Determination of solute descriptors by chromatographic methods.

Science.gov (United States)

Poole, Colin F; Atapattu, Sanka N; Poole, Salwa K; Bell, Andrea K

2009-10-12

The solvation parameter model is now well established as a useful tool for obtaining quantitative structure-property relationships for chemical, biomedical and environmental processes. The model correlates a free-energy related property of a system to six free-energy derived descriptors describing molecular properties. These molecular descriptors are defined as L (gas-liquid partition coefficient on hexadecane at 298K), V (McGowan's characteristic volume), E (excess molar refraction), S (dipolarity/polarizability), A (hydrogen-bond acidity), and B (hydrogen-bond basicity). McGowan's characteristic volume is trivially calculated from structure and the excess molar refraction can be calculated for liquids from their refractive index and easily estimated for solids. The remaining four descriptors are derived by experiment using (largely) two-phase partitioning, chromatography, and solubility measurements. In this article, the use of gas chromatography, reversed-phase liquid chromatography, micellar electrokinetic chromatography, and two-phase partitioning for determining solute descriptors is described. A large database of experimental retention factors and partition coefficients is constructed after first applying selection tools to remove unreliable experimental values and an optimized collection of varied compounds with descriptor values suitable for calibrating chromatographic systems is presented. These optimized descriptors are demonstrated to be robust and more suitable than other groups of descriptors characterizing the separation properties of chromatographic systems.

Joint Textual And Visual Cues For Retrieving Images Using Latent Semantic Indexing

OpenAIRE

Pecenovic, Zoran; Ayer, Serge; Vetterli, Martin

2001-01-01

In this article we present a novel approach of integrating textual and visual descriptors of images in a unified retrieval structure. The methodology, inspired from text retrieval and information filtering is based on Latent Semantic Indexing (LS1).

Applying semantic web services to enterprise web

OpenAIRE

Hu, Y; Yang, Q P; Sun, X; Wei, P

2008-01-01

Enterprise Web provides a convenient, extendable, integrated platform for information sharing and knowledge management. However, it still has many drawbacks due to complexity and increasing information glut, as well as the heterogeneity of the information processed. Research in the field of Semantic Web Services has shown the possibility of adding higher level of semantic functionality onto the top of current Enterprise Web, enhancing usability and usefulness of resource, enabling decision su...

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.

Learning to assign binary weights to binary descriptor

Science.gov (United States)

Huang, Zhoudi; Wei, Zhenzhong; Zhang, Guangjun

2016-10-01

Constructing robust binary local feature descriptors are receiving increasing interest due to their binary nature, which can enable fast processing while requiring significantly less memory than their floating-point competitors. To bridge the performance gap between the binary and floating-point descriptors without increasing the computational cost of computing and matching, optimal binary weights are learning to assign to binary descriptor for considering each bit might contribute differently to the distinctiveness and robustness. Technically, a large-scale regularized optimization method is applied to learn float weights for each bit of the binary descriptor. Furthermore, binary approximation for the float weights is performed by utilizing an efficient alternatively greedy strategy, which can significantly improve the discriminative power while preserve fast matching advantage. Extensive experimental results on two challenging datasets (Brown dataset and Oxford dataset) demonstrate the effectiveness and efficiency of the proposed method.

JET ENGINE INLET DISTORTION SCREEN AND DESCRIPTOR EVALUATION

Directory of Open Access Journals (Sweden)

Jiří Pečinka

2017-02-01

Full Text Available Total pressure distortion is one of the three basic flow distortions (total pressure, total temperature and swirl distortion that might appear at the inlet of a gas turbine engine (GTE during operation. Different numerical parameters are used for assessing the total pressure distortion intensity and extent. These summary descriptors are based on the distribution of total pressure in the aerodynamic interface plane. There are two descriptors largely spread around the world, however, three or four others are still in use and can be found in current references. The staff at the University of Defence decided to compare the most common descriptors using basic flow distortion patterns in order to select the most appropriate descriptor for future department research. The most common descriptors were identified based on their prevalence in widely accessible publications. The construction and use of these descriptors are reviewed in the paper. Subsequently, they are applied to radial, angular, and combined distortion patterns of different intensities and with varied mass flow rates. The tests were performed on a specially designed test bench using an electrically driven standalone industrial centrifugal compressor, sucking air through the inlet of a TJ100 small turbojet engine. Distortion screens were placed into the inlet channel to create the desired total pressure distortions. Of the three basic distortions, only the total pressure distortion descriptors were evaluated. However, both total and static pressures were collected using a multi probe rotational measurement system.

Module descriptor

DEFF Research Database (Denmark)

Vincenti, Gordon; Klausen, Bodil; Kjær Jensen, Jesper

2016-01-01

The Module Descriptor including a Teacher’s Guide explains and describes how to work innovatively and co-creatively with wicked problems and young people. The descriptor shows how interested educators and lecturers in Europe can copy the lessons of the Erasmus+ project HIP when teaching their own...

Two-dimensional hidden semantic information model for target saliency detection and eyetracking identification

Science.gov (United States)

Wan, Weibing; Yuan, Lingfeng; Zhao, Qunfei; Fang, Tao

2018-01-01

Saliency detection has been applied to the target acquisition case. This paper proposes a two-dimensional hidden Markov model (2D-HMM) that exploits the hidden semantic information of an image to detect its salient regions. A spatial pyramid histogram of oriented gradient descriptors is used to extract features. After encoding the image by a learned dictionary, the 2D-Viterbi algorithm is applied to infer the saliency map. This model can predict fixation of the targets and further creates robust and effective depictions of the targets' change in posture and viewpoint. To validate the model with a human visual search mechanism, two eyetrack experiments are employed to train our model directly from eye movement data. The results show that our model achieves better performance than visual attention. Moreover, it indicates the plausibility of utilizing visual track data to identify targets.

8th Workshop on Coupled Descriptor Systems

CERN Document Server

Bartel, Andreas; Günther, Michael; Maten, E; Müller, Peter

2014-01-01

This book contains the proceedings of the 8th Workshop on Coupled Descriptor Systems held March 2013 in the Castle of Eringerfeld, Geseke in the neighborhood of Paderborn, Germany. It examines the wide range of current research topics in descriptor systems, including mathematical modeling, index analysis, wellposedness of problems, stiffness and different time-scales, cosimulation and splitting methods and convergence analysis. In addition, the book also presents applications from the automotive and circuit industries that show that descriptor systems provide challenging problems from the point of view of both theory and practice.   The book contains nine papers and is organized into three parts: control, simulation, and model order reduction. It will serve as an ideal resource for applied mathematicians and engineers, in particular those from mechanics and electromagnetics, who work with coupled differential equations.

Systems biological approach of molecular descriptors connectivity: optimal descriptors for oral bioavailability prediction.

Science.gov (United States)

Ahmed, Shiek S S J; Ramakrishnan, V

2012-01-01

Poor oral bioavailability is an important parameter accounting for the failure of the drug candidates. Approximately, 50% of developing drugs fail because of unfavorable oral bioavailability. In silico prediction of oral bioavailability (%F) based on physiochemical properties are highly needed. Although many computational models have been developed to predict oral bioavailability, their accuracy remains low with a significant number of false positives. In this study, we present an oral bioavailability model based on systems biological approach, using a machine learning algorithm coupled with an optimal discriminative set of physiochemical properties. The models were developed based on computationally derived 247 physicochemical descriptors from 2279 molecules, among which 969, 605 and 705 molecules were corresponds to oral bioavailability, intestinal absorption (HIA) and caco-2 permeability data set, respectively. The partial least squares discriminate analysis showed 49 descriptors of HIA and 50 descriptors of caco-2 are the major contributing descriptors in classifying into groups. Of these descriptors, 47 descriptors were commonly associated to HIA and caco-2, which suggests to play a vital role in classifying oral bioavailability. To determine the best machine learning algorithm, 21 classifiers were compared using a bioavailability data set of 969 molecules with 47 descriptors. Each molecule in the data set was represented by a set of 47 physiochemical properties with the functional relevance labeled as (+bioavailability/-bioavailability) to indicate good-bioavailability/poor-bioavailability molecules. The best-performing algorithm was the logistic algorithm. The correlation based feature selection (CFS) algorithm was implemented, which confirms that these 47 descriptors are the fundamental descriptors for oral bioavailability prediction. The logistic algorithm with 47 selected descriptors correctly predicted the oral bioavailability, with a predictive accuracy

Representations for Semantic Learning Webs: Semantic Web Technology in Learning Support

Science.gov (United States)

Dzbor, M.; Stutt, A.; Motta, E.; Collins, T.

2007-01-01

Recent work on applying semantic technologies to learning has concentrated on providing novel means of accessing and making use of learning objects. However, this is unnecessarily limiting: semantic technologies will make it possible to develop a range of educational Semantic Web services, such as interpretation, structure-visualization, support…

Jet-Based Local Image Descriptors

DEFF Research Database (Denmark)

Larsen, Anders Boesen Lindbo; Darkner, Sune; Dahl, Anders Lindbjerg

2012-01-01

We present a general novel image descriptor based on higherorder differential geometry and investigate the effect of common descriptor choices. Our investigation is twofold in that we develop a jet-based descriptor and perform a comparative evaluation with current state-of-the-art descriptors on ...

Local Descriptors of Dynamic and Nondynamic Correlation.

Science.gov (United States)

Ramos-Cordoba, Eloy; Matito, Eduard

2017-06-13

Quantitatively accurate electronic structure calculations rely on the proper description of electron correlation. A judicious choice of the approximate quantum chemistry method depends upon the importance of dynamic and nondynamic correlation, which is usually assesed by scalar measures. Existing measures of electron correlation do not consider separately the regions of the Cartesian space where dynamic or nondynamic correlation are most important. We introduce real-space descriptors of dynamic and nondynamic electron correlation that admit orbital decomposition. Integration of the local descriptors yields global numbers that can be used to quantify dynamic and nondynamic correlation. Illustrative examples over different chemical systems with varying electron correlation regimes are used to demonstrate the capabilities of the local descriptors. Since the expressions only require orbitals and occupation numbers, they can be readily applied in the context of local correlation methods, hybrid methods, density matrix functional theory, and fractional-occupancy density functional theory.

