for the test dataset at 36 h. The application of this method in real food has been addressed through the analysis of Botrytis cinerea, Rhizopus stolonifer and Colletotrichum acutatum inoculated in peaches, demonstrating that the HIS technique was effective for simulation of fungal infection in real food. This paper supplied a new technique and useful information for further study into modeling the growth of fungi and detecting fruit spoilage caused by fungi based on HIS.

Use of partial least squares discriminant analysis on visible-near infrared multispectral image data to examine germination ability and germ length in spinach seeds

DEFF Research Database (Denmark)

Shetty, Nisha; Olesen, Merete Halkjær; Gislum, René

2012-01-01

Because of the difficulties in obtaining homogenous germination of spinach seeds for baby leaf production, the possibility of using partial least squares discriminant analysis (PLS-DA) on features extracted from multispectral images of spinach seeds was investigated. The objective has been...... to discriminate between different seed sizes, as well as to predict germination ability and germ length. Images of 300 seeds including small, medium, and large seeds were taken, and the seeds were examined for germination ability and germ length. PLS-DA loadings plots were used to reduce the multidimensional...

Radioactivity distribution measurement of various natural material surfaces with imaging plate

International Nuclear Information System (INIS)

Mori, C.; Suzuki, T.; Koido, S.; Uritani, A.; Yanagida, K.; Wu, Y.; Nishizawa, K.

1996-01-01

Distribution images of natural radioactivity in natural materials such as vegetables were obtained by using Imaging Platc. In ssuch cases, it is necessary to reduce background radiation intensity by one order or more. Graded shielding is very important. Espacially, the innermost surface of a shielding box sshould be covered with acrylic rein plate. We obtained natural radioactivity distribution images of vegetable, sea food, mea etc. Most β-rays emitted from 40 K print the radioactivity distribution image. Comparison between γ-ray intensity of KCL solution measured with HPGe detector and that of natural material specimen gave the radioactivity around 0.06- 0.04Bq/g depending on the kind and the part of specimens. (author). 6 refs., 5 figs., 1 tab

Identification, classification, and discrimination of agave syrups from natural sweeteners by infrared spectroscopy and HPAEC-PAD.

Science.gov (United States)

Mellado-Mojica, Erika; López, Mercedes G

2015-01-15

Agave syrups are gaining popularity as new natural sweeteners. Identification, classification and discrimination by infrared spectroscopy coupled to chemometrics (NIR-MIR-SIMCA-PCA) and HPAEC-PAD of agave syrups from natural sweeteners were achieved. MIR-SIMCA-PCA allowed us to classify the natural sweeteners according to their natural source. Natural syrups exhibited differences in the MIR spectra region 1500-900 cm(-1). The agave syrups displayed strong absorption in the MIR spectra region 1061-1,063 cm(-1), in agreement with their high fructose content. Additionally, MIR-SIMCA-PCA allowed us to differentiate among syrups from different Agave species (Agavetequilana and Agavesalmiana). Thin-layer chromatography and HPAEC-PAD revealed glucose, fructose, and sucrose as the principal carbohydrates in all of the syrups. Oligosaccharide profiles showed that A. tequilana syrups are mainly composed of fructose (>60%) and fructooligosaccharides, while A. salmiana syrups contain more sucrose (28-32%). We conclude that MIR-SIMCA-PCA and HPAEC-PAD can be used to unequivocally identify and classified agave syrups. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

P1-14: Relationship between Colorfulness Adaptation and Spatial Frequency Components in Natural Image

Directory of Open Access Journals (Sweden)

Shun Sakaibara

2012-10-01

Full Text Available We previously found the effect of colorfulness-adaptation in natural images. It was observed to be stronger in natural images than unnatural images, suggesting the influence of naturalness on the adaptation. However, what characteristics of images and what levels of visual system were involved were not examined enough. This research investigates whether the effect of colorfulness-adaptation is associated with spatial frequency components in natural images. If adaptation was a mechanism in early cortical level, the effect would be strong for adaptation and test images sharing similar spatial frequency components. In the experiment, we examined how the colorfulness impression of a test image changed following adaptation images with different levels of saturation. We selected several types of natural image from a standard image database for test and adaptation images. We also processed them to make shuffled images with spatial frequency component differed from the originals and phase-scrambled images with the component similar to the originals, for both adaptation and test images. Observers evaluated whether a test image was colorful or faded. Results show that the colorfulness perception of the test images was influenced by the saturation of the adaptation images. The effect was the strongest for the combination of natural (original adaptation and natural test images regardless of image types. The effect for the combination of phase-scrambled images was weaker than those of original images and stronger than those of shuffled images. They suggest that not only the spatial frequency components of an image but also the recognition of images would contribute to colorfulness-adaptation.

Task-irrelevant emotion facilitates face discrimination learning.

Science.gov (United States)

Lorenzino, Martina; Caudek, Corrado

2015-03-01

We understand poorly how the ability to discriminate faces from one another is shaped by visual experience. The purpose of the present study is to determine whether face discrimination learning can be facilitated by facial emotions. To answer this question, we used a task-irrelevant perceptual learning paradigm because it closely mimics the learning processes that, in daily life, occur without a conscious intention to learn and without an attentional focus on specific facial features. We measured face discrimination thresholds before and after training. During the training phase (4 days), participants performed a contrast discrimination task on face images. They were not informed that we introduced (task-irrelevant) subtle variations in the face images from trial to trial. For the Identity group, the task-irrelevant features were variations along a morphing continuum of facial identity. For the Emotion group, the task-irrelevant features were variations along an emotional expression morphing continuum. The Control group did not undergo contrast discrimination learning and only performed the pre-training and post-training tests, with the same temporal gap between them as the other two groups. Results indicate that face discrimination improved, but only for the Emotion group. Participants in the Emotion group, moreover, showed face discrimination improvements also for stimulus variations along the facial identity dimension, even if these (task-irrelevant) stimulus features had not been presented during training. The present results highlight the importance of emotions for face discrimination learning. Copyright © 2015 Elsevier Ltd. All rights reserved.

Magnetic resonance imaging of anterior temporal lobe cysts in children: discriminating special imaging features in a particular group of diseases

International Nuclear Information System (INIS)

Hoffmann Nunes, Renato; Torres Pacheco, Felipe; Rocha, Antonio Jose da

2014-01-01

We hypothesized that disorders with anterior temporal lobe (ATL) cysts might exhibit common peculiarities and distinguishable imaging features that could be useful for diagnosis. We reviewed a series of patients for neuroimaging contributions to specific diagnoses. A literature search was conducted, and institutional imaging files were reviewed to identify MR examinations with ATL cysts in children. Patients were divided according to head size, calcifications, white matter and cortical abnormalities. Unsupervised hierarchical clustering of patients on the basis of their MR and CT items was performed. We identified 23 patients in our database in whom MR revealed ATL cysts. Our series included five patients with congenital muscular dystrophy (05/23 = 21.7 %), six with megalencephalic leukoencephalopathy with subcortical cysts (06/23 = 26.1 %), three with non-megalencephalic leukoencephalopathy with subcortical cysts (03/23 = 13.1 %), seven with congenital cytomegalovirus disease (07/23 = 30.4 %) and two with Aicardi-Goutieres syndrome (02/23 = 8.7 %). After analysis, 11 clusters resulted in the highest discriminative indices. Thereafter, patients' clusters were linked to their underlying diseases. The features that best discriminated between clusters included brainstem abnormalities, cerebral calcifications and some peculiar grey and white matter abnormalities. A flow chart was drafted to guide the radiologist in these diagnoses. The authors encourage the combined interpretation of these features in the herein proposed approach that confidently predicted the final diagnosis in this particular group of disorders associated with ATL cysts. (orig.)

Magnetic resonance imaging of anterior temporal lobe cysts in children: discriminating special imaging features in a particular group of diseases

Energy Technology Data Exchange (ETDEWEB)

Hoffmann Nunes, Renato; Torres Pacheco, Felipe; Rocha, Antonio Jose da [Fleury Medicina e Saude, Division of Neuroradiology, Sao Paulo (Brazil); Servico de Diagnostico por Imagem, Division of Neuroradiology, Santa Casa de Misericordia de Sao Paulo Paulo, Sao Paulo (Brazil)

2014-07-15

We hypothesized that disorders with anterior temporal lobe (ATL) cysts might exhibit common peculiarities and distinguishable imaging features that could be useful for diagnosis. We reviewed a series of patients for neuroimaging contributions to specific diagnoses. A literature search was conducted, and institutional imaging files were reviewed to identify MR examinations with ATL cysts in children. Patients were divided according to head size, calcifications, white matter and cortical abnormalities. Unsupervised hierarchical clustering of patients on the basis of their MR and CT items was performed. We identified 23 patients in our database in whom MR revealed ATL cysts. Our series included five patients with congenital muscular dystrophy (05/23 = 21.7 %), six with megalencephalic leukoencephalopathy with subcortical cysts (06/23 = 26.1 %), three with non-megalencephalic leukoencephalopathy with subcortical cysts (03/23 = 13.1 %), seven with congenital cytomegalovirus disease (07/23 = 30.4 %) and two with Aicardi-Goutieres syndrome (02/23 = 8.7 %). After analysis, 11 clusters resulted in the highest discriminative indices. Thereafter, patients' clusters were linked to their underlying diseases. The features that best discriminated between clusters included brainstem abnormalities, cerebral calcifications and some peculiar grey and white matter abnormalities. A flow chart was drafted to guide the radiologist in these diagnoses. The authors encourage the combined interpretation of these features in the herein proposed approach that confidently predicted the final diagnosis in this particular group of disorders associated with ATL cysts. (orig.)

Discrimination of prostate cancer from normal peripheral zone and central gland tissue by using dynamic contrast-enhanced MR imaging

NARCIS (Netherlands)

Engelbrecht, Marc R.; Huisman, Henkjan J.; Laheij, Robert J. F.; Jager, Gerrit J.; van Leenders, Geert J. L. H.; Hulsbergen-van de Kaa, Christina A.; de La Rosette, Jean J. M. C. H.; Blickman, Johan G.; Barentsz, Jelle O.

2003-01-01

PURPOSE: To evaluate which parameters of dynamic magnetic resonance (MR) imaging and T2 relaxation rate would result in optimal discrimination of prostatic carcinoma from normal peripheral zone (PZ) and central gland (CG) tissues and to correlate these parameters with tumor stage, Gleason score,

Assessing natural hazard risk using images and data

Science.gov (United States)

Mccullough, H. L.; Dunbar, P. K.; Varner, J. D.; Mungov, G.

2012-12-01

Photographs and other visual media provide valuable pre- and post-event data for natural hazard assessment. Scientific research, mitigation, and forecasting rely on visual data for risk analysis, inundation mapping and historic records. Instrumental data only reveal a portion of the whole story; photographs explicitly illustrate the physical and societal impacts from the event. Visual data is rapidly increasing as the availability of portable high resolution cameras and video recorders becomes more attainable. Incorporating these data into archives ensures a more complete historical account of events. Integrating natural hazards data, such as tsunami, earthquake and volcanic eruption events, socio-economic information, and tsunami deposits and runups along with images and photographs enhances event comprehension. Global historic databases at NOAA's National Geophysical Data Center (NGDC) consolidate these data, providing the user with easy access to a network of information. NGDC's Natural Hazards Image Database (ngdc.noaa.gov/hazardimages) was recently improved to provide a more efficient and dynamic user interface. It uses the Google Maps API and Keyhole Markup Language (KML) to provide geographic context to the images and events. Descriptive tags, or keywords, have been applied to each image, enabling easier navigation and discovery. In addition, the Natural Hazards Map Viewer (maps.ngdc.noaa.gov/viewers/hazards) provides the ability to search and browse data layers on a Mercator-projection globe with a variety of map backgrounds. This combination of features creates a simple and effective way to enhance our understanding of hazard events and risks using imagery.

The effects of nature images on pain in a simulated hospital patient room.

Science.gov (United States)

Vincent, Ellen; Battisto, Dina; Grimes, Larry; McCubbin, James

2010-01-01

Views of nature have been reported to relieve stress and pain, making nature an ideal medium for use in healthcare settings. In hospitals whose design does not allow for a view of nature, virtual and surrogate views of nature may be viable therapeutic options. This study tests the effects of specific nature images, as defined by Appleton's prospect refuge theory of landscape preference, on participants experiencing pain. The hypotheses were: (1) Nature views are variable in their impact on specific psychological and physiological health status indicators; and (2) Prospect and refuge nature scenes are more therapeutic than hazard nature scenes. The research question was (1) Which nature image categories are most therapeutic as evidenced by reduced pain and positive mood? An experiment using mixed methods assessed the effects of four different nature scenes on physiological (blood pressure, heart rate) and psychological (mood) responses when a person was subjected to a pain stressor. Four groups were subjected to a specific nature image category of prospect, refuge, hazard, or mixed prospect and refuge; the fifth group viewed no image. The Short-Form McGill Pain Questionnaire and the Profile of Mood States survey instruments were used to assess pain and mood, respectively. Continuous physiological readings of heart rate and blood pressure were collected. Pain was induced through a cold pressor task, which required participants to immerse their nondominant hand in ice water for up to 120 seconds. The mixed prospect and refuge image treatment showed significantly lower sensory pain responses, and the no-image treatment indicated significantly higher affective pain perception responses. The hazard image treatment had significantly lower diastolic blood pressure readings during the pain treatment, but it also had significantly high total mood disturbance. Although there was no clear "most" therapeutic image, the mixed prospect and refuge image showed significant

Effects of exposure to information about appearance stereotyping and discrimination on women's body images.

Science.gov (United States)

Lavin, M A; Cash, T F

2001-01-01

There is widespread public dissemination of research findings and media messages regarding social advantages of physical attractiveness and liabilities of unattractiveness. The purpose of this experimental study was to determine the effects of such information on women's body-image experiences. College women (n = 66) listened to one of two audiotapes that detailed research-based information either on the subject of appearance stereotyping and discrimination or on the control topic of television violence and aggression. Although the two conditions did not differentially alter mood, exposure to appearance-related versus control information produced significantly less favorable body-image evaluations. Furthermore, as predicted, women who were schematically invested in their physical appearance were especially susceptible to the deleterious effects of the appearance information. The scientific and clinical implications of these findings were discussed, particularly with respect to eating disturbances.

Discrimination of hydrothermal alteration mineral assemblages at Virginia City, Nevada, using the airborne imaging spectrometer

Science.gov (United States)

Hutsinpiller, Amy

1988-01-01

The purpose of this study is to use airborne imaging spectrometer data to discriminate hydrothermal alteration mineral assemblages associated with silver and gold mineralization at Virginia City, NV. The data is corrected for vertical striping and sample gradients, and converted to flat-field logarithmic residuals. Log residual spectra from areas known to be altered are compared to field spectra for kaolinitic, illitic, sericitic, and propylitic alteration types. The areal distributions of these alteration types are estimated using a spectral matching technique. Both visual examination of spectra and the matching techniques are effective in distinguishing kaolinitic, illitic, and propylitic alteration types from each other. However, illitic and sericitic alteration cannot be separated using these techniques because the spectra of illite and sericite are very similar. A principal components analysis of 14 channels in the 2.14-2.38 micron wavelength region is also successful in discriminating and mapping illitic, kaolinitic, and propylitic alteration types.

Experienced and anticipated discrimination against people with schizophrenia

Directory of Open Access Journals (Sweden)

Milačić-Vidojević Ivona

2011-01-01

Full Text Available Aim of this research was to describe the nature, direction and severity of anticipated and experienced discrimination reported by people with schizophrenia. We applied interview to 50 patients with diagnosis of schizophrenia in two psychiatric hospitals in Belgrade. Discrimination was measured with discrimination and stigma scale (DISC which produce 3 subscores, positive experienced discrimination, negative experienced discrimination and anticipated discrimination. The same scale was used in cross-cultural research in 27 european countries. Results have shown that participants from Serbia do not recognize discrimination in all areas of life equally. The discrimination recognized is more frequentlly negative then positive and is associated with existentially important realms of life. Due to anticipated discrimination participants in our study prevent themselves from looking for a close relationship. Anticipated discrimination could not be predicted on the grounds of experienced, positive or negative discrimination.

An automated image processing method for classification of diabetic retinopathy stages from conjunctival microvasculature images

Science.gov (United States)

Khansari, Maziyar M.; O'Neill, William; Penn, Richard; Blair, Norman P.; Chau, Felix; Shahidi, Mahnaz

2017-03-01

The conjunctiva is a densely vascularized tissue of the eye that provides an opportunity for imaging of human microcirculation. In the current study, automated fine structure analysis of conjunctival microvasculature images was performed to discriminate stages of diabetic retinopathy (DR). The study population consisted of one group of nondiabetic control subjects (NC) and 3 groups of diabetic subjects, with no clinical DR (NDR), non-proliferative DR (NPDR), or proliferative DR (PDR). Ordinary least square regression and Fisher linear discriminant analyses were performed to automatically discriminate images between group pairs of subjects. Human observers who were masked to the grouping of subjects performed image discrimination between group pairs. Over 80% and 70% of images of subjects with clinical and non-clinical DR were correctly discriminated by the automated method, respectively. The discrimination rates of the automated method were higher than human observers. The fine structure analysis of conjunctival microvasculature images provided discrimination of DR stages and can be potentially useful for DR screening and monitoring.

Pediatric adrenocortical neoplasms: can imaging reliably discriminate adenomas from carcinomas?

International Nuclear Information System (INIS)

Flynt, Kelsey A.; Dillman, Jonathan R.; Smith, Ethan A.; Strouse, Peter J.; Davenport, Matthew S.; Caoili, Elaine M.; Else, Tobias

2015-01-01

There is a paucity of literature describing and comparing the imaging features of adrenocortical adenomas and carcinomas in children and adolescents. To document the CT and MRI features of adrenocortical neoplasms in a pediatric population and to determine whether imaging findings (other than metastatic disease) can distinguish adenomas from carcinomas. We searched institutional medical records to identify pediatric patients with adrenocortical neoplasms. Pre-treatment CT and MRI examinations were reviewed by two radiologists in consensus, and pertinent imaging findings were documented. We also recorded relevant histopathological, demographic, clinical follow-up and survival data. We used the Student's t-test and Wilcoxon rank sum test to compare parametric and nonparametric continuous data, and the Fisher exact test to compare proportions. We used receiver operating characteristic (ROC) curve analyses to evaluate the diagnostic performances of tumor diameter and volume for discriminating carcinoma from adenoma. A P-value ≤0.05 was considered statistically significant. Among the adrenocortical lesions, 9 were adenomas, 15 were carcinomas, and 1 was of uncertain malignant potential. There were no differences in mean age, gender or sidedness between adenomas and carcinomas. Carcinomas were significantly larger than adenomas based on mean estimated volume (581 ml, range 16-2,101 vs. 54 ml, range 3-197 ml; P-value = 0.003; ROC area under the curve = 0.92) and mean maximum transverse plane diameter (9.9 cm, range 3.0-14.9 vs. 4.4 cm, range 1.9-8.2 cm; P-value = 0.0001; ROC area under the curve = 0.92). Carcinomas also were more heterogeneous than adenomas on post-contrast imaging (13/14 vs. 2/9; odds ratio [OR] = 45.5; P-value = 0.001). Six of 13 carcinomas and 1 of 8 adenomas contained calcification at CT (OR = 6.0; P-value = 0.17). Seven of 15 children with carcinomas exhibited metastatic disease at diagnosis, and three had inferior vena cava invasion. Median

Pediatric adrenocortical neoplasms: can imaging reliably discriminate adenomas from carcinomas?

Energy Technology Data Exchange (ETDEWEB)

Flynt, Kelsey A.; Dillman, Jonathan R.; Smith, Ethan A.; Strouse, Peter J. [University of Michigan Health System, Section of Pediatric Radiology, C. S. Mott Children' s Hospital, Department of Radiology, Ann Arbor, MI (United States); Davenport, Matthew S.; Caoili, Elaine M. [University of Michigan Health System, Division of Abdominal Imaging, Department of Radiology, Ann Arbor, MI (United States); Else, Tobias [University of Michigan Health System, Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, Ann Arbor, MI (United States)

2015-08-15

There is a paucity of literature describing and comparing the imaging features of adrenocortical adenomas and carcinomas in children and adolescents. To document the CT and MRI features of adrenocortical neoplasms in a pediatric population and to determine whether imaging findings (other than metastatic disease) can distinguish adenomas from carcinomas. We searched institutional medical records to identify pediatric patients with adrenocortical neoplasms. Pre-treatment CT and MRI examinations were reviewed by two radiologists in consensus, and pertinent imaging findings were documented. We also recorded relevant histopathological, demographic, clinical follow-up and survival data. We used the Student's t-test and Wilcoxon rank sum test to compare parametric and nonparametric continuous data, and the Fisher exact test to compare proportions. We used receiver operating characteristic (ROC) curve analyses to evaluate the diagnostic performances of tumor diameter and volume for discriminating carcinoma from adenoma. A P-value ≤0.05 was considered statistically significant. Among the adrenocortical lesions, 9 were adenomas, 15 were carcinomas, and 1 was of uncertain malignant potential. There were no differences in mean age, gender or sidedness between adenomas and carcinomas. Carcinomas were significantly larger than adenomas based on mean estimated volume (581 ml, range 16-2,101 vs. 54 ml, range 3-197 ml; P-value = 0.003; ROC area under the curve = 0.92) and mean maximum transverse plane diameter (9.9 cm, range 3.0-14.9 vs. 4.4 cm, range 1.9-8.2 cm; P-value = 0.0001; ROC area under the curve = 0.92). Carcinomas also were more heterogeneous than adenomas on post-contrast imaging (13/14 vs. 2/9; odds ratio [OR] = 45.5; P-value = 0.001). Six of 13 carcinomas and 1 of 8 adenomas contained calcification at CT (OR = 6.0; P-value = 0.17). Seven of 15 children with carcinomas exhibited metastatic disease at diagnosis, and three had inferior vena cava invasion. Median

Shifts in color discrimination during early pregnancy.

Science.gov (United States)

Orbán, Levente L; Dastur, Farhad N

2012-05-25

The present study explores two hypotheses: a) women during early pregnancy should experience increased color discrimination ability, and b) women during early pregnancy should experience shifts in subjective preference away from images of foods that appear either unripe or spoiled. Both of these hypotheses derive from an adaptive view of pregnancy sickness that proposes the function of pregnancy sickness is to decrease the likelihood of ingestion of foods with toxins or teratogens. Changes to color discrimination could be part of a network of perceptual and physiological defenses (e.g., changes to olfaction, nausea, vomiting) that support such a function. Participants included 13 pregnant women and 18 non-pregnant women. Pregnant women scored significantly higher than non-pregnant controls on the Farnsworth-Munsell (FM) 100 Hue Test, an objective test of color discrimination, although no difference was found between groups in preferences for food images at different stages of ripeness or spoilage. These results are the first indication that changes to color discrimination may occur during early pregnancy, and is consistent with the view that pregnancy sickness may function as an adaptive defense mechanism.

Humans make efficient use of natural image statistics when performing spatial interpolation.

Science.gov (United States)

D'Antona, Anthony D; Perry, Jeffrey S; Geisler, Wilson S

2013-12-16

Visual systems learn through evolution and experience over the lifespan to exploit the statistical structure of natural images when performing visual tasks. Understanding which aspects of this statistical structure are incorporated into the human nervous system is a fundamental goal in vision science. To address this goal, we measured human ability to estimate the intensity of missing image pixels in natural images. Human estimation accuracy is compared with various simple heuristics (e.g., local mean) and with optimal observers that have nearly complete knowledge of the local statistical structure of natural images. Human estimates are more accurate than those of simple heuristics, and they match the performance of an optimal observer that knows the local statistical structure of relative intensities (contrasts). This optimal observer predicts the detailed pattern of human estimation errors and hence the results place strong constraints on the underlying neural mechanisms. However, humans do not reach the performance of an optimal observer that knows the local statistical structure of the absolute intensities, which reflect both local relative intensities and local mean intensity. As predicted from a statistical analysis of natural images, human estimation accuracy is negligibly improved by expanding the context from a local patch to the whole image. Our results demonstrate that the human visual system exploits efficiently the statistical structure of natural images.

Impact of the "Like Minds, Like Mine" anti-stigma and discrimination campaign in New Zealand on anticipated and experienced discrimination.

Science.gov (United States)

Thornicroft, Calum; Wyllie, Allan; Thornicroft, Graham; Mehta, Nisha

2014-04-01

The "Like Minds, Like Mine" anti-stigma and discrimination programme has been running in New Zealand since 1997. We aimed to investigate the nature and degree of anticipated and experienced discrimination reported by people with mental illness, and their views on whether the campaign was contributing to reductions in stigma and discrimination. Questionnaires were sent to randomly selected people who were representative of those who had recently used mental health services in New Zealand. The measure used was the modified Discrimination and Stigma Scale (DISC-12), adding questions on the effect of "Like Minds, Like Mine", and also assessing overall changes in discrimination in the previous 5 years. A total of 1135 participants completed the questionnaire. This included 225 Ma-ori, 196 Pacific, and 152 Asian persons. Over half of all participants reported improvement in discrimination over the previous 5 years, and 48% thought that the "Like Minds Like Mine" programme had assisted in reducing discrimination "moderately" or "a lot". Nevertheless, a clear majority (89%) reported experiencing at least "a little" unfair treatment in the previous 12 months due to their mental health problems. The primary source of both positive and negative discrimination was the family. Many (57%) participants had concealed or hidden their mental health problems from others, and 33% had stopped themselves from applying for work because they anticipated discrimination. Family, friendship, and social life were the most common areas of discrimination reported by the participants; however, many believed the overall level of discrimination had reduced over the previous 5 years. Overall, these results characterize the nature of stigma and discrimination anticipated and experienced by people with mental health problems and indicate modest but clear and positive recent progress in their reduction.

Discriminating cosmic muons and X-rays based on rise time using a GEM detector

Science.gov (United States)

Wu, Hui-Yin; Zhao, Sheng-Ying; Wang, Xiao-Dong; Zhang, Xian-Ming; Qi, Hui-Rong; Zhang, Wei; Wu, Ke-Yan; Hu, Bi-Tao; Zhang, Yi

2016-08-01

Gas electron multiplier (GEM) detectors have been used in cosmic muon scattering tomography and neutron imaging over the last decade. In this work, a triple GEM device with an effective readout area of 10 cm × 10 cm is developed, and a method of discriminating between cosmic muons and X-rays based on rise time is tested. The energy resolution of the GEM detector is tested by 55Fe ray source to prove the GEM detector has a good performance. Analysis of the complete signal-cycles allows us to get the rise time and pulse heights. The experiment result indicates that cosmic muons and X-rays can be discriminated with an appropriate rise time threshold. Supported by National Natural Science Foundation of China (11135002, 11275235, 11405077, 11575073)

Effect of background radiation shielding on natural radioactivity distribution measurement with imaging plate

International Nuclear Information System (INIS)

Mori, C.; Suzuki, T.; Koido, S.; Uritani, A.; Miyahara, H.; Yanagida, K.; Miyahara, J.; Takahashi, K.

1996-01-01

Distribution images of natural radioactivity contained in various natural materials such as vegetable, animal meat and pottery work can be obtained with an imaging plate which has high sensitivity for nuclear radiations. For such very low levels of radioactivity, natural background radiations must be reduced using a shielding box. The lining, on the inside of the box, with low atomic number material such as acrylic resin is very effective in reducing electrons, β-rays and low energy X- and γ-rays emitted from the inner surface of the shielding material. Some images of natural radioactivity distribution were obtained and the radioactivity, mainly 40 K, contained in natural materials was measured by using an HPGe detector and also the imaging plate itself. (orig.)

Screening of a virtual mirror-image library of natural products.

Science.gov (United States)

Noguchi, Taro; Oishi, Shinya; Honda, Kaori; Kondoh, Yasumitsu; Saito, Tamio; Ohno, Hiroaki; Osada, Hiroyuki; Fujii, Nobutaka

2016-06-08

We established a facile access to an unexplored mirror-image library of chiral natural product derivatives using d-protein technology. In this process, two chemical syntheses of mirror-image substances including a target protein and hit compound(s) allow the lead discovery from a virtual mirror-image library without the synthesis of numerous mirror-image compounds.

Estimating 3D tilt from local image cues in natural scenes

OpenAIRE

Burge, Johannes; McCann, Brian C.; Geisler, Wilson S.

2016-01-01

Estimating three-dimensional (3D) surface orientation (slant and tilt) is an important first step toward estimating 3D shape. Here, we examine how three local image cues from the same location (disparity gradient, luminance gradient, and dominant texture orientation) should be combined to estimate 3D tilt in natural scenes. We collected a database of natural stereoscopic images with precisely co-registered range images that provide the ground-truth distance at each pixel location. We then ana...

Feelings: what questions best discriminate women with and without eating disorders?

Science.gov (United States)

Abraham, S F; von Lojewski, A; Anderson, G; Clarke, S; Russell, J

2009-03-01

This study explored feelings that discriminate between eating disorder and community groups of women. Responses to 25 questions about body image (9), eating (8) self-esteem (3) general psychology (5) were collected in 2002-2003 (N=268) and 2005-2006 (N=472). Wilk's lambda was used to test discrimination. The most discriminating psychological questions were: 'feeling unhappy and unable to cope as well as usual', 'unease attending social functions', 'fearing loss of control over emotions'; and for eating questions were: 'feeling uneasy if other people saw you eating', 'feeling preoccupied with food/eating', 'fearing loss of control over eating'. For body image only 'feeling preoccupied with body weight/shape' and 'fearing loss of control over your body' discriminated. Questions relating to weight and shape for self-esteem ('feeling fat', 'fearing weight gain' and 'wanting to lose weight') discriminated poorly. Results for both cohorts were consistent. Preoccupation with thoughts of eating or body image and fear of loss of control of these would be useful additions to eating disorders criteria. Psychological impairment should also be present.

Semiconductor Laser Multi-Spectral Sensing and Imaging

Directory of Open Access Journals (Sweden)

Han Q. Le

2010-01-01

Full Text Available Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO. These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers.

Semiconductor laser multi-spectral sensing and imaging.

Science.gov (United States)

Le, Han Q; Wang, Yang

2010-01-01

Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO). These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers.

Orthogonal sparse linear discriminant analysis

Science.gov (United States)

Liu, Zhonghua; Liu, Gang; Pu, Jiexin; Wang, Xiaohong; Wang, Haijun

2018-03-01

Linear discriminant analysis (LDA) is a linear feature extraction approach, and it has received much attention. On the basis of LDA, researchers have done a lot of research work on it, and many variant versions of LDA were proposed. However, the inherent problem of LDA cannot be solved very well by the variant methods. The major disadvantages of the classical LDA are as follows. First, it is sensitive to outliers and noises. Second, only the global discriminant structure is preserved, while the local discriminant information is ignored. In this paper, we present a new orthogonal sparse linear discriminant analysis (OSLDA) algorithm. The k nearest neighbour graph is first constructed to preserve the locality discriminant information of sample points. Then, L2,1-norm constraint on the projection matrix is used to act as loss function, which can make the proposed method robust to outliers in data points. Extensive experiments have been performed on several standard public image databases, and the experiment results demonstrate the performance of the proposed OSLDA algorithm.

Using Dynamic Fourier Analysis to Discriminate Between Seismic Signals from Natural Earthquakes and Mining Explosions

Directory of Open Access Journals (Sweden)

Maria C. Mariani

2017-08-01

Full Text Available A sequence of intraplate earthquakes occurred in Arizona at the same location where miningexplosions were carried out in previous years. The explosions and some of the earthquakes generatedvery similar seismic signals. In this study Dynamic Fourier Analysis is used for discriminating signalsoriginating from natural earthquakes and mining explosions. Frequency analysis of seismogramsrecorded at regional distances shows that compared with the mining explosions the earthquake signalshave larger amplitudes in the frequency interval ~ 6 to 8 Hz and significantly smaller amplitudes inthe frequency interval ~ 2 to 4 Hz. This type of analysis permits identifying characteristics in theseismograms frequency yielding to detect potentially risky seismic events.

Supralinearity and particle discrimination in nuclear emulsion

International Nuclear Information System (INIS)

Katz, R.; Larsson, L.; Pinkerton, F.E.; Benton, E.V.

1977-01-01

Nuclear emulsions may be desensitized in manufacture and/or may be so processed as to discriminate against small latent image sites; to yield supralinear sensitometric response after x-irradiation; and to discriminate against lightly ionizing radiations in favor of heavily ionizing particles. In a circumstance where one electron passing through an emulsion grain is unlikely to generate a latent image sufficiently large to yield a visible grain after development, some larger number of electrons is required, resulting in 'many-hit' statistics, supralinearity, and particle discrimination: for lightly ionizing particles are not likely to generate more than one delta-ray (secondary electron) in their passage through or near a grain. Since these properties are analogous to the response of many biological cells to ionizing radiations, such emulsion-developer combinations have the potential to mimic the response of biological systems to particulate radiations of different charge and speed. (author)

Modified natural nanoparticles as contrast agents for medical imaging

NARCIS (Netherlands)

Cormode, David P.; Jarzyna, Peter A.; Mulder, Willem J. M.; Fayad, Zahi A.

2010-01-01

The development of novel and effective contrast agents is one of the drivers of the ongoing improvement in medical imaging. Many of the new agents reported are nanoparticle-based. There are a variety of natural nanoparticles known, e.g. lipoproteins, viruses or ferritin. Natural nanoparticles have

Shifts in Color Discrimination during Early Pregnancy

Directory of Open Access Journals (Sweden)

Levente L. Orbán

2012-04-01

Full Text Available The present study explores two hypotheses: a women during early pregnancy should experience increased color discrimination ability, and b women during early pregnancy should experience shifts in subjective preference away from images of foods that appear either unripe or spoiled. Both of these hypotheses derive from an adaptive view of pregnancy sickness that proposes the function of pregnancy sickness is to decrease the likelihood of ingestion of foods with toxins or teratogens. Changes to color discrimination could be part of a network of perceptual and physiological defenses (e.g., changes to olfaction, nausea, vomiting that support such a function. Participants included 13 pregnant women and 18 non-pregnant women. Pregnant women scored significantly higher than non-pregnant controls on the Farnsworth-Munsell (FM 100 Hue Test, an objective test of color discrimination, although no difference was found between groups in preferences for food images at different stages of ripeness or spoilage. These results are the first indication that changes to color discrimination may occur during early pregnancy, and is consistent with the view that pregnancy sickness may function as an adaptive defense mechanism.

Learning Dictionaries of Discriminative Image Patches

DEFF Research Database (Denmark)

Dahl, Anders Lindbjerg; Larsen, Rasmus

2011-01-01

using dictionaries of image patches with associated label data. The approach is based on ideas from sparse generative image models and texton based texture modeling. The intensity and label dictionaries are learned from training images with associated label information of (a subset) of the pixels based...... on a modified vector quantization approach. For new images the intensity dictionary is used to encode the image data and the label dictionary is used to build a segmentation of the image. We demonstrate the algorithm on composite and real texture images and show how successful training is possible even...

Range-Image Acquisition for Discriminated Objects in a Range-gated Robot Vision System

Energy Technology Data Exchange (ETDEWEB)

Park, Seung-Kyu; Ahn, Yong-Jin; Park, Nak-Kyu; Baik, Sung-Hoon; Choi, Young-Soo; Jeong, Kyung-Min [KAERI, Daejeon (Korea, Republic of)

2015-05-15

demonstrated 3D imaging based on range-gated imaging. Robot vision is a key technology to remotely monitor structural safety in radiation area of nuclear industry. Especially, visualization technique in low-visibility areas, such as smoking and fog areas, is essential to monitor structural safety in emergency smoking areas. In this paper, a range acquisition technique to discriminate objects is developed. The developed technique to acquire object range images is adapted to a range-gated vision system. Visualization experiments are carried out to detect objects in low-visibility fog environment. The experimental result of this newly approach vision system is described in this paper.

Range-Image Acquisition for Discriminated Objects in a Range-gated Robot Vision System

International Nuclear Information System (INIS)

Park, Seung-Kyu; Ahn, Yong-Jin; Park, Nak-Kyu; Baik, Sung-Hoon; Choi, Young-Soo; Jeong, Kyung-Min

2015-01-01

demonstrated 3D imaging based on range-gated imaging. Robot vision is a key technology to remotely monitor structural safety in radiation area of nuclear industry. Especially, visualization technique in low-visibility areas, such as smoking and fog areas, is essential to monitor structural safety in emergency smoking areas. In this paper, a range acquisition technique to discriminate objects is developed. The developed technique to acquire object range images is adapted to a range-gated vision system. Visualization experiments are carried out to detect objects in low-visibility fog environment. The experimental result of this newly approach vision system is described in this paper

Discriminating between natural versus induced seismicity from long-term deformation history of intraplate faults.

Science.gov (United States)

Magnani, Maria Beatrice; Blanpied, Michael L; DeShon, Heather R; Hornbach, Matthew J

2017-11-01

To assess whether recent seismicity is induced by human activity or is of natural origin, we analyze fault displacements on high-resolution seismic reflection profiles for two regions in the central United States (CUS): the Fort Worth Basin (FWB) of Texas and the northern Mississippi embayment (NME). Since 2009, earthquake activity in the CUS has increased markedly, and numerous publications suggest that this increase is primarily due to induced earthquakes caused by deep-well injection of wastewater, both flowback water from hydrofracturing operations and produced water accompanying hydrocarbon production. Alternatively, some argue that these earthquakes are natural and that the seismicity increase is a normal variation that occurs over millions of years. Our analysis shows that within the NME, faults deform both Quaternary alluvium and underlying sediments dating from Paleozoic through Tertiary, with displacement increasing with geologic unit age, documenting a long history of natural activity. In the FWB, a region of ongoing wastewater injection, basement faults show deformation of the Proterozoic and Paleozoic units, but little or no deformation of younger strata. Specifically, vertical displacements in the post-Pennsylvanian formations, if any, are below the resolution (~15 m) of the seismic data, far less than expected had these faults accumulated deformation over millions of years. Our results support the assertion that recent FWB earthquakes are of induced origin; this conclusion is entirely independent of analyses correlating seismicity and wastewater injection practices. To our knowledge, this is the first study to discriminate natural and induced seismicity using classical structural geology analysis techniques.

Temporal adaptation enhances efficient contrast gain control on natural images.

Directory of Open Access Journals (Sweden)

Fabian Sinz

Full Text Available Divisive normalization in primary visual cortex has been linked to adaptation to natural image statistics in accordance to Barlow's redundancy reduction hypothesis. Using recent advances in natural image modeling, we show that the previously studied static model of divisive normalization is rather inefficient in reducing local contrast correlations, but that a simple temporal contrast adaptation mechanism of the half-saturation constant can substantially increase its efficiency. Our findings reveal the experimentally observed temporal dynamics of divisive normalization to be critical for redundancy reduction.

Combining features from ERP components in single-trial EEG for discriminating four-category visual objects

Science.gov (United States)

Wang, Changming; Xiong, Shi; Hu, Xiaoping; Yao, Li; Zhang, Jiacai

2012-10-01

Categorization of images containing visual objects can be successfully recognized using single-trial electroencephalograph (EEG) measured when subjects view images. Previous studies have shown that task-related information contained in event-related potential (ERP) components could discriminate two or three categories of object images. In this study, we investigated whether four categories of objects (human faces, buildings, cats and cars) could be mutually discriminated using single-trial EEG data. Here, the EEG waveforms acquired while subjects were viewing four categories of object images were segmented into several ERP components (P1, N1, P2a and P2b), and then Fisher linear discriminant analysis (Fisher-LDA) was used to classify EEG features extracted from ERP components. Firstly, we compared the classification results using features from single ERP components, and identified that the N1 component achieved the highest classification accuracies. Secondly, we discriminated four categories of objects using combining features from multiple ERP components, and showed that combination of ERP components improved four-category classification accuracies by utilizing the complementarity of discriminative information in ERP components. These findings confirmed that four categories of object images could be discriminated with single-trial EEG and could direct us to select effective EEG features for classifying visual objects.