Mordred: a molecular descriptor calculator.

Science.gov (United States)

Moriwaki, Hirotomo; Tian, Yu-Shi; Kawashita, Norihito; Takagi, Tatsuya

2018-02-06

Molecular descriptors are widely employed to present molecular characteristics in cheminformatics. Various molecular-descriptor-calculation software programs have been developed. However, users of those programs must contend with several issues, including software bugs, insufficient update frequencies, and software licensing constraints. To address these issues, we propose Mordred, a developed descriptor-calculation software application that can calculate more than 1800 two- and three-dimensional descriptors. It is freely available via GitHub. Mordred can be easily installed and used in the command line interface, as a web application, or as a high-flexibility Python package on all major platforms (Windows, Linux, and macOS). Performance benchmark results show that Mordred is at least twice as fast as the well-known PaDEL-Descriptor and it can calculate descriptors for large molecules, which cannot be accomplished by other software. Owing to its good performance, convenience, number of descriptors, and a lax licensing constraint, Mordred is a promising choice of molecular descriptor calculation software that can be utilized for cheminformatics studies, such as those on quantitative structure-property relationships.

The great descriptor melting pot: mixing descriptors for the common good of QSAR models.

Science.gov (United States)

Tseng, Yufeng J; Hopfinger, Anton J; Esposito, Emilio Xavier

2012-01-01

The usefulness and utility of QSAR modeling depends heavily on the ability to estimate the values of molecular descriptors relevant to the endpoints of interest followed by an optimized selection of descriptors to form the best QSAR models from a representative set of the endpoints of interest. The performance of a QSAR model is directly related to its molecular descriptors. QSAR modeling, specifically model construction and optimization, has benefited from its ability to borrow from other unrelated fields, yet the molecular descriptors that form QSAR models have remained basically unchanged in both form and preferred usage. There are many types of endpoints that require multiple classes of descriptors (descriptors that encode 1D through multi-dimensional, 4D and above, content) needed to most fully capture the molecular features and interactions that contribute to the endpoint. The advantages of QSAR models constructed from multiple, and different, descriptor classes have been demonstrated in the exploration of markedly different, and principally biological systems and endpoints. Multiple examples of such QSAR applications using different descriptor sets are described and that examined. The take-home-message is that a major part of the future of QSAR analysis, and its application to modeling biological potency, ADME-Tox properties, general use in virtual screening applications, as well as its expanding use into new fields for building QSPR models, lies in developing strategies that combine and use 1D through nD molecular descriptors.

Local intensity area descriptor for facial recognition in ideal and noise conditions

Science.gov (United States)

Tran, Chi-Kien; Tseng, Chin-Dar; Chao, Pei-Ju; Ting, Hui-Min; Chang, Liyun; Huang, Yu-Jie; Lee, Tsair-Fwu

2017-03-01

We propose a local texture descriptor, local intensity area descriptor (LIAD), which is applied for human facial recognition in ideal and noisy conditions. Each facial image is divided into small regions from which LIAD histograms are extracted and concatenated into a single feature vector to represent the facial image. The recognition is performed using a nearest neighbor classifier with histogram intersection and chi-square statistics as dissimilarity measures. Experiments were conducted with LIAD using the ORL database of faces (Olivetti Research Laboratory, Cambridge), the Face94 face database, the Georgia Tech face database, and the FERET database. The results demonstrated the improvement in accuracy of our proposed descriptor compared to conventional descriptors [local binary pattern (LBP), uniform LBP, local ternary pattern, histogram of oriented gradients, and local directional pattern]. Moreover, the proposed descriptor was less sensitive to noise and had low histogram dimensionality. Thus, it is expected to be a powerful texture descriptor that can be used for various computer vision problems.

RANZAR Body Systems Framework of diagnostic imaging examination descriptors

International Nuclear Information System (INIS)

Pitman, Alexander D.; Penlington, Lisa; Doromal, Darren; Vukolova, Natalia; Slater, Gregory

2014-01-01

A unified and logical system of descriptors for diagnostic imaging examinations and procedures is a desirable resource for radiology in Australia and New Zealand and is needed to support core activities of RANZCR. Existing descriptor systems available in Australia and New Zealand (including the Medicare DIST and the ACC Schedule) have significant limitations and are inappropriate for broader clinical application. An anatomically based grid was constructed, with anatomical structures arranged in rows and diagnostic imaging modalities arranged in columns (including nuclear medicine and positron emission tomography). The grid was segregated into five body systems. The cells at the intersection of an anatomical structure row and an imaging modality column were populated with short, formulaic descriptors of the applicable diagnostic imaging examinations. Clinically illogical or physically impossible combinations were ‘greyed out’. Where the same examination applied to different anatomical structures, the descriptor was kept identical for the purposes of streamlining. The resulting Body Systems Framework of diagnostic imaging examination descriptors lists all the reasonably common diagnostic imaging examinations currently performed in Australia and New Zealand using a unified grid structure allowing navigation by both referrers and radiologists. The Framework has been placed on the RANZCR website and is available for access free of charge by registered users. The Body Systems Framework of diagnostic imaging examination descriptors is a system of descriptors based on relationships between anatomical structures and imaging modalities. The Framework is now available as a resource and reference point for the radiology profession and to support core College activities.

RANZCR Body Systems Framework of diagnostic imaging examination descriptors.

Science.gov (United States)

Pitman, Alexander G; Penlington, Lisa; Doromal, Darren; Slater, Gregory; Vukolova, Natalia

2014-08-01

A unified and logical system of descriptors for diagnostic imaging examinations and procedures is a desirable resource for radiology in Australia and New Zealand and is needed to support core activities of RANZCR. Existing descriptor systems available in Australia and New Zealand (including the Medicare DIST and the ACC Schedule) have significant limitations and are inappropriate for broader clinical application. An anatomically based grid was constructed, with anatomical structures arranged in rows and diagnostic imaging modalities arranged in columns (including nuclear medicine and positron emission tomography). The grid was segregated into five body systems. The cells at the intersection of an anatomical structure row and an imaging modality column were populated with short, formulaic descriptors of the applicable diagnostic imaging examinations. Clinically illogical or physically impossible combinations were 'greyed out'. Where the same examination applied to different anatomical structures, the descriptor was kept identical for the purposes of streamlining. The resulting Body Systems Framework of diagnostic imaging examination descriptors lists all the reasonably common diagnostic imaging examinations currently performed in Australia and New Zealand using a unified grid structure allowing navigation by both referrers and radiologists. The Framework has been placed on the RANZCR website and is available for access free of charge by registered users. The Body Systems Framework of diagnostic imaging examination descriptors is a system of descriptors based on relationships between anatomical structures and imaging modalities. The Framework is now available as a resource and reference point for the radiology profession and to support core College activities. © 2014 The Royal Australian and New Zealand College of Radiologists.

Dyspnea descriptors developed in Brazil: application in obese patients and in patients with cardiorespiratory diseases.

Science.gov (United States)

Teixeira, Christiane Aires; Rodrigues Júnior, Antonio Luiz; Straccia, Luciana Cristina; Vianna, Elcio Dos Santos Oliveira; Silva, Geruza Alves da; Martinez, José Antônio Baddini

2011-01-01

To develop a set of descriptive terms applied to the sensation of dyspnea (dyspnea descriptors) for use in Brazil and to investigate the usefulness of these descriptors in four distinct clinical conditions that can be accompanied by dyspnea. We collected 111 dyspnea descriptors from 67 patients and 10 health professionals. These descriptors were analyzed and reduced to 15 based on their frequency of use, similarity of meaning, and potential pathophysiological value. Those 15 descriptors were applied in 50 asthma patients, 50 COPD patients, 30 patients with heart failure, and 50 patients with class II or III obesity. The three best descriptors, as selected by the patients, were studied by cluster analysis. Potential associations between the identified clusters and the four clinical conditions were also investigated. The use of this set of descriptors led to a solution with seven clusters, designated sufoco (suffocating), aperto (tight), rápido (rapid), fadiga (fatigue), abafado (stuffy), trabalho/inspiração (work/inhalation), and falta de ar (shortness of breath). Overlapping of descriptors was quite common among the patients, regardless of their clinical condition. Asthma was significantly associated with the sufoco and trabalho/inspiração clusters, whereas COPD and heart failure were associated with the sufoco, trabalho/inspiração, and falta de ar clusters. Obesity was associated only with the falta de ar cluster. In Brazil, patients who are accustomed to perceiving dyspnea employ various descriptors in order to describe the symptom, and these descriptors can be grouped into similar clusters. In our study sample, such clusters showed no usefulness in differentiating among the four clinical conditions evaluated.

DDC Descriptor Frequencies.

Science.gov (United States)

Klingbiel, Paul H.; Jacobs, Charles R.

This report summarizes the frequency of use of the 7144 descriptors used for indexing technical reports in the Defense Documentation Center (DDC) collection. The descriptors are arranged alphabetically in the first section and by frequency in the second section. The frequency data cover about 427,000 AD documents spanning the interval from March…

FEATURE DESCRIPTOR BY CONVOLUTION AND POOLING AUTOENCODERS

Directory of Open Access Journals (Sweden)

L. Chen

2015-03-01

Full Text Available In this paper we present several descriptors for feature-based matching based on autoencoders, and we evaluate the performance of these descriptors. In a training phase, we learn autoencoders from image patches extracted in local windows surrounding key points determined by the Difference of Gaussian extractor. In the matching phase, we construct key point descriptors based on the learned autoencoders, and we use these descriptors as the basis for local keypoint descriptor matching. Three types of descriptors based on autoencoders are presented. To evaluate the performance of these descriptors, recall and 1-precision curves are generated for different kinds of transformations, e.g. zoom and rotation, viewpoint change, using a standard benchmark data set. We compare the performance of these descriptors with the one achieved for SIFT. Early results presented in this paper show that, whereas SIFT in general performs better than the new descriptors, the descriptors based on autoencoders show some potential for feature based matching.

Word maturity indices with latent semantic analysis: why, when, and where is Procrustes rotation applied?

Science.gov (United States)

Jorge-Botana, Guillermo; Olmos, Ricardo; Luzón, José M

2018-01-01

The aim of this paper is to describe and explain one useful computational methodology to model the semantic development of word representation: Word maturity. In particular, the methodology is based on the longitudinal word monitoring created by Kirylev and Landauer using latent semantic analysis for the representation of lexical units. The paper is divided into two parts. First, the steps required to model the development of the meaning of words are explained in detail. We describe the technical and theoretical aspects of each step. Second, we provide a simple example of application of this methodology with some simple tools that can be used by applied researchers. This paper can serve as a user-friendly guide for researchers interested in modeling changes in the semantic representations of words. Some current aspects of the technique and future directions are also discussed. WIREs Cogn Sci 2018, 9:e1457. doi: 10.1002/wcs.1457 This article is categorized under: Computer Science > Natural Language Processing Linguistics > Language Acquisition Psychology > Development and Aging. © 2017 Wiley Periodicals, Inc.

The influence of certain molecular descriptors of fecal elimination of angiotensin II receptor antagonists

Directory of Open Access Journals (Sweden)

Trbojević-Stanković Jasna B.

2015-01-01

Full Text Available Angiotensin II receptor antagonists (ARBs modulate the function of the renin-angiotensin-aldosterone system and are commonly prescribed antihypertensive drugs, especially in patients with renal failure. In this study, the relationship between several molecular properties of seven ARBs (candesartan, eprosartan, irbesartan, losartan, olmesartan, telmisartan, valsartan and their fecal elimination data obtained from the literature were investigated. The ARB molecular descriptors were calculated using three software packages. Simple linear regression analysis showed the best 2 correlation between fecal elimination data and lipophilicity descriptor, ClogP values (R2 = 0.725. Multiple linear regression was applied to examine the correlation of ARBs’ fecal elimination data with their lipophilicity and one additional, calculated descriptor. The best correlation (R2 = 0.909 with an acceptable probability value, P <0.05 was established between the ARB fecal elimination data and their lipophilicity and aqueous solubility data. Applying computed molecular descriptors for evaluating drug elimination is of great importance in drug research.

Shuffling cross-validation-bee algorithm as a new descriptor selection method for retention studies of pesticides in biopartitioning micellar chromatography.

Science.gov (United States)

Zarei, Kobra; Atabati, Morteza; Ahmadi, Monire

2017-05-04

Bee algorithm (BA) is an optimization algorithm inspired by the natural foraging behaviour of honey bees to find the optimal solution which can be proposed to feature selection. In this paper, shuffling cross-validation-BA (CV-BA) was applied to select the best descriptors that could describe the retention factor (log k) in the biopartitioning micellar chromatography (BMC) of 79 heterogeneous pesticides. Six descriptors were obtained using BA and then the selected descriptors were applied for model development using multiple linear regression (MLR). The descriptor selection was also performed using stepwise, genetic algorithm and simulated annealing methods and MLR was applied to model development and then the results were compared with those obtained from shuffling CV-BA. The results showed that shuffling CV-BA can be applied as a powerful descriptor selection method. Support vector machine (SVM) was also applied for model development using six selected descriptors by BA. The obtained statistical results using SVM were better than those obtained using MLR, as the root mean square error (RMSE) and correlation coefficient (R) for whole data set (training and test), using shuffling CV-BA-MLR, were obtained as 0.1863 and 0.9426, respectively, while these amounts for the shuffling CV-BA-SVM method were obtained as 0.0704 and 0.9922, respectively.

GenMol trademark supramolecular descriptors predicting reliable sensitivity of energetic compounds

Energy Technology Data Exchange (ETDEWEB)

Benazet, Stephane; Jacob, Guy [SNPE Materiaux Energetiques, Vert Le Petit (France); Pepe, Gerard [CINaM UPR-CNRS 3118, Campus de Luminy Case, Marseille (France)

2009-04-15

Structure/activity relationship methodology has been applied to the problem of the prediction of the energetic molecule's sensitivity. This parameter knowledge is of great importance to increase the safety of operations in the field of synthesis and manipulation of such compounds. It has been shown that descriptors of the solid state interactions and surface topology issued from GenMol {sup trademark} software calculations greatly enhanced the correlation between measured and predicted sensitivity. As the structural parameters used to establish the descriptors are experimental ones, their physical significance is particularly preserved which allows to give a good prediction for impact or friction sensitivity by the so defined descriptors. (Abstract Copyright [2009], Wiley Periodicals, Inc.)

Functional Constructivism: In Search of Formal Descriptors.

Science.gov (United States)

Trofimova, Irina

2017-10-01

The Functional Constructivism (FC) paradigm is an alternative to behaviorism and considers behavior as being generated every time anew, based on an individual's capacities, environmental resources and demands. Walter Freeman's work provided us with evidence supporting the FC principles. In this paper we make parallels between gradual construction processes leading to the formation of individual behavior and habits, and evolutionary processes leading to the establishment of biological systems. Referencing evolutionary theory, several formal descriptors of such processes are proposed. These FC descriptors refer to the most universal aspects for constructing consistent structures: expansion of degrees of freedom, integration processes based on internal and external compatibility between systems and maintenance processes, all given in four different classes of systems: (a) Zone of Proximate Development (poorly defined) systems; (b) peer systems with emerging reproduction of multiple siblings; (c) systems with internalized integration of behavioral elements ('cruise controls'); and (d) systems capable of handling low-probability, not yet present events. The recursive dynamics within this set of descriptors acting on (traditional) downward, upward and horizontal directions of evolution, is conceptualized as diagonal evolution, or di-evolution. Two examples applying these FC descriptors to taxonomy are given: classification of the functionality of neuro-transmitters and temperament traits; classification of mental disorders. The paper is an early step towards finding a formal language describing universal tendencies in highly diverse, complex and multi-level transient systems known in ecology and biology as 'contingency cycles.'

Automated detection of microaneurysms using robust blob descriptors

Science.gov (United States)

Adal, K.; Ali, S.; Sidibé, D.; Karnowski, T.; Chaum, E.; Mériaudeau, F.

2013-03-01

Microaneurysms (MAs) are among the first signs of diabetic retinopathy (DR) that can be seen as round dark-red structures in digital color fundus photographs of retina. In recent years, automated computer-aided detection and diagnosis (CAD) of MAs has attracted many researchers due to its low-cost and versatile nature. In this paper, the MA detection problem is modeled as finding interest points from a given image and several interest point descriptors are introduced and integrated with machine learning techniques to detect MAs. The proposed approach starts by applying a novel fundus image contrast enhancement technique using Singular Value Decomposition (SVD) of fundus images. Then, Hessian-based candidate selection algorithm is applied to extract image regions which are more likely to be MAs. For each candidate region, robust low-level blob descriptors such as Speeded Up Robust Features (SURF) and Intensity Normalized Radon Transform are extracted to characterize candidate MA regions. The combined features are then classified using SVM which has been trained using ten manually annotated training images. The performance of the overall system is evaluated on Retinopathy Online Challenge (ROC) competition database. Preliminary results show the competitiveness of the proposed candidate selection techniques against state-of-the art methods as well as the promising future for the proposed descriptors to be used in the localization of MAs from fundus images.

Word-embeddings Italian semantic spaces: A semantic model for psycholinguistic research

Directory of Open Access Journals (Sweden)

Marelli Marco

2017-01-01

Full Text Available Distributional semantics has been for long a source of successful models in psycholinguistics, permitting to obtain semantic estimates for a large number of words in an automatic and fast way. However, resources in this respect remain scarce or limitedly accessible for languages different from English. The present paper describes WEISS (Word-Embeddings Italian Semantic Space, a distributional semantic model based on Italian. WEISS includes models of semantic representations that are trained adopting state-of-the-art word-embeddings methods, applying neural networks to induce distributed representations for lexical meanings. The resource is evaluated against two test sets, demonstrating that WEISS obtains a better performance with respect to a baseline encoding word associations. Moreover, an extensive qualitative analysis of the WEISS output provides examples of the model potentialities in capturing several semantic phenomena. Two variants of WEISS are released and made easily accessible via web through the SNAUT graphic interface.

How diverse are diversity assessment methods? A comparative analysis and benchmarking of molecular descriptor space.

Science.gov (United States)

Koutsoukas, Alexios; Paricharak, Shardul; Galloway, Warren R J D; Spring, David R; Ijzerman, Adriaan P; Glen, Robert C; Marcus, David; Bender, Andreas

2014-01-27

Chemical diversity is a widely applied approach to select structurally diverse subsets of molecules, often with the objective of maximizing the number of hits in biological screening. While many methods exist in the area, few systematic comparisons using current descriptors in particular with the objective of assessing diversity in bioactivity space have been published, and this shortage is what the current study is aiming to address. In this work, 13 widely used molecular descriptors were compared, including fingerprint-based descriptors (ECFP4, FCFP4, MACCS keys), pharmacophore-based descriptors (TAT, TAD, TGT, TGD, GpiDAPH3), shape-based descriptors (rapid overlay of chemical structures (ROCS) and principal moments of inertia (PMI)), a connectivity-matrix-based descriptor (BCUT), physicochemical-property-based descriptors (prop2D), and a more recently introduced molecular descriptor type (namely, "Bayes Affinity Fingerprints"). We assessed both the similar behavior of the descriptors in assessing the diversity of chemical libraries, and their ability to select compounds from libraries that are diverse in bioactivity space, which is a property of much practical relevance in screening library design. This is particularly evident, given that many future targets to be screened are not known in advance, but that the library should still maximize the likelihood of containing bioactive matter also for future screening campaigns. Overall, our results showed that descriptors based on atom topology (i.e., fingerprint-based descriptors and pharmacophore-based descriptors) correlate well in rank-ordering compounds, both within and between descriptor types. On the other hand, shape-based descriptors such as ROCS and PMI showed weak correlation with the other descriptors utilized in this study, demonstrating significantly different behavior. We then applied eight of the molecular descriptors compared in this study to sample a diverse subset of sample compounds (4%) from an

Reactive Kripke semantics

CERN Document Server

Gabbay, Dov M

2013-01-01

This text offers an extension to the traditional Kripke semantics for non-classical logics by adding the notion of reactivity. Reactive Kripke models change their accessibility relation as we progress in the evaluation process of formulas in the model. This feature makes the reactive Kripke semantics strictly stronger and more applicable than the traditional one. Here we investigate the properties and axiomatisations of this new and most effective semantics, and we offer a wide landscape of applications of the idea of reactivity. Applied topics include reactive automata, reactive grammars, rea

Semantic Versus Syntactic Cutting Planes

OpenAIRE

Filmus, Yuval; Hrubeš, Pavel; Lauria, Massimo

2016-01-01

In this paper, we compare the strength of the semantic and syntactic version of the cutting planes proof system. First, we show that the lower bound technique of Pudlák applies also to semantic cutting planes: the proof system has feasible interpolation via monotone real circuits, which gives an exponential lower bound on lengths of semantic cutting planes refutations. Second, we show that semantic refutations are stronger than syntactic ones. In particular, we give a formula for whic...