Inheritance of carbon isotope discrimination and water-use efficiency in cowpea

International Nuclear Information System (INIS)

Ismail, A.M.; Hall, A.E.

1993-01-01

Theory has been developed predicting an association between water-use efficiency (WUE = total biomass/transpiration) and leaf discrimination against 13C carbon isotope discrimination which could be used to indirectly select for WUE in C3 plants. Previous studies indicated variation in WUE and carbon isotope discrimination among genotypes of cowpea [Vigna unguiculata (L.) Walp.] and due to drought. Moreover, a highly significant negative correlation between WUE and carbon isotope discrimination was observed for both genotypic and drought effects, as expected based on theory. Present studies were conducted to investigate whether the inheritance of WUE and carbon isotope discrimination is nuclear or maternal, and whether any dominance is present. Contrasting cowpea accessions and hybrids were grown over 2 yr in two outdoor pot experiments, subjected to wet or dry treatments, and under full irrigation in natural soil conditions in 1 yr. Highly significant differences in WUE were observed among cowpea parents and hybrids, and due to drought, which were strongly and negatively correlated with carbon isotope discrimination as expected based on theory. Data from reciprocal crosses indicated that both WUE and carbon isotope discrimination are controlled by nuclear genes. High WUE and low carbon isotope discrimination exhibited partial dominance under pot conditions. In contrast, high carbon isotope discrimination was partially dominant for plants grown under natural soil conditions but in a similar aerial environment as in the pot studies. We speculate that differences in rooting conditions were responsible for the differences in extent of dominance for carbon isotope discrimination of plants growing under pot conditions compared with natural soil conditions in a similar field aerial environment

Young women's genital self-image and effects of exposure to pictures of natural vulvas.

Science.gov (United States)

Laan, Ellen; Martoredjo, Daphne K; Hesselink, Sara; Snijders, Nóinín; van Lunsen, Rik H W

2017-12-01

Many women have doubts about the normality of the physical appearance of their vulvas. This study measured genital self-image in a convenience sample of college-educated women, and assessed whether exposure to pictures of natural vulvas influenced their genital self-image. Forty-three women were either shown pictures of natural vulvas (N = 29) or pictures of neutral objects (N = 14). Genital self-image was measured before and after exposure to the pictures and two weeks later. Sexual function, sexual distress, self-esteem and trait anxiety were measured to investigate whether these factors influenced genital self-image scores after vulva picture exposure. A majority of the participants felt generally positively about their genitals. Having been exposed to pictures of natural vulvas resulted in an even more positive genital self-image, irrespective of levels of sexual function, sexual distress, self-esteem and trait anxiety. In the women who had seen the vulva pictures, the positive effect on genital self-image was still present after two weeks. The results of this study seem to indicate that even in young women with a relatively positive genital self-image, exposure to pictures of a large variety of natural vulvas positively affects genital self-image. This finding may suggest that exposure to pictures of natural vulvas may also lead to a more positive genital self-image in women who consider labiaplasty.

Indexing Natural Products for Their Potential Anti-Diabetic Activity: Filtering and Mapping Discriminative Physicochemical Properties.

Science.gov (United States)

Zeidan, Mouhammad; Rayan, Mahmoud; Zeidan, Nuha; Falah, Mizied; Rayan, Anwar

2017-09-17

Diabetes mellitus (DM) poses a major health problem, for which there is an unmet need to develop novel drugs. The application of in silico techniques and optimization algorithms is instrumental to achieving this goal. A set of 97 approved anti-diabetic drugs, representing the active domain, and a set of 2892 natural products, representing the inactive domain, were used to construct predictive models and to index anti-diabetic bioactivity. Our recently-developed approach of 'iterative stochastic elimination' was utilized. This article describes a highly discriminative and robust model, with an area under the curve above 0.96. Using the indexing model and a mix ratio of 1:1000 (active/inactive), 65% of the anti-diabetic drugs in the sample were captured in the top 1% of the screened compounds, compared to 1% in the random model. Some of the natural products that scored highly as potential anti-diabetic drug candidates are disclosed. One of those natural products is caffeine, which is noted in the scientific literature as having the capability to decrease blood glucose levels. The other nine phytochemicals await evaluation in a wet lab for their anti-diabetic activity. The indexing model proposed herein is useful for the virtual screening of large chemical databases and for the construction of anti-diabetes focused libraries.

Aggregation-Induced-Emission Materials with Different Electric Charges as an Artificial Tongue: Design, Construction, and Assembly with Various Pathogenic Bacteria for Effective Bacterial Imaging and Discrimination.

Science.gov (United States)

Liu, Guang-Jian; Tian, Sheng-Nan; Li, Cui-Yun; Xing, Guo-Wen; Zhou, Lei

2017-08-30

Imaging-based total bacterial count and type identification of bacteria play crucial roles in clinical diagnostics, public health, biological and medical science, and environmental protection. Herein, we designed and synthesized a series of tetraphenylethenes (TPEs) functionalized with one or two aldehyde, carboxylic acid, and quaternary ammonium groups, which were successfully used as fluorescent materials for rapid and efficient staining of eight kinds of representative bacterial species, including pathogenic bacteria Vibrio cholera, Klebsiella pneumoniae, and Listeria monocytogenes and potential bioterrorism agent Yersinia pestis. By comparing the fluorescence intensity changes of the aggregation-induced-emission (AIE) materials before and after bacteria incubation, the sensing mechanisms (electrostatic versus hydrophobic interactions) were simply discussed. Moreover, the designed AIE materials were successfully used as an efficient artificial tongue for bacteria discrimination, and all of the bacteria tested were identified via linear discriminant analysis. Our current work provided a general method for simultaneous broad-spectrum bacterial imaging and species discrimination, which is helpful for bacteria surveillance in many fields.

Multispectral Image Analysis for Robust Prediction of Astaxanthin Coating

DEFF Research Database (Denmark)

Ljungqvist, Martin Georg; Frosch, Stina; Nielsen, Michael Engelbrecht

2013-01-01

The aim of this study was to investigate the possibility of predicting the type and concentration level of astaxanthin coating of aquaculture feed pellets using multispectral image analysis. We used both natural and synthetic astaxanthin, and we used several different concentration levels...... of synthetic astaxanthin in combination with four different recipes of feed pellets. We used a VideometerLab with 20 spectral bands in the range of 385-1050 nm. We used linear discriminant analysis and sparse linear discriminant analysis for classification and variable selection. We used partial least squares...

Trace elemental imaging of rare earth elements discriminates tissues at microscale in flat fossils.

Science.gov (United States)

Gueriau, Pierre; Mocuta, Cristian; Dutheil, Didier B; Cohen, Serge X; Thiaudière, Dominique; Charbonnier, Sylvain; Clément, Gaël; Bertrand, Loïc

2014-01-01

The interpretation of flattened fossils remains a major challenge due to compression of their complex anatomies during fossilization, making critical anatomical features invisible or hardly discernible. Key features are often hidden under greatly preserved decay prone tissues, or an unpreparable sedimentary matrix. A method offering access to such anatomical features is of paramount interest to resolve taxonomic affinities and to study fossils after a least possible invasive preparation. Unfortunately, the widely-used X-ray micro-computed tomography, for visualizing hidden or internal structures of a broad range of fossils, is generally inapplicable to flattened specimens, due to the very high differential absorbance in distinct directions. Here we show that synchrotron X-ray fluorescence spectral raster-scanning coupled to spectral decomposition or a much faster Kullback-Leibler divergence based statistical analysis provides microscale visualization of tissues. We imaged exceptionally well-preserved fossils from the Late Cretaceous without needing any prior delicate preparation. The contrasting elemental distributions greatly improved the discrimination of skeletal elements material from both the sedimentary matrix and fossilized soft tissues. Aside content in alkaline earth elements and phosphorus, a critical parameter for tissue discrimination is the distinct amounts of rare earth elements. Local quantification of rare earths may open new avenues for fossil description but also in paleoenvironmental and taphonomical studies.

Local figure-ground cues are valid for natural images.

Science.gov (United States)

Fowlkes, Charless C; Martin, David R; Malik, Jitendra

2007-06-08

Figure-ground organization refers to the visual perception that a contour separating two regions belongs to one of the regions. Recent studies have found neural correlates of figure-ground assignment in V2 as early as 10-25 ms after response onset, providing strong support for the role of local bottom-up processing. How much information about figure-ground assignment is available from locally computed cues? Using a large collection of natural images, in which neighboring regions were assigned a figure-ground relation by human observers, we quantified the extent to which figural regions locally tend to be smaller, more convex, and lie below ground regions. Our results suggest that these Gestalt cues are ecologically valid, and we quantify their relative power. We have also developed a simple bottom-up computational model of figure-ground assignment that takes image contours as input. Using parameters fit to natural image statistics, the model is capable of matching human-level performance when scene context limited.

A natural-color mapping for single-band night-time image based on FPGA

Science.gov (United States)

Wang, Yilun; Qian, Yunsheng

2018-01-01

A natural-color mapping for single-band night-time image method based on FPGA can transmit the color of the reference image to single-band night-time image, which is consistent with human visual habits and can help observers identify the target. This paper introduces the processing of the natural-color mapping algorithm based on FPGA. Firstly, the image can be transformed based on histogram equalization, and the intensity features and standard deviation features of reference image are stored in SRAM. Then, the real-time digital images' intensity features and standard deviation features are calculated by FPGA. At last, FPGA completes the color mapping through matching pixels between images using the features in luminance channel.

Image segregation in strabismic amblyopia.

Science.gov (United States)

Levi, Dennis M

2007-06-01

Humans with naturally occurring amblyopia show deficits thought to involve mechanisms downstream of V1. These include excessive crowding, abnormal global image processing, spatial sampling and symmetry detection and undercounting. Several recent studies suggest that humans with naturally occurring amblyopia show deficits in global image segregation. The current experiments were designed to study figure-ground segregation in amblyopic observers with documented deficits in crowding, symmetry detection, spatial sampling and counting, using similar stimuli. Observers had to discriminate the orientation of a figure (an "E"-like pattern made up of 17 horizontal Gabor patches), embedded in a 7x7 array of Gabor patches. When the 32 "background" patches are vertical, the "E" pops-out, due to segregation by orientation and performance is perfect; however, if the background patches are all, or mostly horizontal, the "E" is camouflaged, and performance is random. Using a method of constant stimuli, we varied the number of "background" patches that were vertical and measured the probability of correct discrimination of the global orientation of the E (up/down/left/right). Surprisingly, amblyopes who showed strong crowding and deficits in symmetry detection and counting, perform normally or very nearly so in this segregation task. I therefore conclude that these deficits are not a consequence of abnormal segregation of figure from background.

Material Discrimination Based on K-edge Characteristics

Directory of Open Access Journals (Sweden)

Peng He

2013-01-01

Full Text Available Spectral/multienergy CT employing the state-of-the-art energy-discriminative photon-counting detector can identify absorption features in the multiple ranges of photon energies and has the potential to distinguish different materials based on K-edge characteristics. K-edge characteristics involve the sudden attenuation increase in the attenuation profile of a relatively high atomic number material. Hence, spectral CT can utilize material K-edge characteristics (sudden attenuation increase to capture images in available energy bins (levels/windows to distinguish different material components. In this paper, we propose an imaging model based on K-edge characteristics for maximum material discrimination with spectral CT. The wider the energy bin width is, the lower the noise level is, but the poorer the reconstructed image contrast is. Here, we introduce the contrast-to-noise ratio (CNR criterion to optimize the energy bin width after the K-edge jump for the maximum CNR. In the simulation, we analyze the reconstructed image quality in different energy bins and demonstrate that our proposed optimization approach can maximize CNR between target region and background region in reconstructed image.

Three-dimensional imaging utilizing energy discrimination

International Nuclear Information System (INIS)

Gunter, D.L.; Hoffman, K.R.; Beck, R.N.

1990-01-01

An algorithm is proposed for three-dimensional image reconstruction in nuclear medicine which uses scattered radiation rather than multiple projected images to determine the source depth within the body. Images taken from numerous energy windows are combined to construct the source distribution in the body. The gamma-ray camera is not moved during the imaging process. Experiments with both Tc-99m and Ga-67 demonstrate that two channels of depth information can be extracted from the low energy images produced by scattered radiation. By combining this technique with standard SPECT reconstruction using multiple projections the authors anticipate much improved spatial resolution in the overall three-dimensional reconstruction

Imaging near-surface heterogeneities by natural migration of backscattered surface waves

KAUST Repository

AlTheyab, Abdullah

2016-02-01

We present a migration method that does not require a velocity model to migrate backscattered surface waves to their projected locations on the surface. This migration method, denoted as natural migration, uses recorded Green\\'s functions along the surface instead of simulated Green\\'s functions. The key assumptions are that the scattering bodies are within the depth interrogated by the surface waves, and the Green\\'s functions are recorded with dense receiver sampling along the free surface. This natural migration takes into account all orders of multiples, mode conversions and non-linear effects of surface waves in the data. The natural imaging formulae are derived for both active source and ambient-noise data, and computer simulations show that natural migration can effectively image near-surface heterogeneities with typical ambient-noise sources and geophone distributions.

Neighbors Based Discriminative Feature Difference Learning for Kinship Verification

DEFF Research Database (Denmark)

Duan, Xiaodong; Tan, Zheng-Hua

2015-01-01

In this paper, we present a discriminative feature difference learning method for facial image based kinship verification. To transform feature difference of an image pair to be discriminative for kinship verification, a linear transformation matrix for feature difference between an image pair...... than the commonly used feature concatenation, leading to a low complexity. Furthermore, there is no positive semi-definitive constrain on the transformation matrix while there is in metric learning methods, leading to an easy solution for the transformation matrix. Experimental results on two public...... databases show that the proposed method combined with a SVM classification method outperforms or is comparable to state-of-the-art kinship verification methods. © Springer International Publishing AG, Part of Springer Science+Business Media...

A model of primate visual cortex based on category-specific redundancies in natural images

Science.gov (United States)

Malmir, Mohsen; Shiry Ghidary, S.

2010-12-01

Neurophysiological and computational studies have proposed that properties of natural images have a prominent role in shaping selectivity of neurons in the visual cortex. An important property of natural images that has been studied extensively is the inherent redundancy in these images. In this paper, the concept of category-specific redundancies is introduced to describe the complex pattern of dependencies between responses of linear filters to natural images. It is proposed that structural similarities between images of different object categories result in dependencies between responses of linear filters in different spatial scales. It is also proposed that the brain gradually removes these dependencies in different areas of the ventral visual hierarchy to provide a more efficient representation of its sensory input. The authors proposed a model to remove these redundancies and trained it with a set of natural images using general learning rules that are developed to remove dependencies between responses of neighbouring neurons. Results of experiments demonstrate the close resemblance of neuronal selectivity between different layers of the model and their corresponding visual areas.

Evidence of Persistent and Pervasive Workplace Discrimination Against LGBT People: The Need for Federal Legislation Prohibiting Discrimination and Providing for Equal Employment Benefits

OpenAIRE

Pizer, Jennifer; Mallory, Christy; Sears, Brad; Hunter, Nan

2012-01-01

Lesbian, gay, bisexual, and transgender (LGBT) people have experienced a long and pervasive history of employment discrimination. Today, more than eight million people in the American workforce identify as LGBT, but there still is no federal law that explicitly prohibits sexual orientation and gender identity discrimination against them.This Article begins by surveying the social science research and other evidence illustrating the nature and scope of the discrimination against LGBT workers a...

Prejudice and Discrimination as Expressions of Violence

Directory of Open Access Journals (Sweden)

Lourdes Bandeira

2002-01-01

Full Text Available This essay examines the construction of prejudice – and the visibility of the ensuing discriminations – associated with the emergence of differences, be it through the affirmation and manipulation of the conditions of difference or through their denial and dissimulation. In both cases, there is a lack of recognition of, or disrespect for, differences that is constitutive of new patterns of violence. This essay builds a bridge between discrimination and violence, emphasizing the diverse forms of discrimination and exclusion, which include: the juridical parameters related to co-existence and re-cognition; the social sciences approach to the construction of differences/non-similarities; the conceptual framework of the category ‘prejudice‘ and its derivative forms of discrimination and social exclusion; the mechanisms of prejudice; and the difference-prejudice relation, image and rationalization of the Other .

Valence of Facial Cues Influences Sheep Learning in a Visual Discrimination Task

Directory of Open Access Journals (Sweden)

Lucille G. A. Bellegarde

2017-11-01

Full Text Available Sheep are one of the most studied farm species in terms of their ability to process information from faces, but little is known about their face-based emotion recognition abilities. We investigated (a whether sheep could use images of sheep faces taken in situation of varying valence as cues in a simultaneous discrimination task and (b whether the valence of the situation affects their learning performance. To accomplish this, we photographed faces of sheep in three situations inducing emotional states of neutral (ruminating in the home pen or negative valence (social isolation or aggressive interaction. Sheep (n = 35 first had to learn a discrimination task with colored cards. Animals that reached the learning criterion (n = 16 were then presented with pairs of images of the face of a single individual taken in the neutral situation and in one of the negative situations. Finally, sheep had to generalize what they had learned to new pairs of images of faces taken in the same situation, but of a different conspecific. All sheep that learned the discrimination task with colored cards reached the learning criterion with images of faces. Sheep that had to associate a negative image with a food reward learned faster than sheep that had to associate a neutral image with a reward. With the exception of sheep from the aggression-rewarded group, sheep generalized this discrimination to images of faces of different individuals. Our results suggest that sheep can perceive the emotional valence displayed on faces of conspecifics and that this valence affects learning processes.

Indexing Natural Products for Their Potential Anti-Diabetic Activity: Filtering and Mapping Discriminative Physicochemical Properties

Directory of Open Access Journals (Sweden)

Mouhammad Zeidan

2017-09-01

Full Text Available Diabetes mellitus (DM poses a major health problem, for which there is an unmet need to develop novel drugs. The application of in silico techniques and optimization algorithms is instrumental to achieving this goal. A set of 97 approved anti-diabetic drugs, representing the active domain, and a set of 2892 natural products, representing the inactive domain, were used to construct predictive models and to index anti-diabetic bioactivity. Our recently-developed approach of ‘iterative stochastic elimination’ was utilized. This article describes a highly discriminative and robust model, with an area under the curve above 0.96. Using the indexing model and a mix ratio of 1:1000 (active/inactive, 65% of the anti-diabetic drugs in the sample were captured in the top 1% of the screened compounds, compared to 1% in the random model. Some of the natural products that scored highly as potential anti-diabetic drug candidates are disclosed. One of those natural products is caffeine, which is noted in the scientific literature as having the capability to decrease blood glucose levels. The other nine phytochemicals await evaluation in a wet lab for their anti-diabetic activity. The indexing model proposed herein is useful for the virtual screening of large chemical databases and for the construction of anti-diabetes focused libraries.

Discrimination learning with variable stimulus 'salience'

Directory of Open Access Journals (Sweden)

Treviño Mario

2011-08-01

Full Text Available Abstract Background In nature, sensory stimuli are organized in heterogeneous combinations. Salient items from these combinations 'stand-out' from their surroundings and determine what and how we learn. Yet, the relationship between varying stimulus salience and discrimination learning remains unclear. Presentation of the hypothesis A rigorous formulation of the problem of discrimination learning should account for varying salience effects. We hypothesize that structural variations in the environment where the conditioned stimulus (CS is embedded will be a significant determinant of learning rate and retention level. Testing the hypothesis Using numerical simulations, we show how a modified version of the Rescorla-Wagner model, an influential theory of associative learning, predicts relevant interactions between varying salience and discrimination learning. Implications of the hypothesis If supported by empirical data, our model will help to interpret critical experiments addressing the relations between attention, discrimination and learning.

Ship-Iceberg Discrimination in Sentinel-2 Multispectral Imagery by Supervised Classification

Directory of Open Access Journals (Sweden)

Peder Heiselberg

2017-11-01

Full Text Available The European Space Agency Sentinel-2 satellites provide multispectral images with pixel sizes down to 10 m. This high resolution allows for fast and frequent detection, classification and discrimination of various objects in the sea, which is relevant in general and specifically for the vast Arctic environment. We analyze several sets of multispectral image data from Denmark and Greenland fall and winter, and describe a supervised search and classification algorithm based on physical parameters that successfully finds and classifies all objects in the sea with reflectance above a threshold. It discriminates between objects like ships, islands, wakes, and icebergs, ice floes, and clouds with accuracy better than 90%. Pan-sharpening the infrared bands leads to classification and discrimination of ice floes and clouds better than 95%. For complex images with abundant ice floes or clouds, however, the false alarm rate dominates for small non-sailing boats.

How discriminating are discriminative instruments?

Science.gov (United States)

Hankins, Matthew

2008-05-27

The McMaster framework introduced by Kirshner & Guyatt is the dominant paradigm for the development of measures of health status and health-related quality of life (HRQL). The framework defines the functions of such instruments as evaluative, predictive or discriminative. Evaluative instruments are required to be sensitive to change (responsiveness), but there is no corresponding index of the degree to which discriminative instruments are sensitive to cross-sectional differences. This paper argues that indices of validity and reliability are not sufficient to demonstrate that a discriminative instrument performs its function of discriminating between individuals, and that the McMaster framework would be augmented by the addition of a separate index of discrimination. The coefficient proposed by Ferguson (Delta) is easily adapted to HRQL instruments and is a direct, non-parametric index of the degree to which an instrument distinguishes between individuals. While Delta should prove useful in the development and evaluation of discriminative instruments, further research is required to elucidate the relationship between the measurement properties of discrimination, reliability and responsiveness.

How discriminating are discriminative instruments?

Directory of Open Access Journals (Sweden)

Hankins Matthew

2008-05-01

Full Text Available Abstract The McMaster framework introduced by Kirshner & Guyatt is the dominant paradigm for the development of measures of health status and health-related quality of life (HRQL. The framework defines the functions of such instruments as evaluative, predictive or discriminative. Evaluative instruments are required to be sensitive to change (responsiveness, but there is no corresponding index of the degree to which discriminative instruments are sensitive to cross-sectional differences. This paper argues that indices of validity and reliability are not sufficient to demonstrate that a discriminative instrument performs its function of discriminating between individuals, and that the McMaster framework would be augmented by the addition of a separate index of discrimination. The coefficient proposed by Ferguson (Delta is easily adapted to HRQL instruments and is a direct, non-parametric index of the degree to which an instrument distinguishes between individuals. While Delta should prove useful in the development and evaluation of discriminative instruments, further research is required to elucidate the relationship between the measurement properties of discrimination, reliability and responsiveness.

A discrimination model in waste plastics sorting using NIR hyperspectral imaging system.

Science.gov (United States)

Zheng, Yan; Bai, Jiarui; Xu, Jingna; Li, Xiayang; Zhang, Yimin

2018-02-01

Classification of plastics is important in the recycling industry. A plastic identification model in the near infrared spectroscopy wavelength range 1000-2500 nm is proposed for the characterization and sorting of waste plastics using acrylonitrile butadiene styrene (ABS), polystyrene (PS), polypropylene (PP), polyethylene (PE), polyethylene terephthalate (PET), and polyvinyl chloride (PVC). The model is built by the feature wavelengths of standard samples applying the principle component analysis (PCA), and the accuracy, property and cross-validation of the model were analyzed. The model just contains a simple equation, center of mass coordinates, and radial distance, with which it is easy to develop classification and sorting software. A hyperspectral imaging system (HIS) with the identification model verified its practical application by using the unknown plastics. Results showed that the identification accuracy of unknown samples is 100%. All results suggested that the discrimination model was potential to an on-line characterization and sorting platform of waste plastics based on HIS. Copyright © 2017 Elsevier Ltd. All rights reserved.

HYDRA: Revealing heterogeneity of imaging and genetic patterns through a multiple max-margin discriminative analysis framework.

Science.gov (United States)

Varol, Erdem; Sotiras, Aristeidis; Davatzikos, Christos

2017-01-15

Multivariate pattern analysis techniques have been increasingly used over the past decade to derive highly sensitive and specific biomarkers of diseases on an individual basis. The driving assumption behind the vast majority of the existing methodologies is that a single imaging pattern can distinguish between healthy and diseased populations, or between two subgroups of patients (e.g., progressors vs. non-progressors). This assumption effectively ignores the ample evidence for the heterogeneous nature of brain diseases. Neurodegenerative, neuropsychiatric and neurodevelopmental disorders are largely characterized by high clinical heterogeneity, which likely stems in part from underlying neuroanatomical heterogeneity of various pathologies. Detecting and characterizing heterogeneity may deepen our understanding of disease mechanisms and lead to patient-specific treatments. However, few approaches tackle disease subtype discovery in a principled machine learning framework. To address this challenge, we present a novel non-linear learning algorithm for simultaneous binary classification and subtype identification, termed HYDRA (Heterogeneity through Discriminative Analysis). Neuroanatomical subtypes are effectively captured by multiple linear hyperplanes, which form a convex polytope that separates two groups (e.g., healthy controls from pathologic samples); each face of this polytope effectively defines a disease subtype. We validated HYDRA on simulated and clinical data. In the latter case, we applied the proposed method independently to the imaging and genetic datasets of the Alzheimer's Disease Neuroimaging Initiative (ADNI 1) study. The imaging dataset consisted of T1-weighted volumetric magnetic resonance images of 123 AD patients and 177 controls. The genetic dataset consisted of single nucleotide polymorphism information of 103 AD patients and 139 controls. We identified 3 reproducible subtypes of atrophy in AD relative to controls: (1) diffuse and extensive

Trace elemental imaging of rare earth elements discriminates tissues at microscale in flat fossils.

Directory of Open Access Journals (Sweden)

Pierre Gueriau

Full Text Available The interpretation of flattened fossils remains a major challenge due to compression of their complex anatomies during fossilization, making critical anatomical features invisible or hardly discernible. Key features are often hidden under greatly preserved decay prone tissues, or an unpreparable sedimentary matrix. A method offering access to such anatomical features is of paramount interest to resolve taxonomic affinities and to study fossils after a least possible invasive preparation. Unfortunately, the widely-used X-ray micro-computed tomography, for visualizing hidden or internal structures of a broad range of fossils, is generally inapplicable to flattened specimens, due to the very high differential absorbance in distinct directions. Here we show that synchrotron X-ray fluorescence spectral raster-scanning coupled to spectral decomposition or a much faster Kullback-Leibler divergence based statistical analysis provides microscale visualization of tissues. We imaged exceptionally well-preserved fossils from the Late Cretaceous without needing any prior delicate preparation. The contrasting elemental distributions greatly improved the discrimination of skeletal elements material from both the sedimentary matrix and fossilized soft tissues. Aside content in alkaline earth elements and phosphorus, a critical parameter for tissue discrimination is the distinct amounts of rare earth elements. Local quantification of rare earths may open new avenues for fossil description but also in paleoenvironmental and taphonomical studies.

Asymmetry and irregularity border as discrimination factor between melanocytic lesions

Science.gov (United States)

Sbrissa, David; Pratavieira, Sebastião.; Salvio, Ana Gabriela; Kurachi, Cristina; Bagnato, Vanderlei Salvadori; Costa, Luciano Da Fontoura; Travieso, Gonzalo

2015-06-01

Image processing tools have been widely used in systems supporting medical diagnosis. The use of mobile devices for the diagnosis of melanoma can assist doctors and improve their diagnosis of a melanocytic lesion. This study proposes a method of image analysis for melanoma discrimination from other types of melanocytic lesions, such as regular and atypical nevi. The process is based on extracting features related with asymmetry and border irregularity. It were collected 104 images, from medical database of two years. The images were obtained with standard digital cameras without lighting and scale control. Metrics relating to the characteristics of shape, asymmetry and curvature of the contour were extracted from segmented images. Linear Discriminant Analysis was performed for dimensionality reduction and data visualization. Segmentation results showed good efficiency in the process, with approximately 88:5% accuracy. Validation results presents sensibility and specificity 85% and 70% for melanoma detection, respectively.

Weighted Discriminative Dictionary Learning based on Low-rank Representation

International Nuclear Information System (INIS)

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. (paper)

Motion nature projection reduces patient's psycho-physiological anxiety during CT imaging.

NARCIS (Netherlands)

Zijlstra, Emma; Hagedoorn, Mariët; Krijnen, Wim; van der Schans, Cees; Mobach, Mark P.

2017-01-01

A growing body of evidence indicates that natural environments can positively influence people. This study investigated whether the use of motion nature projection in computed tomography (CT) imaging rooms is effective in mitigating psycho-physiological anxiety (vs. no intervention) using a

Sparse representation for infrared Dim target detection via a discriminative over-complete dictionary learned online.

Science.gov (United States)

Li, Zheng-Zhou; Chen, Jing; Hou, Qian; Fu, Hong-Xia; Dai, Zhen; Jin, Gang; Li, Ru-Zhang; Liu, Chang-Ju

2014-05-27

It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD) algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn't be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively.

Sparse Representation for Infrared Dim Target Detection via a Discriminative Over-Complete Dictionary Learned Online

Directory of Open Access Journals (Sweden)

Zheng-Zhou Li

2014-05-01

Full Text Available It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn’t be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively.

Discriminative Elastic-Net Regularized Linear Regression.

Science.gov (United States)

Zhang, Zheng; Lai, Zhihui; Xu, Yong; Shao, Ling; Wu, Jian; Xie, Guo-Sen

2017-03-01

In this paper, we aim at learning compact and discriminative linear regression models. Linear regression has been widely used in different problems. However, most of the existing linear regression methods exploit the conventional zero-one matrix as the regression targets, which greatly narrows the flexibility of the regression model. Another major limitation of these methods is that the learned projection matrix fails to precisely project the image features to the target space due to their weak discriminative capability. To this end, we present an elastic-net regularized linear regression (ENLR) framework, and develop two robust linear regression models which possess the following special characteristics. First, our methods exploit two particular strategies to enlarge the margins of different classes by relaxing the strict binary targets into a more feasible variable matrix. Second, a robust elastic-net regularization of singular values is introduced to enhance the compactness and effectiveness of the learned projection matrix. Third, the resulting optimization problem of ENLR has a closed-form solution in each iteration, which can be solved efficiently. Finally, rather than directly exploiting the projection matrix for recognition, our methods employ the transformed features as the new discriminate representations to make final image classification. Compared with the traditional linear regression model and some of its variants, our method is much more accurate in image classification. Extensive experiments conducted on publicly available data sets well demonstrate that the proposed framework can outperform the state-of-the-art methods. The MATLAB codes of our methods can be available at http://www.yongxu.org/lunwen.html.

Ship-Iceberg Discrimination in Sentinel-2 Multispectral Imagery by Supervised Classification

DEFF Research Database (Denmark)

Heiselberg, Peder; Heiselberg, Henning

2017-01-01

. It discriminates between objects like ships, islands, wakes, and icebergs, ice floes, and clouds with accuracy better than 90%. Pan-sharpening the infrared bands leads to classification and discrimination of ice floes and clouds better than 95%. For complex images with abundant ice floes or clouds, however...

Automated Image Sampling and Classification Can Be Used to Explore Perceived Naturalness of Urban Spaces.

Directory of Open Access Journals (Sweden)

Roger Hyam

Full Text Available The psychological restorative effects of exposure to nature are well established and extend to just viewing of images of nature. A previous study has shown that Perceived Naturalness (PN of images correlates with their restorative value. This study tests whether it is possible to detect degree of PN of images using an image classifier. It takes images that have been scored by humans for PN (including a subset that have been assessed for restorative value and passes them through the Google Vision API image classification service. The resulting labels are assigned to broad semantic classes to create a Calculated Semantic Naturalness (CSN metric for each image. It was found that CSN correlates with PN. CSN was then calculated for a geospatial sampling of Google Street View images across the city of Edinburgh. CSN was found to correlate with PN in this sample also indicating the technique may be useful in large scale studies. Because CSN correlates with PN which correlates with restorativeness it is suggested that CSN or a similar measure may be useful in automatically detecting restorative images and locations. In an exploratory aside CSN was not found to correlate with an indicator of socioeconomic deprivation.

Social and nonsocial category discriminations in a chimpanzee (Pan troglodytes) and American black bears (Ursus americanus).

Science.gov (United States)

Vonk, Jennifer; Johnson-Ulrich, Zoe

2014-09-01

One captive adult chimpanzee and 3 adult American black bears were presented with a series of natural category discrimination tasks on a touch-screen computer. This is the first explicit comparison of bear and primate abilities using identical tasks, and the first test of a social concept in a carnivore. The discriminations involved a social relationship category (mother/offspring) and a nonsocial category involving food items. The social category discrimination could be made using knowledge of the overarching mother/offspring concept, whereas the nonsocial category discriminations could be made only by using perceptual rules, such as "choose images that show larger and smaller items of the same type." The bears failed to show above-chance transfer on either the social or nonsocial discriminations, indicating that they did not use either the perceptual rule or knowledge of the overarching concept of mother/offspring to guide their choices in these tasks. However, at least 1 bear remembered previously reinforced stimuli when these stimuli were recombined, later. The chimpanzee showed transfer on a control task and did not consistently apply a perceptual rule to solve the nonsocial task, so it is possible that he eventually acquired the social concept. Further comparisons between species on identical tasks assessing social knowledge will help illuminate the selective pressures responsible for a range of social cognitive skills.

Perceptions about gender-based discrimination in a selection of South African companies / Renier Steyn

OpenAIRE

Steyn, Renier

2014-01-01

Introduction: From a legal point of view, gender-based discrimination is not condoned in the workplace. However, perceptions that such discrimination exists persist. Understanding the extent and nature of the phenomenon may contribute to the management thereof. Aim: The aim of this research was to report on the nature and level of workplace gender-based discrimination from the perspective of managers and employees, as well as by making use of objective measures. Method: Interviews were conduc...

Thermal infrared imaging of the variability of canopy-air temperature difference distribution for heavy metal stress levels discrimination in rice

Science.gov (United States)

Zhang, Biyao; Liu, Xiangnan; Liu, Meiling; Wang, Dongmin

2017-04-01

This paper addresses the assessment and interpretation of the canopy-air temperature difference (Tc-Ta) distribution as an indicator for discriminating between heavy metal stress levels. Tc-Ta distribution is simulated by coupling the energy balance equation with modified leaf angle distribution. Statistical indices including average value (AVG), standard deviation (SD), median, and span of Tc-Ta in the field of view of a digital thermal imager are calculated to describe Tc-Ta distribution quantitatively and, consequently, became the stress indicators. In the application, two grains of rice growing sites under "mild" and "severe" stress level were selected as study areas. A total of 96 thermal images obtained from the field measurements in the three growth stages were used for a separate application of a theoretical variation of Tc-Ta distribution. The results demonstrated that the statistical indices calculated from both simulated and measured data exhibited an upward trend as the stress level becomes serious because heavy metal stress would only raise a portion of the leaves in the canopy. Meteorological factors could barely affect the sensitivity of the statistical indices with the exception of the wind speed. Among the statistical indices, AVG and SD were demonstrated to be better indicators for stress levels discrimination.

Spatial discrimination and visual discrimination

DEFF Research Database (Denmark)

Haagensen, Annika M. J.; Grand, Nanna; Klastrup, Signe

2013-01-01

Two methods investigating learning and memory in juvenile Gottingen minipigs were evaluated for potential use in preclinical toxicity testing. Twelve minipigs were tested using a spatial hole-board discrimination test including a learning phase and two memory phases. Five minipigs were tested...... in a visual discrimination test. The juvenile minipigs were able to learn the spatial hole-board discrimination test and showed improved working and reference memory during the learning phase. Performance in the memory phases was affected by the retention intervals, but the minipigs were able to remember...... the concept of the test in both memory phases. Working memory and reference memory were significantly improved in the last trials of the memory phases. In the visual discrimination test, the minipigs learned to discriminate between the three figures presented to them within 9-14 sessions. For the memory test...

Combination of RGB and multispectral imagery for discrimination of cabernet sauvignon grapevine elements.

Science.gov (United States)

Fernández, Roemi; Montes, Héctor; Salinas, Carlota; Sarria, Javier; Armada, Manuel

2013-06-19

This paper proposes a sequential masking algorithm based on the K-means method that combines RGB and multispectral imagery for discrimination of Cabernet Sauvignon grapevine elements in unstructured natural environments, without placing any screen behind the canopy and without any previous preparation of the vineyard. In this way, image pixels are classified into five clusters corresponding to leaves, stems, branches, fruit and background. A custom-made sensory rig that integrates a CCD camera and a servo-controlled filter wheel has been specially designed and manufactured for the acquisition of images during the experimental stage. The proposed algorithm is extremely simple, efficient, and provides a satisfactory rate of classification success. All these features turn out the proposed algorithm into an appropriate candidate to be employed in numerous tasks of the precision viticulture, such as yield estimation, water and nutrients needs estimation, spraying and harvesting.

Autofluorescence imaging system to discriminate and quantify the distribution of benthic cyanobacteria and diatoms

DEFF Research Database (Denmark)

Carreira, Cátia; Staal, Marc Jaap; Middelboe, Mathias

2015-01-01

successfully to (mixed) laboratory cultures as well as natural photosynthetic microbial mats. Cultures of the diatom Nitzschia capitellata and the cyanobacterium Geitlerinema sp. showed close correlation between autofluorescence and cell abundance. This simple and cheap imaging system allows fast observations...

Text Detection in Natural Scene Images by Stroke Gabor Words.

Science.gov (United States)

Yi, Chucai; Tian, Yingli

2011-01-01

In this paper, we propose a novel algorithm, based on stroke components and descriptive Gabor filters, to detect text regions in natural scene images. Text characters and strings are constructed by stroke components as basic units. Gabor filters are used to describe and analyze the stroke components in text characters or strings. We define a suitability measurement to analyze the confidence of Gabor filters in describing stroke component and the suitability of Gabor filters on an image window. From the training set, we compute a set of Gabor filters that can describe principle stroke components of text by their parameters. Then a K -means algorithm is applied to cluster the descriptive Gabor filters. The clustering centers are defined as Stroke Gabor Words (SGWs) to provide a universal description of stroke components. By suitability evaluation on positive and negative training samples respectively, each SGW generates a pair of characteristic distributions of suitability measurements. On a testing natural scene image, heuristic layout analysis is applied first to extract candidate image windows. Then we compute the principle SGWs for each image window to describe its principle stroke components. Characteristic distributions generated by principle SGWs are used to classify text or nontext windows. Experimental results on benchmark datasets demonstrate that our algorithm can handle complex backgrounds and variant text patterns (font, color, scale, etc.).

Image analysis of food particles can discriminate deficient mastication of mixed foodstuffs simulating daily meal.

Science.gov (United States)

Sugimoto, K; Hashimoto, Y; Fukuike, C; Kodama, N; Minagi, S

2014-03-01

Because food texture is regarded as an important factor for smooth deglutition, identification of objective parameters that could provide a basis for food texture selection for elderly or dysphagic patients is of great importance. We aimed to develop an objective evaluation method of mastication using a mixed test food comprising foodstuffs, simulating daily dietary life. The particle size distribution (>2 mm in diameter) in a bolus was analysed using a digital image under dark-field illumination. Ten female participants (mean age ± s.d., 27·6 ± 2·6 years) masticated a mixed test food comprising prescribed amounts of rice, sausage, hard omelette, raw cabbage and raw cucumber with 100%, 75%, 50% and 25% of the number of their masticatory strokes. A single set of coefficient thresholds of 0·10 for the homogeneity index and 1·62 for the particle size index showed excellent discrimination of deficient masticatory conditions with high sensitivity (0·90) and specificity (0·77). Based on the results of this study, normal mastication was discriminated from deficient masticatory conditions using a large particle analysis of mixed foodstuffs, thus showing the possibility of future application of this method for objective decision-making regarding the properties of meals served to dysphagic patients. © 2014 John Wiley & Sons Ltd.