The Evaluation of Angiotensin-Converting Enzyme Inhibitors in Renal Elimination with Selected Molecular Descriptors

Directory of Open Access Journals (Sweden)

Trbojevic Jovana

2017-06-01

Full Text Available Angiotensin-converting enzyme (ACE inhibitors modulate the function of the renin-angiotensin-aldosterone system, and they are commonly prescribed antihypertensive drugs especially in patients with renal failure. In this study, the relationships between several molecular properties of eight ACE inhibitors (enalapril, quinapril, fosinopril, ramipril, benazepril, perindopril, moexipril, trandolapril and their renal elimination data, from relevant literature, were investigated. The ’molecular descriptors of the ACE inhibitors, which included aqueous solubility data (logS; an electronic descriptor, polar surface area (PSA;, a constitutional parameter, molecular mass (Mr; and a geometric descriptor, volume value (Vol, as well as lipophilicity descriptors (logP values, were calculated using different software packages. Simple linear regression analysis showed the best correlation between renal elimination data and lipophilicity descriptor AClogP values (R2 = 0.5742. In the next stage of the study, multiple linear regression was applied to assess a higher correlation between the ACE inhibitors’ renal elimination data and lipophilicity, AClogP, with one additional descriptor as an independent variable. Good correlations were established between renal elimination data from the literature and the AClogP lipophilicity descriptor using the constitutional parameter (molecular mass (R2 = 0.7425 or the geometric descriptor (volume value (R2 = 0.7224 as an independent variable. The application of computed molecular descriptors in evaluating drug elimination is of great importance in drug research.

Novel topological descriptors for analyzing biological networks

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Varmuza Kurt K

2010-06-01

Full Text Available Abstract Background Topological descriptors, other graph measures, and in a broader sense, graph-theoretical methods, have been proven as powerful tools to perform biological network analysis. However, the majority of the developed descriptors and graph-theoretical methods does not have the ability to take vertex- and edge-labels into account, e.g., atom- and bond-types when considering molecular graphs. Indeed, this feature is important to characterize biological networks more meaningfully instead of only considering pure topological information. Results In this paper, we put the emphasis on analyzing a special type of biological networks, namely bio-chemical structures. First, we derive entropic measures to calculate the information content of vertex- and edge-labeled graphs and investigate some useful properties thereof. Second, we apply the mentioned measures combined with other well-known descriptors to supervised machine learning methods for predicting Ames mutagenicity. Moreover, we investigate the influence of our topological descriptors - measures for only unlabeled vs. measures for labeled graphs - on the prediction performance of the underlying graph classification problem. Conclusions Our study demonstrates that the application of entropic measures to molecules representing graphs is useful to characterize such structures meaningfully. For instance, we have found that if one extends the measures for determining the structural information content of unlabeled graphs to labeled graphs, the uniqueness of the resulting indices is higher. Because measures to structurally characterize labeled graphs are clearly underrepresented so far, the further development of such methods might be valuable and fruitful for solving problems within biological network analysis.

Enrichment of true positives from structural alerts through the use of novel atomic fragment based descriptors

DEFF Research Database (Denmark)

Long, A.; Rydberg, Patrik

2013-01-01

To enhance the discrimination rate for methods applying structural alerts and biotransformation rules in the prediction of toxicity and drug metabolism we have developed a set of novel fragment based atomic descriptors. These atomic descriptors encode the properties of the fragments separating an...

Semantic Analysis of Multimedial Information Usign Both Audio and Visual Clues

Directory of Open Access Journals (Sweden)

Andrej Lukac

2008-01-01

Full Text Available Nowadays, there is a lot of information in databases (text, audio/video form, etc.. It is important to be able to describe this data for better orientation in them. It is necessary to apply audio/video properties, which are used for metadata management, segmenting the document into semantically meaningful units, classifying each unit into a predefined scene type, indexing, summarizing the document for efficient retrieval and browsing. Data can be used for system that automatically searches for a specific person in a sequence also for special video sequences. Audio/video properties are presented by descriptors and description schemes. There are many features that can be used to characterize multimedial signals. We can analyze audio and video sequences jointly or considered them completely separately. Our aim is oriented to possibilities of combining multimedial features. Focus is direct into discussion programs, because there are more decisions how to combine audio features with video sequences.

Dynamic Post-Earthquake Image Segmentation with an Adaptive Spectral-Spatial Descriptor

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Genyun Sun

2017-08-01

Full Text Available The region merging algorithm is a widely used segmentation technique for very high resolution (VHR remote sensing images. However, the segmentation of post-earthquake VHR images is more difficult due to the complexity of these images, especially high intra-class and low inter-class variability among damage objects. Herein two key issues must be resolved: the first is to find an appropriate descriptor to measure the similarity of two adjacent regions since they exhibit high complexity among the diverse damage objects, such as landslides, debris flow, and collapsed buildings. The other is how to solve over-segmentation and under-segmentation problems, which are commonly encountered with conventional merging strategies due to their strong dependence on local information. To tackle these two issues, an adaptive dynamic region merging approach (ADRM is introduced, which combines an adaptive spectral-spatial descriptor and a dynamic merging strategy to adapt to the changes of merging regions for successfully detecting objects scattered globally in a post-earthquake image. In the new descriptor, the spectral similarity and spatial similarity of any two adjacent regions are automatically combined to measure their similarity. Accordingly, the new descriptor offers adaptive semantic descriptions for geo-objects and thus is capable of characterizing different damage objects. Besides, in the dynamic region merging strategy, the adaptive spectral-spatial descriptor is embedded in the defined testing order and combined with graph models to construct a dynamic merging strategy. The new strategy can find the global optimal merging order and ensures that the most similar regions are merged at first. With combination of the two strategies, ADRM can identify spatially scattered objects and alleviates the phenomenon of over-segmentation and under-segmentation. The performance of ADRM has been evaluated by comparing with four state-of-the-art segmentation methods

Relationship Structures and Semantic Type Assignments of the UMLS Enriched Semantic Network

Science.gov (United States)

Zhang, Li; Halper, Michael; Perl, Yehoshua; Geller, James; Cimino, James J.

2005-01-01

Objective: The Enriched Semantic Network (ESN) was introduced as an extension of the Unified Medical Language System (UMLS) Semantic Network (SN). Its multiple subsumption configuration and concomitant multiple inheritance make the ESN's relationship structures and semantic type assignments different from those of the SN. A technique for deriving the relationship structures of the ESN's semantic types and an automated technique for deriving the ESN's semantic type assignments from those of the SN are presented. Design: The technique to derive the ESN's relationship structures finds all newly inherited relationships in the ESN. All such relationships are audited for semantic validity, and the blocking mechanism is used to block invalid relationships. The mapping technique to derive the ESN's semantic type assignments uses current SN semantic type assignments and preserves nonredundant categorizations, while preventing new redundant categorizations. Results: Among the 426 newly inherited relationships, 326 are deemed valid. Seven blockings are applied to avoid inheritance of the 100 invalid relationships. Sixteen semantic types have different relationship structures in the ESN as compared to those in the SN. The mapping of semantic type assignments from the SN to the ESN avoids the generation of 26,950 redundant categorizations. The resulting ESN contains 138 semantic types, 149 IS-A links, 7,303 relationships, and 1,013,876 semantic type assignments. Conclusion: The ESN's multiple inheritance provides more complete relationship structures than in the SN. The ESN's semantic type assignments avoid the existing redundant categorizations appearing in the SN and prevent new ones that might arise due to multiple parents. Compared to the SN, the ESN provides a more accurate unifying semantic abstraction of the UMLS Metathesaurus. PMID:16049233

A comparison between space-time video descriptors

Science.gov (United States)

Costantini, Luca; Capodiferro, Licia; Neri, Alessandro

2013-02-01

The description of space-time patches is a fundamental task in many applications such as video retrieval or classification. Each space-time patch can be described by using a set of orthogonal functions that represent a subspace, for example a sphere or a cylinder, within the patch. In this work, our aim is to investigate the differences between the spherical descriptors and the cylindrical descriptors. In order to compute the descriptors, the 3D spherical and cylindrical Zernike polynomials are employed. This is important because both the functions are based on the same family of polynomials, and only the symmetry is different. Our experimental results show that the cylindrical descriptor outperforms the spherical descriptor. However, the performances of the two descriptors are similar.

Topological Substituent Descriptors

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Mircea V. DIUDEA

2002-12-01

Full Text Available Motivation. Substituted 1,3,5-triazines are known as useful herbicidal substances. In view of reducing the cost of biological screening, computational methods are carried out for evaluating the biological activity of organic compounds. Often a class of bioactives differs only in the substituent attached to a basic skeleton. In such cases substituent descriptors will give the same prospecting results as in case of using the whole molecule description, but with significantly reduced computational time. Such descriptors are useful in describing steric effects involved in chemical reactions. Method. Molecular topology is the method used for substituent description and multi linear regression analysis as a statistical tool. Results. Novel topological descriptors, XLDS and Ws, based on the layer matrix of distance sums and walks in molecular graphs, respectively, are proposed for describing the topology of substituents linked on a chemical skeleton. They are tested for modeling the esterification reaction in the class of benzoic acids and herbicidal activity of 2-difluoromethylthio-4,6-bis(monoalkylamino-1,3,5-triazines. Conclusions. Ws substituent descriptor, based on walks in graph, satisfactorily describes the steric effect of alkyl substituents behaving in esterification reaction, with good correlations to the Taft and Charton steric parameters, respectively. Modeling the herbicidal activity of the seo of 1,3,5-triazines exceeded the models reported in literature, so far.

TreeBASIS Feature Descriptor and Its Hardware Implementation

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Spencer Fowers

2014-01-01

Full Text Available This paper presents a novel feature descriptor called TreeBASIS that provides improvements in descriptor size, computation time, matching speed, and accuracy. This new descriptor uses a binary vocabulary tree that is computed using basis dictionary images and a test set of feature region images. To facilitate real-time implementation, a feature region image is binary quantized and the resulting quantized vector is passed into the BASIS vocabulary tree. A Hamming distance is then computed between the feature region image and the effectively descriptive basis dictionary image at a node to determine the branch taken and the path the feature region image takes is saved as a descriptor. The TreeBASIS feature descriptor is an excellent candidate for hardware implementation because of its reduced descriptor size and the fact that descriptors can be created and features matched without the use of floating point operations. The TreeBASIS descriptor is more computationally and space efficient than other descriptors such as BASIS, SIFT, and SURF. Moreover, it can be computed entirely in hardware without the support of a CPU for additional software-based computations. Experimental results and a hardware implementation show that the TreeBASIS descriptor compares well with other descriptors for frame-to-frame homography computation while requiring fewer hardware resources.

Semantic markup of nouns and adjectives for the Electronic corpus of texts in Tuvan language

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Bajlak Ch. Oorzhak

2016-12-01

Full Text Available The article examines the progress of semantic markup of the Electronic corpus of texts in Tuvan language (ECTTL, which is another stage of adding Tuvan texts to the database and marking up the corpus. ECTTL is a collaborative project by researchers from Tuvan State University (Research and Education Center of Turkic Studies and Department of Information Technologies. Semantic markup of Tuvan lexis will come as a search engine and reference system which will help users find text snippets containing words with desired meanings in ECTTL. The first stage of this process is setting up databases of basic lexemes of Tuvan language. All meaningful lexemes were classified into the following semantic groups: humans, animals, objects, natural objects and phenomena, and abstract concepts. All Tuvan object nouns, as well as both descriptive and relative adjectives, were assigned to one of these lexico-semantic classes. Each class, sub-class and descriptor is tagged in Tuvan, Russian and English; these tags, in turn, will help automatize searching. The databases of meaningful lexemes of Tuvan language will also outline their lexical combinations. The automatized system will contain information on semantic combinations of adjectives with nouns, adverbs with verbs, nouns with verbs, as well as on the combinations which are semantically incompatible.

Fourier descriptors analysis of anisotropy and preferred Orientation in geological samples

International Nuclear Information System (INIS)

Santiago Buey, C. de

2011-01-01

This study focuses on the use of Fourier descriptors to evaluate and quantify two specific fabric characteristics of geological materials: anisotropy of particles or voids morphologies and particle orientation. To this end, a theoretical section of a rock was created, made of ellipses and rectangles of different axes ratios and different orientations. The Fourier descriptors method was applied to calculate the anisotropy and orientation of each particle and, finally, a rose diagram was constructed to represent the particles orientations distribution and to observe the presence or not of any preferred orientation. (Author) 15 refs.

Simple idea to generate fragment and pharmacophore descriptors and their implications in chemical informatics.

Science.gov (United States)

Catana, Cornel

2009-03-01

Using a well-defined set of fragments/pharmacophores, a new methodology to calculate fragment/ pharmacophore descriptors for any molecule onto which at least one fragment/pharmacophore can be mapped is presented. To each fragment/pharmacophore present in a molecule, we attach a descriptor that is calculated by identifying the molecule's atoms onto which it maps and summing over its constituent atomic descriptors. The attached descriptors are named C-fragment/pharmacophore descriptors, and this methodology can be applied to any descriptors defined at the atomic level, such as the partition coefficient, molar refractivity, electrotopological state, etc. By using this methodology, the same fragment/pharmacophore can be shown to have different values in different molecules resulting in better discrimination power. As we know, fragment and pharmacophore fingerprints have a lot of applications in chemical informatics. This study has attempted to find the impact of replacing the traditional value of "1" in a fingerprint with real numbers derived form C-fragment/pharmacophore descriptors. One way to do this is to assess the utility of C-fragment/ pharmacophore descriptors in modeling different end points. Here, we exemplify with data from CYP and hERG. The fact that, in many cases, the obtained models were fairly successful and C-fragment descriptors were ranked among the top ones supports the idea that they play an important role in correlation. When we modeled hERG with C-pharmacophore descriptors, however, the model performances decreased slightly, and we attribute this, mainly to the fact that there is no technique capable of handling multiple instances (states). We hope this will open new research, especially in the emerging field of machine learning. Further research is needed to see the impact of C-fragment/pharmacophore descriptors in similarity/dissimilarity applications.

Benchmarking of protein descriptor sets in proteochemometric modeling (part 2): modeling performance of 13 amino acid descriptor sets

Science.gov (United States)

2013-01-01

Background While a large body of work exists on comparing and benchmarking descriptors of molecular structures, a similar comparison of protein descriptor sets is lacking. Hence, in the current work a total of 13 amino acid descriptor sets have been benchmarked with respect to their ability of establishing bioactivity models. The descriptor sets included in the study are Z-scales (3 variants), VHSE, T-scales, ST-scales, MS-WHIM, FASGAI, BLOSUM, a novel protein descriptor set (termed ProtFP (4 variants)), and in addition we created and benchmarked three pairs of descriptor combinations. Prediction performance was evaluated in seven structure-activity benchmarks which comprise Angiotensin Converting Enzyme (ACE) dipeptidic inhibitor data, and three proteochemometric data sets, namely (1) GPCR ligands modeled against a GPCR panel, (2) enzyme inhibitors (NNRTIs) with associated bioactivities against a set of HIV enzyme mutants, and (3) enzyme inhibitors (PIs) with associated bioactivities on a large set of HIV enzyme mutants. Results The amino acid descriptor sets compared here show similar performance (set differences ( > 0.3 log units RMSE difference and >0.7 difference in MCC). Combining different descriptor sets generally leads to better modeling performance than utilizing individual sets. The best performers were Z-scales (3) combined with ProtFP (Feature), or Z-Scales (3) combined with an average Z-Scale value for each target, while ProtFP (PCA8), ST-Scales, and ProtFP (Feature) rank last. Conclusions While amino acid descriptor sets capture different aspects of amino acids their ability to be used for bioactivity modeling is still – on average – surprisingly similar. Still, combining sets describing complementary information consistently leads to small but consistent improvement in modeling performance (average MCC 0.01 better, average RMSE 0.01 log units lower). Finally, performance differences exist between the targets compared thereby underlining that

Fingerprint Identification Using SIFT-Based Minutia Descriptors and Improved All Descriptor-Pair Matching

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Jiuqiang Han

2013-03-01

Full Text Available The performance of conventional minutiae-based fingerprint authentication algorithms degrades significantly when dealing with low quality fingerprints with lots of cuts or scratches. A similar degradation of the minutiae-based algorithms is observed when small overlapping areas appear because of the quite narrow width of the sensors. Based on the detection of minutiae, Scale Invariant Feature Transformation (SIFT descriptors are employed to fulfill verification tasks in the above difficult scenarios. However, the original SIFT algorithm is not suitable for fingerprint because of: (1 the similar patterns of parallel ridges; and (2 high computational resource consumption. To enhance the efficiency and effectiveness of the algorithm for fingerprint verification, we propose a SIFT-based Minutia Descriptor (SMD to improve the SIFT algorithm through image processing, descriptor extraction and matcher. A two-step fast matcher, named improved All Descriptor-Pair Matching (iADM, is also proposed to implement the 1:N verifications in real-time. Fingerprint Identification using SMD and iADM (FISiA achieved a significant improvement with respect to accuracy in representative databases compared with the conventional minutiae-based method. The speed of FISiA also can meet real-time requirements.

Ant colony optimization as a descriptor selection in QSPR modeling: Estimation of the λmax of anthraquinones-based dyes

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Morteza Atabati

2016-09-01

Full Text Available Quantitative structure–property relationship (QSPR studies based on ant colony optimization (ACO were carried out for the prediction of λmax of 9,10-anthraquinone derivatives. ACO is a meta-heuristic algorithm, which is derived from the observation of real ants and proposed to feature selection. After optimization of 3D geometry of structures by the semi-empirical quantum-chemical calculation at AM1 level, different descriptors were calculated by the HyperChem and Dragon softwares (1514 descriptors. A major problem of QSPR is the high dimensionality of the descriptor space; therefore, descriptor selection is the most important step. In this paper, an ACO algorithm was used to select the best descriptors. Then selected descriptors were applied for model development using multiple linear regression. The average absolute relative deviation and correlation coefficient for the calibration set were obtained as 3.3% and 0.9591, respectively, while the average absolute relative deviation and correlation coefficient for the prediction set were obtained as 5.0% and 0.9526, respectively. The results showed that the applied procedure is suitable for prediction of λmax of 9,10-anthraquinone derivatives.

Replenishing data descriptors in a DMA injection FIFO buffer

Science.gov (United States)

Archer, Charles J [Rochester, MN; Blocksome, Michael A [Rochester, MN; Cernohous, Bob R [Rochester, MN; Heidelberger, Philip [Cortlandt Manor, NY; Kumar, Sameer [White Plains, NY; Parker, Jeffrey J [Rochester, MN

2011-10-11

Methods, apparatus, and products are disclosed for replenishing data descriptors in a Direct Memory Access (`DMA`) injection first-in-first-out (`FIFO`) buffer that include: determining, by a messaging module on an origin compute node, whether a number of data descriptors in a DMA injection FIFO buffer exceeds a predetermined threshold, each data descriptor specifying an application message for transmission to a target compute node; queuing, by the messaging module, a plurality of new data descriptors in a pending descriptor queue if the number of the data descriptors in the DMA injection FIFO buffer exceeds the predetermined threshold; establishing, by the messaging module, interrupt criteria that specify when to replenish the injection FIFO buffer with the plurality of new data descriptors in the pending descriptor queue; and injecting, by the messaging module, the plurality of new data descriptors into the injection FIFO buffer in dependence upon the interrupt criteria.