Discrimination and Anti-discrimination in Denmark

DEFF Research Database (Denmark)

Olsen, Tore Vincents

The purpose of this report is to describe and analyse Danish anti-discrimination legislation and the debate about discrimination in Denmark in order to identify present and future legal challenges. The main focus is the implementation of the EU anti-discrimination directives in Danish law...

Transformation invariant image indexing and retrieval for image databases

NARCIS (Netherlands)

Gevers, Th.; Smeulders, A.W.M.

1994-01-01

This paper presents a novel design of an image database system which supports storage, indexing and retrieval of images by content. The image retrieval methodology is based on the observation that images can be discriminated by the presence of image objects and their spatial relations. Images in the

Epilepsy and workplace discrimination: population characteristics and trends.

Science.gov (United States)

West, Michael D; Dye, Amy N; McMahon, Brian T

2006-08-01

This study investigates the nature of allegations of workplace discrimination made by job seekers and workers with epilepsy. Demographic characteristics of individuals making allegations were consistent with those of individuals with epilepsy nationwide. Approximately three-fourths of allegations were related to post-hire issues, such as discrimination in promotion and termination, disciplinary actions, and harassment. The lowest rate of merit allegation was related to discrimination in hiring. Comparison of merit allegations before and after the U.S. Supreme Court's Sutton decision revealed that claimants have had higher rates of success following the decision, suggesting that the Sutton decision has had no negative effect on claimants with epilepsy.

Classification of Astaxanthin Colouration of Salmonid Fish using Spectral Imaging and Tricolour Measurement

DEFF Research Database (Denmark)

Ljungqvist, Martin Georg; Dissing, Bjørn Skovlund; Nielsen, Michael Engelbrecht

capturing, tricolour CIELAB measurement, and manual SalmoFan inspection. Furthermore it was tested whether the best predictions come from measurements of the steak or the fillet of the fish. Methods used for classication were linear discriminant analysis (LDA), quadratic discriminant analysis (QDA......The goal of this study was to investigate if it is possible to differentiate between rainbow trout (Oncorhynchus mykiss) having been fed with natural or synthetic astaxanthin. Three different techniques were used for visual inspection of the surface colour of the fish meat: multi-spectral image...

Discrimination between Newly Formed and Aged Thrombi Using Empirical Mode Decomposition of Ultrasound B-Scan Image

Directory of Open Access Journals (Sweden)

Jui Fang

2015-01-01

Full Text Available Ultrasound imaging is a first-line diagnostic method for screening the thrombus. During thrombus aging, the proportion of red blood cells (RBCs in the thrombus decreases and therefore the signal intensity of B-scan can be used to detect the thrombus age. To avoid the effect of system gain on the measurements, this study proposed using the empirical mode decomposition (EMD of ultrasound image as a strategy to classify newly formed and aged thrombi. Porcine blood samples were used for the in vitro induction of fresh and aged thrombi (at hematocrits of 40%. Each thrombus was imaged using an ultrasound scanner at different gains (15, 20, and 30 dB. Then, EMD of ultrasound signals was performed to obtain the first and second intrinsic mode functions (IMFs, which were further used to calculate the IMF-based echogenicity ratio (IER. The results showed that the performance of using signal amplitude of B-scan to reflect the thrombus age depends on gain. However, the IER is less affected by the gain in discriminating between fresh and aged thrombi. In the future, ultrasound B-scan combined with the EMD may be used to identify the thrombus age for the establishment of thrombolytic treatment planning.

Manifold regularized discriminative nonnegative matrix factorization with fast gradient descent.

Science.gov (United States)

Guan, Naiyang; Tao, Dacheng; Luo, Zhigang; Yuan, Bo

2011-07-01

Nonnegative matrix factorization (NMF) has become a popular data-representation method and has been widely used in image processing and pattern-recognition problems. This is because the learned bases can be interpreted as a natural parts-based representation of data and this interpretation is consistent with the psychological intuition of combining parts to form a whole. For practical classification tasks, however, NMF ignores both the local geometry of data and the discriminative information of different classes. In addition, existing research results show that the learned basis is unnecessarily parts-based because there is neither explicit nor implicit constraint to ensure the representation parts-based. In this paper, we introduce the manifold regularization and the margin maximization to NMF and obtain the manifold regularized discriminative NMF (MD-NMF) to overcome the aforementioned problems. The multiplicative update rule (MUR) can be applied to optimizing MD-NMF, but it converges slowly. In this paper, we propose a fast gradient descent (FGD) to optimize MD-NMF. FGD contains a Newton method that searches the optimal step length, and thus, FGD converges much faster than MUR. In addition, FGD includes MUR as a special case and can be applied to optimizing NMF and its variants. For a problem with 165 samples in R(1600), FGD converges in 28 s, while MUR requires 282 s. We also apply FGD in a variant of MD-NMF and experimental results confirm its efficiency. Experimental results on several face image datasets suggest the effectiveness of MD-NMF.

A toolbox and sample object perception data for equalization of natural images

Directory of Open Access Journals (Sweden)

Wilma A. Bainbridge

2015-12-01

Full Text Available For psychologists and neuroscientists, careful selection of their stimuli is essential, so that low-level visual features such as color or spatial frequency do not serve as confounds between conditions of interest. Here, we detail the Natural Image Statistical Toolbox, which allows scientists to measure, visualize, and control stimulus sets along a set of low-level visual properties. Additionally, we provide a set of object images varying along several perceptual object properties, including physical size and interaction envelope size (i.e., the space around an object transversed during an interaction, serving as a test-bed for the Natural Image Statistical Toolbox. This stimulus set is also a highly characterized set useful to psychology and neuroscience studies on object perception.

The immune system, natural autoantibodies and general homeostasis in health and disease.

Science.gov (United States)

Poletaev, A; Boura, P

2011-10-01

It is generally accepted that the destination of the immune system is not only to discriminate between self and non-self but also to mount responses against non-self. During the last decades, it became evident that weak self-reactivity is a necessary condition for immune homeostasis. Natural self reactivity and the internal image created by autoantibodies, participate greatly to the maintenance of homeostasis. Under conditions of increased or altered antigenic pressure, the homeostatic status is disrupted and the organism becomes vulnerable to the emergence of diseases. "Immunculus" is the self-reactive and interconnected entity of the immune system, provided by a complicated network of natural autoantibobies of different specificity, as a mosaic picture. Quantitative changes in each part of the image are related to variations of expression of relative antigens. The immune system takes in account image information from the continuous screening of the antigenic status and compares between presented state and the desired (optimal) one. Substantial and prolonged deviations from the optimal state, triggers the induction of compensatory and reparative processes, aiming to restore molecular and functional homeostasis. So, natural autoimmunity through the ability of natural a-Abs to induce mechanisms of natural and acquired immunity, aims to prevent pathogenic processes and maintain or restore health status.

SU-F-R-39: Effects of Radiation Dose Reduction On Renal Cell Carcinoma Discrimination Using Multi-Phasic CT Imaging

Energy Technology Data Exchange (ETDEWEB)

Wahi-Anwar, M; Young, S; Lo, P; Raman, S; Kim, H; Brown, M; McNitt-Gray, M; Coy, H; Ashen-Garry, D; Pace-Soler, E [UCLA School of Medicine, Los Angeles, CA (United States)

2016-06-15

Purpose: A method to discriminate different types of renal cell carcinoma (RCC) was developed using attenuation values observed in multiphasic contrast-enhanced CT. This work evaluates the sensitivity of this RCC discrimination task at different CT radiation dose levels. Methods: We selected 5 cases of kidney lesion patients who had undergone four-phase CT scans covering the abdomen to the lilac crest. Through an IRB-approved study, the scans were conducted on 64-slice CT scanners (Definition AS/Definition Flash, Siemens Healthcare) using automatic tube-current modulation (TCM). The protocol included an initial baseline unenhanced scan, followed by three post-contrast injection phases. CTDIvol (32 cm phantom) measured between 9 to 35 mGy for any given phase. As a preliminary study, we limited the scope to the cortico-medullary phase—shown previously to be the most discriminative phase. A previously validated method was used to simulate a reduced dose acquisition via adding noise to raw CT sinogram data, emulating corresponding images at simulated doses of 50%, 25%, and 10%. To discriminate the lesion subtype, ROIs were placed in the most enhancing region of the lesion. The mean HU value of an ROI was extracted and used to discriminate to the worst-case RCC subtype, ranked in the order of clear cell, papillary, chromophobe and the benign oncocytoma. Results: Two patients exhibited a change of worst case RCC subtype between original and simulated scans, at 25% and 10% doses. In one case, the worst-case RCC subtype changed from oncocytoma to chromophobe at 10% and 25% doses, while the other case changed from oncocytoma to clear cell at 10% dose. Conclusion: Based on preliminary results from an initial cohort of 5 patients, worst-case RCC subtypes remained constant at all simulated dose levels except for 2 patients. Further study conducted on more patients will be needed to confirm our findings. Institutional research agreement, Siemens Healthcare; Past recipient

SU-F-R-39: Effects of Radiation Dose Reduction On Renal Cell Carcinoma Discrimination Using Multi-Phasic CT Imaging

International Nuclear Information System (INIS)

Wahi-Anwar, M; Young, S; Lo, P; Raman, S; Kim, H; Brown, M; McNitt-Gray, M; Coy, H; Ashen-Garry, D; Pace-Soler, E

2016-01-01

Purpose: A method to discriminate different types of renal cell carcinoma (RCC) was developed using attenuation values observed in multiphasic contrast-enhanced CT. This work evaluates the sensitivity of this RCC discrimination task at different CT radiation dose levels. Methods: We selected 5 cases of kidney lesion patients who had undergone four-phase CT scans covering the abdomen to the lilac crest. Through an IRB-approved study, the scans were conducted on 64-slice CT scanners (Definition AS/Definition Flash, Siemens Healthcare) using automatic tube-current modulation (TCM). The protocol included an initial baseline unenhanced scan, followed by three post-contrast injection phases. CTDIvol (32 cm phantom) measured between 9 to 35 mGy for any given phase. As a preliminary study, we limited the scope to the cortico-medullary phase—shown previously to be the most discriminative phase. A previously validated method was used to simulate a reduced dose acquisition via adding noise to raw CT sinogram data, emulating corresponding images at simulated doses of 50%, 25%, and 10%. To discriminate the lesion subtype, ROIs were placed in the most enhancing region of the lesion. The mean HU value of an ROI was extracted and used to discriminate to the worst-case RCC subtype, ranked in the order of clear cell, papillary, chromophobe and the benign oncocytoma. Results: Two patients exhibited a change of worst case RCC subtype between original and simulated scans, at 25% and 10% doses. In one case, the worst-case RCC subtype changed from oncocytoma to chromophobe at 10% and 25% doses, while the other case changed from oncocytoma to clear cell at 10% dose. Conclusion: Based on preliminary results from an initial cohort of 5 patients, worst-case RCC subtypes remained constant at all simulated dose levels except for 2 patients. Further study conducted on more patients will be needed to confirm our findings. Institutional research agreement, Siemens Healthcare; Past recipient

Number of perceptually distinct surface colors in natural scenes.

Science.gov (United States)

Marín-Franch, Iván; Foster, David H

2010-09-30

The ability to perceptually identify distinct surfaces in natural scenes by virtue of their color depends not only on the relative frequency of surface colors but also on the probabilistic nature of observer judgments. Previous methods of estimating the number of discriminable surface colors, whether based on theoretical color gamuts or recorded from real scenes, have taken a deterministic approach. Thus, a three-dimensional representation of the gamut of colors is divided into elementary cells or points which are spaced at one discrimination-threshold unit intervals and which are then counted. In this study, information-theoretic methods were used to take into account both differing surface-color frequencies and observer response uncertainty. Spectral radiances were calculated from 50 hyperspectral images of natural scenes and were represented in a perceptually almost uniform color space. The average number of perceptually distinct surface colors was estimated as 7.3 × 10(3), much smaller than that based on counting methods. This number is also much smaller than the number of distinct points in a scene that are, in principle, available for reliable identification under illuminant changes, suggesting that color constancy, or the lack of it, does not generally determine the limit on the use of color for surface identification.

A neural network approach to discrimination between defects and calyces in oranges

Directory of Open Access Journals (Sweden)

Salvatore Ingrassia

1993-11-01

Full Text Available The problem of automatic discrimination among pictures concerning either defects or calyces in oranges is approached. The method here proposed is based on a statistical analysis of the grey-levels and the shape of calyces in the pictures. Some suitable statistical indices are considered and the discriminant function is designed by means of a neural network on the basis of a suitable vector representation of the images. Numerical experiments give 5 misclassifications in a set of 52 images, where only three defects have been classified as calyces.

Imaging near-surface heterogeneities by natural migration of surface waves

KAUST Repository

Liu, Zhaolun; AlTheyab, Abdullah; Hanafy, Sherif M.; Schuster, Gerard T.

2016-01-01

We demonstrate that near-surface heterogeneities can be imaged by natural migration of backscattered surface waves in common shot gathers. No velocity model is required because the data are migrated onto surface points with the virtual Green

Combination of RGB and Multispectral Imagery for Discrimination of Cabernet Sauvignon Grapevine Elements

Directory of Open Access Journals (Sweden)

Carlota Salinas

2013-06-01

Full Text Available This paper proposes a sequential masking algorithm based on the K-means method that combines RGB and multispectral imagery for discrimination of Cabernet Sauvignon grapevine elements in unstructured natural environments, without placing any screen behind the canopy and without any previous preparation of the vineyard. In this way, image pixels are classified into five clusters corresponding to leaves, stems, branches, fruit and background. A custom-made sensory rig that integrates a CCD camera and a servo-controlled filter wheel has been specially designed and manufactured for the acquisition of images during the experimental stage. The proposed algorithm is extremely simple, efficient, and provides a satisfactory rate of classification success. All these features turn out the proposed algorithm into an appropriate candidate to be employed in numerous tasks of the precision viticulture, such as yield estimation, water and nutrients needs estimation, spraying and harvesting.

Challenging Racism in Brazil. Legal Suits in the Context of the 1951 Anti-Discrimination Law

Directory of Open Access Journals (Sweden)

Jerry Dávila

Full Text Available Abstract This article examines efforts to define the nature of racial discrimination in Brazil, within an environment shaped by perceptions of the meaning of racism in the United States and perceptions about the nature of race relations in the lusophone world. The article asks how did black Brazilians work to define discrimination, and what opportunities did they find to mount challenges? This study elucidates reactions to discrimination, looking for these acts where they occurred rather than where the U.S. experience tells us to find them, exploring efforts to define discrimination and to create means to challenge it. Though these efforts often dialogued with ever-present perceptions about race in the U.S., they were adapted to particular legal, political, social and cultural circumstances in the Brazil of their time. In particular, I examine challenges to discrimination through criminal suits brought under Brazil's 1951 anti-discrimination law.

Discriminative sparse coding on multi-manifolds

KAUST Repository

Wang, J.J.-Y.; Bensmail, H.; Yao, N.; Gao, Xin

2013-01-01

Sparse coding has been popularly used as an effective data representation method in various applications, such as computer vision, medical imaging and bioinformatics. However, the conventional sparse coding algorithms and their manifold-regularized variants (graph sparse coding and Laplacian sparse coding), learn codebooks and codes in an unsupervised manner and neglect class information that is available in the training set. To address this problem, we propose a novel discriminative sparse coding method based on multi-manifolds, that learns discriminative class-conditioned codebooks and sparse codes from both data feature spaces and class labels. First, the entire training set is partitioned into multiple manifolds according to the class labels. Then, we formulate the sparse coding as a manifold-manifold matching problem and learn class-conditioned codebooks and codes to maximize the manifold margins of different classes. Lastly, we present a data sample-manifold matching-based strategy to classify the unlabeled data samples. Experimental results on somatic mutations identification and breast tumor classification based on ultrasonic images demonstrate the efficacy of the proposed data representation and classification approach. 2013 The Authors. All rights reserved.

Discriminative sparse coding on multi-manifolds

KAUST Repository

Wang, J.J.-Y.

2013-09-26

Sparse coding has been popularly used as an effective data representation method in various applications, such as computer vision, medical imaging and bioinformatics. However, the conventional sparse coding algorithms and their manifold-regularized variants (graph sparse coding and Laplacian sparse coding), learn codebooks and codes in an unsupervised manner and neglect class information that is available in the training set. To address this problem, we propose a novel discriminative sparse coding method based on multi-manifolds, that learns discriminative class-conditioned codebooks and sparse codes from both data feature spaces and class labels. First, the entire training set is partitioned into multiple manifolds according to the class labels. Then, we formulate the sparse coding as a manifold-manifold matching problem and learn class-conditioned codebooks and codes to maximize the manifold margins of different classes. Lastly, we present a data sample-manifold matching-based strategy to classify the unlabeled data samples. Experimental results on somatic mutations identification and breast tumor classification based on ultrasonic images demonstrate the efficacy of the proposed data representation and classification approach. 2013 The Authors. All rights reserved.

The study for practicality of remote fire monitoring using the image

Energy Technology Data Exchange (ETDEWEB)

Kim, Tae Joon; Hwang, Sung Tai; Jeong, Kwung Chai; Jeong, Ji Young; Kim, Go Leo; Baik, Hong Kee; Baik, Moon Kee; Kim, Joo Sung; No, In Young

1999-12-01

1. Object; The study for practicality of remote fire monitoring system early to be able to the fire with small scaled fire in nuclear facility and commercial building. 2. Content; Examination of algorithm for artificial intelligence neural network(NN), Achieving of image preprocessing technology need to application, Production of image files of firing, Experiment of the feature extraction from images, Construction of experimental equipment and software for discrimination of the fire, Experiment of functionality of software for fire monitoring, Learning of neural network with the image and testing of discrimination of the fire. 3. Results; The technology of feature extraction of event related with neural network, discrimination of event generation, and enhancement to be discriminated the fire with learning of neural network was established. The present ability of discrimination of the fire that the reliability was about 99 percent as error of discrimination being about 0.0098 in case of learning, but it is difficult to discriminate because of various kinds of background images. Later it will be required the working for reducing the error of discrimination of the fire, with non-fire images. (author)

Classification of natural circulation two-phase flow patterns using fuzzy inference on image analysis

International Nuclear Information System (INIS)

Mesquita, R.N. de; Masotti, P.H.F.; Penha, R.M.L.; Andrade, D.A.; Sabundjian, G.; Torres, W.M.

2012-01-01

Highlights: ► A fuzzy classification system for two-phase flow instability patterns is developed. ► Flow patterns are classified based on images of natural circulation experiments. ► Fuzzy inference is optimized to use single grayscale profiles as input. - Abstract: Two-phase flow on natural circulation phenomenon has been an important theme on recent studies related to nuclear reactor designs. The accuracy of heat transfer estimation has been improved with new models that require precise prediction of pattern transitions of flow. In this work, visualization of natural circulation cycles is used to study two-phase flow patterns associated with phase transients and static instabilities of flow. A Fuzzy Flow-type Classification System (FFCS) was developed to classify these patterns based only on image extracted features. Image acquisition and temperature measurements were simultaneously done. Experiments in natural circulation facility were adjusted to generate a series of characteristic two-phase flow instability periodic cycles. The facility is composed of a loop of glass tubes, a heat source using electrical heaters, a cold source using a helicoidal heat exchanger, a visualization section and thermocouples positioned over different loop sections. The instability cyclic period is estimated based on temperature measurements associated with the detection of a flow transition image pattern. FFCS shows good results provided that adequate image acquisition parameters and pre-processing adjustments are used.

MIDAS: Regionally linear multivariate discriminative statistical mapping.

Science.gov (United States)

Varol, Erdem; Sotiras, Aristeidis; Davatzikos, Christos

2018-07-01

Statistical parametric maps formed via voxel-wise mass-univariate tests, such as the general linear model, are commonly used to test hypotheses about regionally specific effects in neuroimaging cross-sectional studies where each subject is represented by a single image. Despite being informative, these techniques remain limited as they ignore multivariate relationships in the data. Most importantly, the commonly employed local Gaussian smoothing, which is important for accounting for registration errors and making the data follow Gaussian distributions, is usually chosen in an ad hoc fashion. Thus, it is often suboptimal for the task of detecting group differences and correlations with non-imaging variables. Information mapping techniques, such as searchlight, which use pattern classifiers to exploit multivariate information and obtain more powerful statistical maps, have become increasingly popular in recent years. However, existing methods may lead to important interpretation errors in practice (i.e., misidentifying a cluster as informative, or failing to detect truly informative voxels), while often being computationally expensive. To address these issues, we introduce a novel efficient multivariate statistical framework for cross-sectional studies, termed MIDAS, seeking highly sensitive and specific voxel-wise brain maps, while leveraging the power of regional discriminant analysis. In MIDAS, locally linear discriminative learning is applied to estimate the pattern that best discriminates between two groups, or predicts a variable of interest. This pattern is equivalent to local filtering by an optimal kernel whose coefficients are the weights of the linear discriminant. By composing information from all neighborhoods that contain a given voxel, MIDAS produces a statistic that collectively reflects the contribution of the voxel to the regional classifiers as well as the discriminative power of the classifiers. Critically, MIDAS efficiently assesses the

The effect of image position on the Independent Components of natural binocular images.

Science.gov (United States)

Hunter, David W; Hibbard, Paul B

2018-01-11

Human visual performance degrades substantially as the angular distance from the fovea increases. This decrease in performance is found for both binocular and monocular vision. Although analysis of the statistics of natural images has provided significant insights into human visual processing, little research has focused on the statistical content of binocular images at eccentric angles. We applied Independent Component Analysis to rectangular image patches cut from locations within binocular images corresponding to different degrees of eccentricity. The distribution of components learned from the varying locations was examined to determine how these distributions varied across eccentricity. We found a general trend towards a broader spread of horizontal and vertical position disparity tunings in eccentric regions compared to the fovea, with the horizontal spread more pronounced than the vertical spread. Eccentric locations above the centroid show a strong bias towards far-tuned components, eccentric locations below the centroid show a strong bias towards near-tuned components. These distributions exhibit substantial similarities with physiological measurements in V1, however in common with previous research we also observe important differences, in particular distributions of binocular phase disparity which do not match physiology.

Discrimination Features of Chromatic Figures in Various Background Characteristics

Directory of Open Access Journals (Sweden)

Y A Chudina

2013-12-01

Full Text Available Visual recognition features of images with different figure-ground segregation have been considered in the article. The research was carried out within the framework of Sokolov and Izmaylov’s spherical model and was based on the construction of color objects discrimination models depending on the changes of background characteristics. The research has revealed the specific influence of the background on figure discrimination. The derived models reflect the mechanisms of the all-in-one perception of the visual space.

Comparison of Hyperspectral and Multispectral Satellites for Discriminating Land Cover in Northern California

Science.gov (United States)

Clark, M. L.; Kilham, N. E.

2015-12-01

Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Most land-cover maps at regional to global scales are produced with remote sensing techniques applied to multispectral satellite imagery with 30-500 m pixel sizes (e.g., Landsat, MODIS). Hyperspectral, or imaging spectrometer, imagery measuring the visible to shortwave infrared regions (VSWIR) of the spectrum have shown impressive capacity to map plant species and coarser land-cover associations, yet techniques have not been widely tested at regional and greater spatial scales. The Hyperspectral Infrared Imager (HyspIRI) mission is a VSWIR hyperspectral and thermal satellite being considered for development by NASA. The goal of this study was to assess multi-temporal, HyspIRI-like satellite imagery for improved land cover mapping relative to multispectral satellites. We mapped FAO Land Cover Classification System (LCCS) classes over 22,500 km2 in the San Francisco Bay Area, California using 30-m HyspIRI, Landsat 8 and Sentinel-2 imagery simulated from data acquired by NASA's AVIRIS airborne sensor. Random Forests (RF) and Multiple-Endmember Spectral Mixture Analysis (MESMA) classifiers were applied to the simulated images and accuracies were compared to those from real Landsat 8 images. The RF classifier was superior to MESMA, and multi-temporal data yielded higher accuracy than summer-only data. With RF, hyperspectral data had overall accuracy of 72.2% and 85.1% with full 20-class and reduced 12-class schemes, respectively. Multispectral imagery had lower accuracy. For example, simulated and real Landsat data had 7.5% and 4.6% lower accuracy than HyspIRI data with 12 classes, respectively. In summary, our results indicate increased mapping accuracy using HyspIRI multi-temporal imagery, particularly in discriminating different natural vegetation types, such as

Differential discriminator

International Nuclear Information System (INIS)

Dukhanov, V.I.; Mazurov, I.B.

1981-01-01

A principal flowsheet of a differential discriminator intended for operation in a spectrometric circuit with statistical time distribution of pulses is described. The differential discriminator includes four integrated discriminators and a channel of piled-up signal rejection. The presence of the rejection channel enables the discriminator to operate effectively at loads of 14x10 3 pulse/s. The temperature instability of the discrimination thresholds equals 250 μV/ 0 C. The discrimination level changes within 0.1-5 V, the level shift constitutes 0.5% for the filling ratio of 1:10. The rejection coefficient is not less than 90%. Alpha spectrum of the 228 Th source is presented to evaluate the discriminator operation with the rejector. The rejector provides 50 ns time resolution

Structural Discrimination

DEFF Research Database (Denmark)

Thorsen, Mira Skadegård

discrimination as two ways of articulating particular, opaque forms of racial discrimination that occur in everyday Danish (and other) contexts, and have therefore become normalized. I present and discuss discrimination as it surfaces in data from my empirical studies of discrimination in Danish contexts...

General tensor discriminant analysis and gabor features for gait recognition.

Science.gov (United States)

Tao, Dacheng; Li, Xuelong; Wu, Xindong; Maybank, Stephen J

2007-10-01

The traditional image representations are not suited to conventional classification methods, such as the linear discriminant analysis (LDA), because of the under sample problem (USP): the dimensionality of the feature space is much higher than the number of training samples. Motivated by the successes of the two dimensional LDA (2DLDA) for face recognition, we develop a general tensor discriminant analysis (GTDA) as a preprocessing step for LDA. The benefits of GTDA compared with existing preprocessing methods, e.g., principal component analysis (PCA) and 2DLDA, include 1) the USP is reduced in subsequent classification by, for example, LDA; 2) the discriminative information in the training tensors is preserved; and 3) GTDA provides stable recognition rates because the alternating projection optimization algorithm to obtain a solution of GTDA converges, while that of 2DLDA does not. We use human gait recognition to validate the proposed GTDA. The averaged gait images are utilized for gait representation. Given the popularity of Gabor function based image decompositions for image understanding and object recognition, we develop three different Gabor function based image representations: 1) the GaborD representation is the sum of Gabor filter responses over directions, 2) GaborS is the sum of Gabor filter responses over scales, and 3) GaborSD is the sum of Gabor filter responses over scales and directions. The GaborD, GaborS and GaborSD representations are applied to the problem of recognizing people from their averaged gait images.A large number of experiments were carried out to evaluate the effectiveness (recognition rate) of gait recognition based on first obtaining a Gabor, GaborD, GaborS or GaborSD image representation, then using GDTA to extract features and finally using LDA for classification. The proposed methods achieved good performance for gait recognition based on image sequences from the USF HumanID Database. Experimental comparisons are made with nine

Principle component analysis and linear discriminant analysis of multi-spectral autofluorescence imaging data for differentiating basal cell carcinoma and healthy skin

Science.gov (United States)

Chernomyrdin, Nikita V.; Zaytsev, Kirill I.; Lesnichaya, Anastasiya D.; Kudrin, Konstantin G.; Cherkasova, Olga P.; Kurlov, Vladimir N.; Shikunova, Irina A.; Perchik, Alexei V.; Yurchenko, Stanislav O.; Reshetov, Igor V.

2016-09-01

In present paper, an ability to differentiate basal cell carcinoma (BCC) and healthy skin by combining multi-spectral autofluorescence imaging, principle component analysis (PCA), and linear discriminant analysis (LDA) has been demonstrated. For this purpose, the experimental setup, which includes excitation and detection branches, has been assembled. The excitation branch utilizes a mercury arc lamp equipped with a 365-nm narrow-linewidth excitation filter, a beam homogenizer, and a mechanical chopper. The detection branch employs a set of bandpass filters with the central wavelength of spectral transparency of λ = 400, 450, 500, and 550 nm, and a digital camera. The setup has been used to study three samples of freshly excised BCC. PCA and LDA have been implemented to analyze the data of multi-spectral fluorescence imaging. Observed results of this pilot study highlight the advantages of proposed imaging technique for skin cancer diagnosis.

Real-time detection of natural objects using AM-coded spectral matching imager

Science.gov (United States)

Kimachi, Akira

2005-01-01

This paper describes application of the amplitude-modulation (AM)-coded spectral matching imager (SMI) to real-time detection of natural objects such as human beings, animals, vegetables, or geological objects or phenomena, which are much more liable to change with time than artificial products while often exhibiting characteristic spectral functions associated with some specific activity states. The AM-SMI produces correlation between spectral functions of the object and a reference at each pixel of the correlation image sensor (CIS) in every frame, based on orthogonal amplitude modulation (AM) of each spectral channel and simultaneous demodulation of all channels on the CIS. This principle makes the SMI suitable to monitoring dynamic behavior of natural objects in real-time by looking at a particular spectral reflectance or transmittance function. A twelve-channel multispectral light source was developed with improved spatial uniformity of spectral irradiance compared to a previous one. Experimental results of spectral matching imaging of human skin and vegetable leaves are demonstrated, as well as a preliminary feasibility test of imaging a reflective object using a test color chart.

In Vivo Imaging of Natural Killer Cell Trafficking in Tumors

NARCIS (Netherlands)

Galli, Filippo; Rapisarda, Anna Serafina; Stabile, Helena; Malviya, Gaurav; Manni, Isabella; Bonanno, Elena; Piaggio, Giulia; Gismondi, Angela; Santoni, Angela; Signore, Alberto

2015-01-01

Natural killer cells (NKs) are important effectors of the innate immune system, with marked antitumor activity. Imaging NK trafficking in vivo may be relevant to following up the efficacy of new therapeutic approaches aiming at increasing tumor-infiltrating NKs (TINKs). The specific aims of present

Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI

Directory of Open Access Journals (Sweden)

Ling-Li Zeng

2018-04-01

Full Text Available Background: A lack of a sufficiently large sample at single sites causes poor generalizability in automatic diagnosis classification of heterogeneous psychiatric disorders such as schizophrenia based on brain imaging scans. Advanced deep learning methods may be capable of learning subtle hidden patterns from high dimensional imaging data, overcome potential site-related variation, and achieve reproducible cross-site classification. However, deep learning-based cross-site transfer classification, despite less imaging site-specificity and more generalizability of diagnostic models, has not been investigated in schizophrenia. Methods: A large multi-site functional MRI sample (n = 734, including 357 schizophrenic patients from seven imaging resources was collected, and a deep discriminant autoencoder network, aimed at learning imaging site-shared functional connectivity features, was developed to discriminate schizophrenic individuals from healthy controls. Findings: Accuracies of approximately 85·0% and 81·0% were obtained in multi-site pooling classification and leave-site-out transfer classification, respectively. The learned functional connectivity features revealed dysregulation of the cortical-striatal-cerebellar circuit in schizophrenia, and the most discriminating functional connections were primarily located within and across the default, salience, and control networks. Interpretation: The findings imply that dysfunctional integration of the cortical-striatal-cerebellar circuit across the default, salience, and control networks may play an important role in the “disconnectivity” model underlying the pathophysiology of schizophrenia. The proposed discriminant deep learning method may be capable of learning reliable connectome patterns and help in understanding the pathophysiology and achieving accurate prediction of schizophrenia across multiple independent imaging sites. Keywords: Schizophrenia, Deep learning, Connectome, f

Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI.

Science.gov (United States)

Zeng, Ling-Li; Wang, Huaning; Hu, Panpan; Yang, Bo; Pu, Weidan; Shen, Hui; Chen, Xingui; Liu, Zhening; Yin, Hong; Tan, Qingrong; Wang, Kai; Hu, Dewen

2018-04-01

A lack of a sufficiently large sample at single sites causes poor generalizability in automatic diagnosis classification of heterogeneous psychiatric disorders such as schizophrenia based on brain imaging scans. Advanced deep learning methods may be capable of learning subtle hidden patterns from high dimensional imaging data, overcome potential site-related variation, and achieve reproducible cross-site classification. However, deep learning-based cross-site transfer classification, despite less imaging site-specificity and more generalizability of diagnostic models, has not been investigated in schizophrenia. A large multi-site functional MRI sample (n = 734, including 357 schizophrenic patients from seven imaging resources) was collected, and a deep discriminant autoencoder network, aimed at learning imaging site-shared functional connectivity features, was developed to discriminate schizophrenic individuals from healthy controls. Accuracies of approximately 85·0% and 81·0% were obtained in multi-site pooling classification and leave-site-out transfer classification, respectively. The learned functional connectivity features revealed dysregulation of the cortical-striatal-cerebellar circuit in schizophrenia, and the most discriminating functional connections were primarily located within and across the default, salience, and control networks. The findings imply that dysfunctional integration of the cortical-striatal-cerebellar circuit across the default, salience, and control networks may play an important role in the "disconnectivity" model underlying the pathophysiology of schizophrenia. The proposed discriminant deep learning method may be capable of learning reliable connectome patterns and help in understanding the pathophysiology and achieving accurate prediction of schizophrenia across multiple independent imaging sites. Copyright © 2018 German Center for Neurodegenerative Diseases (DZNE). Published by Elsevier B.V. All rights reserved.

Imaging near-surface heterogeneities by natural migration of surface waves

KAUST Repository

Liu, Zhaolun

2016-09-06

We demonstrate that near-surface heterogeneities can be imaged by natural migration of backscattered surface waves in common shot gathers. No velocity model is required because the data are migrated onto surface points with the virtual Green\\'s functions computed from the shot gathers. Migrating shot gathers recorded by 2D and 3D land surveys validates the effectiveness of detecting nearsurface heterogeneities by natural migration. The implication is that more accurate hazard maps can be created by migrating surface waves in land surveys.

Spatial layout affects speed discrimination

Science.gov (United States)

Verghese, P.; Stone, L. S.

1997-01-01

We address a surprising result in a previous study of speed discrimination with multiple moving gratings: discrimination thresholds decreased when the number of stimuli was increased, but remained unchanged when the area of a single stimulus was increased [Verghese & Stone (1995). Vision Research, 35, 2811-2823]. In this study, we manipulated the spatial- and phase relationship between multiple grating patches to determine their effect on speed discrimination thresholds. In a fusion experiment, we merged multiple stimulus patches, in stages, into a single patch. Thresholds increased as the patches were brought closer and their phase relationship was adjusted to be consistent with a single patch. Thresholds increased further still as these patches were fused into a single patch. In a fission experiment, we divided a single large patch into multiple patches by superimposing a cross with luminance equal to that of the background. Thresholds decreased as the large patch was divided into quadrants and decreased further as the quadrants were maximally separated. However, when the cross luminance was darker than the background, it was perceived as an occluder and thresholds, on average, were unchanged from that for the single large patch. A control experiment shows that the observed trend in discrimination thresholds is not due to the differences in perceived speed of the stimuli. These results suggest that the parsing of the visual image into entities affects the combination of speed information across space, and that each discrete entity effectively provides a single independent estimate of speed.

Performance and strategy comparisons of human listeners and logistic regression in discriminating underwater targets.

Science.gov (United States)

Yang, Lixue; Chen, Kean

2015-11-01

To improve the design of underwater target recognition systems based on auditory perception, this study compared human listeners with automatic classifiers. Performances measures and strategies in three discrimination experiments, including discriminations between man-made and natural targets, between ships and submarines, and among three types of ships, were used. In the experiments, the subjects were asked to assign a score to each sound based on how confident they were about the category to which it belonged, and logistic regression, which represents linear discriminative models, also completed three similar tasks by utilizing many auditory features. The results indicated that the performances of logistic regression improved as the ratio between inter- and intra-class differences became larger, whereas the performances of the human subjects were limited by their unfamiliarity with the targets. Logistic regression performed better than the human subjects in all tasks but the discrimination between man-made and natural targets, and the strategies employed by excellent human subjects were similar to that of logistic regression. Logistic regression and several human subjects demonstrated similar performances when discriminating man-made and natural targets, but in this case, their strategies were not similar. An appropriate fusion of their strategies led to further improvement in recognition accuracy.

The potential of imaging subsurface heterogeneities by local, natural earthquakes

NARCIS (Netherlands)

Nishitsuji, Y.; Doi, I.; Draganov, D.S.

2014-01-01

We have developed a new imaging technique of subsurface heterogeneities that uses Sp-waves from natural earthquakes. This technique can be used as a first screening tool in frontier exploration areas before conventional active exploration. Analyzing Sp-waves from 28 earthquakes (Mj 2.0 to 4.2)

Examining Workplace Discrimination in a Discrimination-Free Environment

OpenAIRE

Braxton, Shawn Lamont

2010-01-01

Examining Workplace Discrimination in a Discrimination-Free Environment Shawn L. Braxton Abstract The purpose of this study is to explore how racial and gender discrimination is reproduced in concrete workplace settings even when anti-discrimination policies are present, and to understand the various reactions utilized by those who commonly experience it. I have selected a particular medical center, henceforth referred to by a pseudonym, â The Bliley Medical Centerâ as my case ...

Comparison of the imaging performances for recently developed monolithic scintillators: CRY018 and CRY019 for dual isotope gamma ray imaging applications

International Nuclear Information System (INIS)

Polito, C.; Pani, R.; Trigila, C.; Cinti, M.N.; Fabbri, A.; Pellegrini, R.; Frantellizzi, V.; Vincentis, G. De; Pani, R.

2017-01-01

The growing interest for new scintillation crystals with outstanding imaging performances (i.e. resolution and efficiency) has suggested the study of recently discovered scintillators named CRY018 and CRY019 . The crystals under investigation are monolithic and have shown enhanced characteristics both for gamma ray spectrometry and for Nuclear Medicine imaging applications such as the dual isotope imaging. Moreover, the non-hygroscopic nature and the absence of afterglow make these scintillators even more attractive for the potential improvement in a wide range of applications. These scintillation crystals show a high energy resolution in the energy range involved in Nuclear Medicine, allowing the discrimination between very close energy values. Moreover, in order to prove their suitability of being powerful imaging systems, the imaging performances like the position linearity and the intrinsic spatial resolution have been evaluated obtaining satisfactory results thanks to the implementation of an optimized algorithm for the images reconstruction.

Comparison of the imaging performances for recently developed monolithic scintillators: CRY018 and CRY019 for dual isotope gamma ray imaging applications

Science.gov (United States)

Polito, C.; Pani, R.; Trigila, C.; Cinti, M. N.; Fabbri, A.; Frantellizzi, V.; De Vincentis, G.; Pellegrini, R.; Pani, R.

2017-01-01

The growing interest for new scintillation crystals with outstanding imaging performances (i.e. resolution and efficiency) has suggested the study of recently discovered scintillators named CRY018 and CRY019. The crystals under investigation are monolithic and have shown enhanced characteristics both for gamma ray spectrometry and for Nuclear Medicine imaging applications such as the dual isotope imaging. Moreover, the non-hygroscopic nature and the absence of afterglow make these scintillators even more attractive for the potential improvement in a wide range of applications. These scintillation crystals show a high energy resolution in the energy range involved in Nuclear Medicine, allowing the discrimination between very close energy values. Moreover, in order to prove their suitability of being powerful imaging systems, the imaging performances like the position linearity and the intrinsic spatial resolution have been evaluated obtaining satisfactory results thanks to the implementation of an optimized algorithm for the images reconstruction.