SVM prediction of ligand-binding sites in bacterial lipoproteins employing shape and physio-chemical descriptors.

Science.gov (United States)

Kadam, Kiran; Prabhakar, Prashant; Jayaraman, V K

2012-11-01

Bacterial lipoproteins play critical roles in various physiological processes including the maintenance of pathogenicity and numbers of them are being considered as potential candidates for generating novel vaccines. In this work, we put forth an algorithm to identify and predict ligand-binding sites in bacterial lipoproteins. The method uses three types of pocket descriptors, namely fpocket descriptors, 3D Zernike descriptors and shell descriptors, and combines them with Support Vector Machine (SVM) method for the classification. The three types of descriptors represent shape-based properties of the pocket as well as its local physio-chemical features. All three types of descriptors, along with their hybrid combinations are evaluated with SVM and to improve classification performance, WEKA-InfoGain feature selection is applied. Results obtained in the study show that the classifier successfully differentiates between ligand-binding and non-binding pockets. For the combination of three types of descriptors, 10 fold cross-validation accuracy of 86.83% is obtained for training while the selected model achieved test Matthews Correlation Coefficient (MCC) of 0.534. Individually or in combination with new and existing methods, our model can be a very useful tool for the prediction of potential ligand-binding sites in bacterial lipoproteins.

Separability of local reactivity descriptors

Indian Academy of Sciences (India)

Unknown

Abstract. The size-dependence of different local reactivity descriptors of dimer A2 and AB type of sys- tems is discussed. We derive analytic results of these descriptors calculated using finite difference approximation. In particular, we studied Fukui functions, relative electrophilicity and relative nucleo- philicity, local softness ...

Evaluating color descriptors for object and scene recognition.

Science.gov (United States)

van de Sande, Koen E A; Gevers, Theo; Snoek, Cees G M

2010-09-01

Image category recognition is important to access visual information on the level of objects and scene types. So far, intensity-based descriptors have been widely used for feature extraction at salient points. To increase illumination invariance and discriminative power, color descriptors have been proposed. Because many different descriptors exist, a structured overview is required of color invariant descriptors in the context of image category recognition. Therefore, this paper studies the invariance properties and the distinctiveness of color descriptors (software to compute the color descriptors from this paper is available from http://www.colordescriptors.com) in a structured way. The analytical invariance properties of color descriptors are explored, using a taxonomy based on invariance properties with respect to photometric transformations, and tested experimentally using a data set with known illumination conditions. In addition, the distinctiveness of color descriptors is assessed experimentally using two benchmarks, one from the image domain and one from the video domain. From the theoretical and experimental results, it can be derived that invariance to light intensity changes and light color changes affects category recognition. The results further reveal that, for light intensity shifts, the usefulness of invariance is category-specific. Overall, when choosing a single descriptor and no prior knowledge about the data set and object and scene categories is available, the OpponentSIFT is recommended. Furthermore, a combined set of color descriptors outperforms intensity-based SIFT and improves category recognition by 8 percent on the PASCAL VOC 2007 and by 7 percent on the Mediamill Challenge.

SEMANTIC WEB MINING: ISSUES AND CHALLENGES

OpenAIRE

Karan Singh*, Anil kumar, Arun Kumar Yadav

2016-01-01

The combination of the two fast evolving scientific research areas “Semantic Web” and “Web Mining” are well-known as “Semantic Web Mining” in computer science. These two areas cover way for the mining of related and meaningful information from the web, by this means giving growth to the term “Semantic Web Mining”. The “Semantic Web” makes mining easy and “Web Mining” can construct new structure of Web. Web Mining applies Data Mining technique on web content, Structure and Usage. This paper gi...

Descriptors of server capabilities in China

DEFF Research Database (Denmark)

Adeyemi, Oluseyi; Slepniov, Dmitrij; Wæhrens, Brian Vejrum

are relevant to determine subsidiary roles and as an indication of the capabilities required. These descriptors are identified through extensive literature review and validated by case studies of two Danish multinational companies subsidiaries operating in China. They provided the empirical basis......China with the huge market potential it possesses is an important issue for subsidiaries of western multinational companies. The objective of this paper is therefore to strengthen researchers’ and practitioners’ perspectives on what are the descriptors of server capabilities. The descriptors...

Surface Area Distribution Descriptor for object matching

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Mohamed F. Gafar

2010-07-01

Full Text Available Matching 3D objects by their similarity is a fundamental problem in computer vision, computer graphics and many other fields. The main challenge in object matching is to find a suitable shape representation that can be used to accurately and quickly discriminate between similar and dissimilar shapes. In this paper we present a new volumetric descriptor to represent 3D objects. The proposed descriptor is used to match objects under rigid transformations including uniform scaling. The descriptor represents the object by dividing it into shells, acquiring the area distribution of the object through those shells. The computed areas are normalised to make the descriptor scale-invariant in addition to rotation and translation invariant. The effectiveness and stability of the proposed descriptor to noise and variant sampling density as well as the effectiveness of the similarity measures are analysed and demonstrated through experimental results.

Descriptor revision belief change through direct choice

CERN Document Server

Hansson, Sven Ove

2017-01-01

This book provides a critical examination of how the choice of what to believe is represented in the standard model of belief change. In particular the use of possible worlds and infinite remainders as objects of choice is critically examined. Descriptors are introduced as a versatile tool for expressing the success conditions of belief change, addressing both local and global descriptor revision. The book presents dynamic descriptors such as Ramsey descriptors that convey how an agent’s beliefs tend to be changed in response to different inputs. It also explores sentential revision and demonstrates how local and global operations of revision by a sentence can be derived as a special case of descriptor revision. Lastly, the book examines revocation, a generalization of contraction in which a specified sentence is removed in a process that may possibly also involve the addition of some new information to the belief set.

Semantics of Kinship Terms in Tamil from the Semantic Typology Point of View

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Анна Александровна Смирнитская

2016-12-01

Full Text Available In this article the author examines the lexical-semantic group “kinship terms” in Tamil, applying the attainments of modern semantic typology and the theory of semantic derivation. The kinship terms describing nuclear and extended family are explored. The “semantic shift” relation between two different meanings is established if such relation is realized by synchronous polysemy in one lexeme, semantic derivation, diachronic semantic change, cognates or some other means. The starting point of the study is the typological data from the DatSemShift catalogue of semantic shifts in languages of the world developed by a group of researchers under the guidance of Anna A. Zalizniak in the Institute of Linguistics, RAS. We verify the presence of semantic shifts described in the Database in Tamil. Also, we propose new semantic shifts specific only for this language. We confirm the presence of semantic relation of the studied type among the meanings with English “labels”: father - parents, girl - daughter, to deliver (a child - parents, - child, old woman - wife, owner - wife and others. The data also allows the assumption that the same relation exists between the meanings: old - grandfather, earth - mother, son - courage, unripe - son and others. The meanings of this field are the sources of semantic movements to abstract notions, lexicon of posession, forms of address and others; in addition many inner semantic relations inside this field are revealed. The meanings covering the nuclear part of the kinship system participate in universal semantic shifts described in the DatSemShift catalogue, while the meanings from collateral branches of this bifurcative kinship system (uncle, aunt turn out to be incomparable with kinship terms from indo-european lineal systems. Their meanings can be included in the DatSemShift catalogue only with an indication of system specifics. The information about semantic shifts can be useful for

Application of the Fourier descriptors method to the morphological classification of particles in geological materials

International Nuclear Information System (INIS)

Manzanas Lopez, J.; Santiago Buey, C.

2010-01-01

This study focuses on the use of Fourier descriptors to quantitatively describe the morphology of particles aggregates or pores in geological materials. Firstly, the mathematical fundaments of the method are explained. Then, the Fourier descriptors method is applied to the Krumbein Scale, a system of measuring roundness and sphericity of particles. the analysis of the comparison shows that there is good correlation between the Sphericity parameter at the Krumbein classifications and the value of the modulus of the Fourier descriptor No-1. This good correlation, along with the mathematical precision which allows to prevent subjective valorisations in the morphological description, corroborates the validity of the method to quantify the sphericity elongation of particles in geological materials. (Author) 12 refs.

Object classification and detection with context kernel descriptors

DEFF Research Database (Denmark)

Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

2014-01-01

Context information is important in object representation. By embedding context cue of image attributes into kernel descriptors, we propose a set of novel kernel descriptors called Context Kernel Descriptors (CKD) for object classification and detection. The motivation of CKD is to use spatial...... consistency of image attributes or features defined within a neighboring region to improve the robustness of descriptor matching in kernel space. For feature selection, Kernel Entropy Component Analysis (KECA) is exploited to learn a subset of discriminative CKD. Different from Kernel Principal Component...

DEVELOPING CEFR ILLUSTRATIVE DESCRIPTORS OF ASPECTS OF MEDIATION

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Brian North

2016-04-01

Full Text Available This article reports on a project commissioned and coordinated by the Council of Europe to develop descriptors for the category ‘Mediation’ in the Common European Framework of Reference for Languages. Mediation is the fourth communicative language activity presented in CEFR Chapter 4, complementing reception, interaction and production. Descriptors for mediation had not been developed in the 1993–6 Swiss National Research Project that produced the original set of illustrative descriptors for the CEFR. The work took place in the context of a wider 2013–6 project to provide an extended set of CEFR illustrative descriptors. The article describes the way in which the approach taken to mediation in the project is broader than the one taken in the presentation of mediation in the CEFR text in 2001. In addition to information transfer (conveying received information the new scheme also embraces the construction of meaning and relational mediation: the process of establishing and managing interpersonal relationships in order to create a positive, collaborative environment. Descriptors were also developed for other, related, areas. The article briefly summarises the three phases of validation to which the draft descriptors were subjected before being calibrated to the mathematic scale underlying the CEFR’s levels and descriptors.

Semantic interpretation of search engine resultant

Science.gov (United States)

Nasution, M. K. M.