Distance Adaptive Tensor Discriminative Geometry Preserving Projection for Face Recognition

Directory of Open Access Journals (Sweden)

Ziqiang Wang

2012-09-01

Full Text Available There is a growing interest in dimensionality reduction techniques for face recognition, however, the traditional dimensionality reduction algorithms often transform the input face image data into vectors before embedding. Such vectorization often ignores the underlying data structure and leads to higher computational complexity. To effectively cope with these problems, a novel dimensionality reduction algorithm termed distance adaptive tensor discriminative geometry preserving projection (DATDGPP is proposed in this paper. The key idea of DATDGPP is as follows: first, the face image data are directly encoded in high-order tensor structure so that the relationships among the face image data can be preserved; second, the data-adaptive tensor distance is adopted to model the correlation among different coordinates of tensor data; third, the transformation matrix which can preserve discrimination and local geometry information is obtained by an iteration algorithm. Experimental results on three face databases show that the proposed algorithm outperforms other representative dimensionality reduction algorithms.

Preferred and acceptable color gamut for reproducing natural image content

NARCIS (Netherlands)

Sekulovski, D.; de Volder, R.J.; Heynderickx, I.E.J.

2009-01-01

The preferred and maximally acceptable chroma for natural images of mainly one hue is determined using both a tuning and a paired-comparison task. The results clearly show the need for wide-gamut displays, but also the limited acceptance of over-saturated colors. Preference in chroma is dominated by

Discriminative object tracking via sparse representation and online dictionary learning.

Science.gov (United States)

Xie, Yuan; Zhang, Wensheng; Li, Cuihua; Lin, Shuyang; Qu, Yanyun; Zhang, Yinghua

2014-04-01

We propose a robust tracking algorithm based on local sparse coding with discriminative dictionary learning and new keypoint matching schema. This algorithm consists of two parts: the local sparse coding with online updated discriminative dictionary for tracking (SOD part), and the keypoint matching refinement for enhancing the tracking performance (KP part). In the SOD part, the local image patches of the target object and background are represented by their sparse codes using an over-complete discriminative dictionary. Such discriminative dictionary, which encodes the information of both the foreground and the background, may provide more discriminative power. Furthermore, in order to adapt the dictionary to the variation of the foreground and background during the tracking, an online learning method is employed to update the dictionary. The KP part utilizes refined keypoint matching schema to improve the performance of the SOD. With the help of sparse representation and online updated discriminative dictionary, the KP part are more robust than the traditional method to reject the incorrect matches and eliminate the outliers. The proposed method is embedded into a Bayesian inference framework for visual tracking. Experimental results on several challenging video sequences demonstrate the effectiveness and robustness of our approach.

Temporal profiles of vegetation indices for characterizing grazing intensity on natural grasslands in Pampa biome

Directory of Open Access Journals (Sweden)

Amanda Heemann Junges

2016-08-01

Full Text Available ABSTRACT The Pampa biome is an important ecosystem in Brazil that is highly relevant to livestock production. The objective of this study was to analyze the potential use of vegetation indices to discriminate grazing intensities on natural grasslands in the Pampa biome. Moderate Resolution Imaging Spectroradiometer (MODIS Normalized Difference Vegetation Index (NDVI and Enhanced Vegetation Index (EVI images from Jan to Dec, 2000 to 2013 series, were analyzed for natural grassland experimental units managed under high (forage allowance of 5 ± 2 % live weight – LW, moderate (13 ± 5 % LW and low grazing intensity (19 ± 7 % LW. Regardless of intensity, the temporal profiles showed lower NDVI and EVI during winter, increased values in spring because of summer species regrowth, slightly decreased values in summer, especially in years when there is a water deficit, and increased values in the fall associated with the beginning of winter forage development. The average temporal profiles of moderate grazing intensity exhibited greater vegetation index values compared with low and high grazing intensities. The temporal profiles of less vegetation index were associated with lower green biomass accumulation caused by the negative impact of stocking rates on the leaf area index under high grazing intensity and a floristic composition with a predominance of tussocks under low grazing intensity. Vegetation indices can be used for distinguishing moderate grazing intensity from low and high intensities. The average EVI values can discriminate moderate grazing intensity during any season, and the NDVI values can discriminate moderate grazing intensity during spring and winter.

Classification and Discrimination of Different Fungal Diseases of Three Infection Levels on Peaches Using Hyperspectral Reflectance Imaging Analysis

Directory of Open Access Journals (Sweden)

Ye Sun

2018-04-01

Full Text Available Peaches are susceptible to infection from several postharvest diseases. In order to control disease and avoid potential health risks, it is important to identify suitable treatments for each disease type. In this study, the spectral and imaging information from hyperspectral reflectance (400~1000 nm was used to evaluate and classify three kinds of common peach disease. To reduce the large dimensionality of the hyperspectral imaging, principal component analysis (PCA was applied to analyse each wavelength image as a whole, and the first principal component was selected to extract the imaging features. A total of 54 parameters were extracted as imaging features for one sample. Three decayed stages (slight, moderate and severe decayed peaches were considered for classification by deep belief network (DBN and partial least squares discriminant analysis (PLSDA in this study. The results showed that the DBN model has better classification results than the classification accuracy of the PLSDA model. The DBN model based on integrated information (494 features showed the highest classification results for the three diseases, with accuracies of 82.5%, 92.5%, and 100% for slightly-decayed, moderately-decayed and severely-decayed samples, respectively. The successive projections algorithm (SPA was used to select the optimal features from the integrated information; then, six optimal features were selected from a total of 494 features to establish the simple model. The SPA-PLSDA model showed better results which were more feasible for industrial application. The results showed that the hyperspectral reflectance imaging technique is feasible for detecting different kinds of diseased peaches, especially at the moderately- and severely-decayed levels.

Small saccades and image complexity during free viewing of natural images in schizophrenia.

Directory of Open Access Journals (Sweden)

Jose Ignacio Egaña

2013-05-01

Full Text Available In schizophrenia, patients display dysfunctions during the execution of simple visual tasks such as anti-saccade or smooth pursuit. In more ecological scenarios, such as free viewing of natural images, patients appear to make fewer and longer visual fixations and display shorter scanpaths. It is not clear whether these measurements reflect alterations in their proficiency to perform basic eye movements, such as saccades and fixations, or are related to high-level mechanisms, such as exploration or attention. We utilized free exploration of natural images of different complexities as a model of an ecological context where normally operative mechanisms of visual control can be accurately measured. We quantified visual exploration as Euclidean distance, scanpaths, saccades and visual fixation, using the standard SR-Research eye tracker algorithm (SR. We then compared this result with a computation that includes microsaccades (EM. We evaluated 8 schizophrenia patients and corresponding healthy controls (HC. Next, we tested whether the decrement in the number of saccades and fixations, as well as their increment in duration reported previously in schizophrenia patients, resulted from the increasing occurrence of undetected microsaccades. We found that when utilizing the standard SR algorithm, patients displayed shorter scanpaths as well as fewer and shorter saccades and fixations. When we employed the EM algorithm, the differences in these parameters between patients and HC were no longer significant. On the other hand, we found that image complexity plays an important role in exploratory behaviors, demonstrating that this factor explains most of differences between eye-movement behaviors in schizophrenia patients. These results help elucidate the mechanisms of visual motor control that are affected in schizophrenia and contribute to the finding of adequate markers for diagnosis and treatment for this condition.

Using the Natural Scenes’ Edges for Assessing Image Quality Blindly and Efficiently

Directory of Open Access Journals (Sweden)

Saifeldeen Abdalmajeed

2015-01-01

Full Text Available Two real blind/no-reference (NR image quality assessment (IQA algorithms in the spatial domain are developed. To measure image quality, the introduced approach uses an unprecedented concept for gathering a set of novel features based on edges of natural scenes. The enhanced sensitivity of the human eye to the information carried by edge and contour of an image supports this claim. The effectiveness of the proposed technique in quantifying image quality has been studied. The gathered features are formed using both Weibull distribution statistics and two sharpness functions to devise two separate NR IQA algorithms. The presented algorithms do not need training on databases of human judgments or even prior knowledge about expected distortions, so they are real NR IQA algorithms. In contrast to the most general no-reference IQA, the model used for this study is generic and has been created in such a way that it is not specified to any particular distortion type. When testing the proposed algorithms on LIVE database, experiments show that they correlate well with subjective opinion scores. They also show that the introduced methods significantly outperform the popular full-reference peak signal-to-noise ratio (PSNR and the structural similarity (SSIM methods. Besides they outperform the recently developed NR natural image quality evaluator (NIQE model.

Natural display mode for digital DICOM-conformant diagnostic imaging.

Science.gov (United States)

Peters, Klaus-Ruediger; Ramsby, Gale R

2002-09-01

The authors performed this study to investigate the verification of the contrast display properties defined by the digital imaging and communication in medicine (DICOM) PS (picture archiving and communication system [PACS] standard) 3.14-2001 gray-scale display function standard and their dependency on display luminance range and video signal bandwidth. Contrast sensitivity and contrast linearity of DICOM-conformant displays were measured in just-noticeable differences (JNDs) on special perceptual contrast test patterns. Measurements were obtained six times at various display settings under dark room conditions. Display luminance range and video bandwidth had a significant effect on contrast perception. The perceptual promises of the standard could be established only with displays that were calibrated to a unity contrast resolution, at which the number of displayed intensity steps was equal to the number of perceivable contrast steps (JNDs). Such display conditions provide for visual perception information at the level of single-step contrast sensitivity and full-range contrast linearity. These "natural display" conditions also help minimize the Mach banding effects that otherwise reduce contrast sensitivity and contrast linearity. Most, if not all, conventionally used digital display modalities are driven with a contrast resolution larger than 1. Such conditions reduce contrast perception when compared with natural imaging conditions. The DICOM-conformant display conditions at unity contrast resolution were characterized as the "natural display" mode, and, thus, the authors a priori recommend them as being useful for making a primary diagnosis with PACS and teleradiology and as a standard for psychophysical research and performance measurements.

Facial discrimination in body dysmorphic, obsessive-compulsive and social anxiety disorders.

Science.gov (United States)

Hübner, Claudia; Wiesendahl, Wiebke; Kleinstäuber, Maria; Stangier, Ulrich; Kathmann, Norbert; Buhlmann, Ulrike

2016-02-28

Body dysmorphic disorder (BDD) is characterized by preoccupation with perceived flaws in one's own appearance. Several risk factors such as aesthetic perceptual sensitivity have been proposed to explain BDD's unique symptomatology. Although research on facial discrimination is limited so far, the few existing studies have produced mixed results. Thus, the purpose of this study was to further examine facial discrimination in BDD. We administered a facial discrimination paradigm, which allows to assess the ability to identify slight to strong facial changes (e.g., hair loss, acne) when presented with an original (unmodified) facial image, relative to a changed (modified) facial image. The experiment was administered in individuals with BDD, social anxiety disorder, obsessive-compulsive disorder, and mentally healthy controls (32 per group, respectively). Overall, groups did not differ with respect to their ability to correctly identify facial aberrations when presented with other people's faces. Our findings do not support the hypothesis of enhanced general aesthetic perceptual sensitivity in individuals with (vs. without) BDD. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Rotation-invariant features for multi-oriented text detection in natural images.

Directory of Open Access Journals (Sweden)

Cong Yao

Full Text Available Texts in natural scenes carry rich semantic information, which can be used to assist a wide range of applications, such as object recognition, image/video retrieval, mapping/navigation, and human computer interaction. However, most existing systems are designed to detect and recognize horizontal (or near-horizontal texts. Due to the increasing popularity of mobile-computing devices and applications, detecting texts of varying orientations from natural images under less controlled conditions has become an important but challenging task. In this paper, we propose a new algorithm to detect texts of varying orientations. Our algorithm is based on a two-level classification scheme and two sets of features specially designed for capturing the intrinsic characteristics of texts. To better evaluate the proposed method and compare it with the competing algorithms, we generate a comprehensive dataset with various types of texts in diverse real-world scenes. We also propose a new evaluation protocol, which is more suitable for benchmarking algorithms for detecting texts in varying orientations. Experiments on benchmark datasets demonstrate that our system compares favorably with the state-of-the-art algorithms when handling horizontal texts and achieves significantly enhanced performance on variant texts in complex natural scenes.

Pigeons can discriminate "good" and "bad" paintings by children.

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Watanabe, Shigeru

2010-01-01

Humans have the unique ability to create art, but non-human animals may be able to discriminate "good" art from "bad" art. In this study, I investigated whether pigeons could be trained to discriminate between paintings that had been judged by humans as either "bad" or "good". To do this, adult human observers first classified several children's paintings as either "good" (beautiful) or "bad" (ugly). Using operant conditioning procedures, pigeons were then reinforced for pecking at "good" paintings. After the pigeons learned the discrimination task, they were presented with novel pictures of both "good" and "bad" children's paintings to test whether they had successfully learned to discriminate between these two stimulus categories. The results showed that pigeons could discriminate novel "good" and "bad" paintings. Then, to determine which cues the subjects used for the discrimination, I conducted tests of the stimuli when the paintings were of reduced size or grayscale. In addition, I tested their ability to discriminate when the painting stimuli were mosaic and partial occluded. The pigeons maintained discrimination performance when the paintings were reduced in size. However, discrimination performance decreased when stimuli were presented as grayscale images or when a mosaic effect was applied to the original stimuli in order to disrupt spatial frequency. Thus, the pigeons used both color and pattern cues for their discrimination. The partial occlusion did not disrupt the discriminative behavior suggesting that the pigeons did not attend to particular parts, namely upper, lower, left or right half, of the paintings. These results suggest that the pigeons are capable of learning the concept of a stimulus class that humans name "good" pictures. The second experiment showed that pigeons learned to discriminate watercolor paintings from pastel paintings. The subjects showed generalization to novel paintings. Then, as the first experiment, size reduction test

Discriminant method for the optimization of radionuclide activity in studies of nuclear medicine

International Nuclear Information System (INIS)

Perez Diaz, Marlen

2003-01-01

It is presented a method for the optimization of the radionuclidic activity to administer to mature patients in studies of Nuclear Medicine. The method is based in technical of discriminant analysis to build a function that discriminates groups with image quality differed on the base of physical parameters as they are the contrast image and the aleatory noise. The image quality is the dependent variable and it is selected by means of experts' evaluation and technical of clustering. The function is a lineal combination of a reduced group of variables physical-medical, able to discriminate the groups starting from a big group of variables measures. The method allows, also, to establish the relative weight of each discriminant variable selected . The behavior of the same ones is analyzed among studies carried out with different administered activity, with the objective of determining the minimum value of this that still allows good results in the image quality (Approach of activity optimization). It is validated the method by means of results comparison with the grateful Curved ROC in studies carried out with the Mannequins of Jaszczak (for planar studies) and of Insert Heart (for studies of SPECT). The optim activity value of the 99mTc, obtained with the application of the method, was coincident with the one obtained after the application of the method ROC to 6 expert observers as much in planar studies as in SPECT for two different cameras gamma. The method was applied later on in static, dynamic studies and of SPECT carried out with camera gamma to a mature population of 210 patient. The decisive variables of the quality of the image were obtained in the nuclear venticulography in rest, the bony gammagraphy, the nuclear renogram, the renal gammagraphy and the cerebral SPECT, as well as some activity values optimized for the equipment conditions and available radiopharmac in the country, allowing to establish a better commitment relationship between image quality

Jet-images: computer vision inspired techniques for jet tagging

Energy Technology Data Exchange (ETDEWEB)

Cogan, Josh; Kagan, Michael; Strauss, Emanuel; Schwarztman, Ariel [SLAC National Accelerator Laboratory,Menlo Park, CA 94028 (United States)

2015-02-18

We introduce a novel approach to jet tagging and classification through the use of techniques inspired by computer vision. Drawing parallels to the problem of facial recognition in images, we define a jet-image using calorimeter towers as the elements of the image and establish jet-image preprocessing methods. For the jet-image processing step, we develop a discriminant for classifying the jet-images derived using Fisher discriminant analysis. The effectiveness of the technique is shown within the context of identifying boosted hadronic W boson decays with respect to a background of quark- and gluon-initiated jets. Using Monte Carlo simulation, we demonstrate that the performance of this technique introduces additional discriminating power over other substructure approaches, and gives significant insight into the internal structure of jets.

Jet-images: computer vision inspired techniques for jet tagging

International Nuclear Information System (INIS)

Cogan, Josh; Kagan, Michael; Strauss, Emanuel; Schwarztman, Ariel

2015-01-01

We introduce a novel approach to jet tagging and classification through the use of techniques inspired by computer vision. Drawing parallels to the problem of facial recognition in images, we define a jet-image using calorimeter towers as the elements of the image and establish jet-image preprocessing methods. For the jet-image processing step, we develop a discriminant for classifying the jet-images derived using Fisher discriminant analysis. The effectiveness of the technique is shown within the context of identifying boosted hadronic W boson decays with respect to a background of quark- and gluon-initiated jets. Using Monte Carlo simulation, we demonstrate that the performance of this technique introduces additional discriminating power over other substructure approaches, and gives significant insight into the internal structure of jets.

Classification of astrocyto-mas and meningiomas using statistical discriminant analysis on MRI data

International Nuclear Information System (INIS)

Siromoney, Anna; Prasad, G.N.S.; Raghuram, Lakshminarayan; Korah, Ipeson; Siromoney, Arul; Chandrasekaran, R.

2001-01-01

The objective of this study was to investigate the usefulness of Multivariate Discriminant Analysis for classifying two groups of primary brain tumours, astrocytomas and meningiomas, from Magnetic Resonance Images. Discriminant analysis is a multivariate technique concerned with separating distinct sets of objects and with allocating new objects to previously defined groups. Allocation or classification rules are usually developed from learning examples in a supervised learning environment. Data from signal intensity measurements in the multiple scan performed on each patient in routine clinical scanning was analysed using Fisher's Classification, which is one method of discriminant analysis

Discrimination between smiling faces: Human observers vs. automated face analysis.

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Del Líbano, Mario; Calvo, Manuel G; Fernández-Martín, Andrés; Recio, Guillermo

2018-05-11

This study investigated (a) how prototypical happy faces (with happy eyes and a smile) can be discriminated from blended expressions with a smile but non-happy eyes, depending on type and intensity of the eye expression; and (b) how smile discrimination differs for human perceivers versus automated face analysis, depending on affective valence and morphological facial features. Human observers categorized faces as happy or non-happy, or rated their valence. Automated analysis (FACET software) computed seven expressions (including joy/happiness) and 20 facial action units (AUs). Physical properties (low-level image statistics and visual saliency) of the face stimuli were controlled. Results revealed, first, that some blended expressions (especially, with angry eyes) had lower discrimination thresholds (i.e., they were identified as "non-happy" at lower non-happy eye intensities) than others (especially, with neutral eyes). Second, discrimination sensitivity was better for human perceivers than for automated FACET analysis. As an additional finding, affective valence predicted human discrimination performance, whereas morphological AUs predicted FACET discrimination. FACET can be a valid tool for categorizing prototypical expressions, but is currently more limited than human observers for discrimination of blended expressions. Configural processing facilitates detection of in/congruence(s) across regions, and thus detection of non-genuine smiling faces (due to non-happy eyes). Copyright © 2018 Elsevier B.V. All rights reserved.

Research of Face Recognition with Fisher Linear Discriminant

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Rahim, R.; Afriliansyah, T.; Winata, H.; Nofriansyah, D.; Ratnadewi; Aryza, S.

2018-01-01

Face identification systems are developing rapidly, and these developments drive the advancement of biometric-based identification systems that have high accuracy. However, to develop a good face recognition system and to have high accuracy is something that’s hard to find. Human faces have diverse expressions and attribute changes such as eyeglasses, mustache, beard and others. Fisher Linear Discriminant (FLD) is a class-specific method that distinguishes facial image images into classes and also creates distance between classes and intra classes so as to produce better classification.

Repetition blindness for natural images of objects with viewpoint changes

Directory of Open Access Journals (Sweden)

Stephane eBuffat

2013-01-01

Full Text Available When stimuli are repeated in a rapid serial visual presentation (RSVP, observers sometimes fail to report the second occurrence of a target. This phenomenon is referred to as repetition blindness (RB. We report an RSVP experiment with photographs in which we manipulated object viewpoints between the first and second occurrences of a target (0-, 45-, or 90-degree changes, and spatial frequency content. Natural images were spatially filtered to produce low, medium, or high spatial-frequency stimuli. RB was observed for all filtering conditions. Surprisingly, for full-spectrum images, RB increased significantly as the viewpoint reached 90 degrees. For filtered images, a similar pattern of results was found for all conditions except for medium spatial-frequency stimuli. These findings suggest that object recognition in RSVP are subtended by viewpoint-specific representations for all spatial frequencies except medium ones.

An automatic method to discriminate malignant masses from normal tissue in digital mammograms

International Nuclear Information System (INIS)

Brake, Guido M. te; Karssemeijer, Nico; Hendriks, Jan H.C.L.

2000-01-01

Specificity levels of automatic mass detection methods in mammography are generally rather low, because suspicious looking normal tissue is often hard to discriminate from real malignant masses. In this work a number of features were defined that are related to image characteristics that radiologists use to discriminate real lesions from normal tissue. An artificial neural network was used to map the computed features to a measure of suspiciousness for each region that was found suspicious by a mass detection method. Two data sets were used to test the method. The first set of 72 malignant cases (132 films) was a consecutive series taken from the Nijmegen screening programme, 208 normal films were added to improve the estimation of the specificity of the method. The second set was part of the new DDSM data set from the University of South Florida. A total of 193 cases (772 films) with 372 annotated malignancies was used. The measure of suspiciousness that was computed using the image characteristics was successful in discriminating tumours from false positive detections. Approximately 75% of all cancers were detected in at least one view at a specificity level of 0.1 false positive per image. (author)

Expanded image database of pistachio x-ray images and classification by conventional methods

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Keagy, Pamela M.; Schatzki, Thomas F.; Le, Lan Chau; Casasent, David P.; Weber, David

1996-12-01

In order to develop sorting methods for insect damaged pistachio nuts, a large data set of pistachio x-ray images (6,759 nuts) was created. Both film and linescan sensor images were acquired, nuts dissected and internal conditions coded using the U.S. Grade standards and definitions for pistachios. A subset of 1199 good and 686 insect damaged nuts was used to calculate and test discriminant functions. Statistical parameters of image histograms were evaluated for inclusion by forward stepwise discrimination. Using three variables in the discriminant function, 89% of test set nuts were correctly identified. Comparable data for 6 human subjects ranged from 67 to 92%. If the loss of good nuts is held to 1% by requiring a high probability to discard a nut as insect damaged, approximately half of the insect damage present in clean pistachio nuts may be detected and removed by x-ray inspection.

Nanoparticle discrimination based on wavelength and lifetime-multiplexed cathodoluminescence microscopy.

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Garming, Mathijs W H; Weppelman, I Gerward C; de Boer, Pascal; Martínez, Felipe Perona; Schirhagl, Romana; Hoogenboom, Jacob P; Moerland, Robert J

2017-08-31

Nanomaterials can be identified in high-resolution electron microscopy images using spectrally-selective cathodoluminescence. Capabilities for multiplex detection can however be limited, e.g., due to spectral overlap or availability of filters. Also, the available photon flux may be limited due to degradation under electron irradiation. Here, we demonstrate single-pass cathodoluminescence-lifetime based discrimination of different nanoparticles, using a pulsed electron beam. We also show that cathodoluminescence lifetime is a robust parameter even when the nanoparticle cathodoluminescence intensity decays over an order of magnitude. We create lifetime maps, where the lifetime of the cathodoluminescence emission is correlated with the emission intensity and secondary-electron images. The consistency of lifetime-based discrimination is verified by also correlating the emission wavelength and the lifetime of nanoparticles. Our results show how cathodoluminescence lifetime provides an additional channel of information in electron microscopy.

Nitrate reductase 15N discrimination in Arabidopsis thaliana, Zea mays, Aspergillus niger, Pichea angusta, and Escherichia coli

Directory of Open Access Journals (Sweden)

Eli eCarlisle

2014-07-01

Full Text Available Stable 15N isotopes have been used to examine movement of nitrogen (N through various pools of the global N cycle. A central reaction in the cycle involves nitrate (NO3– reduction to nitrite (NO2– catalyzed via nitrate reductase (NR. Discrimination against 15N by NR is a major determinant of isotopic differences among N pools. Here, we measured in vitro 15N discrimination by several NRs purified from plants, fungi, and a bacterium to determine the intrinsic 15N discrimination by the enzyme and to evaluate the validity of measurements made using 15N-enriched NO3–. Observed NR isotope discrimination ranged from 22‰ to 32‰ (kinetic isotope effects of 1.022 to 1.032 among the different isozymes at natural abundance 15N (0.37%. As the fractional 15N content of substrate NO3– increased from natural abundance, the product 15N fraction deviated significantly from that expected based on substrate enrichment and 15N discrimination measured at natural abundance. Additionally, isotopic discrimination by denitrifying bacteria used to reduce NO3– and NO2– in some protocols became a greater source of error as 15N enrichment increased. We briefly discuss potential causes of artifactual results with enriched 15N and recommend against the use of highly enriched 15N tracers to study N discrimination in plants or soils.

Natural and Synthetic Biohydrogels Design, Characterization, Network Structure Imaging and Modeling

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Marmorat, Clement

Biocompatible hydrogels can be derived from materials that are naturally obtained, such as proteins or polysaccharides, or synthetic, such as poloxamers. In order to be classified as biocompatible, these water-swollen networks can not trigger a toxic response once introduced into a biological or physiological environment and, therefore, must be immunoneutral. Hyaluronic acid hydrogels can be great candidates for tissue engineering applications as long as the cross-linking chemistry and process does not affect the biocompatibility of the natural protein matrix. Thermoreversible hydrogels have the advantage of undergoing a sol/gel phase transition at specific temperatures. Thus, they are excellent candidates for biomedical applications such as drug delivery systems, wound healing coatings or cellular scaffolds. Although these hydrogels can be used in their natural form without further modification or chemical alteration, the original protein or polymer matrix is often strengthened by the use of a crosslinking agent to achieve a specific set of properties. In the case of gelatin fibril formation at low temperatures or the micellization of triblock copolymers in solution with temperature increase, the natural phase transition is modified when crosslinkers are introduced to alter the biohydrogels properties and, ultimately, disturb the system's equilibrium. By using spectroscopy techniques, rheology and cryo-imaging we investigated several biocompatible polymeric networks in their natural form as well as their engineered structures to better understand the mechanisms of gelation and artificial internal re-organization of the networks. Natural and synthetic biohydrogels were designed and their mechanical properties were characterized before imaging. Models that better describe the relationship between network configuration and resulting mechanical properties showed great agreement with experimental mesh size observations. Finally, a novel set of hybrid gels was developed

Visualizing the Limits of Low Vision in Detecting Natural Image Features

NARCIS (Netherlands)

Hogervorst, M.A.; Damme, W.J.M. van

2008-01-01

Purpose. The purpose of our study was to develop a tool to visualize the limitations posed by visual impairments in detecting small and low-contrast elements in natural images. This visualization tool incorporates existing models of several aspects of visual perception, such as the band-limited

Pulse duration discriminator

International Nuclear Information System (INIS)

Kosakovskij, L.F.

1980-01-01

Basic circuits of a discriminator for discrimination of pulses with the duration greater than the preset one, and of a multifunctional discriminator allowing to discriminate pulses with the duration greater (tsub(p)>tsub(s)) and lesser (tsub(p) tsub(s) and with the duration tsub(p) [ru

An Investigation of Zimbabwe High School Chemistry Students' Laboratory Work-Based Images of the Nature of Science

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Vhurumuku, Elaosi; Holtman, Lorna; Mikalsen, Oyvind; Kolsto, Stein D.

2006-01-01

This study investigates the proximal and distal images of the nature of science (NOS) that A-level students develop from their participation in chemistry laboratory work. We also explored the nature of the interactions among the students' proximal and distal images of the NOS and students' participation in laboratory work. Students' views of the…

Image as the elements of attractiveness of the destinations of the nature-oriented tourism

Directory of Open Access Journals (Sweden)

Josef Navrátil

2012-01-01

Full Text Available The aim of this paper is to assess the relations between partial components of image of various touristically attractive locations. This research is focused on specific locations in vulnerable areas since the sustainable way of the tourism development concerns them in the highest manner and the touristic pressure on these locations permanently increases. The paper makes effort to extend the usual and nearly traditional understanding of the image in the tourism, which is usually related only to the problems of brand and/or the tourist destination. This is done through a survey realized at 26 selected locations with the aim to obtain 64 completely filled-in questionnaires in each location. Particular statements of respondents concerning the image of the visited location were summarized to the 20 categories. A multidimensional analysis was used to reveal the relations in partial answers. Authors have identified an important number of elements of image of the tourist attractions. By means of the analysis authors have identified differences between historic attractions and nature attractions. However, authors have identified simultaneously both the natural type of the image of the destination and the culture-historical type of image of the destination in all studied locations.

Sensitivity and Specificity of Cardiac Tissue Discrimination Using Fiber-Optics Confocal Microscopy.

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Huang, Chao; Sachse, Frank B; Hitchcock, Robert W; Kaza, Aditya K

2016-01-01

Disturbances of the cardiac conduction system constitute a major risk after surgical repair of complex cases of congenital heart disease. Intraoperative identification of the conduction system may reduce the incidence of these disturbances. We previously developed an approach to identify cardiac tissue types using fiber-optics confocal microscopy and extracellular fluorophores. Here, we applied this approach to investigate sensitivity and specificity of human and automated classification in discriminating images of atrial working myocardium and specialized tissue of the conduction system. Two-dimensional image sequences from atrial working myocardium and nodal tissue of isolated perfused rodent hearts were acquired using a fiber-optics confocal microscope (Leica FCM1000). We compared two methods for local application of extracellular fluorophores: topical via pipette and with a dye carrier. Eight blinded examiners evaluated 162 randomly selected images of atrial working myocardium (n = 81) and nodal tissue (n = 81). In addition, we evaluated the images using automated classification. Blinded examiners achieved a sensitivity and specificity of 99.2 ± 0.3% and 98.0 ± 0.7%, respectively, with the dye carrier method of dye application. Sensitivity and specificity was similar for dye application via a pipette (99.2 ± 0.3% and 94.0 ± 2.4%, respectively). Sensitivity and specificity for automated methods of tissue discrimination were similarly high. Human and automated classification achieved high sensitivity and specificity in discriminating atrial working myocardium and nodal tissue. We suggest that our findings facilitate clinical translation of fiber-optics confocal microscopy as an intraoperative imaging modality to reduce the incidence of conduction disturbances during surgical correction of congenital heart disease.

A progressive data compression scheme based upon adaptive transform coding: Mixture block coding of natural images

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Rost, Martin C.; Sayood, Khalid

1991-01-01

A method for efficiently coding natural images using a vector-quantized variable-blocksized transform source coder is presented. The method, mixture block coding (MBC), incorporates variable-rate coding by using a mixture of discrete cosine transform (DCT) source coders. Which coders are selected to code any given image region is made through a threshold driven distortion criterion. In this paper, MBC is used in two different applications. The base method is concerned with single-pass low-rate image data compression. The second is a natural extension of the base method which allows for low-rate progressive transmission (PT). Since the base method adapts easily to progressive coding, it offers the aesthetic advantage of progressive coding without incorporating extensive channel overhead. Image compression rates of approximately 0.5 bit/pel are demonstrated for both monochrome and color images.

A face recognition algorithm based on multiple individual discriminative models

DEFF Research Database (Denmark)

Fagertun, Jens; Gomez, David Delgado; Ersbøll, Bjarne Kjær

2005-01-01

Abstract—In this paper, a novel algorithm for facial recognition is proposed. The technique combines the color texture and geometrical configuration provided by face images. Landmarks and pixel intensities are used by Principal Component Analysis and Fisher Linear Discriminant Analysis to associate...

Conceptual and visual features contribute to visual memory for natural images.

Directory of Open Access Journals (Sweden)

Gesche M Huebner

Full Text Available We examined the role of conceptual and visual similarity in a memory task for natural images. The important novelty of our approach was that visual similarity was determined using an algorithm [1] instead of being judged subjectively. This similarity index takes colours and spatial frequencies into account. For each target, four distractors were selected that were (1 conceptually and visually similar, (2 only conceptually similar, (3 only visually similar, or (4 neither conceptually nor visually similar to the target image. Participants viewed 219 images with the instruction to memorize them. Memory for a subset of these images was tested subsequently. In Experiment 1, participants performed a two-alternative forced choice recognition task and in Experiment 2, a yes/no-recognition task. In Experiment 3, testing occurred after a delay of one week. We analyzed the distribution of errors depending on distractor type. Performance was lowest when the distractor image was conceptually and visually similar to the target image, indicating that both factors matter in such a memory task. After delayed testing, these differences disappeared. Overall performance was high, indicating a large-capacity, detailed visual long-term memory.

Benign focal liver lesions: discrimination from malignant mimickers.

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Alobaidi, Mohammad; Shirkhoda, Ali

2004-01-01

Focal lesions of the liver often have various imaging characteristics which may be interpreted as either benign or malignant. Understanding the underlying pathophysiology of these liver lesions may lead to characteristic imaging manifestations, which direct the radiologist to the diagnosis. Benign lesions include congenital hepatic cyst, autosomal dominant polycystic disease, hemangioma, focal nodular hyperplasia (FNH), hepatic adenoma, inflammatory pseudotumor, peliosis hepatis, focal fatty infiltration, hamartoma, and infectious processes such as hepatic abscess, echinococcal cyst, and candidiasis. Characteristic imaging features, clinical symptoms, and treatment/prognosis will be discussed. Emphasis will be placed on key reliable features of each disease to develop a method of discriminating these lesions from other benign and malignant disorders.

Low-level contrast statistics of natural images can modulate the frequency of event-related potentials (ERP in humans

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Masoud Ghodrati

2016-12-01

Full Text Available Humans are fast and accurate in categorizing complex natural images. It is, however, unclear what features of visual information are exploited by brain to perceive the images with such speed and accuracy. It has been shown that low-level contrast statistics of natural scenes can explain the variance of amplitude of event-related potentials (ERP in response to rapidly presented images. In this study, we investigated the effect of these statistics on frequency content of ERPs. We recorded ERPs from human subjects, while they viewed natural images each presented for 70 ms. Our results showed that Weibull contrast statistics, as a biologically plausible model, explained the variance of ERPs the best, compared to other image statistics that we assessed. Our time-frequency analysis revealed a significant correlation between these statistics and ERPs’ power within theta frequency band (~3-7 Hz. This is interesting, as theta band is believed to be involved in context updating and semantic encoding. This correlation became significant at ~110 ms after stimulus onset, and peaked at 138 ms. Our results show that not only the amplitude but also the frequency of neural responses can be modulated with low-level contrast statistics of natural images and highlights their potential role in scene perception.

Experiments performed with a functional model based on statistical discrimination in mixed nuclear radiation field

International Nuclear Information System (INIS)

Valcov, N.; Celarel, A.; Purghel, L.

1999-01-01

By using the statistical discrimination technique, the components of on ionization current, due to a mixed radiation field, may be simultaneously measured. A functional model, including a serially manufactured gamma-ray ratemeter was developed, as an intermediate step in the design of specialised nuclear instrumentation, in order to check the concept of statistical discrimination method. The obtained results are in good agreement with the estimations of the statistical discrimination method. The main characteristics of the functional model are the following: - dynamic range of measurement: >300: l; - simultaneous measurement of natural radiation background and gamma-ray fields; - accuracy (for equal exposure rates from gamma's and natural radiation background): 17%, for both radiation fields; - minimum detectable exposure rate: 2μR/h. (authors)

Impaired verbal memory in Parkinson disease: relationship to prefrontal dysfunction and somatosensory discrimination

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Weniger Dorothea

2009-12-01

Full Text Available Abstract Objective To study the neurocognitive profile and its relationship to prefrontal dysfunction in non-demented Parkinson's disease (PD with deficient haptic perception. Methods Twelve right-handed patients with PD and 12 healthy control subjects underwent thorough neuropsychological testing including Rey complex figure, Rey auditory verbal and figural learning test, figural and verbal fluency, and Stroop test. Test scores reflecting significant differences between patients and healthy subjects were correlated with the individual expression coefficients of one principal component, obtained in a principal component analysis of an oxygen-15-labeled water PET study exploring somatosensory discrimination that differentiated between the two groups and involved prefrontal cortices. Results We found significantly decreased total scores for the verbal learning trials and verbal delayed free recall in PD patients compared with normal volunteers. Further analysis of these parameters using Spearman's ranking correlation showed a significantly negative correlation of deficient verbal recall with expression coefficients of the principal component whose image showed a subcortical-cortical network, including right dorsolateral-prefrontal cortex, in PD patients. Conclusion PD patients with disrupted right dorsolateral prefrontal cortex function and associated diminished somatosensory discrimination are impaired also in verbal memory functions. A negative correlation between delayed verbal free recall and PET activation in a network including the prefrontal cortices suggests that verbal cues and accordingly declarative memory processes may be operative in PD during activities that demand sustained attention such as somatosensory discrimination. Verbal cues may be compensatory in nature and help to non-specifically enhance focused attention in the presence of a functionally disrupted prefrontal cortex.

The zebrafish world of colors and shapes: preference and discrimination.

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Oliveira, Jessica; Silveira, Mayara; Chacon, Diana; Luchiari, Ana

2015-04-01

Natural environment imposes many challenges to animals, which have to use cognitive abilities to cope with and exploit it to enhance their fitness. Since zebrafish is a well-established model for cognitive studies and high-throughput screening for drugs and diseases that affect cognition, we tested their ability for ambient color preference and 3D objects discrimination to establish a protocol for memory evaluation. For the color preference test, zebrafish were observed in a multiple-chamber tank with different environmental color options. Zebrafish showed preference for blue and green, and avoided yellow and red. For the 3D objects discrimination, zebrafish were allowed to explore two equal objects and then observed in a one-trial test in which a new color, size, or shape of the object was presented. Zebrafish showed discrimination for color, shape, and color+shape combined, but not size. These results imply that zebrafish seem to use some categorical system to discriminate items, and distracters affect their ability for discrimination. The type of variables available (color and shape) may favor zebrafish objects perception and facilitate discrimination processing. We suggest that this easy and simple memory test could serve as a useful screening tool for cognitive dysfunction and neurotoxicological studies.

The impact of image fusion in resolving discrepant findings between FDG-PET and MRI/CT in patients with gynaecological cancers

International Nuclear Information System (INIS)

Tsai, Cheng-Chien; Kao, Pan-Fu; Yen, Tzu-Chen; Tsai, Chien-Sheng; Hong, Ji-Hong; Ng, Koon-Kwan; Lai, Chyong-Huey; Chang, Ting-Chang; Hsueh, Swei

2003-01-01

This study was performed to prospectively investigate the impact of image fusion in resolving discrepant findings between fluorine-18 fluorodeoxyglucose positron emission tomography (FDG-PET) and magnetic resonance imaging (MRI) or X-ray computed tomography (CT) in patients with gynaecological cancers. Discrepant findings were defined as lesions where the difference between the FDG-PET and MRI/CT images was assigned a value of at least 2 on a 5-point probability scale. The FDG-PET and MRI/CT images were taken within 1 month of each other. Image fusion between FDG-PET and CT was performed by automatic registration between the two images. During an 18-month period, 34 malignant lesions and seven benign lesions from 32 patients who had undergone either surgical excision or a CT-guided histopathological investigation were included for analysis. Among these cases, image fusion was most frequently required to determine the nature and/or the extent of abdominal and pelvic lesions (28/41, 68%), especially as regards peritoneal seeding (8/41, 20%). Image fusion was most useful in providing better localisation for biopsy (16/41, 39%) and in discriminating between lesions with pathological versus physiological FDG uptake (12/41, 29%). Image fusion changed the original diagnosis based on MRI/CT alone in 9/41 lesions (22%), and the original diagnosis based on FDG-PET alone in 5/41 lesions (12%). It led to alteration of treatment planning (surgery or radiotherapy) in seven of the 32 patients (22%). In patients with gynaecological cancers, the technique of image fusion is helpful in discriminating the nature of FDG-avid lesions, in effectively localising lesions for CT-guided biopsy and in providing better surgical or radiotherapy planning. (orig.)

Quantifying explainable discrimination and removing illegal discrimination in automated decision making

KAUST Repository

Kamiran, Faisal

2012-11-18

Recently, the following discrimination-aware classification problem was introduced. Historical data used for supervised learning may contain discrimination, for instance, with respect to gender. The question addressed by discrimination-aware techniques is, given sensitive attribute, how to train discrimination-free classifiers on such historical data that are discriminative, with respect to the given sensitive attribute. Existing techniques that deal with this problem aim at removing all discrimination and do not take into account that part of the discrimination may be explainable by other attributes. For example, in a job application, the education level of a job candidate could be such an explainable attribute. If the data contain many highly educated male candidates and only few highly educated women, a difference in acceptance rates between woman and man does not necessarily reflect gender discrimination, as it could be explained by the different levels of education. Even though selecting on education level would result in more males being accepted, a difference with respect to such a criterion would not be considered to be undesirable, nor illegal. Current state-of-the-art techniques, however, do not take such gender-neutral explanations into account and tend to overreact and actually start reverse discriminating, as we will show in this paper. Therefore, we introduce and analyze the refined notion of conditional non-discrimination in classifier design. We show that some of the differences in decisions across the sensitive groups can be explainable and are hence tolerable. Therefore, we develop methodology for quantifying the explainable discrimination and algorithmic techniques for removing the illegal discrimination when one or more attributes are considered as explanatory. Experimental evaluation on synthetic and real-world classification datasets demonstrates that the new techniques are superior to the old ones in this new context, as they succeed in

Fluorescent carbon nanoparticles derived from natural materials of mango fruit for bio-imaging probes

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Jeong, Chan Jin; Roy, Arup Kumer; Kim, Sung Han; Lee, Jung-Eun; Jeong, Ji Hoon; Insik; Park, Sung Young

2014-11-01

Water soluble fluorescent carbon nanoparticles (FCP) obtained from a single natural source, mango fruit, were developed as unique materials for non-toxic bio-imaging with different colors and particle sizes. The prepared FCPs showed blue (FCP-B), green (FCP-G) and yellow (FCP-Y) fluorescence, derived by the controlled carbonization method. The FCPs demonstrated hydrodynamic diameters of 5-15 nm, holding great promise for clinical applications. The biocompatible FCPs demonstrated great potential in biological fields through the results of in vitro imaging and in vivo biodistribution. Using intravenously administered FCPs with different colored particles, we precisely defined the clearance and biodistribution, showing rapid and efficient urinary excretion for safe elimination from the body. These findings therefore suggest the promising possibility of using natural sources for producing fluorescent materials.Water soluble fluorescent carbon nanoparticles (FCP) obtained from a single natural source, mango fruit, were developed as unique materials for non-toxic bio-imaging with different colors and particle sizes. The prepared FCPs showed blue (FCP-B), green (FCP-G) and yellow (FCP-Y) fluorescence, derived by the controlled carbonization method. The FCPs demonstrated hydrodynamic diameters of 5-15 nm, holding great promise for clinical applications. The biocompatible FCPs demonstrated great potential in biological fields through the results of in vitro imaging and in vivo biodistribution. Using intravenously administered FCPs with different colored particles, we precisely defined the clearance and biodistribution, showing rapid and efficient urinary excretion for safe elimination from the body. These findings therefore suggest the promising possibility of using natural sources for producing fluorescent materials. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr04805a

Perceived Discrimination in LGBTIQ Discourse: A Typology of Verbal Discrimination

Directory of Open Access Journals (Sweden)

Sol Rojas Lizana

2014-08-01

Full Text Available New within the field of Discourse Analysis, Perceived Discrimination (PD is the study of discourse that focuses on the perspective of the victims of discrimination. This article explores the experiences of verbal discrimination as reported by eighteen LGBTIQ participants during semi-structured, co-constructed interviews. Data were classified in order to develop a taxonomy of discrimination based on Mellor’s (2003, 2004. This taxonomy foregrounds two types of discrimination: verbal and behavioural. In this paper, I exemplify the forms of verbal discrimination encountered and offer an analysis of the discourse used in the construction of the experiences and of the effects reported. The results show that verbal discrimination is an overt phenomenon and that participants are stressed by the ever present possibility of facing it. Verbal discrimination is mainly triggered by a perceived transgression to the normalised standards of people’s behaviour, movements and look in a heterosexist society. It presents three subtypes: name calling, abuse and remarks. These subtypes are described through the analysis of keywords, effects and expressions (such as faggot, gay, dyke, queer, the pronoun ‘it’, religious comments and other remarks. The type of discrimination used was associated with the level of acquaintance perpetrators have with the experiencers; that is, name calling was used by people unknown to the victims while abuse and remarks by acquaintances and family members. Participants resorted to several discursive strategies to convey their intentions. They used mitigation strategies when wanting to minimize the experience, hedging and repetition were used for emphasis, and to convey urgency and pervasiveness. Metaphorical expressions related to internal or external injuries were also used to express the powerful effect of verbal discrimination on people.

Detection of Lettuce Discoloration Using Hyperspectral Reflectance Imaging.

Science.gov (United States)

Mo, Changyeun; Kim, Giyoung; Lim, Jongguk; Kim, Moon S; Cho, Hyunjeong; Cho, Byoung-Kwan

2015-11-20

Rapid visible/near-infrared (VNIR) hyperspectral imaging methods, employing both a single waveband algorithm and multi-spectral algorithms, were developed in order to discrimination between sound and discolored lettuce. Reflectance spectra for sound and discolored lettuce surfaces were extracted from hyperspectral reflectance images obtained in the 400-1000 nm wavelength range. The optimal wavebands for discriminating between discolored and sound lettuce surfaces were determined using one-way analysis of variance. Multi-spectral imaging algorithms developed using ratio and subtraction functions resulted in enhanced classification accuracy of above 99.9% for discolored and sound areas on both adaxial and abaxial lettuce surfaces. Ratio imaging (RI) and subtraction imaging (SI) algorithms at wavelengths of 552/701 nm and 557-701 nm, respectively, exhibited better classification performances compared to results obtained for all possible two-waveband combinations. These results suggest that hyperspectral reflectance imaging techniques can potentially be used to discriminate between discolored and sound fresh-cut lettuce.

Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

Directory of Open Access Journals (Sweden)

Shengwen Guo

2017-05-01

Full Text Available Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI. Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI, the converted MCI (cMCI, and the normal control (NC groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM. An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and

Design and technical evaluation of fibre-coupled Raman probes for the image-guided discrimination of cancerous skin

International Nuclear Information System (INIS)

Schleusener, J; Reble, C; Helfmann, J; Gersonde, I; Cappius, H-J; Glanert, M; Fluhr, J W; Meinke, M C

2014-01-01

Two different designs for fibre-coupled Raman probes are presented that are optimized for discriminating cancerous and normal skin by achieving high epithelial sensitivity to detect a major component of the Raman signal from the depth range of the epithelium. This is achieved by optimizing Raman spot diameters to the range of ≈200 µm, which distinguishes this approach from the common applications of either Raman microspectroscopy (1–5 µm) or measurements on larger sampling volume using spot sizes of a few mm. Video imaging with a depicted area in the order of a few cm, to allow comparing Raman measurements to the location of the histo-pathologic findings, is integrated in both designs. This is important due to the inhomogeneity of cancerous lesions. Video image acquisition is achieved using white light LED illumination, which avoids ambient light artefacts. The design requirements focus either on a compact light-weight configuration, for pen-like handling, or on a video-visible measurement spot to enable increased positioning accuracy. Both probes are evaluated with regard to spot size, Rayleigh suppression, background fluorescence, depth sensitivity, clinical handling and ambient light suppression. Ex vivo measurements on porcine ear skin correlates well with findings of other groups. (paper)

From Pixels to Response Maps: Discriminative Image Filtering for Face Alignment in the Wild.

Science.gov (United States)

Asthana, Akshay; Zafeiriou, Stefanos; Tzimiropoulos, Georgios; Cheng, Shiyang; Pantic, Maja

2015-06-01

We propose a face alignment framework that relies on the texture model generated by the responses of discriminatively trained part-based filters. Unlike standard texture models built from pixel intensities or responses generated by generic filters (e.g. Gabor), our framework has two important advantages. First, by virtue of discriminative training, invariance to external variations (like identity, pose, illumination and expression) is achieved. Second, we show that the responses generated by discriminatively trained filters (or patch-experts) are sparse and can be modeled using a very small number of parameters. As a result, the optimization methods based on the proposed texture model can better cope with unseen variations. We illustrate this point by formulating both part-based and holistic approaches for generic face alignment and show that our framework outperforms the state-of-the-art on multiple "wild" databases. The code and dataset annotations are available for research purposes from http://ibug.doc.ic.ac.uk/resources.

Use of Multispectral Imaging in Varietal Identification of Tomato

DEFF Research Database (Denmark)

Shrestha, Santosh; Deleuran, Lise Christina; Olesen, Merete Halkjær

2015-01-01

Abstract: Multispectral imaging is an emerging non-destructive technology. In this work its potential for varietal discrimination and identification of tomato cultivars of Nepal was investigated. Two sample sets were used for the study, one with two parents and their crosses and other with eleven...... obtained provide an opportunity of using multispectral imaging technology as a primary tool in a scientific community for identification/discrimination of plant varieties in regard to genetic purity and plant variety protection/registration.......Abstract: Multispectral imaging is an emerging non-destructive technology. In this work its potential for varietal discrimination and identification of tomato cultivars of Nepal was investigated. Two sample sets were used for the study, one with two parents and their crosses and other with eleven...... cultivars to study parents and offspring relationship and varietal identification respectively. Normalized canonical discriminant analysis (nCDA) and principal component analysis (PCA) were used to analyze and compare the results for parents and offspring study. Both the results showed clear discrimination...

Logistic discriminant analysis of breast cancer using ultrasound measurement

International Nuclear Information System (INIS)

Abdolmaleki, P.; Mokhtari Dizaji, M.; Vahead, M.R.; Gity, M.

2004-01-01

Background: Logistic discriminant method was applied to differentiate malignant from benign in a group of patients with proved breast lesions of the basis of ultrasonic parameters. Materials and methods: Our database include 273 patients' ultrasonographic pictures consisting of 14 quantitative variables. The measured variables were ultrasound propagation velocity, acoustic impedance and attenuation coefficient at 10 MHz in breast lesions at 20, 25, 30 and 35 d ig c temperature, physical density and age. This database was randomly divided into the estimation of 201 and validation of 72 samples. The estimation samples were used to build the logistic discriminant model, and validation samples were used to validate the performance. Finally important criteria such as sensitivity, specificity, accuracy and area under the receiver operating characteristic curve were evaluated. Results: Our results showed that the logistic discriminant method was able to classify correctly 67 out of 72 cases presented in the validation sample. The results indicate a remarkable diagnostic accuracy of 93%. Conclusion: A logistic discriminator approach is capable of predicting the probability of malignancy of breast cancer. Features from ultrasonic measurement on ultrasound imaging is used in this approach

Gamma-ray imaging probes

International Nuclear Information System (INIS)

Wild, W.J.

1988-01-01

External nuclear medicine diagnostic imaging of early primary and metastatic lung cancer tumors is difficult due to the poor sensitivity and resolution of existing gamma cameras. Nonimaging counting detectors used for internal tumor detection give ambiguous results because distant background variations are difficult to discriminate from neighboring tumor sites. This suggests that an internal imaging nuclear medicine probe, particularly an esophageal probe, may be advantageously used to detect small tumors because of the ability to discriminate against background variations and the capability to get close to sites neighboring the esophagus. The design, theory of operation, preliminary bench tests, characterization of noise behavior and optimization of such an imaging probe is the central theme of this work

Pulse-width discriminators

International Nuclear Information System (INIS)

Budyashov, Yu.G.; Grebenyuk, V.M.; Zinov, V.G.

1978-01-01

A pulse duration discriminator is described which is intended for processing signals from multilayer scintillators. The basic elements of the scintillator are: an input gate, a current generator, an integrating capacitor, a Schmidt trigger and an anticoincidence circuit. The basic circuit of the discriminator and its time diagrams explaining its operating are given. The discriminator is based on microcircuits. Pulse duration discrimination threshold changes continuously from 20 to 100 ns, while its amplitude threshold changes within 20 to 100 mV. The temperature instability of discrimination thresholds (both in pulse width and in amplitude) is better than 0.1 per cent/deg C

Forced sterilization of women as discrimination.

Science.gov (United States)

Patel, Priti

2017-01-01

There has been a long history of subjecting marginalized women to forced and coerced sterilization. In recent years, the practice has been documented in countries in North and South America, Europe, Asia, and Africa. It has targeted women who are ethnic and racial minorities, women with disabilities, women living with HIV, and poor women. A handful of courts have issued decisions on the recent forced sterilization of marginalized women finding that such actions violate the women's rights. However, they have all failed to address the women's claims of discrimination. The failure to acknowledge that forced sterilization is at its core a violation of the prohibition of discrimination undermines efforts to eradicate the practice. It further fails to recognize that coerced and forced sterilization fundamentally seeks to deny women deemed as "unworthy" the ability to procreate. Four key principles outlined in the human rights in patient care framework highlight the importance of a finding that the prohibition of discrimination was violated in cases of forced sterilization: the need to highlight the vulnerability of marginalized populations to discrimination in health care settings; the importance of the rights of medical providers; the role of the state in addressing systemic human rights violations in health care settings; and the application of human rights to patient care. Based on these principles, it is clear that finding a violation of the prohibition of discrimination in forced sterilization cases is critical in addressing the systemic nature of the practice, acknowledging the marginalization of specific groups and effectively ending forced sterilization through addressing the underlying purpose of the practice. If litigators, non-governmental organizations and judicial officers are mindful of these principles when dealing with cases of forced sterilization, it is likely that they will be better able to eradicate forced sterilization.

Precise natural radiography of seafloor sedimentary cores by using imaging plate

International Nuclear Information System (INIS)

Sugihara, Makoto; Tsuchiya, Noriyoshi

2007-01-01

The radiation measurement for seafloor sedimentary cores was carried out by using the Imaging Plate (IP). The precise natural radiography was obtained with 48 hours (exposure time) in a shield box. Layered structures of seafloor sediments that have relatively low radioactivity like biogenic matters could be detected by autoradiography, and it was possible to identify optically unclear layers of sediments with differences of radiation characteristics. The detection limit of thickness of suspended particle layers like volcanic ashes might be sub millimeters. It was possible to identify the pinpoint position where radioactive mineral emitted α-rays at the surface of sample. Identification of pinpoint position could be possible suppose radioactive minerals that emits α-ray exposed at the surface of sample. Distribution of dose (PSL value of IP) was related to CT value (X-ray CT), which indicates dose of sedimentary core have relationships with density and atomic number of sediments. The natural radiography for seafloor sediments cores by using the Imaging Plate is considered to be a powerful new tool as a non-destructive core analysis. (author)

Justice seems not to be for all: the role played by justice perceptions in discrimination against immigrants

OpenAIRE

Nunes, Aline Vieira de Lima

2013-01-01

Doctor in Psychology This thesis aimed to examine how justice perceptions are related with the perpetuation of discrimination, exploring the role played by the scope of justice and belief in a just world (BJW) in the legitimation of discrimination against immigrants. Based on the assumptions of the Justified Discrimination Model (JDM), individuals need to search for justification in order to legitimize the discriminatory behaviour, preserving their self-image as a fair indiv...

Discriminating between benign and malignant breast tumors using 3D convolutional neural network in dynamic contrast enhanced-MR images

Science.gov (United States)

Li, Jing; Fan, Ming; Zhang, Juan; Li, Lihua

2017-03-01

Convolutional neural networks (CNNs) are the state-of-the-art deep learning network architectures that can be used in a range of applications, including computer vision and medical image analysis. It exhibits a powerful representation learning mechanism with an automated design to learn features directly from the data. However, the common 2D CNNs only use the two dimension spatial information without evaluating the correlation between the adjoin slices. In this study, we established a method of 3D CNNs to discriminate between malignant and benign breast tumors. To this end, 143 patients were enrolled which include 66 benign and 77 malignant instances. The MRI images were pre-processed for noise reduction and breast tumor region segmentation. Data augmentation by spatial translating, rotating and vertical and horizontal flipping is applied to the cases to reduce possible over-fitting. A region-of-interest (ROI) and a volume-of-interest (VOI) were segmented in 2D and 3D DCE-MRI, respectively. The enhancement ratio for each MR series was calculated for the 2D and 3D images. The results for the enhancement ratio images in the two series are integrated for classification. The results of the area under the ROC curve(AUC) values are 0.739 and 0.801 for 2D and 3D methods, respectively. The results for 3D CNN which combined 5 slices for each enhancement ratio images achieved a high accuracy(Acc), sensitivity(Sens) and specificity(Spec) of 0.781, 0.744 and 0.823, respectively. This study indicates that 3D CNN deep learning methods can be a promising technology for breast tumor classification without manual feature extraction.

Cogent Confabulation based Expert System for Segmentation and Classification of Natural Landscape Images

Directory of Open Access Journals (Sweden)

BRAOVIC, M.

2017-05-01

Full Text Available Ever since there has been an increase in the number of automatic wildfire monitoring and surveillance systems in the last few years, natural landscape images have been of great importance. In this paper we propose an expert system for fast segmentation and classification of regions on natural landscape images that is suitable for real-time applications. We focus primarily on Mediterranean landscape images since the Mediterranean area and areas with similar climate are the ones most associated with high wildfire risk. The proposed expert system is based on cogent confabulation theory and knowledge bases that contain information about local and global features, optimal color spaces suitable for classification of certain regions, and context of each class. The obtained results indicate that the proposed expert system significantly outperforms well-known classifiers that it was compared against in both accuracy and speed, and that it is effective and efficient for real-time applications. Additionally, we present a FESB MLID dataset on which we conducted our research and that we made publicly available.

Combustion monitoring of a water tube boiler using a discriminant radial basis network.

Science.gov (United States)

Sujatha, K; Pappa, N

2011-01-01

This research work includes a combination of Fisher's linear discriminant (FLD) analysis and a radial basis network (RBN) for monitoring the combustion conditions for a coal fired boiler so as to allow control of the air/fuel ratio. For this, two-dimensional flame images are required, which were captured with a CCD camera; the features of the images-average intensity, area, brightness and orientation etc of the flame-are extracted after preprocessing the images. The FLD is applied to reduce the n-dimensional feature size to a two-dimensional feature size for faster learning of the RBN. Also, three classes of images corresponding to different burning conditions of the flames have been extracted from continuous video processing. In this, the corresponding temperatures, and the carbon monoxide (CO) emissions and those of other flue gases have been obtained through measurement. Further, the training and testing of Fisher's linear discriminant radial basis network (FLDRBN), with the data collected, have been carried out and the performance of the algorithms is presented. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Multimodality imaging and state-of-art GPU technology in discriminating benign from malignant breast lesions on real time decision support system

International Nuclear Information System (INIS)

Kostopoulos, S; Glotsos, D; Kalatzis, I; Asvestas, P; Cavouras, D; Sidiropoulos, K; Dimitropoulos, N

2014-01-01

The aim of this study was to design a pattern recognition system for assisting the diagnosis of breast lesions, using image information from Ultrasound (US) and Digital Mammography (DM) imaging modalities. State-of-art computer technology was employed based on commercial Graphics Processing Unit (GPU) cards and parallel programming. An experienced radiologist outlined breast lesions on both US and DM images from 59 patients employing a custom designed computer software application. Textural features were extracted from each lesion and were used to design the pattern recognition system. Several classifiers were tested for highest performance in discriminating benign from malignant lesions. Classifiers were also combined into ensemble schemes for further improvement of the system's classification accuracy. Following the pattern recognition system optimization, the final system was designed employing the Probabilistic Neural Network classifier (PNN) on the GPU card (GeForce 580GTX) using CUDA programming framework and C++ programming language. The use of such state-of-art technology renders the system capable of redesigning itself on site once additional verified US and DM data are collected. Mixture of US and DM features optimized performance with over 90% accuracy in correctly classifying the lesions

Quantifying explainable discrimination and removing illegal discrimination in automated decision making

NARCIS (Netherlands)

Kamiran, F.; Zliobaite, I.; Calders, T.G.K.

2013-01-01

Recently, the following discrimination-aware classification problem was introduced. Historical data used for supervised learning may contain discrimination, for instance, with respect to gender. The question addressed by discrimination-aware techniques is, given sensitive attribute, how to train

Characteristics of compressed natural gas jet and jet-wall impingement using the Schlieren imaging technique

International Nuclear Information System (INIS)

Ismael, M A; Heikal, M R; Baharom, M B

2013-01-01

An experimental study was performed to investigate the compressed natural gas jet characteristics and jet-wall impingement using the Schlieren imaging technique and image processing. An injector driver was used to drive the natural gas injector and synchronized with camera triggering. A constant-volume optical chamber was designed to facilitate maximum optical access for the study of the jet macroscopic characteristics and jet-wall impingement at different injection pressures and injectors-wall distances. Measurement of the jet tip penetration and cone angle at different conditions are presented in this paper together with temporal presentation of the jet radial travel along the wall.

Social Status Correlates of Reporting Racial Discrimination and Gender Discrimination among Racially Diverse Women

Science.gov (United States)

Ro, Annie E.; Choi, Kyung-Hee

2009-01-01

The growing body of research on discrimination and health indicates a deleterious effect of discrimination on various health outcomes. However, less is known about the sociodemographic correlates of reporting racial discrimination and gender discrimination among racially diverse women. We examined the associations of social status characteristics with lifetime experiences of racial discrimination and gender discrimination using a racially-diverse sample of 754 women attending family planning clinics in Northern California (11.4% African American, 16.8% Latina, 10.1% Asian and 61.7% Caucasian). A multivariate analysis revealed that race, financial difficulty and marital status were significantly correlated with higher reports of racial discrimination, while race, education, financial difficulty and nativity were significantly correlated with gender discrimination scores. Our findings suggest that the social patterning of perceiving racial discrimination is somewhat different from that of gender discrimination. This has implications in the realm of discrimination research and applied interventions, as different forms of discrimination may have unique covariates that should be accounted for in research analysis or program design. PMID:19485231

Social status correlates of reporting gender discrimination and racial discrimination among racially diverse women.

Science.gov (United States)

Ro, Annie E; Choi, Kyung-Hee

2009-01-01

The growing body of research on discrimination and health indicates a deleterious effect of discrimination on various health outcomes. However, less is known about the sociodemographic correlates of reporting racial discrimination and gender discrimination among racially diverse women. We examined the associations of social status characteristics with lifetime experiences of racial discrimination and gender discrimination using a racially-diverse sample of 754 women attending family planning clinics in North California (11.4% African American, 16.8% Latina, 10.1% Asian and 61.7% Caucasian). A multivariate analysis revealed that race, financial difficulty and marital status were significantly correlated with higher reports of racial discrimination, while race, education, financial difficulty and nativity were significantly correlated with gender discrimination scores. Our findings suggest that the social patterning of perceiving racial discrimination is somewhat different from that of gender discrimination. This has implications in the realm of discrimination research and applied interventions, as different forms of discrimination may have unique covariates that should be accounted for in research analysis or program design.

A Tentative Application Of Morphological Filters To Time-Varying Images

Science.gov (United States)

Billard, D.; Poquillon, B.

1989-03-01

In this paper, morphological filters, which are commonly used to process either 2D or multidimensional static images, are generalized to the analysis of time-varying image sequence. The introduction of the time dimension induces then interesting prop-erties when designing such spatio-temporal morphological filters. In particular, the specification of spatio-temporal structuring ele-ments (equivalent to time-varying spatial structuring elements) can be adjusted according to the temporal variations of the image sequences to be processed : this allows to derive specific morphological transforms to perform noise filtering or moving objects discrimination on dynamic images viewed by a non-stationary sensor. First, a brief introduction to the basic principles underlying morphological filters will be given. Then, a straightforward gener-alization of these principles to time-varying images will be pro-posed. This will lead us to define spatio-temporal opening and closing and to introduce some of their possible applications to process dynamic images. At last, preliminary results obtained us-ing a natural forward looking infrared (FUR) image sequence are presented.

Hyperspectral image analysis. A tutorial

International Nuclear Information System (INIS)

Amigo, José Manuel; Babamoradi, Hamid; Elcoroaristizabal, Saioa

2015-01-01

This tutorial aims at providing guidelines and practical tools to assist with the analysis of hyperspectral images. Topics like hyperspectral image acquisition, image pre-processing, multivariate exploratory analysis, hyperspectral image resolution, classification and final digital image processing will be exposed, and some guidelines given and discussed. Due to the broad character of current applications and the vast number of multivariate methods available, this paper has focused on an industrial chemical framework to explain, in a step-wise manner, how to develop a classification methodology to differentiate between several types of plastics by using Near infrared hyperspectral imaging and Partial Least Squares – Discriminant Analysis. Thus, the reader is guided through every single step and oriented in order to adapt those strategies to the user's case. - Highlights: • Comprehensive tutorial of Hyperspectral Image analysis. • Hierarchical discrimination of six classes of plastics containing flame retardant. • Step by step guidelines to perform class-modeling on hyperspectral images. • Fusion of multivariate data analysis and digital image processing methods. • Promising methodology for real-time detection of plastics containing flame retardant.

Lexical exposure to native language dialects can improve non-native phonetic discrimination.

Science.gov (United States)

Olmstead, Annie J; Viswanathan, Navin

2018-04-01

Nonnative phonetic learning is an area of great interest for language researchers, learners, and educators alike. In two studies, we examined whether nonnative phonetic discrimination of Hindi dental and retroflex stops can be improved by exposure to lexical items bearing the critical nonnative stops. We extend the lexical retuning paradigm of Norris, McQueen, and Cutler (Cognitive Psychology, 47, 204-238, 2003) by having naive American English (AE)-speaking participants perform a pretest-training-posttest procedure. They performed an AXB discrimination task with the Hindi retroflex and dental stops before and after transcribing naturally produced words from an Indian English speaker that either contained these tokens or not. Only those participants who heard words with the critical nonnative phones improved in their posttest discrimination. This finding suggests that exposure to nonnative phones in native lexical contexts supports learning of difficult nonnative phonetic discrimination.

Handling conditional discrimination

NARCIS (Netherlands)

Zliobaite, I.; Kamiran, F.; Calders, T.G.K.

2011-01-01

Historical data used for supervised learning may contain discrimination. We study how to train classifiers on such data, so that they are discrimination free with respect to a given sensitive attribute, e.g., gender. Existing techniques that deal with this problem aim at removing all discrimination

Cardiovascular MR T2-STIR imaging does not discriminate between intramyocardial haemorrhage and microvascular obstruction during the subacute phase of a reperfused myocardial infarction

DEFF Research Database (Denmark)

Hansen, Esben Søvsø Szocska; Pedersen, Steen Fjord; Pedersen, Steen Bønløkke

2016-01-01

) and T2 weighted short tau inversion recovery (T2-STIR) imaging have been used to detect IMH and to explore its clinical importance. IMH is typically identified within the area-at-risk as a hypointense signal core on T2-STIR images. Because MVO will also appear as a hypointense signal core, T2-STIR...... imaging may not be an optimal method for assessing IMH. In this study, we sought to investigate the ability of T2-STIR to discriminate between MVO with IMH in a porcine myocardial ischaemia-reperfusion model that expressed MVO with and without IMH. METHOD: MVO with and without IMH (defined from both...... MVO in all hearts. CMR and pathology showed that IMH was present in 6 of 13 (46%) infarcts. The sensitivity and specificity of T2-STIR hypointense signal core for identification of IMH was 100% and 29%, respectively. T2-values between hypointense signal core in the pigs with and without IMH were...

Visual Aversive Learning Compromises Sensory Discrimination.

Science.gov (United States)

Shalev, Lee; Paz, Rony; Avidan, Galia

2018-03-14

Aversive learning is thought to modulate perceptual thresholds, which can lead to overgeneralization. However, it remains undetermined whether this modulation is domain specific or a general effect. Moreover, despite the unique role of the visual modality in human perception, it is unclear whether this aspect of aversive learning exists in this modality. The current study was designed to examine the effect of visual aversive outcomes on the perception of basic visual and auditory features. We tested the ability of healthy participants, both males and females, to discriminate between neutral stimuli, before and after visual learning. In each experiment, neutral stimuli were associated with aversive images in an experimental group and with neutral images in a control group. Participants demonstrated a deterioration in discrimination (higher discrimination thresholds) only after aversive learning. This deterioration was measured for both auditory (tone frequency) and visual (orientation and contrast) features. The effect was replicated in five different experiments and lasted for at least 24 h. fMRI neural responses and pupil size were also measured during learning. We showed an increase in neural activations in the anterior cingulate cortex, insula, and amygdala during aversive compared with neutral learning. Interestingly, the early visual cortex showed increased brain activity during aversive compared with neutral context trials, with identical visual information. Our findings imply the existence of a central multimodal mechanism, which modulates early perceptual properties, following exposure to negative situations. Such a mechanism could contribute to abnormal responses that underlie anxiety states, even in new and safe environments. SIGNIFICANCE STATEMENT Using a visual aversive-learning paradigm, we found deteriorated discrimination abilities for visual and auditory stimuli that were associated with visual aversive stimuli. We showed increased neural

Workplace discrimination and HIV/AIDS: the national EEOC ADA research project.

Science.gov (United States)

Conyers, Liza; Boomer, K B; McMahon, Brian T

2005-01-01

This article utilizes data from the Equal Employment Opportunity Commission's Integrated Mission System database to document the levels of employment discrimination involving individuals with HIV/AIDS. The researchers explore the theory that the nature of HIV/AIDS related employment discrimination is rooted in deeper stigmatization than discrimination against other disability groups. Researchers compare and contrast key demographic characteristics of Charging Parties and Respondents involved in HIV/AIDS related allegations of discrimination and their proportion of EEOC merit resolutions to those of persons with other physical, sensory, and neurological impairments. Findings indicate that, in contrast to the general disability group, HIV/AIDS was more likely to be male, ethnic minorities, between the ages of 25-44, in white collar jobs, in the South and West and to work for businesses with 15 to 100 employees. Additionally, the allegations in HIV/AIDS were more likely to receive merit resolution from the EEOC by a large difference of ten percent.

Social Status Correlates of Reporting Racial Discrimination and Gender Discrimination among Racially Diverse Women

OpenAIRE

Ro, Annie E.; Choi, Kyung-Hee

2009-01-01

The growing body of research on discrimination and health indicates a deleterious effect of discrimination on various health outcomes. However, less is known about the sociodemographic correlates of reporting racial discrimination and gender discrimination among racially diverse women. We examined the associations of social status characteristics with lifetime experiences of racial discrimination and gender discrimination using a racially-diverse sample of 754 women attending family planning ...

Racial discrimination, gender discrimination, and substance abuse among Latina/os nationwide.

Science.gov (United States)

Otiniano Verissimo, Angie Denisse; Gee, Gilbert C; Ford, Chandra L; Iguchi, Martin Y

2014-01-01

This study investigates the relationship between discrimination and substance abuse among Latina/os, and further examines whether this relationship differs by gender and type of discrimination. Analyses focus on the Latina/o respondents (n = 1,039 men; n = 1,273 women) from the National Latino and Asian American Study carried out from 2002-2003. Outcomes were alcohol abuse and drug abuse measured using DSM-IV definitions and criteria. Additional covariates included immigrant characteristics and demographics. Analyses were completed using gender-stratified multinomial logistic regression. Men reported more discrimination (39.6% vs. 30.3%) and had higher prevalence of alcohol abuse (16.5% vs. 4.5%) and drug abuse (9.5% vs. 2.3%) than women. Discrimination was significantly associated with increased risk of alcohol abuse for women and increased risk of drug abuse for men. Men and women also varied in the types of discrimination (e.g., racial vs. gender) reported, and in the associations between these types of discrimination and substance abuse. These data indicate that discrimination is associated with different substance abuse outcomes between genders. Future research should consider the mechanisms that explain these differences.

Optical imaging through turbid media with a degenerate four wave mixing correlation time gate

International Nuclear Information System (INIS)

Sappey, A.D.

1994-01-01

A novel method for detection of ballistic light and rejection of unwanted diffusive light to image structures inside highly scattering media is demonstrated. Degenerate four wave mixing (DFWM) of a doubled YAG laser in Rhodamine 6G is used to provide an ultrafast correlation time gate to discriminate against light that has undergone multiple scattering and therefore lost memory of the structures inside the scattering medium. We present preliminary results that determine the nature of the DFWM grating, confirm the coherence time of the laser, prove the phase-conjugate nature of the signal beam, and determine the dependence of the signal (reflectivity) on dye concentration and laser intensity. Finally, we have obtained images of a test cross-hair pattern through highly turbid suspensions of whole milk in water that are opaque to the naked eye. These imaging experiments demonstrate the utility of DFWM for imaging through turbid media. Based on our results, the use of DFWM as an ultrafast time gate for the detection of ballistic light in optical mammography appears to hold great promise for improving the current state of the art

Classification in Medical Imaging

DEFF Research Database (Denmark)

Chen, Chen

Classification is extensively used in the context of medical image analysis for the purpose of diagnosis or prognosis. In order to classify image content correctly, one needs to extract efficient features with discriminative properties and build classifiers based on these features. In addition...... on characterizing human faces and emphysema disease in lung CT images....

LABOR DISCRIMINATION IN BULGARIA

Directory of Open Access Journals (Sweden)

Vyara Slavyanska

2017-03-01

Full Text Available Labor discrimination is a phenomenon with very serious social and economic consequences, which has increased actuality and importance in Bulgaria nowadays. Because of the high price of discrimination, building effective anti-discrimination legislation occupies a special place in the policy of the European Union. Despite the European directives, the presence of anti-discrimination legislation and the broadly declared anti-discrimination inclinations in our country, these are absolutely not enough for providing environment of equality, with a climate of respect and tolerance to the differences. It turns out that certain groups are definitely victims of labor discrimination. In this connection the present article consecutively identifies these groups, as well as the reasons for their discrimination, underlining the necessity and benefits of the integration of the different.

Undergraduate honors students' images of science: Nature of scientific work and scientific knowledge

Science.gov (United States)

Wallace, Michael L.

This exploratory study assessed the influence of an implicit, inquiry-oriented nature of science (NOS) instructional approach undertaken in an interdisciplinary college science course on undergraduate honor students' (UHS) understanding of the aspects of NOS for scientific work and scientific knowledge. In this study, the nature of scientific work concentrated upon the delineation of science from pseudoscience and the value scientists place on reproducibility. The nature of scientific knowledge concentrated upon how UHS view scientific theories and how they believe scientists utilize scientific theories in their research. The 39 UHS who participated in the study were non-science majors enrolled in a Honors College sponsored interdisciplinary science course where the instructors took an implicit NOS instructional approach. An open-ended assessment instrument, the UFO Scenario, was designed for the course and used to assess UHS' images of science at the beginning and end of the semester. The mixed-design study employed both qualitative and quantitative techniques to analyze the open-ended responses. The qualitative techniques of open and axial coding were utilized to find recurring themes within UHS' responses. McNemar's chi-square test for two dependent samples was used to identify whether any statistically significant changes occurred within responses from the beginning to the end of the semester. At the start of the study, the majority of UHS held mixed NOS views, but were able to accurately define what a scientific theory is and explicate how scientists utilize theories within scientific research. Postinstruction assessment indicated that UHS did not make significant gains in their understanding of the nature of scientific work or scientific knowledge and their overall images of science remained static. The results of the present study found implicit NOS instruction even with an extensive inquiry-oriented component was an ineffective approach for modifying UHS

Temporal discrimination, a cervical dystonia endophenotype: penetrance and functional correlates.

Science.gov (United States)

Kimmich, Okka; Molloy, Anna; Whelan, Robert; Williams, Laura; Bradley, David; Balsters, Joshua; Molloy, Fiona; Lynch, Tim; Healy, Daniel G; Walsh, Cathal; O'Riordan, Seán; Reilly, Richard B; Hutchinson, Michael

2014-05-01

The pathogenesis of adult-onset primary dystonia remains poorly understood. There is variable age-related and gender-related expression of the phenotype, the commonest of which is cervical dystonia. Endophenotypes may provide insight into underlying genetic and pathophysiological mechanisms of dystonia. The temporal discrimination threshold (TDT)-the shortest time interval at which two separate stimuli can be detected as being asynchronous-is abnormal both in patients with cervical dystonia and in their unaffected first-degree relatives. Functional magnetic resonance imaging (fMRI) studies have shown that putaminal activation positively correlates with the ease of temporal discrimination between two stimuli in healthy individuals. We hypothesized that abnormal temporal discrimination would exhibit similar age-related and gender-related penetrance as cervical dystonia and that unaffected relatives with an abnormal TDT would have reduced putaminal activation during a temporal discrimination task. TDTs were examined in a group of 192 healthy controls and in 158 unaffected first-degree relatives of 84 patients with cervical dystonia. In 24 unaffected first-degree relatives, fMRI scanning was performed during a temporal discrimination task. The prevalence of abnormal TDTs in unaffected female relatives reached 50% after age 48 years; whereas, in male relatives, penetrance of the endophenotype was reduced. By fMRI, relatives who had abnormal TDTs, compared with relatives who had normal TDTs, had significantly less activation in the putamina and in the middle frontal and precentral gyri. Only the degree of reduction of putaminal activity correlated significantly with worsening of temporal discrimination. These findings further support abnormal temporal discrimination as an endophenotype of cervical dystonia involving disordered basal ganglia circuits. © 2014 International Parkinson and Movement Disorder Society.

Image-based diagnosis of alzheimer-type dementia. Measurements of hippocampal and ventricular areas in MR images

International Nuclear Information System (INIS)

Kodama, Naoki; Shimada, Tetsuo; Fukumoto, Ichiro

2002-01-01

We studied the possibility of objective diagnosis of Alzheimer-type dementia through radiological findings by evaluating cerebral and hippocampal atrophy in magnetic resonance images of patients with dementia. A statistically significant difference was seen in the hippocampus area index (HAI) and the ventricle area index (VAI) of healthy elderly individuals. Discriminant analysis with these two indexes demonstrated a sensitivity of 90.2% and a specificity of 81.8%, with an overall accuracy of 87.7%. Multiple discriminant analysis with VAI and HAI by stage of dementia showed an overall accuracy of 61.6% for discrimination of four stages. These results indicate that quantitative magnetic resonance imaging measurements can be used as an objective diagnostic technique for Alzheimer-type dementia. (author)

Magnetic resonance imaging of the prostate

DEFF Research Database (Denmark)

Iversen, P; Kjaer, L; Thomsen, C

1988-01-01

Magnetic resonance imaging offers new possibilities in investigation of the prostate gland. Current results of imaging and tissue discrimination in the evaluation of prostatic disease are reviewed. Magnetic resonance imaging may be useful in the staging of carcinoma of the prostate....