2018-01-01

In semantic, logical language can be interpreted in various forms, but the certainty of meaning is included in the uncertainty, which directly always influences the role of technology. One results of this uncertainty applies to search engines as user interfaces with information spaces such as the Web. Therefore, the behaviour of search engine results should be interpreted with certainty through semantic formulation as interpretation. Behaviour formulation shows there are various interpretations that can be done semantically either temporary, inclusion, or repeat.

Molecular structure descriptors in the computer-aided design of biologically active compounds

International Nuclear Information System (INIS)

Raevsky, Oleg A

1999-01-01

The current state of description of molecular structure in computer-aided molecular design of biologically active compounds by means of descriptors is analysed. The information contents of descriptors increases in the following sequence: element-level descriptors-structural formulae descriptors-electronic structure descriptors-molecular shape descriptors-intermolecular interaction descriptors. Each subsequent class of descriptors normally covers information contained in the previous-level ones. It is emphasised that it is practically impossible to describe all the features of a molecular structure in terms of any single class of descriptors. It is recommended to optimise the number of descriptors used by means of appropriate statistical procedures and characteristics of structure-property models based on these descriptors. The bibliography includes 371 references.

Constraint-Based Abstract Semantics for Temporal Logic

DEFF Research Database (Denmark)

Banda, Gourinath; Gallagher, John Patrick

2010-01-01

Abstract interpretation provides a practical approach to verifying properties of infinite-state systems. We apply the framework of abstract interpretation to derive an abstract semantic function for the modal mu-calculus, which is the basis for abstract model checking. The abstract semantic funct...

Recognition of handwritten characters using local gradient feature descriptors

NARCIS (Netherlands)

Surinta, Olarik; Karaaba, Mahir F.; Schomaker, Lambert R.B.; Wiering, Marco A.

2015-01-01

Abstract In this paper we propose to use local gradient feature descriptors, namely the scale invariant feature transform keypoint descriptor and the histogram of oriented gradients, for handwritten character recognition. The local gradient feature descriptors are used to extract feature vectors

Construction of coffee transcriptome networks based on gene annotation semantics

Directory of Open Access Journals (Sweden)

Castillo Luis F.

2012-12-01

Full Text Available Gene annotation is a process that encompasses multiple approaches on the analysis of nucleic acids or protein sequences in order to assign structural and functional characteristics to gene models. When thousands of gene models are being described in an organism genome, construction and visualization of gene networks impose novel challenges in the understanding of complex expression patterns and the generation of new knowledge in genomics research. In order to take advantage of accumulated text data after conventional gene sequence analysis, this work applied semantics in combination with visualization tools to build transcriptome networks from a set of coffee gene annotations. A set of selected coffee transcriptome sequences, chosen by the quality of the sequence comparison reported by Basic Local Alignment Search Tool (BLAST and Interproscan, were filtered out by coverage, identity, length of the query, and e-values. Meanwhile, term descriptors for molecular biology and biochemistry were obtained along the Wordnet dictionary in order to construct a Resource Description Framework (RDF using Ruby scripts and Methontology to find associations between concepts. Relationships between sequence annotations and semantic concepts were graphically represented through a total of 6845 oriented vectors, which were reduced to 745 non-redundant associations. A large gene network connecting transcripts by way of relational concepts was created where detailed connections remain to be validated for biological significance based on current biochemical and genetics frameworks. Besides reusing text information in the generation of gene connections and for data mining purposes, this tool development opens the possibility to visualize complex and abundant transcriptome data, and triggers the formulation of new hypotheses in metabolic pathways analysis.

Ensembles of Novel Visual Keywords Descriptors for Image Categorization

NARCIS (Netherlands)

Abdullah, Azizi; Veltkamp, Remco C.; Wiering, Marco

2010-01-01

Object recognition systems need effective image descriptors to obtain good performance levels. Currently, the most widely used image descriptor is the SIFT descriptor that computes histograms of orientation gradients around points in an image. A possible problem of this approach is that the number

Applying Semantic Web technologies to improve the retrieval, credibility and use of health-related web resources.

Science.gov (United States)

Mayer, Miguel A; Karampiperis, Pythagoras; Kukurikos, Antonis; Karkaletsis, Vangelis; Stamatakis, Kostas; Villarroel, Dagmar; Leis, Angela

2011-06-01

The number of health-related websites is increasing day-by-day; however, their quality is variable and difficult to assess. Various "trust marks" and filtering portals have been created in order to assist consumers in retrieving quality medical information. Consumers are using search engines as the main tool to get health information; however, the major problem is that the meaning of the web content is not machine-readable in the sense that computers cannot understand words and sentences as humans can. In addition, trust marks are invisible to search engines, thus limiting their usefulness in practice. During the last five years there have been different attempts to use Semantic Web tools to label health-related web resources to help internet users identify trustworthy resources. This paper discusses how Semantic Web technologies can be applied in practice to generate machine-readable labels and display their content, as well as to empower end-users by providing them with the infrastructure for expressing and sharing their opinions on the quality of health-related web resources.

Semantic web for integrated network analysis in biomedicine.

Science.gov (United States)

Chen, Huajun; Ding, Li; Wu, Zhaohui; Yu, Tong; Dhanapalan, Lavanya; Chen, Jake Y

2009-03-01

The Semantic Web technology enables integration of heterogeneous data on the World Wide Web by making the semantics of data explicit through formal ontologies. In this article, we survey the feasibility and state of the art of utilizing the Semantic Web technology to represent, integrate and analyze the knowledge in various biomedical networks. We introduce a new conceptual framework, semantic graph mining, to enable researchers to integrate graph mining with ontology reasoning in network data analysis. Through four case studies, we demonstrate how semantic graph mining can be applied to the analysis of disease-causal genes, Gene Ontology category cross-talks, drug efficacy analysis and herb-drug interactions analysis.

Clinical phenotype-based gene prioritization: an initial study using semantic similarity and the human phenotype ontology.

Science.gov (United States)

Masino, Aaron J; Dechene, Elizabeth T; Dulik, Matthew C; Wilkens, Alisha; Spinner, Nancy B; Krantz, Ian D; Pennington, Jeffrey W; Robinson, Peter N; White, Peter S

2014-07-21

Exome sequencing is a promising method for diagnosing patients with a complex phenotype. However, variant interpretation relative to patient phenotype can be challenging in some scenarios, particularly clinical assessment of rare complex phenotypes. Each patient's sequence reveals many possibly damaging variants that must be individually assessed to establish clear association with patient phenotype. To assist interpretation, we implemented an algorithm that ranks a given set of genes relative to patient phenotype. The algorithm orders genes by the semantic similarity computed between phenotypic descriptors associated with each gene and those describing the patient. Phenotypic descriptor terms are taken from the Human Phenotype Ontology (HPO) and semantic similarity is derived from each term's information content. Model validation was performed via simulation and with clinical data. We simulated 33 Mendelian diseases with 100 patients per disease. We modeled clinical conditions by adding noise and imprecision, i.e. phenotypic terms unrelated to the disease and terms less specific than the actual disease terms. We ranked the causative gene against all 2488 HPO annotated genes. The median causative gene rank was 1 for the optimal and noise cases, 12 for the imprecision case, and 60 for the imprecision with noise case. Additionally, we examined a clinical cohort of subjects with hearing impairment. The disease gene median rank was 22. However, when also considering the patient's exome data and filtering non-exomic and common variants, the median rank improved to 3. Semantic similarity can rank a causative gene highly within a gene list relative to patient phenotype characteristics, provided that imprecision is mitigated. The clinical case results suggest that phenotype rank combined with variant analysis provides significant improvement over the individual approaches. We expect that this combined prioritization approach may increase accuracy and decrease effort for

Szeged Matrix Property Indices as Descriptors to Characterize Fullerenes

Directory of Open Access Journals (Sweden)

Jäntschi Lorentz

2016-12-01

Full Text Available Fullerenes are class of allotropes of carbon organized as closed cages or tubes of carbon atoms. The fullerenes with small number of atoms were not frequently investigated. This paper presents a detailed treatment of total strain energy as function of structural feature extracted from isomers of C40 fullerene using Szeged Matrix Property Indices (SMPI. The paper has a two-fold structure. First, the total strain energy of C40 fullerene isomers (40 structures was linked with SMPI descriptors under two scenarios, one which incorporate just the SMPI descriptors and the other one which contains also five calculated properties (dipole moment, scf-binding-energy, scf-core-energy, scf-electronic-energy, and heat of formation. Second, the performing models identified on C40 fullerene family or the descriptors of these models were used to predict the total strain energy on C42 fullerene isomers. The obtained results show that the inclusion of properties in the pool of descriptors led to the reduction of accurate linear models. One property, namely scf-binding-energy proved a significant contribution to total strain energy of C40 fullerene isomers. However, the top-three most performing models contain just SMPI descriptors. A model with four descriptors proved most accurate model and show fair abilities in prediction of the same property on C42 fullerene isomers when the approach considered the descriptors identified on C40 as the predicting descriptors for C42 fullerene isomers.

Semantic Web Requirements through Web Mining Techniques

OpenAIRE

Hassanzadeh, Hamed; Keyvanpour, Mohammad Reza

2012-01-01

In recent years, Semantic web has become a topic of active research in several fields of computer science and has applied in a wide range of domains such as bioinformatics, life sciences, and knowledge management. The two fast-developing research areas semantic web and web mining can complement each other and their different techniques can be used jointly or separately to solve the issues in both areas. In addition, since shifting from current web to semantic web mainly depends on the enhance...

Uncovering the Geometry of Barrierless Reactions Using Lagrangian Descriptors.

Science.gov (United States)

Junginger, Andrej; Hernandez, Rigoberto

2016-03-03

Transition-state theories describing barrierless chemical reactions, or more general activated problems, are often hampered by the lack of a saddle around which the dividing surface can be constructed. For example, the time-dependent transition-state trajectory uncovering the nonrecrossing dividing surface in thermal reactions in the framework of the Langevin equation has relied on perturbative approaches in the vicinity of the saddle. We recently obtained an alternative approach using Lagrangian descriptors to construct time-dependent and recrossing-free dividing surfaces. This is a nonperturbative approach making no reference to a putative saddle. Here we show how the Lagrangian descriptor can be used to obtain the transition-state geometry of a dissipated and thermalized reaction across barrierless potentials. We illustrate the method in the case of a 1D Brownian motion for both barrierless and step potentials; however, the method is not restricted and can be directly applied to different kinds of potentials and higher dimensional systems.