Simultaneous topography and recognition imaging: physical aspects and optimal imaging conditions

International Nuclear Information System (INIS)

Preiner, Johannes; Ebner, Andreas; Zhu Rong; Hinterdorfer, Peter; Chtcheglova, Lilia

2009-01-01

Simultaneous topography and recognition imaging (TREC) allows for the investigation of receptor distributions on natural biological surfaces under physiological conditions. Based on atomic force microscopy (AFM) in combination with a cantilever tip carrying a ligand molecule, it enables us to sense topography and recognition of receptor molecules simultaneously with nanometre accuracy. In this study we introduce optimized handling conditions and investigate the physical properties of the cantilever-tip-sample ensemble, which is essential for the interpretation of the experimental data gained from this technique. In contrast to conventional AFM methods, TREC is based on a more sophisticated feedback loop, which enables us to discriminate topographical contributions from recognition events in the AFM cantilever motion. The features of this feedback loop were investigated through a detailed analysis of the topography and recognition data obtained on a model protein system. Single avidin molecules immobilized on a mica substrate were imaged with an AFM tip functionalized with a biotinylated IgG. A simple procedure for adjusting the optimal amplitude for TREC imaging is described by exploiting the sharp localization of the TREC signal within a small range of oscillation amplitudes. This procedure can also be used for proving the specificity of the detected receptor-ligand interactions. For understanding and eliminating topographical crosstalk in the recognition images we developed a simple theoretical model, which nicely explains its origin and its dependence on the excitation frequency.

Study on Development of Non-Destructive Measurement Technique for Viability of Lettuce Seed (Lactuca sativa L) Using Hyperspectral Reflectance Imaging

Energy Technology Data Exchange (ETDEWEB)

Ahn, Chi Kook; Cho, Byoung Kwan [College of Agriculture and Life Science, Chungnam National University, Daejeon (Korea, Republic of); Mo, Chang Yeon [National Acadamy of Agricultural Science, Daejeon (Korea, Republic of); Kim, Moon S. [Environmental Microbial and Food Safety Laboratory, Animal and Natural Resources Institute, Agricultural Research Service, United States Department of Agriculture, Washington (United States)

2012-10-15

In this study, the feasibility of hyperspectral reflectance imaging technique was investigated for the discrimination of viable and non-viable lettuce seeds. The spectral data of hyperspectral reflectance images with the spectral range between 750 nm and 1000 nm were used to develop PLS-DA model for the classification of viable and non-viable lettuce seeds. The discrimination accuracy of the calibration set was 81.6% and that of the test set was 81.2%. The image analysis method was developed to construct the discriminant images of non-viable seeds with the developed PLS-DA model. The discrimination accuracy obtained from the resultant image were 91%, which showed the feasibility of hyperspectral reflectance imaging technique for the mass discrimination of non-viable lettuce seeds from viable ones.

Study on Development of Non-Destructive Measurement Technique for Viability of Lettuce Seed (Lactuca sativa L) Using Hyperspectral Reflectance Imaging

International Nuclear Information System (INIS)

Ahn, Chi Kook; Cho, Byoung Kwan; Mo, Chang Yeon; Kim, Moon S.

2012-01-01

In this study, the feasibility of hyperspectral reflectance imaging technique was investigated for the discrimination of viable and non-viable lettuce seeds. The spectral data of hyperspectral reflectance images with the spectral range between 750 nm and 1000 nm were used to develop PLS-DA model for the classification of viable and non-viable lettuce seeds. The discrimination accuracy of the calibration set was 81.6% and that of the test set was 81.2%. The image analysis method was developed to construct the discriminant images of non-viable seeds with the developed PLS-DA model. The discrimination accuracy obtained from the resultant image were 91%, which showed the feasibility of hyperspectral reflectance imaging technique for the mass discrimination of non-viable lettuce seeds from viable ones.

Set discrimination of quantum states

International Nuclear Information System (INIS)

Zhang Shengyu; Ying Mingsheng

2002-01-01

We introduce a notion of set discrimination, which is an interesting extension of quantum state discrimination. A state is secretly chosen from a number of quantum states, which are partitioned into some disjoint sets. A set discrimination is required to identify which set the given state belongs to. Several essential problems are addressed in this paper, including the condition of perfect set discrimination, unambiguous set discrimination, and in the latter case, the efficiency of the discrimination. This generalizes some important results on quantum state discrimination in the literature. A combination of state and set discrimination and the efficiency are also studied

Age and disability employment discrimination: occupational rehabilitation implications.

Science.gov (United States)

Bjelland, Melissa J; Bruyère, Susanne M; von Schrader, Sarah; Houtenville, Andrew J; Ruiz-Quintanilla, Antonio; Webber, Douglas A

2010-12-01

As concerns grow that a thinning labor force due to retirement will lead to worker shortages, it becomes critical to support positive employment outcomes of groups who have been underutilized, specifically older workers and workers with disabilities. Better understanding perceived age and disability discrimination and their intersection can help rehabilitation specialists and employers address challenges expected as a result of the evolving workforce. Using U.S. Equal Employment Opportunity Commission Integrated Mission System data, we investigate the nature of employment discrimination charges that cite the Americans with Disabilities Act or Age Discrimination in Employment Act individually or jointly. We focus on trends in joint filings over time and across categories of age, types of disabilities, and alleged discriminatory behavior. We find that employment discrimination claims that originate from older or disabled workers are concentrated within a subset of issues that include reasonable accommodation, retaliation, and termination. Age-related disabilities are more frequently referenced in joint cases than in the overall pool of ADA filings, while the psychiatric disorders are less often referenced in joint cases. When examining charges made by those protected under both the ADA and ADEA, results from a logit model indicate that in comparison to charges filed under the ADA alone, jointly-filed ADA/ADEA charges are more likely to be filed by older individuals, by those who perceive discrimination in hiring and termination, and to originate from within the smallest firms. In light of these findings, rehabilitation and workplace practices to maximize the hiring and retention of older workers and those with disabilities are discussed.

Discrimination of skin diseases using the multimodal imaging approach

Science.gov (United States)

Vogler, N.; Heuke, S.; Akimov, D.; Latka, I.; Kluschke, F.; Röwert-Huber, H.-J.; Lademann, J.; Dietzek, B.; Popp, J.

2012-06-01

Optical microspectroscopic tools reveal great potential for dermatologic diagnostics in the clinical day-to-day routine. To enhance the diagnostic value of individual nonlinear optical imaging modalities such as coherent anti-Stokes Raman scattering (CARS), second harmonic generation (SHG) or two-photon excited fluorescence (TPF), the approach of multimodal imaging has recently been developed. Here, we present an application of nonlinear optical multimodal imaging with Raman-scattering microscopy to study sizable human-tissue cross-sections. The samples investigated contain both healthy tissue and various skin tumors. This contribution details the rich information content, which can be obtained from the multimodal approach: While CARS microscopy, which - in contrast to spontaneous Raman-scattering microscopy - is not hampered by single-photon excited fluorescence, is used to monitor the lipid and protein distribution in the samples, SHG imaging selectively highlights the distribution of collagen structures within the tissue. This is due to the fact, that SHG is only generated in structures which lack inversion geometry. Finally, TPF reveals the distribution of autofluorophores in tissue. The combination of these techniques, i.e. multimodal imaging, allows for recording chemical images of large area samples and is - as this contribution will highlight - of high clinically diagnostic value.

Discrimination and delusional ideation.

Science.gov (United States)

Janssen, I; Hanssen, M; Bak, M; Bijl, R V; de Graaf, R; Vollebergh, W; McKenzie, K; van Os, J

2003-01-01

In the UK and The Netherlands, people with high rates of psychosis are chronically exposed to discrimination. To test whether perceived discrimination is associated longitudinally with onset of psychosis. A 3-year prospective study of cohorts with no history of psychosis and differential rates of reported discrimination on the basis of age, gender, disability, appearance, skin colour or ethnicity and sexual orientation was conducted in the Dutch general population (n=4076). The main outcome was onset of psychotic symptoms (delusions and hallucinations). The rate of delusional ideation was 0.5% (n=19) in those who did not report discrimination, 0.9% (n=4) in those who reported discrimination in one domain, and 2.7% (n=3) in those who reported discrimination in more than one domain (exact P=0.027). This association remained after adjustment for possible confounders. No association was found between baseline discrimination and onset of hallucinatory experiences. Perceived discrimination may induce delusional ideation and thus contribute to the high observed rates of psychotic disorder in exposed minority populations.

Application of mathematical morphology in discrimination nuclear track images

International Nuclear Information System (INIS)

Zhang Qingxian; Ge Liangquan; Xiao Caijin

2008-01-01

Solid nuclear tracks test is an important and usual method in radioactivity test. But how to divide the overlapped tracks is the key of the processing of digital images of the nuclear tracks. Mathematical Morphology is used in processing of digital images of the nuclear tracks. As a result, the method has been programmed by c++ and used in experiments. It is successful in processing of digital images of the nuclear tracks. (authors)

Perceptions of weight discrimination: prevalence and comparison to race and gender discrimination in America.

Science.gov (United States)

Puhl, R M; Andreyeva, T; Brownell, K D

2008-06-01

Limited data are available on the prevalence and patterns of body weight discrimination from representative samples. This study examined experiences of weight/height discrimination in a nationally representative sample of US adults and compared their prevalence and patterns with discrimination experiences based on race and gender. Data were from the National Survey of Midlife Development in the United States, a 1995-1996 community-based survey of English-speaking adults aged 25-74 (N=2290). Reported experiences of weight/height discrimination included a variety of institutional settings and interpersonal relationships. Multivariate regression analyses were used to predict weight/height discrimination controlling for sociodemographic characteristics and body weight status. The prevalence of weight/height discrimination ranged from 5% among men to 10% among women, but these average percentages obscure the much higher risk of weight discrimination among heavier individuals (40% for adults with body mass index (BMI) of 35 and above). Younger individuals with a higher BMI had a particularly high risk of weight/height discrimination regardless of their race, education and weight status. Women were at greater risk for weight/height discrimination than men, especially women with a BMI of 30-35 who were three times more likely to report weight/height discrimination compared to male peers of a similar weight. Weight/height discrimination is prevalent in American society and is relatively close to reported rates of racial discrimination, particularly among women. Both institutional forms of weight/height discrimination (for example, in employment settings) and interpersonal mistreatment due to weight/height (for example, being called names) were common, and in some cases were even more prevalent than discrimination due to gender and race.

Magnetic resonance imaging of the prostate

DEFF Research Database (Denmark)

Iversen, P; Kjaer, L; Thomsen, C

1987-01-01

Magnetic resonance imaging offers new possibilities in the investigation of the prostate. The current results of imaging and tissue discrimination in the evaluation of prostatic disease are reviewed. Magnetic resonance imaging may be of value in the staging of carcinoma of the prostate....

Place of birth effects on self-reported discrimination: Variations by type of discrimination.

Science.gov (United States)

Brondolo, Elizabeth; Rahim, Reanne; Grimaldi, Stephanie; Ashraf, Amina; Bui, Nini; Schwartz, Joseph

2015-11-01

Researchers have suggested that perceptions of discrimination may vary depending on place of birth and the length of time spent living in the U.S., variables related to acculturation. However, the existing literature provides a mixed picture, with data suggesting that the effects of acculturation on perceptions of discrimination vary by race and other sociodemographic factors. This study evaluated the role of place of birth (POB: defined as U.S.-born vs. foreign-born), age at immigration, and length of residence in the U.S. on self-reported discrimination in a sample of urban-dwelling Asian and Black adults (n= 1454). Analyses examined POB effects on different types of discrimination including race-related stigmatization, exclusion, threat, and workplace discrimination. Sociodemographic variables (including age, gender, employment status and education level) were tested as potential moderators of the relationship between POB and discrimination. The results revealed a significant main effect for POB on discrimination, with U.S.-born individuals reporting significantly more discrimination than foreign-born individuals, although the effect was reduced when sociodemographic variables were controlled. Across the sample, POB effects were seen only for race-related stigmatization and exclusion, not for threat and workplace discrimination. With the exception of limited effects for gender, sociodemographic variables did not moderate these effects. Younger age at immigration and greater years of residence in the U.S. were also positively associated with higher levels of perceived discrimination. These findings suggest increasing acculturation may shape the experience and perception of racial and ethnic discrimination.

Place of birth effects on self-reported discrimination: Variations by type of discrimination

Science.gov (United States)

Brondolo, Elizabeth; Rahim, Reanne; Grimaldi, Stephanie; Ashraf, Amina; Bui, Nini; Schwartz, Joseph

2016-01-01

Researchers have suggested that perceptions of discrimination may vary depending on place of birth and the length of time spent living in the U.S., variables related to acculturation. However, the existing literature provides a mixed picture, with data suggesting that the effects of acculturation on perceptions of discrimination vary by race and other sociodemographic factors. This study evaluated the role of place of birth (POB: defined as U.S.-born vs. foreign-born), age at immigration, and length of residence in the U.S. on self-reported discrimination in a sample of urban-dwelling Asian and Black adults (n= 1454). Analyses examined POB effects on different types of discrimination including race-related stigmatization, exclusion, threat, and workplace discrimination. Sociodemographic variables (including age, gender, employment status and education level) were tested as potential moderators of the relationship between POB and discrimination. The results revealed a significant main effect for POB on discrimination, with U.S.-born individuals reporting significantly more discrimination than foreign-born individuals, although the effect was reduced when sociodemographic variables were controlled. Across the sample, POB effects were seen only for race-related stigmatization and exclusion, not for threat and workplace discrimination. With the exception of limited effects for gender, sociodemographic variables did not moderate these effects. Younger age at immigration and greater years of residence in the U.S. were also positively associated with higher levels of perceived discrimination. These findings suggest increasing acculturation may shape the experience and perception of racial and ethnic discrimination. PMID:27647943

Natural-color and color-infrared image mosaics of the Colorado River corridor in Arizona derived from the May 2009 airborne image collection

Science.gov (United States)

Davis, Philip A.

2013-01-01

The Grand Canyon Monitoring and Research Center (GCMRC) of the U.S. Geological Survey (USGS) periodically collects airborne image data for the Colorado River corridor within Arizona (fig. 1) to allow scientists to study the impacts of Glen Canyon Dam water release on the corridor’s natural and cultural resources. These data are collected from just above Glen Canyon Dam (in Lake Powell) down to the entrance of Lake Mead, for a total distance of 450 kilometers (km) and within a 500-meter (m) swath centered on the river’s mainstem and its seven main tributaries (fig. 1). The most recent airborne data collection in 2009 acquired image data in four wavelength bands (blue, green, red, and near infrared) at a spatial resolution of 20 centimeters (cm). The image collection used the latest model of the Leica ADS40 airborne digital sensor (the SH52), which uses a single optic for all four bands and collects and stores band radiance in 12-bits. Davis (2012) reported on the performance of the SH52 sensor and on the processing steps required to produce the nearly flawless four-band image mosaic (sectioned into map tiles) for the river corridor. The final image mosaic has a total of only 3 km of surface defects in addition to some areas of cloud shadow because of persistent inclement weather during data collection. The 2009 four-band image mosaic is perhaps the best image dataset that exists for the entire Arizona part of the Colorado River. Some analyses of these image mosaics do not require the full 12-bit dynamic range or all four bands of the calibrated image database, in which atmospheric scattering (or haze) had not been removed from the four bands. To provide scientists and the general public with image products that are more useful for visual interpretation, the 12-bit image data were converted to 8-bit natural-color and color-infrared images, which also removed atmospheric scattering within each wavelength-band image. The conversion required an evaluation of the

Discriminant Analysis of Defective and Non-Defective Field Pea (Pisum sativum L.) into Broad Market Grades Based on Digital Image Features.

Science.gov (United States)

McDonald, Linda S; Panozzo, Joseph F; Salisbury, Phillip A; Ford, Rebecca

2016-01-01

Field peas (Pisum sativum L.) are generally traded based on seed appearance, which subjectively defines broad market-grades. In this study, we developed an objective Linear Discriminant Analysis (LDA) model to classify market grades of field peas based on seed colour, shape and size traits extracted from digital images. Seeds were imaged in a high-throughput system consisting of a camera and laser positioned over a conveyor belt. Six colour intensity digital images were captured (under 405, 470, 530, 590, 660 and 850nm light) for each seed, and surface height was measured at each pixel by laser. Colour, shape and size traits were compiled across all seed in each sample to determine the median trait values. Defective and non-defective seed samples were used to calibrate and validate the model. Colour components were sufficient to correctly classify all non-defective seed samples into correct market grades. Defective samples required a combination of colour, shape and size traits to achieve 87% and 77% accuracy in market grade classification of calibration and validation sample-sets respectively. Following these results, we used the same colour, shape and size traits to develop an LDA model which correctly classified over 97% of all validation samples as defective or non-defective.

Words Get in the Way: Linguistic Effects on Talker Discrimination.

Science.gov (United States)

Narayan, Chandan R; Mak, Lorinda; Bialystok, Ellen

2017-07-01

A speech perception experiment provides evidence that the linguistic relationship between words affects the discrimination of their talkers. Listeners discriminated two talkers' voices with various linguistic relationships between their spoken words. Listeners were asked whether two words were spoken by the same person or not. Word pairs varied with respect to the linguistic relationship between the component words, forming either: phonological rhymes, lexical compounds, reversed compounds, or unrelated pairs. The degree of linguistic relationship between the words affected talker discrimination in a graded fashion, revealing biases listeners have regarding the nature of words and the talkers that speak them. These results indicate that listeners expect a talker's words to be linguistically related, and more generally, indexical processing is affected by linguistic information in a top-down fashion even when listeners are not told to attend to it. Copyright © 2016 Cognitive Science Society, Inc.

Infrared laser transillumination CT imaging system using parallel fiber arrays and optical switches for finger joint imaging

Science.gov (United States)

Sasaki, Yoshiaki; Emori, Ryota; Inage, Hiroki; Goto, Masaki; Takahashi, Ryo; Yuasa, Tetsuya; Taniguchi, Hiroshi; Devaraj, Balasigamani; Akatsuka, Takao

2004-05-01

The heterodyne detection technique, on which the coherent detection imaging (CDI) method founds, can discriminate and select very weak, highly directional forward scattered, and coherence retaining photons that emerge from scattering media in spite of their complex and highly scattering nature. That property enables us to reconstruct tomographic images using the same reconstruction technique as that of X-Ray CT, i.e., the filtered backprojection method. Our group had so far developed a transillumination laser CT imaging method based on the CDI method in the visible and near-infrared regions and reconstruction from projections, and reported a variety of tomographic images both in vitro and in vivo of biological objects to demonstrate the effectiveness to biomedical use. Since the previous system was not optimized, it took several hours to obtain a single image. For a practical use, we developed a prototype CDI-based imaging system using parallel fiber array and optical switches to reduce the measurement time significantly. Here, we describe a prototype transillumination laser CT imaging system using fiber-optic based on optical heterodyne detection for early diagnosis of rheumatoid arthritis (RA), by demonstrating the tomographic imaging of acrylic phantom as well as the fundamental imaging properties. We expect that further refinements of the fiber-optic-based laser CT imaging system could lead to a novel and practical diagnostic tool for rheumatoid arthritis and other joint- and bone-related diseases in human finger.

Necrotizing Fasciitis versus Pyomyositis: Discrimination with Using MR Imaging

Energy Technology Data Exchange (ETDEWEB)

Seok, Jee Hyun; Jee, Won Hee; Chun, Kyung Ah; Kim, Ji Young; Jung, Chan Kwon; Kim, Yang Ree; Kim, Yang Soo; Chung, Yang Guk [The Catholic University of Korea, Seoul (Korea, Republic of); Eo, Wan Kyu [KyungHee University, Seoul (Korea, Republic of)

2009-04-15

We wanted to evaluate the MR findings for differentiating between necrotizing fasciitis (NF) and pyomyositis (PM). The MR images of 19 patients with surgically confirmed NF (n = 11) and pathologically confirmed PM (n = 8) were retrospectively reviewed with regard to the presence or absence of any MRI finding criteria that could differentiate between them. The patients with NF had a significantly greater prevalence of the following MR findings (p < 0.05): a peripheral band-like hyperintense signal in muscles on fat-suppressed T2-weighted images (73% of the patients with NF vs. 0% of the patients with PM), peripheral band-like contrast enhancement (CE) of muscles (82% vs. 0%, respectively) and thin smooth enhancement of the deep fascia (82% vs. 13%, respectively). The patients with PM had a significantly greater prevalence of the following MRI findings (p < 0.05): a diffuse hyperintense signal in muscles on fat-suppressed T2-weighted images (27% of the patients with NF vs. 100% in the patients with PM), diffuse CE of muscles (18% vs. 100%, respectively), thick irregular enhancement of the deep fascia (0% vs. 75%, respectively) and intramuscular abscess (0% vs. 88%, respectively). For all patients with NF and PM, the superficial fascia and muscle showed hyperintense signals on T2- weighted images and CE was seen on fat-suppressed CE T1-weighted images. The subcutaneous tissue and deep fascia showed hyperintense signals on T2- weighted images and CE was seen in all the patients with NF and in seven (88%) of the eight patients with PM, respectively. MR imaging is helpful for differentiating between NF and PM.

Necrotizing Fasciitis versus Pyomyositis: Discrimination with Using MR Imaging

International Nuclear Information System (INIS)

Seok, Jee Hyun; Jee, Won Hee; Chun, Kyung Ah; Kim, Ji Young; Jung, Chan Kwon; Kim, Yang Ree; Kim, Yang Soo; Chung, Yang Guk; Eo, Wan Kyu

2009-01-01

We wanted to evaluate the MR findings for differentiating between necrotizing fasciitis (NF) and pyomyositis (PM). The MR images of 19 patients with surgically confirmed NF (n = 11) and pathologically confirmed PM (n = 8) were retrospectively reviewed with regard to the presence or absence of any MRI finding criteria that could differentiate between them. The patients with NF had a significantly greater prevalence of the following MR findings (p < 0.05): a peripheral band-like hyperintense signal in muscles on fat-suppressed T2-weighted images (73% of the patients with NF vs. 0% of the patients with PM), peripheral band-like contrast enhancement (CE) of muscles (82% vs. 0%, respectively) and thin smooth enhancement of the deep fascia (82% vs. 13%, respectively). The patients with PM had a significantly greater prevalence of the following MRI findings (p < 0.05): a diffuse hyperintense signal in muscles on fat-suppressed T2-weighted images (27% of the patients with NF vs. 100% in the patients with PM), diffuse CE of muscles (18% vs. 100%, respectively), thick irregular enhancement of the deep fascia (0% vs. 75%, respectively) and intramuscular abscess (0% vs. 88%, respectively). For all patients with NF and PM, the superficial fascia and muscle showed hyperintense signals on T2- weighted images and CE was seen on fat-suppressed CE T1-weighted images. The subcutaneous tissue and deep fascia showed hyperintense signals on T2- weighted images and CE was seen in all the patients with NF and in seven (88%) of the eight patients with PM, respectively. MR imaging is helpful for differentiating between NF and PM

Microfocus X-ray imaging of Brazil nuts for quality control

Energy Technology Data Exchange (ETDEWEB)

Franco, Margareth Kazuyo Kobayashi Dias, E-mail: mkfranco@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Yokaichiya, Fabiano, E-mail: fabiano.yokaichiya@helmholtz-berlin.de [Department Quantum Phenomena in Novel Materials, Helmholtz Zentrum Berlim für Materialien und Energie GmbH, Berlin (Germany); Kardjilov, Nikolay, E-mail: kardjilov@helmholtz-berlim.de [Institut Angewandte Materialforschung, Helmholtz Zentrum Berlim für Materialien und Energie GmbH, Berlin (Germany); Ferraz, Antonio Carlos de Oliveira, E-mail: carlos@feagri.unicamp.br [Universidade Estadual de Campinas (FEAGRI/UNICAMP), SP (Brazil). Faculdade de Engenharia Agricola

2015-07-15

Non-destructive quality assessment of food prior to processing is desirable in commercial facilities due to its non-invasive nature, for economic reasons and for its safety appeals. Grading Brazil nuts in this way allows for the separation of undesirable nuts to avoid contamination during the automatic nut shelling process. The aim of this study was to evaluate the feasibility of X-ray phase contrast enhanced imaging in assessing nut quality. For this goal, details of the imaging technique are described and phase contrast X-ray and microtomography imaging of nut samples are investigated. Both high quality (i.e. 'sound' nuts as well as treated nuts were examined. It was concluded that both the X-ray imaging and tomography techniques have the potential to discriminate morphological features of the nut and to identify 'sound' kernels from atypical ones. Larger nuts and nuts with a larger gap area between shell and kernel were concluded to have more atypical formations. Both techniques also seemed promising for use in automatic sorting lines. However, by using microtomography, the visualization of finer formations not noticeable in the X-ray images was possible. Further studies shall be carried out to investigate the nature of these formations, how they affect nut quality and their evolution with storage time. (author)

Microfocus X-ray imaging of Brazil nuts for quality control

International Nuclear Information System (INIS)

Franco, Margareth Kazuyo Kobayashi Dias; Yokaichiya, Fabiano; Kardjilov, Nikolay; Ferraz, Antonio Carlos de Oliveira

2015-01-01

Non-destructive quality assessment of food prior to processing is desirable in commercial facilities due to its non-invasive nature, for economic reasons and for its safety appeals. Grading Brazil nuts in this way allows for the separation of undesirable nuts to avoid contamination during the automatic nut shelling process. The aim of this study was to evaluate the feasibility of X-ray phase contrast enhanced imaging in assessing nut quality. For this goal, details of the imaging technique are described and phase contrast X-ray and microtomography imaging of nut samples are investigated. Both high quality (i.e. 'sound' nuts as well as treated nuts were examined. It was concluded that both the X-ray imaging and tomography techniques have the potential to discriminate morphological features of the nut and to identify 'sound' kernels from atypical ones. Larger nuts and nuts with a larger gap area between shell and kernel were concluded to have more atypical formations. Both techniques also seemed promising for use in automatic sorting lines. However, by using microtomography, the visualization of finer formations not noticeable in the X-ray images was possible. Further studies shall be carried out to investigate the nature of these formations, how they affect nut quality and their evolution with storage time. (author)

CubeSat for Natural-Hazard Estimation With Ionospheric Sciences (CNEWS): A Concept Development to Aid Tsunami Early Warning Systems

Science.gov (United States)

Komjathy, A.; Romero-Wolf, A.; Yang, Y. M.; Langley, R. B.; Foster, J. H.

2014-12-01

The Jet Propulsion Laboratory, the University New Brunswick (Canada) and the University of Hawaii have developed a concept to provide open ocean tsunami wave height estimates using very accurate measurements of absolute total electron content (TEC) perturbations. Ionosphere-derived tsunami wave height estimates from our CubeSat for Natural-Hazard Estimation With Ionospheric Sciences (CNEWS) mission will refine the tsunami source energy calculation and improve the tsunami scale calculation for a localized region. As a secondary science objective, transmitting impulsive HF/VHF (10-40 MHz) transmissions through the ionosphere will provide in-situ geomagnetic disturbance measurements, which allow for discrimination between tsunami-induced signatures and space-weather-related fluctuations. NASA has invested several millions of dollars in the development of a tsunami warning system based on geodetic measurements from ground-based GPS stations. Leveraging this investment by simultaneously using ionospheric measurement from this GPS network for the detection of tsunamis represents a significant step forward. GPS ionospheric imaging is limited, however, by the slowly changing satellite geometry and its weak absolute TEC resolution (about 3 TECU). It has also been shown that GPS ionospheric imaging alone cannot distinguish between space weather fluctuations and those due to natural hazards. The very precise ionospheric measurements generated by CNEWS are expected to provide a quasi-static image of tsunami ionospheric signatures that we will use in an advanced model inversion technique to estimate tsunami wave heights at 10 cm (one sigma) uncertainty. The geomagnetic field strength resolution is also a key constraint for discriminating between natural hazards and space weather effects. HF/VHF impulses can resolve absolute TEC measurements at the 0.02 TECU level and geomagnetic field strength may be measured at 50 nT resolution.

Event Discrimination Using Seismoacoustic Catalog Probabilities

Science.gov (United States)

Albert, S.; Arrowsmith, S.; Bowman, D.; Downey, N.; Koch, C.

2017-12-01

Presented here are three seismoacoustic catalogs from various years and locations throughout Utah and New Mexico. To create these catalogs, we combine seismic and acoustic events detected and located using different algorithms. Seismoacoustic events are formed based on similarity of origin time and location. Following seismoacoustic fusion, the data is compared against ground truth events. Each catalog contains events originating from both natural and anthropogenic sources. By creating these seismoacoustic catalogs, we show that the fusion of seismic and acoustic data leads to a better understanding of the nature of individual events. The probability of an event being a surface blast given its presence in each seismoacoustic catalog is quantified. We use these probabilities to discriminate between events from natural and anthropogenic sources. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA-0003525.

Socially-Tolerable Discrimination

OpenAIRE

Amegashie, J. Atsu

2008-01-01

History is replete with overt discrimination on the basis of race, gender, age, citizenship, ethnicity, marital status, academic performance, health status, volume of market transactions, religion, sexual orientation, etc. However, these forms of discrimination are not equally tolerable. For example, discrimination based on immutable or prohibitively unalterable characteristics such as race, gender, or ethnicity is much less acceptable. Why? I develop a simple rent-seeking model of conflict w...

Discrimination of commercial cheeses from fatty acid profiles and phytosterol contents obtained by GC and PCA.

Science.gov (United States)

Kim, Nam Sook; Lee, Ji Hyun; Han, Kyoung Moon; Kim, Ji Won; Cho, Sooyeul; Kim, Jinho

2014-01-15

In this study, a method for discriminating natural mozzarella cheese from cheese substitutes, using fatty acid profiles, phytosterol contents, and statistical comparison, was developed. A total of 27 cheeses were evaluated: eight natural mozzarella cheeses (NMCs), four imitation mozzarella cheeses (IMCs), 12 processed cheeses (PCs) and three mixed cheeses (MCs) composed of NMCs and IMCs. The fatty acid composition of the NMC class was distinct from those of the IMC and MC classes, but statistically similar (pIMCs, but similar (pIMCs, but discrimination between the NMCs and the PCs could not be achieved. Copyright © 2013 Elsevier Ltd. All rights reserved.

Racial/Ethnic Workplace Discrimination

Science.gov (United States)

Chavez, Laura J.; Ornelas, India J.; Lyles, Courtney R.; Williams, Emily C.

2014-01-01

Background Experiences of discrimination are associated with tobacco and alcohol use, and work is a common setting where individuals experience racial/ethnic discrimination. Few studies have evaluated the association between workplace discrimination and these behaviors, and none have described associations across race/ethnicity. Purpose To examine the association between workplace discrimination and tobacco and alcohol use in a large, multistate sample of U.S. adult respondents to the Behavioral Risk Factor Surveillance System survey Reactions to Race Module (2004–2010). Methods Multivariable logistic regression analyses evaluated cross-sectional associations between self-reported workplace discrimination and tobacco (current and daily smoking) and alcohol use (any and heavy use, and binge drinking) among all participants and stratified by race/ethnicity, adjusting for relevant covariates. Data were analyzed in 2013. Results Among respondents, 70,080 completed the workplace discrimination measure. Discrimination was more common among black non-Hispanic (21%), Hispanic (12%), and other race respondents (11%) than white non-Hispanics (4%) (pdiscrimination was associated with current smoking (risk ratio [RR]=1.32, 95% CI=1.19, 1.47), daily smoking (RR=1.41, 95% CI=1.24, 1.61), and heavy drinking (RR=1.11, 95% CI=1.01, 1.22), but not binge or any drinking. Among Hispanics, workplace discrimination was associated with increased heavy and binge drinking, but not any alcohol use or smoking. Workplace discrimination among black non-Hispanics and white Non-Hispanics was associated with increased current and daily smoking, but not alcohol outcomes. Conclusions Workplace discrimination is common, associated with smoking and alcohol use, and merits further policy attention given the impact of these behaviors on morbidity and mortality. PMID:25441232

High content live cell imaging for the discovery of new antimalarial marine natural products

Directory of Open Access Journals (Sweden)

Cervantes Serena

2012-01-01

Full Text Available Abstract Background The human malaria parasite remains a burden in developing nations. It is responsible for up to one million deaths a year, a number that could rise due to increasing multi-drug resistance to all antimalarial drugs currently available. Therefore, there is an urgent need for the discovery of new drug therapies. Recently, our laboratory developed a simple one-step fluorescence-based live cell-imaging assay to integrate the complex biology of the human malaria parasite into drug discovery. Here we used our newly developed live cell-imaging platform to discover novel marine natural products and their cellular phenotypic effects against the most lethal malaria parasite, Plasmodium falciparum. Methods A high content live cell imaging platform was used to screen marine extracts effects on malaria. Parasites were grown in vitro in the presence of extracts, stained with RNA sensitive dye, and imaged at timed intervals with the BD Pathway HT automated confocal microscope. Results Image analysis validated our new methodology at a larger scale level and revealed potential antimalarial activity of selected extracts with a minimal cytotoxic effect on host red blood cells. To further validate our assay, we investigated parasite's phenotypes when incubated with the purified bioactive natural product bromophycolide A. We show that bromophycolide A has a strong and specific morphological effect on parasites, similar to the ones observed from the initial extracts. Conclusion Collectively, our results show that high-content live cell-imaging (HCLCI can be used to screen chemical libraries and identify parasite specific inhibitors with limited host cytotoxic effects. All together we provide new leads for the discovery of novel antimalarials.

High content live cell imaging for the discovery of new antimalarial marine natural products.

Science.gov (United States)

Cervantes, Serena; Stout, Paige E; Prudhomme, Jacques; Engel, Sebastian; Bruton, Matthew; Cervantes, Michael; Carter, David; Tae-Chang, Young; Hay, Mark E; Aalbersberg, William; Kubanek, Julia; Le Roch, Karine G

2012-01-03

The human malaria parasite remains a burden in developing nations. It is responsible for up to one million deaths a year, a number that could rise due to increasing multi-drug resistance to all antimalarial drugs currently available. Therefore, there is an urgent need for the discovery of new drug therapies. Recently, our laboratory developed a simple one-step fluorescence-based live cell-imaging assay to integrate the complex biology of the human malaria parasite into drug discovery. Here we used our newly developed live cell-imaging platform to discover novel marine natural products and their cellular phenotypic effects against the most lethal malaria parasite, Plasmodium falciparum. A high content live cell imaging platform was used to screen marine extracts effects on malaria. Parasites were grown in vitro in the presence of extracts, stained with RNA sensitive dye, and imaged at timed intervals with the BD Pathway HT automated confocal microscope. Image analysis validated our new methodology at a larger scale level and revealed potential antimalarial activity of selected extracts with a minimal cytotoxic effect on host red blood cells. To further validate our assay, we investigated parasite's phenotypes when incubated with the purified bioactive natural product bromophycolide A. We show that bromophycolide A has a strong and specific morphological effect on parasites, similar to the ones observed from the initial extracts. Collectively, our results show that high-content live cell-imaging (HCLCI) can be used to screen chemical libraries and identify parasite specific inhibitors with limited host cytotoxic effects. All together we provide new leads for the discovery of novel antimalarials. © 2011 Cervantes et al; licensee BioMed Central Ltd.

Neutron-gamma discrimination in mixed field by pulse shape discriminator

International Nuclear Information System (INIS)

Sharghi Ido, A.; Shahriari, M.; Etaati, G. R.

2009-01-01

In this study, a pulse shape discriminator, incorporating zero-crossing method has been developed. The separate measurements with 241 Am-Be and 252 Cf sources undertaken by BC501A liquid have shown that the purposed and the common-used pulse shape discriminator's are in good agreement. The improved characteristics of the presented pulse shape discriminator are FOM=1.36 at a threshold of 60 ke Vee and 1.5μsec dead time which allows the count rates up to 50 k Hz

Social behavior and kin discrimination in a mixed group of cloned and non cloned heifers (Bos taurus).

Science.gov (United States)

Coulon, M; Baudoin, C; Abdi, H; Heyman, Y; Deputte, B L

2010-12-01

For more than ten years, reproductive biotechnologies using somatic cell nuclear transfer have made possible the production of cloned animals in various domestic and laboratory species. The influence of the cloning process on offspring characteristics has been studied in various developmental aspects, however, it has not yet been documented in detail for behavioral traits. Behavioral studies of cloned animals have failed to show clear inter-individual differences associated with the cloning process. Preliminary results showed that clones favor each other's company. Preferential social interactions were observed among cloned heifers from the same donor in a mixed herd that also included cloned heifers and control heifers produced by artificial insemination (AI). These results suggest behavioral differences between cloned and non-cloned animals and similarities between clones from the same donor. The aim of the present study was to replicate and to extend these previous results and to study behavioral and cognitive mechanisms of this preferential grouping. We studied a group composed of five cloned heifers derived from the same donor cow, two cloned heifers derived from another donor cow, and AI heifers. Cloned heifers from the same donor were more spatially associated and interacted more between themselves than with heifers derived from another donor or with the AI individuals. This pattern indicates a possible kin discrimination in clones. To study this process, we performed an experiment (using an instrumental conditioning procedure with food reward) of visual discrimination between images of heads of familiar heifers, either related to the subjects or not. The results showed that all subjects (AI and cloned heifers) discriminated between images of familiar cloned heifers produced from the same donor and images of familiar unrelated heifers. Cattle discriminated well between images and used morphological similarities characteristic of cloned related heifers. Our

The Smell of Age: Perception and Discrimination of Body Odors of Different Ages

OpenAIRE

Mitro, Susanna; Gordon, Amy R.; Olsson, Mats J.; Lundström, Johan N.

2012-01-01

Our natural body odor goes through several stages of age-dependent changes in chemical composition as we grow older. Similar changes have been reported for several animal species and are thought to facilitate age discrimination of an individual based on body odors, alone. We sought to determine whether humans are able to discriminate between body odor of humans of different ages. Body odors were sampled from three distinct age groups: Young (20-30 years old), Middle-age (45-55), and Old-age (...

Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep Learning.

Science.gov (United States)

Wang, Jinhua; Yang, Xi; Cai, Hongmin; Tan, Wanchang; Jin, Cangzheng; Li, Li

2016-06-07

Microcalcification is an effective indicator of early breast cancer. To improve the diagnostic accuracy of microcalcifications, this study evaluates the performance of deep learning-based models on large datasets for its discrimination. A semi-automated segmentation method was used to characterize all microcalcifications. A discrimination classifier model was constructed to assess the accuracies of microcalcifications and breast masses, either in isolation or combination, for classifying breast lesions. Performances were compared to benchmark models. Our deep learning model achieved a discriminative accuracy of 87.3% if microcalcifications were characterized alone, compared to 85.8% with a support vector machine. The accuracies were 61.3% for both methods with masses alone and improved to 89.7% and 85.8% after the combined analysis with microcalcifications. Image segmentation with our deep learning model yielded 15, 26 and 41 features for the three scenarios, respectively. Overall, deep learning based on large datasets was superior to standard methods for the discrimination of microcalcifications. Accuracy was increased by adopting a combinatorial approach to detect microcalcifications and masses simultaneously. This may have clinical value for early detection and treatment of breast cancer.

Global diffusion tensor imaging derived metrics differentiate glioblastoma multiforme vs. normal brains by using discriminant analysis: introduction of a novel whole-brain approach.

Science.gov (United States)

Roldan-Valadez, Ernesto; Rios, Camilo; Cortez-Conradis, David; Favila, Rafael; Moreno-Jimenez, Sergio

2014-06-01

Histological behavior of glioblastoma multiforme suggests it would benefit more from a global rather than regional evaluation. A global (whole-brain) calculation of diffusion tensor imaging (DTI) derived tensor metrics offers a valid method to detect the integrity of white matter structures without missing infiltrated brain areas not seen in conventional sequences. In this study we calculated a predictive model of brain infiltration in patients with glioblastoma using global tensor metrics. Retrospective, case and control study; 11 global DTI-derived tensor metrics were calculated in 27 patients with glioblastoma multiforme and 34 controls: mean diffusivity, fractional anisotropy, pure isotropic diffusion, pure anisotropic diffusion, the total magnitude of the diffusion tensor, linear tensor, planar tensor, spherical tensor, relative anisotropy, axial diffusivity and radial diffusivity. The multivariate discriminant analysis of these variables (including age) with a diagnostic test evaluation was performed. The simultaneous analysis of 732 measures from 12 continuous variables in 61 subjects revealed one discriminant model that significantly differentiated normal brains and brains with glioblastoma: Wilks' λ = 0.324, χ(2) (3) = 38.907, p tensor and linear tensor. These metrics might be clinically applied for diagnosis, follow-up, and the study of other neurological diseases.

Blood-specific isotopic discrimination factors in the Magellanic penguin (Spheniscus magellanicus).

Science.gov (United States)

Ciancio, Javier E; Righi, Carina; Faiella, Adrián; Frere, Esteban

2016-08-30

The use of stable isotopes for ecological studies has increased exponentially in recent years. Isotopic trophic studies are based on the assumption that animals are what they eat plus a discrimination factor. The discrimination factor is affected by many variables and can be determined empirically. The Magellanic penguin is a highly abundant marine bird that plays a key role in the southern oceans. This study provides the first estimation of the Magellanic penguin blood discrimination factor for (13) C and (15) N. A two and a half month feeding experiment was performed, in which ten captive penguins were fed their main natural prey (anchovy Engraulis anchoita). The discrimination factors were estimated by comparing anchovy δ(13) C and δ(15) N values (obtained with isotope ratio mass spectrometry using lipid-extracted and bulk anchovy muscle) with penguin blood δ(13) C and δ(15) N values. Penguin blood was shown to be enriched, compared with anchovies, for (13) C and (15) N. No changes were observed in the stable isotope ratios of anchovies and discrimination factors during the experiment. The overall discrimination factors were 0.93 ± 0.12 (bulk) and 0.41 ± 0.12 (lipid-free) for (13) C; and 2.81 ± 0.17 (bulk) and 2.31 ± 0.17 (lipid-free) for (15) N. Having an accurate discrimination factor for the studied species is key in any trophic or food web isotopic study. Comparisons of estimated diet-to-blood discrimination factors with published values of aquatic piscivore birds showed that the (13) C discrimination factor is particularly variable, and therefore ecologists should be cautious when using a surrogate value from other species. In this study, the Magellanic penguin discrimination factor of a tissue that does not require euthanasia was obtained, a fundamental input for trophic isotopic modeling of the species. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Implementing Natural Resources Cadastral Plan in Pasargadae District of Iran by Using Quick Bird Images

Science.gov (United States)

Azhdari, G. H.; Deilami, K.; Firooznia, E.

2015-12-01

Natural Resources are essential for security and sustainable development of each country. Therefore, in order to reach sustainable development, conservation as well as optimum utilization of natural resources, executing of natural resources cadastral plan is necessary and essential. Governments conduct lands management in Iran, so there is a need for comprehensive plan with arranged program for best evaluation. In this research as a pilot, Pasargadae city is opted. Pasargadae region is located in north-east of Shiraz in Fars province with Latitude and longitude of 30° 15 ´ 53 ° N and 53° 13 ´ 29 ° E respectively. In order to generate the cadastral maps, Firstly, images from QuickBird satellite with 50-60 centimeters resolution were georeferenced by utilizing ground control points with accurate GPS coordinates. In addition to satellite images, old paper maps with 1:10000 scale in local coordinate system from agriculture ministry in 1963 were digitized according to 1:25000 scale map from army geographical organization with AutoCad software. Beside, paper maps with 1:50000 scale and Google Earth were used to find the changes during time. All the above maps were added to QuickBird images as new layers by using ArcMap software. These maps also were utilized to determine the different land-uses. Thus, by employing ArcMap software lands divide into 2 groups: firstly, lands with official document, which is owned by either natural or legal persons, and secondly national lands under different uses such as forestry, range management and desertification plans. Consequently, the generation of cadastral maps leads to better difference between private and national lands. In addition, producing cadastral maps prevent the destruction and illegal possession of natural lands by individuals.

Discriminative and predictive validity of the scoliosis research society-22 questionnaire in management and curve-severity subgroups of adolescents with idiopathic scoliosis.

Science.gov (United States)

Parent, Eric C; Hill, Doug; Mahood, Jim; Moreau, Marc; Raso, Jim; Lou, Edmond

2009-10-15

Prospective cross-sectional measurement study. To determine the ability of the Scoliosis Research Society (SRS)-22 questionnaire to discriminate among management and scoliosis severity subgroups and to correlate with internal and external measures of curve severity. In earlier studies of the SRS-22 discriminative ability, age was not a controlled factor. The ability of the SRS-22 to predict curve severity has not been thoroughly examined. The SRS-22 was completed by 227 females with adolescent idiopathic scoliosis. Using Analysis of covariance analyses controlling for age, the SRS-22 scores were compared among management subgroups (observation, brace, presurgery, and postsurgery) and curve-severity subgroups (in nonoperated subjects: Cobb angles of 50 degrees). A stepwise discriminant analysis was used to identify the SRS-22 domains most discriminative for curve-severity categories. Correlation between SRS-22 scores and radiographic or surface topography measurements was used to determine the predictive ability of the questionnaire. Pain was better for subjects treated with braces than for those planning surgery. Self-image was better for subjects under observation or postsurgery than for those planning surgery. Satisfaction was better for the brace and postsurgery subgroups than for the observation or presurgery subgroups. Statistically significant mean differences between subgroups were all larger than 0.5, which is within the range of minimal clinically important differences recommended for each of the 5-point SRS-22 domain scoring scales. Pain and mental health were worse for those with Cobb angles of >50 degrees than with Cobb angles of 30 degrees to 50 degrees. Self-image and total scores were worse for those with Cobb angles of >50 degrees than both other subgroups. Using discriminant analysis, self-image was the only SRS-22 domain score selected to classify subjects within curve severity subgroups. The percentage of patients accurately classified was 54

Using hyperspectral imaging technology to identify diseased tomato leaves

Science.gov (United States)

Li, Cuiling; Wang, Xiu; Zhao, Xueguan; Meng, Zhijun; Zou, Wei

2016-11-01

In the process of tomato plants growth, due to the effect of plants genetic factors, poor environment factors, or disoperation of parasites, there will generate a series of unusual symptoms on tomato plants from physiology, organization structure and external form, as a result, they cannot grow normally, and further to influence the tomato yield and economic benefits. Hyperspectral image usually has high spectral resolution, not only contains spectral information, but also contains the image information, so this study adopted hyperspectral imaging technology to identify diseased tomato leaves, and developed a simple hyperspectral imaging system, including a halogen lamp light source unit, a hyperspectral image acquisition unit and a data processing unit. Spectrometer detection wavelength ranged from 400nm to 1000nm. After hyperspectral images of tomato leaves being captured, it was needed to calibrate hyperspectral images. This research used spectrum angle matching method and spectral red edge parameters discriminant method respectively to identify diseased tomato leaves. Using spectral red edge parameters discriminant method produced higher recognition accuracy, the accuracy was higher than 90%. Research results have shown that using hyperspectral imaging technology to identify diseased tomato leaves is feasible, and provides the discriminant basis for subsequent disease control of tomato plants.

DISCRIMINATION OF WOMEN IN THE LABOUR MARKET OF SR AND MODELS OF DISCRIMINATION

OpenAIRE

Ján Vravec; Radovan Baèík

2012-01-01

IThe paper deals with the problem of women’s discrimination in the labour market. Significant differences, among women and men in the labour market, are especially in unemployment rate in reward system, and high horizontal and vertical segregation of women. The aspects of discrimination arise despite of existing legislation, which gender discrimination strictly prohibits. An analysis of arguments, consequences and models of women’s discrimination in the labour market can significantly help to...

Nature, Origin and Transfers of SPM (Mineral, Organic, and Biological) in Hydrosystems : a New Methodological Approach by Morphogranulometry

Science.gov (United States)

Viennet, D.; Fournier, M.; Copard, Y.; Dupont, J. P.

2017-12-01

Source to sink is one of the main concepts in Earth Sciences for a better knowledge of hydrosystems dynamics. Regarding this issue, the present day challenge consists in the characterization by in-situ measurements of the nature and the origin of suspended particles matters (SPM). Few methods can fully cover such requirements and among them, the methodology using the form of particles deserves to be developed. Indeed, morphometry of particles is widely used in sedimentology to identify different sedimentary stocks, source-to-sink transport and sedimentation mechanisms. Currently, morphometry analyses are carried out by scanning electron microscope coupled to image analysis to measure various size and shape descriptors on particles like flatness, elongation, circularity, sphericity, bluntness, fractal dimension. However, complexity and time of analysis are the main limitations of this technique for a long-term monitoring of SPM transfers. Here we present an experimental morphometric approach using a morphogranulometer (a CCD camera coupled to a peristaltic pump). The camera takes pictures while the sample is circulating through a flow cell, leading to the analysis of numerous particles in a short time. The image analysis provides size and shape information discriminating various particles stocks according to their nature and origin by statistical analyses. Measurements were carried out on standard samples of particles commonly found in natural waters. The size and morphological distributions of the different mineral fractions (clay, sand, oxides etc), biologic (microalgae, pollen, etc) and organic (peat, coal, soil organic matter, etc) samples are statistically independent and can be discriminated on a 4D graph. Next step will be on field in situ measurements in a sink-spring network to understand the transfers of the particles stocks inside this simple karstic network. Such a development would be promising for the characterisation of natural hydrosystems.

Quantum-state discrimination

International Nuclear Information System (INIS)

Roa, Luis; Retamal, Juan Carlos; Saavedra, Carlos

2002-01-01

A proposal for a physical implementation of a quantum-state discrimination protocol using an ion in a linear trap is studied, where two nonorthogonal quantum states are codified using two electronic states of the ion. In addition, a protocol is given for discriminating superpositions of nonorthogonal entangled states between ions inside widely separated optical cavities. The discrimination protocol is extended to the case of N linearly independent nonorthogonal quantum states lying in a space of 2N-1 dimensions

Advanced signal processing analysis of laser-induced breakdown spectroscopy data for the discrimination of obsidian sources.

Science.gov (United States)

Remus, Jeremiah J; Harmon, Russell S; Hark, Richard R; Haverstock, Gregory; Baron, Dirk; Potter, Ian K; Bristol, Samantha K; East, Lucille J

2012-03-01

Obsidian is a natural glass of volcanic origin and a primary resource used by indigenous peoples across North America for making tools. Geochemical studies of obsidian enhance understanding of artifact production and procurement and remain a priority activity within the archaeological community. Laser-induced breakdown spectroscopy (LIBS) is an analytical technique being examined as a means for identifying obsidian from different sources on the basis of its 'geochemical fingerprint'. This study tested whether two major California obsidian centers could be distinguished from other obsidian localities and the extent to which subsources could be recognized within each of these centers. LIBS data sets were collected in two different spectral bands (350±130 nm and 690±115 nm) using a Nd:YAG 1064 nm laser operated at ~23 mJ, a Czerny-Turner spectrograph with 0.2-0.3 nm spectral resolution and a high performance imaging charge couple device (ICCD) detector. Classification of the samples was performed using partial least-squares discriminant analysis (PLSDA), a common chemometric technique for performing statistical regression on high-dimensional data. Discrimination of samples from the Coso Volcanic Field, Bodie Hills, and other major obsidian areas in north-central California was possible with an accuracy of greater than 90% using either spectral band. © 2012 Optical Society of America

Perceived discrimination: why applicants and employees expect and perceive discrimination

NARCIS (Netherlands)

Abu Ghazaleh, N.

2012-01-01

In this dissertation we have investigated perceptions of discrimination. We have shown discrimination exists in the eyes of applicants and employees and especially when from an ethnic minority group. There are psychological variables that influence these perceptions differently for minority and

Application of Phase Congruency for Discriminating Some Lung Diseases Using Chest Radiograph

Directory of Open Access Journals (Sweden)

Omar Mohd Rijal

2015-01-01

Full Text Available A novel procedure using phase congruency is proposed for discriminating some lung disease using chest radiograph. Phase congruency provides information about transitions between adjacent pixels. Abrupt changes of phase congruency values between pixels may suggest a possible boundary or another feature that may be used for discrimination. This property of phase congruency may have potential for deciding between disease present and disease absent where the regions of infection on the images have no obvious shape, size, or configuration. Five texture measures calculated from phase congruency and Gabor were shown to be normally distributed. This gave good indicators of discrimination errors in the form of the probability of Type I Error (δ and the probability of Type II Error (β. However, since 1 −  δ is the true positive fraction (TPF and β is the false positive fraction (FPF, an ROC analysis was used to decide on the choice of texture measures. Given that features are normally distributed, for the discrimination between disease present and disease absent, energy, contrast, and homogeneity from phase congruency gave better results compared to those using Gabor. Similarly, for the more difficult problem of discriminating lobar pneumonia and lung cancer, entropy and homogeneity from phase congruency gave better results relative to Gabor.

Comparing gender discrimination and inequality in indie and traditional publishing.

Science.gov (United States)

Weinberg, Dana B; Kapelner, Adam

2018-01-01

In traditional publishing, female authors' titles command nearly half (45%) the price of male authors' and are underrepresented in more prestigious genres, and books are published by publishing houses, which determined whose books get published, subject classification, and retail price. In the last decade, the growth of digital technologies and sales platforms have enabled unprecedented numbers of authors to bypass publishers to publish and sell books. The rise of indie publishing (aka self-publishing) reflects the growth of the "gig" economy, where the influence of firms has diminished and workers are exposed more directly to external markets. Encompassing the traditional and the gig economy, the book industry illuminates how the gig economy may disrupt, replicate, or transform the gender discrimination mechanisms and inequality found in the traditional economy. In a natural experiment spanning from 2002 to 2012 and including over two million book titles, we compare discrimination mechanisms and inequality in indie and traditional publishing. We find that indie publishing, though more egalitarian, largely replicates traditional publishing's gender discrimination patterns, showing an unequal distribution of male and female authors by genre (allocative discrimination), devaluation of genres written predominantly by female authors (valuative discrimination), and lower prices within genres for books by female authors (within-job discrimination). However, these discrimination mechanisms are associated with far less price inequality in indie, only 7%, in large part due to the smaller and lower range of prices in indie publishing compared to traditional publishing. We conclude that, with greater freedom, workers in the gig economy may be inclined to greater equality but will largely replicate existing labor market segmentation and the lower valuation of female-typical work and of female workers. Nonetheless, price setting for work may be more similar for workers in the

Cancer, comorbidity and workplace discrimination: The US experience.

Science.gov (United States)

Gehrke, Amanda K; Feuerstein, Michael

2017-09-01

Cancer survivors with comorbidities have more work-related challenges than cancer survivors without these other health problems. This study evaluated how these cancer survivors with comorbidities are faring under a newly revised workplace discrimination policy, which better accounts for the episodic nature of chronic illnesses. The sample included 18-64 year olds with a history of cancer who filed allegations of workplace discrimination in 2009-2011 (N = 1.291) in the US. Multivariable logistic regressions were used. Cancer survivors with comorbidities were more likely to file discrimination claims related to the terms of their employment (OR = 1.37, 95% CI = 1.04-1.80) than cancer survivors without comorbidities. Terms of employment-related claims were more likely to be ruled in favour of cancer survivors (versus employers), regardless of comorbidity status (OR = 1.44, 95% CI = 1.06-1.96). Despite this policy reform, alleged discrimination related to terms of employment existed at higher rates in cancer survivors with concurrent health problems. If employment is a goal in this high-risk group, replication of findings in other countries, studies on potential mechanisms and development of innovative interventions in these higher risk cases are warranted. Efforts should be made to mitigate the impact of these comorbid health problems on work-related function. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Semi-Supervised Tensor-Based Graph Embedding Learning and Its Application to Visual Discriminant Tracking.

Science.gov (United States)

Hu, Weiming; Gao, Jin; Xing, Junliang; Zhang, Chao; Maybank, Stephen

2017-01-01

An appearance model adaptable to changes in object appearance is critical in visual object tracking. In this paper, we treat an image patch as a two-order tensor which preserves the original image structure. We design two graphs for characterizing the intrinsic local geometrical structure of the tensor samples of the object and the background. Graph embedding is used to reduce the dimensions of the tensors while preserving the structure of the graphs. Then, a discriminant embedding space is constructed. We prove two propositions for finding the transformation matrices which are used to map the original tensor samples to the tensor-based graph embedding space. In order to encode more discriminant information in the embedding space, we propose a transfer-learning- based semi-supervised strategy to iteratively adjust the embedding space into which discriminative information obtained from earlier times is transferred. We apply the proposed semi-supervised tensor-based graph embedding learning algorithm to visual tracking. The new tracking algorithm captures an object's appearance characteristics during tracking and uses a particle filter to estimate the optimal object state. Experimental results on the CVPR 2013 benchmark dataset demonstrate the effectiveness of the proposed tracking algorithm.

The Badness of Discrimination

DEFF Research Database (Denmark)

Lippert-Rasmussen, Kasper

2006-01-01

. In this paper I address these issues. First, I offer a taxonomy of discrimination. I then argue that discrimination is bad, when it is, because it harms people. Finally, I criticize a rival, disrespect-based account according to which discrimination is bad regardless of whether it causes harm....

Exposure to Discrimination and Heart Rate Variability Reactivity to Acute Stress among Women with Diabetes.

Science.gov (United States)

Wagner, Julie; Lampert, Rachel; Tennen, Howard; Feinn, Richard

2015-08-01

Exposure to racial discrimination has been linked to physiological reactivity. This study investigated self-reported exposure to racial discrimination and parasympathetic [high-frequency heart rate variability (HF-HRV)] and sympathetic (norepinephrine and cortisol) activity at baseline and then again after acute laboratory stress. Lifetime exposure to racial discrimination was measured with the Schedule of Racist Events scale. Thirty-two women (16 Black and 16 White) with type 2 diabetes performed a public speaking stressor. Beat-to-beat intervals were recorded on electrocardiograph recorders, and HF-HRV was calculated using spectral analysis and natural log transformed. Norepinephrine and cortisol were measured in blood. Higher discrimination predicted lower stressor HF-HRV, even after controlling for baseline HF-HRV. When race, age, A1c and baseline systolic blood pressure were also controlled, racial discrimination remained a significant independent predictor of stressor HF-HRV. There was no association between lifetime discrimination and sympathetic markers. In conclusion, preliminary data suggest that among women with type 2 diabetes mellitus (T2DM), exposure to racial discrimination is adversely associated with parasympathetic, but not sympathetic, reactivity. Copyright © 2013 John Wiley & Sons, Ltd.

Distinguishing mixed quantum states: Minimum-error discrimination versus optimum unambiguous discrimination

International Nuclear Information System (INIS)

Herzog, Ulrike; Bergou, Janos A.

2004-01-01

We consider two different optimized measurement strategies for the discrimination of nonorthogonal quantum states. The first is ambiguous discrimination with a minimum probability of inferring an erroneous result, and the second is unambiguous, i.e., error-free, discrimination with a minimum probability of getting an inconclusive outcome, where the measurement fails to give a definite answer. For distinguishing between two mixed quantum states, we investigate the relation between the minimum-error probability achievable in ambiguous discrimination, and the minimum failure probability that can be reached in unambiguous discrimination of the same two states. The latter turns out to be at least twice as large as the former for any two given states. As an example, we treat the case where the state of the quantum system is known to be, with arbitrary prior probability, either a given pure state, or a uniform statistical mixture of any number of mutually orthogonal states. For this case we derive an analytical result for the minimum probability of error and perform a quantitative comparison with the minimum failure probability

Visual feature discrimination versus compression ratio for polygonal shape descriptors

Science.gov (United States)

Heuer, Joerg; Sanahuja, Francesc; Kaup, Andre

2000-10-01

In the last decade several methods for low level indexing of visual features appeared. Most often these were evaluated with respect to their discrimination power using measures like precision and recall. Accordingly, the targeted application was indexing of visual data within databases. During the standardization process of MPEG-7 the view on indexing of visual data changed, taking also communication aspects into account where coding efficiency is important. Even if the descriptors used for indexing are small compared to the size of images, it is recognized that there can be several descriptors linked to an image, characterizing different features and regions. Beside the importance of a small memory footprint for the transmission of the descriptor and the memory footprint in a database, eventually the search and filtering can be sped up by reducing the dimensionality of the descriptor if the metric of the matching can be adjusted. Based on a polygon shape descriptor presented for MPEG-7 this paper compares the discrimination power versus memory consumption of the descriptor. Different methods based on quantization are presented and their effect on the retrieval performance are measured. Finally an optimized computation of the descriptor is presented.

Mass discrimination

Energy Technology Data Exchange (ETDEWEB)

Broeckman, A. [Rijksuniversiteit Utrecht (Netherlands)

1978-12-15

In thermal ionization mass spectrometry the phenomenon of mass discrimination has led to the use of a correction factor for isotope ratio-measurements. The correction factor is defined as the measured ratio divided by the true or accepted value of this ratio. In fact this factor corrects for systematic errors of the whole procedure; however mass discrimination is often associated just with the mass spectrometer.

Salient Region Detection via Feature Combination and Discriminative Classifier

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Deming Kong

2015-01-01

Full Text Available We introduce a novel approach to detect salient regions of an image via feature combination and discriminative classifier. Our method, which is based on hierarchical image abstraction, uses the logistic regression approach to map the regional feature vector to a saliency score. Four saliency cues are used in our approach, including color contrast in a global context, center-boundary priors, spatially compact color distribution, and objectness, which is as an atomic feature of segmented region in the image. By mapping a four-dimensional regional feature to fifteen-dimensional feature vector, we can linearly separate the salient regions from the clustered background by finding an optimal linear combination of feature coefficients in the fifteen-dimensional feature space and finally fuse the saliency maps across multiple levels. Furthermore, we introduce the weighted salient image center into our saliency analysis task. Extensive experiments on two large benchmark datasets show that the proposed approach achieves the best performance over several state-of-the-art approaches.

MARS spectral molecular imaging of lamb tissue: data collection and image analysis

CERN Document Server

Aamir, R; Bateman, C.J.; Butler, A.P.H.; Butler, P.H.; Anderson, N.G.; Bell, S.T.; Panta, R.K.; Healy, J.L.; Mohr, J.L.; Rajendran, K.; Walsh, M.F.; Ruiter, N.de; Gieseg, S.P.; Woodfield, T.; Renaud, P.F.; Brooke, L.; Abdul-Majid, S.; Clyne, M.; Glendenning, R.; Bones, P.J.; Billinghurst, M.; Bartneck, C.; Mandalika, H.; Grasset, R.; Schleich, N.; Scott, N.; Nik, S.J.; Opie, A.; Janmale, T.; Tang, D.N.; Kim, D.; Doesburg, R.M.; Zainon, R.; Ronaldson, J.P.; Cook, N.J.; Smithies, D.J.; Hodge, K.

2014-01-01

Spectral molecular imaging is a new imaging technique able to discriminate and quantify different components of tissue simultaneously at high spatial and high energy resolution. Our MARS scanner is an x-ray based small animal CT system designed to be used in the diagnostic energy range (20 to 140 keV). In this paper, we demonstrate the use of the MARS scanner, equipped with the Medipix3RX spectroscopic photon-processing detector, to discriminate fat, calcium, and water in tissue. We present data collected from a sample of lamb meat including bone as an illustrative example of human tissue imaging. The data is analyzed using our 3D Algebraic Reconstruction Algorithm (MARS-ART) and by material decomposition based on a constrained linear least squares algorithm. The results presented here clearly show the quantification of lipid-like, water-like and bone-like components of tissue. However, it is also clear to us that better algorithms could extract more information of clinical interest from our data. Because we ...

Ethnic identity, racial discrimination and attenuated psychotic symptoms in an urban population of emerging adults.

Science.gov (United States)

Anglin, Deidre M; Lui, Florence; Espinosa, Adriana; Tikhonov, Aleksandr; Ellman, Lauren

2018-06-01

Studies suggest strong ethnic identity generally protects against negative mental health outcomes associated with racial discrimination. In light of evidence suggesting racial discrimination may enhance psychosis risk in racial and ethnic minority (REM) populations, the present study explored the relationship between ethnic identity and attenuated positive psychotic symptoms (APPS) and whether ethnic identity moderates the association between racial discrimination and these symptoms. A sample of 644 non-help-seeking REM emerging adults was administered self-report inventories for psychosis risk, experiences of discrimination and ethnic identity. Latent class analysis was applied to determine the nature and number of ethnic identity types in this population. The direct association between ethnic identity and APPS and the interaction between ethnic identity and racial discrimination on APPS were determined in linear regression analyses. Results indicated three ethnic identity classes (very low, moderate to high and very high). Ethnic identity was not directly related to APPS; however, it was related to APPS under racially discriminating conditions. Specifically, participants who experienced discrimination in the moderate to high or very high ethnic identity classes reported fewer symptoms than participants who experienced discrimination in the very low ethnic identity class. Strong ethnic group affiliation and connection may serve a protective function for psychosis risk in racially discriminating environments and contexts among REM young adults. The possible social benefits of strong ethnic identification among REM youth who face racial discrimination should be explored further in clinical high-risk studies. © 2016 John Wiley & Sons Australia, Ltd.

Perceptions of genetic discrimination among people at risk for Huntington's disease: a cross sectional survey.

Science.gov (United States)

Bombard, Yvonne; Veenstra, Gerry; Friedman, Jan M; Creighton, Susan; Currie, Lauren; Paulsen, Jane S; Bottorff, Joan L; Hayden, Michael R

2009-06-09

To assess the nature and prevalence of genetic discrimination experienced by people at risk for Huntington's disease who had undergone genetic testing or remained untested. Cross sectional, self reported survey. Seven genetics and movement disorders clinics servicing rural and urban communities in Canada. 233 genetically tested and untested asymptomatic people at risk for Huntington's disease (response rate 80%): 167 underwent testing (83 had the Huntington's disease mutation, 84 did not) and 66 chose not to be tested. Self reported experiences of genetic discrimination and related psychological distress based on family history or genetic test results. Discrimination was reported by 93 respondents (39.9%). Reported experiences occurred most often in insurance (29.2%), family (15.5%), and social (12.4%) settings. There were few reports of discrimination in employment (6.9%), health care (8.6%), or public sector settings (3.9%). Although respondents who were aware that they carried the Huntington's disease mutation reported the highest levels of discrimination, participation in genetic testing was not associated with increased levels of genetic discrimination. Family history of Huntington's disease, rather than the result of genetic testing, was the main reason given for experiences of genetic discrimination. Psychological distress was associated with genetic discrimination (PGenetic discrimination was commonly reported by people at risk for Huntington's disease and was a source of psychological distress. Family history, and not genetic testing, was the major reason for genetic discrimination.

Gender-Based Discrimination In Nursing: A Ghanaian

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DF Ofori

2007-12-01

Full Text Available Purpose and objectives: The 'glass escalator' phenomenon holds that men in female dominated professions like nursing can rise quickly to the top. However, they can also suffer discrimination. This phenomenon is widely recognised in advanced countries. Trained, mostly female nurses have been leaving Ghana in droves for greener pastures abroad, particularly the US and UK, with serious consequences on the health delivery service in Ghana. Conversely, increasing numbers of males are joining the nursing profession. It examines whether male nurses in Ghana enjoy any hidden advantages, and if so, what makes the men successful (even with their limited numbers in a women-dominated field and what the implications are for both male and female nurses. Problem investigated: The article explores gender-based discrimination and the phenomenon of the glass escalator in a developing country context. It examines the position of male nurses in Ghana; the type, nature and extent of advantages they enjoy and any discrimination they face in a female-dominated field. Methodology: An in-depth cross-sectional questionnaire was employed. A thematic and cluster analysis of findings was executed, with data captured using Statistical Package for Social Sciences (SPSS. A combination of descriptive accounts as well as summary statistics using chi-square and correlations was used to examine the findings. Findings and implications: This paper reports the findings of an empirical study that show that male nurses neither suffer gender-based discrimination nor occupy the top positions in the nursing field. It also found that a majority of males do not want to leave the profession even though they feel they are assigned more responsibilities and are sometimes passed over for promotion. Originality: Whilst representing a modest contribution to research in gender-based discrimination in nursing, this paper is a first attempt to investigate the phenomenon in a Ghanaian context, with

Neuronal discrimination capacity

International Nuclear Information System (INIS)

Deng Yingchun; Williams, Peter; Feng Jianfeng; Liu Feng

2003-01-01

We explore neuronal mechanisms of discriminating between masked signals. It is found that when the correlation between input signals is zero, the output signals are separable if and only if input signals are separable. With positively (negatively) correlated signals, the output signals are separable (mixed) even when input signals are mixed (separable). Exact values of discrimination capacity are obtained for two most interesting cases: the exactly balanced inhibitory and excitatory input case and the uncorrelated input case. Interestingly, the discrimination capacity obtained in these cases is independent of model parameters, input distribution and is universal. Our results also suggest a functional role of inhibitory inputs and correlated inputs or, more generally, the large variability of efferent spike trains observed in in vivo experiments: the larger the variability of efferent spike trains, the easier it is to discriminate between masked input signals

Neuronal discrimination capacity

Energy Technology Data Exchange (ETDEWEB)

Deng Yingchun [Department of Mathematics, Hunan Normal University 410081, Changsha (China); COGS, University of Sussex at Brighton, BN1 9QH (United Kingdom); Williams, Peter; Feng Jianfeng [COGS, University of Sussex at Brighton, BN1 9QH (United Kingdom); Liu Feng [COGS, University of Sussex at Brighton, BN1 9QH (United Kingdom); Physics Department, Nanjing University (China)

2003-12-19

We explore neuronal mechanisms of discriminating between masked signals. It is found that when the correlation between input signals is zero, the output signals are separable if and only if input signals are separable. With positively (negatively) correlated signals, the output signals are separable (mixed) even when input signals are mixed (separable). Exact values of discrimination capacity are obtained for two most interesting cases: the exactly balanced inhibitory and excitatory input case and the uncorrelated input case. Interestingly, the discrimination capacity obtained in these cases is independent of model parameters, input distribution and is universal. Our results also suggest a functional role of inhibitory inputs and correlated inputs or, more generally, the large variability of efferent spike trains observed in in vivo experiments: the larger the variability of efferent spike trains, the easier it is to discriminate between masked input signals.

Workplace discrimination: experiences of practicing physicians.

Science.gov (United States)

Coombs, Alice A Tolbert; King, Roderick K

2005-04-01

In response to a growing concern regarding physician discrimination in the workplace, this study was developed to: (1) describe the types of discrimination that exist for the practicing physician and (2) determine which groups of physicians are more likely to experience the various forms of discrimination. Surveys were mailed to 1930 practicing physicians in Massachusetts. Participants were asked if they had encountered discrimination, how significant the discrimination was against a specific group, the frequency of personal discrimination, and the type of discrimination. Factor analysis identified four types of discrimination: career advancement, punitive behaviors, practice barriers and hiring barriers. A total of 445 responses were received (a 24% response rate). Sixty-three percent of responding physicians had experienced some form of discrimination. Respondents were women (46%), racial/ethnic minorities (42%) and international medical graduates (IMGs) (40%). In addition, 26% of those classified as white were also IMGs. Over 60% of respondents believed discrimination against IMGs was very or somewhat significant. Almost 27% of males acknowledged that gender bias against females was very or somewhat significant. IMGs were more likely to indicate that discrimination against IMGs was significant in their current organization. Of U.S. medical graduates (USMGs) 44% reported that discrimination against IMGs in their current organization was significant. Nonwhites were more likely to report that discrimination based on race/ethnicity was significant. Nearly 29% of white respondents also believed that such discrimination was very or somewhat significant. Physicians practicing in academic, research, and private practice sectors experience discrimination based on gender, ethnic/racial, and IMG status.

MR imaging of prostate. Preliminary experience with calculated imaging in 28 cases

International Nuclear Information System (INIS)

Gevenois, P.A.; Van Regemorter, G.; Ghysels, M.; Delepaut, A.; Van Gansbeke, D.; Struyven, J.

1988-01-01

The majority of studies with MR imaging in prostate disease are based on a semiology obtained using images weighted in T1 and T2. A study was carried out to evaluate effects of images calculated in T1 and T2 obtained at 0.5T. This preliminary study concerns 28 prostate examinations with spin-echo acquisition and inversion-recuperation parameters, and provided images calculated in T1, weighted and calculated in T2. Images allowed detection and characterization of prostate lesions. However, although calculated images accentuate discrimination of the method, the weighted images conserve their place because of their improved spatial resolution [fr

From discrimination to internalized mental illness stigma: The mediating roles of anticipated discrimination and anticipated stigma.

Science.gov (United States)

Quinn, Diane M; Williams, Michelle K; Weisz, Bradley M

2015-06-01

Internalizing mental illness stigma is related to poorer well-being, but less is known about the factors that predict levels of internalized stigma. This study explored how experiences of discrimination relate to greater anticipation of discrimination and devaluation in the future and how anticipation of stigma in turn predicts greater stigma internalization. Participants were 105 adults with mental illness who self-reported their experiences of discrimination based on their mental illness, their anticipation of discrimination and social devaluation from others in the future, and their level of internalized stigma. Participants were approached in several locations and completed surveys on laptop computers. Correlational analyses indicated that more experiences of discrimination due to one's mental illness were related to increased anticipated discrimination in the future, increased anticipated social stigma from others, and greater internalized stigma. Multiple serial mediator analyses showed that the effect of experiences of discrimination on internalized stigma was fully mediated by increased anticipated discrimination and anticipated stigma. Experiences of discrimination over one's lifetime may influence not only how much future discrimination people with mental illness are concerned with but also how much they internalize negative feelings about the self. Mental health professionals may need to address concerns with future discrimination and devaluation in order to decrease internalized stigma. (c) 2015 APA, all rights reserved).

La double nature de l’image d’auteur The double nature of the author’s image

Directory of Open Access Journals (Sweden)

Ruth Amossy

2009-10-01

Full Text Available L’image d’auteur se décline selon deux modalités principales : l’image de soi que projette l’auteur dans le discours littéraire, ou ethos auctorial ; et l’image de l’auteur produite aux alentours de l’œuvre dans les discours éditoriaux, critiques et autres, ou représentation de l’auteur construite par une tierce personne. Ce travail, situé au carrefour de l’analyse du discours, de la rhétorique et de la narratologie, se propose d’éclairer ce double régime d’images en suggérant d’en explorer plus systématiquement les interrelations. En un premier temps de la recherche, il s’attache à préciser la notion d’image d’auteur pour inviter à une investigation plus approfondie de sa fabrique discursive dans les commentaires éditoriaux, médiatiques, critiques, … Il étudie ensuite la notion d’ethos auctorial en en exposant la construction et les fonctions dans le discours littéraire. Enfin, il esquisse l’analyse d’un fragment de Les bienveillantes de Littell pour éclairer l’articulation complexe des images intra- et extratextuelles de l’auteur.When dealing with the author’s image, one has to distinguish between the image of self built by the author in her text, or “authorial ethos”; and the image of the author as produced outside the literary work in the discourses of the editor, the critics, etc., or representation of the author constructed by another person. At the crossroad of Discourse Analysis, Rhetoric and Narratology, this paper endeavors to illuminate these two categories of images, calling for a further exploration of their intrinsic interrelation. It first describes the notion of author’s image, inviting to an in-depth analysis of its various manifestations; it illuminates the notion of authorial ethos, showing how it is constructed and what functions it fulfils in literary discourse. It then proceeds to a short analysis of a text borrowed from Littell’s novel, The Kindly

Automated Detection of Buildings from Heterogeneous VHR Satellite Images for Rapid Response to Natural Disasters

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Shaodan Li

2017-11-01

Full Text Available In this paper, we present a novel approach for automatically detecting buildings from multiple heterogeneous and uncalibrated very high-resolution (VHR satellite images for a rapid response to natural disasters. In the proposed method, a simple and efficient visual attention method is first used to extract built-up area candidates (BACs from each multispectral (MS satellite image. After this, morphological building indices (MBIs are extracted from all the masked panchromatic (PAN and MS images with BACs to characterize the structural features of buildings. Finally, buildings are automatically detected in a hierarchical probabilistic model by fusing the MBI and masked PAN images. The experimental results show that the proposed method is comparable to supervised classification methods in terms of recall, precision and F-value.

Natural image sequences constrain dynamic receptive fields and imply a sparse code.

Science.gov (United States)

Häusler, Chris; Susemihl, Alex; Nawrot, Martin P

2013-11-06

In their natural environment, animals experience a complex and dynamic visual scenery. Under such natural stimulus conditions, neurons in the visual cortex employ a spatially and temporally sparse code. For the input scenario of natural still images, previous work demonstrated that unsupervised feature learning combined with the constraint of sparse coding can predict physiologically measured receptive fields of simple cells in the primary visual cortex. This convincingly indicated that the mammalian visual system is adapted to the natural spatial input statistics. Here, we extend this approach to the time domain in order to predict dynamic receptive fields that can account for both spatial and temporal sparse activation in biological neurons. We rely on temporal restricted Boltzmann machines and suggest a novel temporal autoencoding training procedure. When tested on a dynamic multi-variate benchmark dataset this method outperformed existing models of this class. Learning features on a large dataset of natural movies allowed us to model spatio-temporal receptive fields for single neurons. They resemble temporally smooth transformations of previously obtained static receptive fields and are thus consistent with existing theories. A neuronal spike response model demonstrates how the dynamic receptive field facilitates temporal and population sparseness. We discuss the potential mechanisms and benefits of a spatially and temporally sparse representation of natural visual input. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Perceived weight discrimination and obesity.

Directory of Open Access Journals (Sweden)

Angelina R Sutin

Full Text Available Weight discrimination is prevalent in American society. Although associated consistently with psychological and economic outcomes, less is known about whether weight discrimination is associated with longitudinal changes in obesity. The objectives of this research are (1 to test whether weight discrimination is associated with risk of becoming obese (Body Mass Index≥30; BMI by follow-up among those not obese at baseline, and (2 to test whether weight discrimination is associated with risk of remaining obese at follow-up among those already obese at baseline. Participants were drawn from the Health and Retirement Study, a nationally representative longitudinal survey of community-dwelling US residents. A total of 6,157 participants (58.6% female completed the discrimination measure and had weight and height available from the 2006 and 2010 assessments. Participants who experienced weight discrimination were approximately 2.5 times more likely to become obese by follow-up (OR = 2.54, 95% CI = 1.58-4.08 and participants who were obese at baseline were three times more likely to remain obese at follow up (OR = 3.20, 95% CI = 2.06-4.97 than those who had not experienced such discrimination. These effects held when controlling for demographic factors (age, sex, ethnicity, education and when baseline BMI was included as a covariate. These effects were also specific to weight discrimination; other forms of discrimination (e.g., sex, race were unrelated to risk of obesity at follow-up. The present research demonstrates that, in addition to poorer mental health outcomes, weight discrimination has implications for obesity. Rather than motivating individuals to lose weight, weight discrimination increases risk for obesity.

Low power constant fraction discriminator

International Nuclear Information System (INIS)

Krishnan, Shanti; Raut, S.M.; Mukhopadhyay, P.K.

2001-01-01

This paper describes the design of a low power ultrafast constant fraction discriminator, which significantly reduces the power consumption. A conventional fast discriminator consumes about 1250 MW of power whereas this low power version consumes about 440 MW. In a multi detector system, where the number of discriminators is very large, reduction of power is of utmost importance. This low power discriminator is being designed for GRACE (Gamma Ray Atmospheric Cerenkov Experiments) telescope where 1000 channels of discriminators are required. A novel method of decreasing power consumption has been described. (author)

Acute neuroinflammation impairs context discrimination memory and disrupts pattern separation processes in hippocampus.

Science.gov (United States)

Czerniawski, Jennifer; Guzowski, John F

2014-09-10

Although it is known that immune system activation can impair cognition, no study to date has linked cognitive deficits during acute neuroinflammation to dysregulation of task-relevant neuronal ensemble activity. Here, we assessed both neural circuit activity and context discrimination memory retrieval, in a within-subjects design, of male rats given systemic administration of saline or lipopolysaccharide (LPS). Rats were exposed over several days to two similar contexts: one of which was paired with weak foot shock and the other was not. After reaching criteria for discriminative freezing, rats were given systemic LPS or saline injection and tested for retrieval of context discrimination 6 h later. Importantly, LPS administration produced an acute neuroinflammatory response in dorsal hippocampus at this time (as assessed by elevation of proinflammatory cytokine mRNA levels) and abolished retrieval of the previously acquired discrimination. The impact of neuroinflammation on hippocampal CA3 and CA1 neural circuit activity was assessed using the Arc/Homer1a cellular analysis of temporal activity by fluorescence in situ hybridization imaging method. Whereas the saline-treated subjects discriminated and had low overlap of hippocampal ensembles activated in the two contexts, LPS-treated subjects did not discriminate and had greater ensemble overlap (i.e., reduced orthogonalization). Additionally, retrieval of standard contextual fear conditioning, which does not require context discrimination, was not affected by pretesting LPS administration. Together, the behavioral and circuit analyses data provide compelling evidence that LPS administration impairs context discrimination memory by disrupting cellular pattern separation processes within the hippocampus, thus linking acute neuroinflammation to disruption of specific neural circuit functions and cognitive impairment. Copyright © 2014 the authors 0270-6474/14/3412470-11$15.00/0.

Sensitivity to the visual field origin of natural image patches in human low-level visual cortex

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Damien J. Mannion

2015-06-01

Full Text Available Asymmetries in the response to visual patterns in the upper and lower visual fields (above and below the centre of gaze have been associated with ecological factors relating to the structure of typical visual environments. Here, we investigated whether the content of the upper and lower visual field representations in low-level regions of human visual cortex are specialised for visual patterns that arise from the upper and lower visual fields in natural images. We presented image patches, drawn from above or below the centre of gaze of an observer navigating a natural environment, to either the upper or lower visual fields of human participants (n = 7 while we used functional magnetic resonance imaging (fMRI to measure the magnitude of evoked activity in the visual areas V1, V2, and V3. We found a significant interaction between the presentation location (upper or lower visual field and the image patch source location (above or below fixation; the responses to lower visual field presentation were significantly greater for image patches sourced from below than above fixation, while the responses in the upper visual field were not significantly different for image patches sourced from above and below fixation. This finding demonstrates an association between the representation of the lower visual field in human visual cortex and the structure of the visual input that is likely to be encountered below the centre of gaze.

Primitive fatherlands. Nature discourses and images from the first Spanish conservationism

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Santos Casado

2017-02-01

Full Text Available The origins of National Parks and other protected areas provide a historiographical window to investigate scientific, cultural, and ideological processes in early-twentiethcentury Spain. On the one hand, nature conservation, in Spain as in other Western countries, was intimately related to turnof- the-century concerns about national and social decadence, especially with regard to the perceived threats posed by industrialization and urbanization processes. On the other hand, while the ideological climate of Spanish regeneracionismo supported a broad movement of modernization and reform, ways to reinvigorate national identity were also sought. Therefore the establishment and first stages of National Parks, Nature Reserves and other conservation schemes were closely linked to the development of ideological discourses and cultural images around Spanish Parks, landscapes, and fauna, seen as powerful repositories of civic virtues and national symbols.

Monitoring the Natural Factors Influence on Vegetation Development by Using Moderate-Resolution Imaging Spectroradiometer (Modis Images with OBIA Method in Uzbekistan

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Sh. B. Akmalov

2016-05-01

Full Text Available In the study, natural and anthropogenic effects on vegetation are discussed and degree of their influence are shown in Syrdarya province (Uzbekistan. A statistical model of integrated meteo- and hydro- remote sensing data was developed. By the use of this model the correlation of various natural factors in vegetation period was analyzed and scale-dependency of spatial relationships between NDVI and three climatic factors were investigated. MODIS NDVI images have been used for the study area and OBIA method was applied via eCognition software.

Does perceived discrimination affect health? Longitudinal relationships between work discrimination and women's physical and emotional health.

Science.gov (United States)

Pavalko, Eliza K; Mossakowski, Krysia N; Hamilton, Vanessa J

2003-03-01

This study uses longitudinal data to examine the causal relationships between perceived work discrimination and women's physical and emotional health. Using data on 1,778 employed women in the National Longitudinal Survey of Mature Women, we investigate the structural and individual characteristics that predict later perceptions of discrimination and the effects of those perceptions on subsequent health. We find that perceptions of discrimination are influenced by job attitudes, prior experiences of discrimination, and work contexts, but prior health is not related to later perceptions. However, perceptions of discrimination do impact subsequent health, and these effects remain significant after controlling for prior emotional health, physical health limitations, discrimination, and job characteristics. Overall, the results provide even stronger support for the health impact of workplace discrimination and suggest a need for further longitudinal analyses of causes and consequences of perceived discrimination.

Strategies of Iranian nurses to overcome professional discrimination: An explorative qualitative study.

Science.gov (United States)

Shohani, Masoumeh

2017-01-01

Discrimination is a situation in which individuals receive unequal social benefits in return for equal roles they play. They react to such a situation in different ways. This study aims at identifying the strategies used by Iranian nurses to overcome professional discrimination. This qualitative study was conducted with the participation of 23 nurses who worked in hospitals in the cities of Tehran, Tabriz, and Ilam. They were selected based on purposive sampling. Data were collected using deep and unstructured interviews in a period of time between May 2013 and June 2014. Interviews were simultaneously analyzed using conventional content analysis method after being transcribed. Ethical consideration: This study was approved by the Regional Committee of Medical Research Ethics. Also, voluntary participation, anonymity, and confidentiality were considered. "Presenting a positive image of oneself," "objection," and "expectation" were three themes extracted through data analysis. Organizational discrimination puts nurses under stress and pressure. Nurses react to unfair behavior in different ways. These reactions are harmful to an organization and lead to negative consequences. Professional discrimination has made nurses adopt strategies which would lead to such consequences, which in turn influences their performance as nurses.

DISCRIMINATION BY ASSOCIATION IN EUROPEAN LAW

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Cătălina-Adriana Ivănuș

2013-11-01

Full Text Available The european law prohibit direct and indirect discrimination and harrasment on grounds of sex, racial or ethnic, religion or belief, disability, age or sexual orientation. The question is what is the situation when someone is discriminated on can claim to be the victim of unlawful discrimination because he or she is associated with another person who has the protected characteristic. The the Court of Justice of the European Union’s judgment in Coleman v Attridge Law and Steve Law confirms, for the first time in European law, the existence of the concept of discrimination by association. In this article I examine the implications of this case on all conceps of discrimination concepts of discrimination in European law (direct discrimination, indirect discrimination and harassment. I also examine the application of discrimination by association to grounds other than disability.

Aberrant functional connectivity for diagnosis of major depressive disorder: a discriminant analysis.

Science.gov (United States)

Cao, Longlong; Guo, Shuixia; Xue, Zhimin; Hu, Yong; Liu, Haihong; Mwansisya, Tumbwene E; Pu, Weidan; Yang, Bo; Liu, Chang; Feng, Jianfeng; Chen, Eric Y H; Liu, Zhening

2014-02-01

Aberrant brain functional connectivity patterns have been reported in major depressive disorder (MDD). It is unknown whether they can be used in discriminant analysis for diagnosis of MDD. In the present study we examined the efficiency of discriminant analysis of MDD by individualized computer-assisted diagnosis. Based on resting-state functional magnetic resonance imaging data, a new approach was adopted to investigate functional connectivity changes in 39 MDD patients and 37 well-matched healthy controls. By using the proposed feature selection method, we identified significant altered functional connections in patients. They were subsequently applied to our analysis as discriminant features using a support vector machine classification method. Furthermore, the relative contribution of functional connectivity was estimated. After subset selection of high-dimension features, the support vector machine classifier reached up to approximately 84% with leave-one-out training during the discrimination process. Through summarizing the classification contribution of functional connectivities, we obtained four obvious contribution modules: inferior orbitofrontal module, supramarginal gyrus module, inferior parietal lobule-posterior cingulated gyrus module and middle temporal gyrus-inferior temporal gyrus module. The experimental results demonstrated that the proposed method is effective in discriminating MDD patients from healthy controls. Functional connectivities might be useful as new biomarkers to assist clinicians in computer auxiliary diagnosis of MDD. © 2013 The Authors. Psychiatry and Clinical Neurosciences © 2013 Japanese Society of Psychiatry and Neurology.

From Discrimination to Internalized Mental Illness Stigma: The Mediating Roles of Anticipated Discrimination and Anticipated Stigma

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Quinn, Diane M.; Williams, Michelle K.; Weisz, Bradley M.

2015-01-01

Objective Internalizing mental illness stigma is related to poorer well-being, but less is known about the factors that predict levels of internalized stigma. This study explored how experiences of discrimination relate to greater anticipation of discrimination and devaluation in the future, and how anticipation of stigma, in turn predicts greater stigma internalization. Method Participants were 105 adults with mental illness who self-reported their experiences of discrimination based on their mental illness, their anticipation of discrimination and social devaluation from others in the future, and their level of internalized stigma. Participants were approached in several locations and completed surveys on laptop computers. Results Correlational analyses indicated that more experiences of discrimination due to one’s mental illness were related to increased anticipated discrimination in the future, increased anticipated social stigma from others, and greater internalized stigma. Multiple serial mediator analyses showed that the effect of experiences of discrimination on internalized stigma was fully mediated by increased anticipated discrimination and anticipated stigma. Conclusion and Implications for Practice Experiences of discrimination over the lifetime may influence not only how much future discrimination people with mental illness are concerned with but also how much they internalize negative feelings about the self. Mental health professionals may need to address concerns with future discrimination and devaluation in order to decrease internalized stigma. PMID:25844910

Hippocampal-cortical contributions to strategic exploration during perceptual discrimination.

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Voss, Joel L; Cohen, Neal J

2017-06-01

The hippocampus is crucial for long-term memory; its involvement in short-term or immediate expressions of memory is more controversial. Rodent hippocampus has been implicated in an expression of memory that occurs on-line during exploration termed "vicarious trial-and-error" (VTE) behavior. VTE occurs when rodents iteratively explore options during perceptual discrimination or at choice points. It is strategic in that it accelerates learning and improves later memory. VTE has been associated with activity of rodent hippocampal neurons, and lesions of hippocampus disrupt VTE and associated learning and memory advantages. Analogous findings of VTE in humans would support the role of hippocampus in active use of short-term memory to guide strategic behavior. We therefore measured VTE using eye-movement tracking during perceptual discrimination and identified relevant neural correlates with functional magnetic resonance imaging. A difficult perceptual-discrimination task was used that required visual information to be maintained during a several second trial, but with no long-term memory component. VTE accelerated discrimination. Neural correlates of VTE included robust activity of hippocampus and activity of a network of medial prefrontal and lateral parietal regions involved in memory-guided behavior. This VTE-related activity was distinct from activity associated with simply viewing visual stimuli and making eye movements during the discrimination task, which occurred in regions frequently associated with visual processing and eye-movement control. Subjects were mostly unaware of performing VTE, thus further distancing VTE from explicit long-term memory processing. These findings bridge the rodent and human literatures on neural substrates of memory-guided behavior, and provide further support for the role of hippocampus and a hippocampal-centered network of cortical regions in the immediate use of memory in on-line processing and the guidance of behavior. © 2017

Contextual interactions in grating plaid configurations are explained by natural image statistics and neural modeling

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Udo Alexander Ernst

2016-10-01

Full Text Available Processing natural scenes requires the visual system to integrate local features into global object descriptions. To achieve coherent representations, the human brain uses statistical dependencies to guide weighting of local feature conjunctions. Pairwise interactions among feature detectors in early visual areas may form the early substrate of these local feature bindings. To investigate local interaction structures in visual cortex, we combined psychophysical experiments with computational modeling and natural scene analysis. We first measured contrast thresholds for 2x2 grating patch arrangements (plaids, which differed in spatial frequency composition (low, high or mixed, number of grating patch co-alignments (0, 1 or 2, and inter-patch distances (1° and 2° of visual angle. Contrast thresholds for the different configurations were compared to the prediction of probability summation (PS among detector families tuned to the four retinal positions. For 1° distance the thresholds for all configurations were larger than predicted by PS, indicating inhibitory interactions. For 2° distance, thresholds were significantly lower compared to PS when the plaids were homogeneous in spatial frequency and orientation, but not when spatial frequencies were mixed or there was at least one misalignment. Next, we constructed a neural population model with horizontal laminar structure, which reproduced the detection thresholds after adaptation of connection weights. Consistent with prior work, contextual interactions were medium-range inhibition and long-range, orientation-specific excitation. However, inclusion of orientation-specific, inhibitory interactions between populations with different spatial frequency preferences were crucial for explaining detection thresholds. Finally, for all plaid configurations we computed their likelihood of occurrence in natural images. The likelihoods turned out to be inversely related to the detection thresholds obtained

Study on Detection and Localization Algorithm of Traffic Signs from Natural Scenes

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Xian-Zhong Han

2014-08-01

Full Text Available Automatic detection and location of traffic signs is an important part of intelligent transportation, especially for unmanned vehicle technology research. For the morphological feature of China road traffic signs, we propose a traffic sign detection method based on color segmentation and shape analysis. Firstly, in order to solve the problems of traffic signs color cast, distortion, and cross-color in natural scenes, the images are processed by white balance, Retinex color enhancement, and affine transformation. Then, the type of traffic signs is discriminated and detected, according to the color and shape characteristics of traffic signs. The experimental results show that this method can effectively detect and recognize traffic signs.

Introduction to integral discriminants

International Nuclear Information System (INIS)

Morozov, A.; Shakirov, Sh.

2009-01-01

The simplest partition function, associated with homogeneous symmetric forms S of degree r in n variables, is integral discriminant J n|r (S) = ∫e -S(x 1 ,...,x n ) dx 1 ...dx n . Actually, S-dependence remains the same if e -S in the integrand is substituted by arbitrary function f(S), i.e. integral discriminant is a characteristic of the form S itself, and not of the averaging procedure. The aim of the present paper is to calculate J n|r in a number of non-Gaussian cases. Using Ward identities - linear differential equations, satisfied by integral discriminants - we calculate J 2|3 ,J 2|4 ,J 2|5 and J 3|3 . In all these examples, integral discriminant appears to be a generalized hypergeometric function. It depends on several SL(n) invariants of S, with essential singularities controlled by the ordinary algebraic discriminant of S.

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

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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.

Quantifying explainable discrimination and removing illegal discrimination in automated decision making

KAUST Repository

Kamiran, Faisal; Žliobaite, Indre; Calders, Toon

2012-01-01

discrimination and do not take into account that part of the discrimination may be explainable by other attributes. For example, in a job application, the education level of a job candidate could be such an explainable attribute. If the data contain many highly

Calcium imaging of basal forebrain activity during innate and learned behaviors

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Thomas Clarke Harrison

2016-05-01

Full Text Available The basal forebrain (BF plays crucial roles in arousal, attention, and memory, and its impairment is associated with a variety of cognitive deficits. The BF consists of cholinergic, GABAergic, and glutamatergic neurons. Electrical or optogenetic stimulation of BF cholinergic neurons enhances cortical processing and behavioral performance, but the natural activity of these cells during behavior is only beginning to be characterized. Even less is known about GABAergic and glutamatergic neurons. Here, we performed microendoscopic calcium imaging of BF neurons as mice engaged in spontaneous behaviors in their home cages (innate or performed a go/no-go auditory discrimination task (learned. Cholinergic neurons were consistently excited during movement, including running and licking, but GABAergic and glutamatergic neurons exhibited diverse responses. All cell types were activated by overt punishment, either inside or outside of the discrimination task. These findings reveal functional similarities and distinctions between BF cell types during both spontaneous and task-related behaviors.

JUSTIFICATION FOR INDIRECT DISCRIMINATION IN EU

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Cătălina-Adriana Ivănuş

2014-11-01

Full Text Available The right to non-discrimination is very important for a civilized society. EU legislation establishes direct and indirect discrimination, harassment, sexual harassment, instruction to discriminate and any less favourable treatment of a woman related to pregnancy or maternity leave as forms of discrimination. The law and the Court of Justice permit the justification of indirect discrimination.

JUSTIFICATION FOR INDIRECT DISCRIMINATION IN EU

OpenAIRE

Cătălina-Adriana Ivănuş

2014-01-01

The right to non-discrimination is very important for a civilized society. EU legislation establishes direct and indirect discrimination, harassment, sexual harassment, instruction to discriminate and any less favourable treatment of a woman related to pregnancy or maternity leave as forms of discrimination. The law and the Court of Justice permit the justification of indirect discrimination.

Automatic telangiectasia analysis in dermoscopy images using adaptive critic design.

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Cheng, B; Stanley, R J; Stoecker, W V; Hinton, K

2012-11-01

Telangiectasia, tiny skin vessels, are important dermoscopy structures used to discriminate basal cell carcinoma (BCC) from benign skin lesions. This research builds off of previously developed image analysis techniques to identify vessels automatically to discriminate benign lesions from BCCs. A biologically inspired reinforcement learning approach is investigated in an adaptive critic design framework to apply action-dependent heuristic dynamic programming (ADHDP) for discrimination based on computed features using different skin lesion contrast variations to promote the discrimination process. Lesion discrimination results for ADHDP are compared with multilayer perception backpropagation artificial neural networks. This study uses a data set of 498 dermoscopy skin lesion images of 263 BCCs and 226 competitive benign images as the input sets. This data set is extended from previous research [Cheng et al., Skin Research and Technology, 2011, 17: 278]. Experimental results yielded a diagnostic accuracy as high as 84.6% using the ADHDP approach, providing an 8.03% improvement over a standard multilayer perception method. We have chosen BCC detection rather than vessel detection as the endpoint. Although vessel detection is inherently easier, BCC detection has potential direct clinical applications. Small BCCs are detectable early by dermoscopy and potentially detectable by the automated methods described in this research. © 2011 John Wiley & Sons A/S.

Discriminative clustering on manifold for adaptive transductive classification.

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Zhang, Zhao; Jia, Lei; Zhang, Min; Li, Bing; Zhang, Li; Li, Fanzhang

2017-10-01

In this paper, we mainly propose a novel adaptive transductive label propagation approach by joint discriminative clustering on manifolds for representing and classifying high-dimensional data. Our framework seamlessly combines the unsupervised manifold learning, discriminative clustering and adaptive classification into a unified model. Also, our method incorporates the adaptive graph weight construction with label propagation. Specifically, our method is capable of propagating label information using adaptive weights over low-dimensional manifold features, which is different from most existing studies that usually predict the labels and construct the weights in the original Euclidean space. For transductive classification by our formulation, we first perform the joint discriminative K-means clustering and manifold learning to capture the low-dimensional nonlinear manifolds. Then, we construct the adaptive weights over the learnt manifold features, where the adaptive weights are calculated through performing the joint minimization of the reconstruction errors over features and soft labels so that the graph weights can be joint-optimal for data representation and classification. Using the adaptive weights, we can easily estimate the unknown labels of samples. After that, our method returns the updated weights for further updating the manifold features. Extensive simulations on image classification and segmentation show that our proposed algorithm can deliver the state-of-the-art performance on several public datasets. Copyright © 2017 Elsevier Ltd. All rights reserved.

Transfer to Intermediate Forms Following Concept Discrimination by Pigeons: Chimeras and Morphs

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Ghosh, Natasha; Lea, S. E. G.; Noury, Malia

2004-01-01

Two experiments examined pigeons' generalization to intermediate forms following training of concept discriminations. In Experiment 1, the training stimuli were sets of images of dogs and cats, and the transfer stimuli were head/body chimeras, which humans tend to categorize more readily in terms of the head part rather than the body part. In…

Logistic discriminant parametric mapping: a novel method for the pixel-based differential diagnosis of Parkinson's disease

International Nuclear Information System (INIS)

Acton, P.D.; Mozley, P.D.; Kung, H.F.; Pennsylvania Univ., Philadelphia, PA

1999-01-01

Positron emission tomography (PET) and single-photon emission tomography (SPET) imaging of the dopaminergic system is a powerful tool for distinguishing groups of patients with neurodegenerative disorders, such as Parkinson's disease (PD). However, the differential diagnosis of individual subjects presenting early in the progress of the disease is much more difficult, particularly using region-of-interest analysis where small localized differences between subjects are diluted. In this paper we present a novel pixel-based technique using logistic discriminant analysis to distinguish between a group of PD patients and age-matched healthy controls. Simulated images of an anthropomorphic head phantom were used to test the sensitivity of the technique to striatal lesions of known size. The methodology was applied to real clinical SPET images of binding of technetium-99m labelled TRODAT-1 to dopamine transporters in PD patients (n=42) and age-matched controls (n=23). The discriminant model was trained on a subset (n=17) of patients for whom the diagnosis was unequivocal. Logistic discriminant parametric maps were obtained for all subjects, showing the probability distribution of pixels classified as being consistent with PD. The probability maps were corrected for correlated multiple comparisons assuming an isotropic Gaussian point spread function. Simulated lesion sizes measured by logistic discriminant parametric mapping (LDPM) gave strong correlations with the known data (r 2 =0.985, P<0.001). LDPM correctly classified all PD patients (sensitivity 100%) and only misclassified one control (specificity 95%). All patients who had equivocal clinical symptoms associated with early onset PD (n=4) were correctly assigned to the patient group. Statistical parametric mapping (SPM) had a sensitivity of only 24% on the same patient group. LDPM is a powerful pixel-based tool for the differential diagnosis of patients with PD and healthy controls. The diagnosis of disease even

Reproducible high-resolution multispectral image acquisition in dermatology

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Duliu, Alexandru; Gardiazabal, José; Lasser, Tobias; Navab, Nassir

2015-07-01

Multispectral image acquisitions are increasingly popular in dermatology, due to their improved spectral resolution which enables better tissue discrimination. Most applications however focus on restricted regions of interest, imaging only small lesions. In this work we present and discuss an imaging framework for high-resolution multispectral imaging on large regions of interest.

Natural history of lesions with the MR imaging appearance of multinodular and vacuolating neuronal tumor

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Alsufayan, Reema [University of Toronto, Toronto (Canada); Alcaide-Leon, Paula; De Tilly, Lyne Noel [University of Toronto, St. Michael' s Hospital, Toronto (Canada); Mandell, Daniel M.; Krings, Timo [University of Toronto, Toronto Western Hospital, UHN Division of Neuroradiology, Toronto, ON (Canada)

2017-09-15

Multinodular and vacuolating neuronal tumor (MVNT) have been recently added to the WHO classification of CNS tumors and has not been extensively reported upon in the radiological literature. We report the first radiological and the largest series of cases, aiming to highlight the natural history of lesions with the imaging appearance of MVNT with long follow-up time. In this retrospective study, we collected cases with the imaging appearance of MVNT. All lesions were evaluated by using routine MR imaging, with follow-up of up to 93 months. Patient demographics, clinical course, and MRI features of the lesions were recorded. Twenty-four subjects were enrolled, f/m = 16:8, age range 24-59 years, with a median age of 45 years. The patients' symptoms were often episodic and most frequently due to headaches in 12 (50%), visual symptoms in 6 (25%), seizures in 5 ± 1 (20-25%), paresthesia in 4 (∝17%), cognitive difficulties in 4 (∝17%), in addition to other variable neurological symptoms, or incidental. A total of 30 lesions identified, 77% of the lesions had gadolinium-enhanced MRI and only 13% showed enhancement. A 6.7% of the lesions that had MRI followed up showed progression, while the rest remained stable up to 93 months interval. All patients had intact neurological examinations (except one case that was diagnosed with optic neuritis), were managed conservatively, and did well. The natural history of lesions with imaging features of MVNT is overall stable from a clinical and imaging appearance over time. (orig.)

Natural history of lesions with the MR imaging appearance of multinodular and vacuolating neuronal tumor

International Nuclear Information System (INIS)

Alsufayan, Reema; Alcaide-Leon, Paula; De Tilly, Lyne Noel; Mandell, Daniel M.; Krings, Timo

2017-01-01

Multinodular and vacuolating neuronal tumor (MVNT) have been recently added to the WHO classification of CNS tumors and has not been extensively reported upon in the radiological literature. We report the first radiological and the largest series of cases, aiming to highlight the natural history of lesions with the imaging appearance of MVNT with long follow-up time. In this retrospective study, we collected cases with the imaging appearance of MVNT. All lesions were evaluated by using routine MR imaging, with follow-up of up to 93 months. Patient demographics, clinical course, and MRI features of the lesions were recorded. Twenty-four subjects were enrolled, f/m = 16:8, age range 24-59 years, with a median age of 45 years. The patients' symptoms were often episodic and most frequently due to headaches in 12 (50%), visual symptoms in 6 (25%), seizures in 5 ± 1 (20-25%), paresthesia in 4 (∝17%), cognitive difficulties in 4 (∝17%), in addition to other variable neurological symptoms, or incidental. A total of 30 lesions identified, 77% of the lesions had gadolinium-enhanced MRI and only 13% showed enhancement. A 6.7% of the lesions that had MRI followed up showed progression, while the rest remained stable up to 93 months interval. All patients had intact neurological examinations (except one case that was diagnosed with optic neuritis), were managed conservatively, and did well. The natural history of lesions with imaging features of MVNT is overall stable from a clinical and imaging appearance over time. (orig.)

Perceiving discrimination in "real life" : Distinguishing negative events from discrimination attributions.

NARCIS (Netherlands)

Thijs, J.T.; Piscoi, Dea

2016-01-01

The present survey study examined a sample of ethnic minority preadolescents (ages 9–13) and made the empirical distinction between their exposure to peer victimization and the extent to which they attributed this to discrimination. Both peer victimization and the attribution to discrimination were

Modeling human color categorization: Color discrimination and color memory

OpenAIRE

Heskes, T.; van den Broek, Egon; Lucas, P.; Hendriks, Maria A.; Vuurpijl, L.G.; Puts, M.J.H.; Wiegerinck, W.

2003-01-01

Color matching in Content-Based Image Retrieval is done using a color space and measuring distances between colors. Such an approach yields non-intuitive results for the user. We introduce color categories (or focal colors), determine that they are valid, and use them in two experiments. The experiments conducted prove the difference between color categorization by the cognitive processes color discrimination and color memory. In addition, they yield a Color Look-Up Table, which can improve c...

Digital voltage discriminator

International Nuclear Information System (INIS)

Zhou Zhicheng

1992-01-01

A digital voltage discriminator is described, which is synthesized by digital comparator and ADC. The threshold is program controllable with high stability. Digital region of confusion is approximately equal to 1.5 LSB. This discriminator has a single channel analyzer function model with channel width of 1.5 LSB

Flash-Type Discrimination

Science.gov (United States)

Koshak, William J.

2010-01-01

This viewgraph presentation describes the significant progress made in the flash-type discrimination algorithm development. The contents include: 1) Highlights of Progress for GLM-R3 Flash-Type discrimination Algorithm Development; 2) Maximum Group Area (MGA) Data; 3) Retrieval Errors from Simulations; and 4) Preliminary Global-scale Retrieval.

Effective and efficient Grassfinch kernel for SVM classification and its application to recognition based on image set

International Nuclear Information System (INIS)

Du, Genyuan; Tian, Shengli; Qiu, Yingyu; Xu, Chunyan

2016-01-01

This paper presents an effective and efficient kernel approach to recognize image set which is represented as a point on extended Grassmannian manifold. Several recent studies focus on the applicability of discriminant analysis on Grassmannian manifold and suffer from not obtaining the inherent nonlinear structure of the data itself. Therefore, we propose an extension of Grassmannian manifold to address this issue. Instead of using a linear data embedding with PCA, we develop a non-linear data embedding of such manifold using kernel PCA. This paper mainly consider three folds: 1) introduce a non-linear data embedding of extended Grassmannian manifold, 2) derive a distance metric of Grassmannian manifold, 3) develop an effective and efficient Grassmannian kernel for SVM classification. The extended Grassmannian manifold naturally arises in the application to recognition based on image set, such as face and object recognition. Experiments on several standard databases show better classification accuracy. Furthermore, experimental results indicate that our proposed approach significantly reduces time complexity in comparison to graph embedding discriminant analysis.

Timbre discrimination in musical patterns.

Science.gov (United States)

Grey, J M

1978-08-01

Most research on timbre perception has studied isolated tones. This study compares timbre discrimination of isolated tones with discrimination in various musical contexts, both single-voiced and multivoiced. Twelve different contexts were used (four isolated tonal comparisons, four single-voice musical patterns, and four multivoice patterns). Listerners judged whether the timbre remained the same or changed during the trial. Two possible versions of any instrumental timbre differed in the physical information used in their synthesis. Three instrumental timbres were tested in all contexts: clarinet, trumpet, and bassoon. The effects of context upon discrimination varied across instruments. The clarinet and trumpet versions were best discriminated in isolated contexts, with discrimination progressively worse in single-voice and multivoice patterns. The bassoon versions were best discriminated in the single-voice patterns, with equal discrimination in the isolated and multivoice cases. It is suggested that these results were due to pronounced physical differences observed between the spectra of the two versions of the bassoon that were not apparent between the versions of the clarinet or trumpet.

Global trends on fears and concerns of genetic discrimination: a systematic literature review.

Science.gov (United States)

Wauters, Annet; Van Hoyweghen, Ine

2016-04-01

Since the 1990s, developments in the field of genetics have led to many questions on the use and possible misuse of genetic information. 'Genetic discrimination' has been defined as the differential treatment of asymptomatic individuals or their relatives on the basis of their real or assumed genetic characteristics. Despite the public policy attention around genetic discrimination, there is currently still much confusion surrounding this phenomenon. On the one hand, there is little evidence of the occurrence of genetic discrimination. On the other hand, it appears that people remain concerned about this theme, and this fear influences their health and life choices. This article makes use of a systematic literature review to investigate what is already known about the nature, extent and background of these fears and concerns. The 42 included studies have found considerable levels of concerns about genetic discrimination. Concerns dominate in insurance contexts and within personal interactions. The extent of concerns appears to vary depending on the type of genetic illness. Furthermore, installed laws prohibiting genetic discrimination do not seem to alleviate existing fears. This raises important questions as to the origins of these fears. Based on the findings, recommendations for future research are made. First, research on the background of fears is needed. Second, future research needs to assess more fully all different forms (for example, direct and indirect) of genetic discrimination. Thirdly, it has to be studied whether genetic discrimination is a form of discrimination that is distinguishable from discrimination based on an illness or disability. Finally, a last element that should be addressed in future research is the most recent developments in research on genomics, such as next-generation sequencing or genome-wide association studies.

Supersensitive detection and discrimination of enantiomers by dorsal olfactory receptors: evidence for hierarchical odour coding.

Science.gov (United States)

Sato, Takaaki; Kobayakawa, Reiko; Kobayakawa, Ko; Emura, Makoto; Itohara, Shigeyoshi; Kizumi, Miwako; Hamana, Hiroshi; Tsuboi, Akio; Hirono, Junzo

2015-09-11

Enantiomeric pairs of mirror-image molecular structures are difficult to resolve by instrumental analyses. The human olfactory system, however, discriminates (-)-wine lactone from its (+)-form rapidly within seconds. To gain insight into receptor coding of enantiomers, we compared behavioural detection and discrimination thresholds of wild-type mice with those of ΔD mice in which all dorsal olfactory receptors are genetically ablated. Surprisingly, wild-type mice displayed an exquisite "supersensitivity" to enantiomeric pairs of wine lactones and carvones. They were capable of supersensitive discrimination of enantiomers, consistent with their high detection sensitivity. In contrast, ΔD mice showed selective major loss of sensitivity to the (+)-enantiomers. The resulting 10(8)-fold differential sensitivity of ΔD mice to (-)- vs. (+)-wine lactone matched that observed in humans. This suggests that humans lack highly sensitive orthologous dorsal receptors for the (+)-enantiomer, similarly to ΔD mice. Moreover, ΔD mice showed >10(10)-fold reductions in enantiomer discrimination sensitivity compared to wild-type mice. ΔD mice detected one or both of the (-)- and (+)-enantiomers over a wide concentration range, but were unable to discriminate them. This "enantiomer odour discrimination paradox" indicates that the most sensitive dorsal receptors play a critical role in hierarchical odour coding for enantiomer identification.

Improved MR breast images by contrast optimization using artificial intelligence

International Nuclear Information System (INIS)

Konig, H.; Gohagan, J.; Laub, G.; Bachus, R.; Heywang, S.; Reinhardt, E.R.

1986-01-01

The clinical relevance of MR imaging of the breast is mainly related to the modelity's ability to differentiate among normal, benign, and malignant tissue and to yield prognostic information. In addition to the MR imaging parameters, morphologic features of these images are calculated. Based on statistical information of a comprehensive, labeled image and knowledge of a data base system, a numerical classifier is deduced. The application of this classifier to all cases leads to estimations of specific tissue types for each pixel. The method is sufficiently sensitive for grading a recognized tissue class. In this manner images with optimal contrast appropriate to particular diagnostic requirements are generated. The discriminant power of each MR imaging parameter as well as of a combination of parameters can be determined objectively with respect to tissue discrimination

From Pixels to Response Maps: Discriminative Image Filtering for Face Alignment in the Wild

NARCIS (Netherlands)

Asthana, Akshay; Asthana, Ashish; Zafeiriou, Stefanos; Tzimiropoulos, Georgios; Cheng, Shiyang; Pantic, Maja

2015-01-01

We propose a face alignment framework that relies on the texture model generated by the responses of discriminatively trained part-based filters. Unlike standard texture models built from pixel intensities or responses generated by generic filters (e.g. Gabor), our framework has two important

Multi-Resolution Wavelet-Transformed Image Analysis of Histological Sections of Breast Carcinomas

Directory of Open Access Journals (Sweden)

Hae-Gil Hwang

2005-01-01

Full Text Available Multi-resolution images of histological sections of breast cancer tissue were analyzed using texture features of Haar- and Daubechies transform wavelets. Tissue samples analyzed were from ductal regions of the breast and included benign ductal hyperplasia, ductal carcinoma in situ (DCIS, and invasive ductal carcinoma (CA. To assess the correlation between computerized image analysis and visual analysis by a pathologist, we created a two-step classification system based on feature extraction and classification. In the feature extraction step, we extracted texture features from wavelet-transformed images at 10× magnification. In the classification step, we applied two types of classifiers to the extracted features, namely a statistics-based multivariate (discriminant analysis and a neural network. Using features from second-level Haar transform wavelet images in combination with discriminant analysis, we obtained classification accuracies of 96.67 and 87.78% for the training and testing set (90 images each, respectively. We conclude that the best classifier of carcinomas in histological sections of breast tissue are the texture features from the second-level Haar transform wavelet images used in a discriminant function.

A naturally occurring contrast agent for OCT imaging of smokers' lung

International Nuclear Information System (INIS)

Yang Ying; Bagnaninchi, Pierre O; Whiteman, Suzanne C; Pittius, Daniel Gey van; Haj, Alicia J El; Spiteri, Monica A; Wang, Ruikang K

2005-01-01

Optical coherence tomography (OCT) offers great potential for clinical applications in terms of its cost, safety and real-time imaging capability. Improvement of its resolution for revealing sub-layers or sub-cellular components within a tissue will further widen its application. In this study we report that carbon pigment, which is frequently present in the lungs of smokers, could be used as a contrast agent to improve the OCT imaging of lung tissue. Carbon produced an intense bright OCT image at a relatively deep location. The parallel histopathological section analysis confirmed the presence of carbon pigment in such tissues. The underlying mechanism of the OCT image formation has been discussed based on a model system in which carbon particles were dispersed in agar gel. Calculations and in-depth intensity profiles of OCT revealed that higher refractive index particles with a size close to or smaller than the wavelength would greatly increase backscattering and generate a sharp contrast, while a particle size several times larger than the wavelength would absorb or obstruct the light path. The naturally occurring contrast agent could provide a diagnostic biomarker of lung tissue in smokers. Furthermore, carbon under such circumstances, can be used as an effective exogenous contrast agent, with which specific components or tissues exhibiting early tumour formation can be optically labelled to delineate the location and boundary, providing potential for early cancer detection and its treatment

A novel CMOS sensor with in-pixel auto-zeroed discrimination for charged particle tracking

International Nuclear Information System (INIS)

Degerli, Y; Guilloux, F; Orsini, F

2014-01-01

With the aim of developing fast and granular Monolithic Active Pixels Sensors (MAPS) as new charged particle tracking detectors for high energy physics experiments, a new rolling shutter binary pixel architecture concept (RSBPix) with in-pixel correlated double sampling, amplification and discrimination is presented. The discriminator features auto-zeroing in order to compensate process-related transistor mismatches. In order to validate the pixel, a first monolithic CMOS sensor prototype, including a pixel array of 96 × 64 pixels, has been designed and fabricated in the Tower-Jazz 0.18 μm CMOS Image Sensor (CIS) process. Results of laboratory tests are presented

Associations of racial discrimination and parental discrimination coping messages with African American adolescent racial identity.

Science.gov (United States)

Richardson, Bridget L; Macon, Tamarie A; Mustafaa, Faheemah N; Bogan, Erin D; Cole-Lewis, Yasmin; Chavous, Tabbye M

2015-06-01

Research links racial identity to important developmental outcomes among African American adolescents, but less is known about the contextual experiences that shape youths' racial identity. In a sample of 491 African American adolescents (48% female), associations of youth-reported experiences of racial discrimination and parental messages about preparation for racial bias with adolescents' later racial identity were examined. Cluster analysis resulted in four profiles of adolescents varying in reported frequency of racial discrimination from teachers and peers at school and frequency of parental racial discrimination coping messages during adolescents' 8th grade year. Boys were disproportionately over-represented in the cluster of youth experiencing more frequent discrimination but receiving fewer parental discrimination coping messages, relative to the overall sample. Also examined were clusters of adolescents' 11th grade racial identity attitudes about the importance of race (centrality), personal group affect (private regard), and perceptions of societal beliefs about African Americans (public regard). Girls and boys did not differ in their representation in racial identity clusters, but 8th grade discrimination/parent messages clusters were associated with 11th grade racial identity cluster membership, and these associations varied across gender groups. Boys experiencing more frequent discrimination but fewer parental coping messages were over-represented in the racial identity cluster characterized by low centrality, low private regard, and average public regard. The findings suggest that adolescents who experience racial discrimination but receive fewer parental supports for negotiating and coping with discrimination may be at heightened risk for internalizing stigmatizing experiences. Also, the findings suggest the need to consider the context of gender in adolescents' racial discrimination and parental racial socialization.

Attribute Learning for SAR Image Classification

Directory of Open Access Journals (Sweden)

Chu He

2017-04-01

Full Text Available This paper presents a classification approach based on attribute learning for high spatial resolution Synthetic Aperture Radar (SAR images. To explore the representative and discriminative attributes of SAR images, first, an iterative unsupervised algorithm is designed to cluster in the low-level feature space, where the maximum edge response and the ratio of mean-to-variance are included; a cross-validation step is applied to prevent overfitting. Second, the most discriminative clustering centers are sorted out to construct an attribute dictionary. By resorting to the attribute dictionary, a representation vector describing certain categories in the SAR image can be generated, which in turn is used to perform the classifying task. The experiments conducted on TerraSAR-X images indicate that those learned attributes have strong visual semantics, which are characterized by bright and dark spots, stripes, or their combinations. The classification method based on these learned attributes achieves better results.

20 CFR 405.30 - Discrimination complaints.

Science.gov (United States)

2010-04-01

... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Discrimination complaints. 405.30 Section 405... INITIAL DISABILITY CLAIMS Introduction, General Description, and Definitions § 405.30 Discrimination... that an adjudicator has improperly discriminated against you, you may file a discrimination complaint...