Semantic Approaches Applied to Scientific Ocean Drilling Data

Science.gov (United States)

Fils, D.; Jenkins, C. J.; Arko, R. A.

2012-12-01

The application of Linked Open Data methods to 40 years of data from scientific ocean drilling is providing users with several new methods for rich-content data search and discovery. Data from the Deep Sea Drilling Project (DSDP), Ocean Drilling Program (ODP) and Integrated Ocean Drilling Program (IODP) have been translated and placed in RDF triple stores to provide access via SPARQL, linked open data patterns, and by embedded structured data through schema.org / RDFa. Existing search services have been re-encoded in this environment which allows the new and established architectures to be contrasted. Vocabularies including computed semantic relations between concepts, allow separate but related data sets to be connected on their concepts and resources even when they are expressed somewhat differently. Scientific ocean drilling produces a wide range of data types and data sets: borehole logging file-based data, images, measurements, visual observations and the physical sample data. The steps involved in connecting these data to concepts using vocabularies will be presented, including the connection of data sets through Vocabulary of Interlinked Datasets (VoID) and open entity collections such as Freebase and dbPedia. Demonstrated examples will include: (i) using RDF Schema for inferencing and in federated searches across NGDC and IODP data, (ii) using structured data in the data.oceandrilling.org web site, (iii) association through semantic methods of age models and depth recorded data to facilitate age based searches for data recorded by depth only.

A 3D visualization of the substituent effect : A brief analysis of two components of the operational formula of dual descriptor for open-shell systems.

Science.gov (United States)

Martínez-Araya, Jorge I; Yepes, Diana; Jaque, Pablo

2017-12-27

Six organometallic compounds coming from a basic Mo-based complex were analyzed from the perspective of the dual descriptor in order to detect subtle influences that a substituent group could exert on the reactive core at a long range. Since the aforementioned complexes are open-shell systems, the used operational formula for the dual descriptor is that one defined for those aforementioned systems, which was then compared with spin density. In addition, dual descriptor was decomposed into two terms, each of which was also applied on every molecular system. The obtained results indicated that components of dual descriptor could become more useful than the operational formula of dual descriptor because differences exerted by the substituents at the para position were better detected by components of dual descriptor rather than the dual descriptor by itself.

Semantic Blogging : Spreading the Semantic Web Meme

OpenAIRE

Cayzer, Steve

2004-01-01

This paper is about semantic blogging, an application of the semantic web to blogging. The semantic web promises to make the web more useful by endowing metadata with machine processable semantics. Blogging is a lightweight web publishing paradigm which provides a very low barrier to entry, useful syndication and aggregation behaviour, a simple to understand structure and decentralized construction of a rich information network. Semantic blogging builds upon the success and clear network valu...

Shape-tailored local descriptors and their application to segmentation and tracking

KAUST Repository

Khan, Naeemullah; Algarni, Marei Saeed Mohammed; Yezzi, Anthony; Sundaramoorthi, Ganesh

2015-01-01

We propose new dense descriptors for texture segmentation. Given a region of arbitrary shape in an image, these descriptors are formed from shape-dependent scale spaces of oriented gradients. These scale spaces are defined by Poisson-like partial differential equations. A key property of our new descriptors is that they do not aggregate image data across the boundary of the region, in contrast to existing descriptors based on aggregation of oriented gradients. As an example, we show how the descriptor can be incorporated in a Mumford-Shah energy for texture segmentation. We test our method on several challenging datasets for texture segmentation and textured object tracking. Experiments indicate that our descriptors lead to more accurate segmentation than non-shape dependent descriptors and the state-of-the-art in texture segmentation.

Shape-tailored local descriptors and their application to segmentation and tracking

KAUST Repository

Khan, Naeemullah

2015-06-07

We propose new dense descriptors for texture segmentation. Given a region of arbitrary shape in an image, these descriptors are formed from shape-dependent scale spaces of oriented gradients. These scale spaces are defined by Poisson-like partial differential equations. A key property of our new descriptors is that they do not aggregate image data across the boundary of the region, in contrast to existing descriptors based on aggregation of oriented gradients. As an example, we show how the descriptor can be incorporated in a Mumford-Shah energy for texture segmentation. We test our method on several challenging datasets for texture segmentation and textured object tracking. Experiments indicate that our descriptors lead to more accurate segmentation than non-shape dependent descriptors and the state-of-the-art in texture segmentation.

Simple knowledge-based descriptors to predict protein-ligand interactions. Methodology and validation

Science.gov (United States)

Nissink, J. Willem M.; Verdonk, Marcel L.; Klebe, Gerhard

2000-11-01

A new type of shape descriptor is proposed to describe the spatial orientation for non-covalent interactions. It is built from simple, anisotropic Gaussian contributions that are parameterised by 10 adjustable values. The descriptors have been used to fit propensity distributions derived from scatter data stored in the IsoStar database. This database holds composite pictures of possible interaction geometries between a common central group and various interacting moieties, as extracted from small-molecule crystal structures. These distributions can be related to probabilities for the occurrence of certain interaction geometries among different functional groups. A fitting procedure is described that generates the descriptors in a fully automated way. For this purpose, we apply a similarity index that is tailored to the problem, the Split Hodgkin Index. It accounts for the similarity in regions of either high or low propensity in a separate way. Although dependent on the division into these two subregions, the index is robust and performs better than the regular Hodgkin index. The reliability and coverage of the fitted descriptors was assessed using SuperStar. SuperStar usually operates on the raw IsoStar data to calculate propensity distributions, e.g., for a binding site in a protein. For our purpose we modified the code to have it operate on our descriptors instead. This resulted in a substantial reduction in calculation time (factor of five to eight) compared to the original implementation. A validation procedure was performed on a set of 130 protein-ligand complexes, using four representative interacting probes to map the properties of the various binding sites: ammonium nitrogen, alcohol oxygen, carbonyl oxygen, and methyl carbon. The predicted `hot spots' for the binding of these probes were compared to the actual arrangement of ligand atoms in experimentally determined protein-ligand complexes. Results indicate that the version of SuperStar that applies to

Biomedical semantics in the Semantic Web.

Science.gov (United States)

Splendiani, Andrea; Burger, Albert; Paschke, Adrian; Romano, Paolo; Marshall, M Scott

2011-03-07

The Semantic Web offers an ideal platform for representing and linking biomedical information, which is a prerequisite for the development and application of analytical tools to address problems in data-intensive areas such as systems biology and translational medicine. As for any new paradigm, the adoption of the Semantic Web offers opportunities and poses questions and challenges to the life sciences scientific community: which technologies in the Semantic Web stack will be more beneficial for the life sciences? Is biomedical information too complex to benefit from simple interlinked representations? What are the implications of adopting a new paradigm for knowledge representation? What are the incentives for the adoption of the Semantic Web, and who are the facilitators? Is there going to be a Semantic Web revolution in the life sciences?We report here a few reflections on these questions, following discussions at the SWAT4LS (Semantic Web Applications and Tools for Life Sciences) workshop series, of which this Journal of Biomedical Semantics special issue presents selected papers from the 2009 edition, held in Amsterdam on November 20th.

The FREPA Descriptors

DEFF Research Database (Denmark)

Daryai-Hansen, Petra; Jaeger, Catherine

2015-01-01

, attitudes and skills, (b) a database of teaching material and (c) a training kit for teachers. The paper presents the FREPA descriptors by comparing them to Byram’s definition of intercultural communicative competence and Deardorff’s intercultural competence model and emphasises that FREPA deepens...

Unsupervised semantic indoor scene classification for robot vision based on context of features using Gist and HSV-SIFT

Science.gov (United States)

Madokoro, H.; Yamanashi, A.; Sato, K.

2013-08-01

This paper presents an unsupervised scene classification method for actualizing semantic recognition of indoor scenes. Background and foreground features are respectively extracted using Gist and color scale-invariant feature transform (SIFT) as feature representations based on context. We used hue, saturation, and value SIFT (HSV-SIFT) because of its simple algorithm with low calculation costs. Our method creates bags of features for voting visual words created from both feature descriptors to a two-dimensional histogram. Moreover, our method generates labels as candidates of categories for time-series images while maintaining stability and plasticity together. Automatic labeling of category maps can be realized using labels created using adaptive resonance theory (ART) as teaching signals for counter propagation networks (CPNs). We evaluated our method for semantic scene classification using KTH's image database for robot localization (KTH-IDOL), which is popularly used for robot localization and navigation. The mean classification accuracies of Gist, gray SIFT, one class support vector machines (OC-SVM), position-invariant robust features (PIRF), and our method are, respectively, 39.7, 58.0, 56.0, 63.6, and 79.4%. The result of our method is 15.8% higher than that of PIRF. Moreover, we applied our method for fine classification using our original mobile robot. We obtained mean classification accuracy of 83.2% for six zones.

Developing Visualization Techniques for Semantics-based Information Networks

Science.gov (United States)

Keller, Richard M.; Hall, David R.

2003-01-01

Information systems incorporating complex network structured information spaces with a semantic underpinning - such as hypermedia networks, semantic networks, topic maps, and concept maps - are being deployed to solve some of NASA s critical information management problems. This paper describes some of the human interaction and navigation problems associated with complex semantic information spaces and describes a set of new visual interface approaches to address these problems. A key strategy is to leverage semantic knowledge represented within these information spaces to construct abstractions and views that will be meaningful to the human user. Human-computer interaction methodologies will guide the development and evaluation of these approaches, which will benefit deployed NASA systems and also apply to information systems based on the emerging Semantic Web.

Correspondence dictionary from free English term to INIS descriptors

International Nuclear Information System (INIS)

1993-03-01

This dictionary is intended for the on-line users of INIS database who select controlled terms (INIS descriptors) starting from free terms. The purpose of terminology control is (1) to reduce the ambiguity of the term use among different subject fields, and (2) to improve the recall by coordinating the synonyms. The controlled terms are collected in the thesaurus, but it is not always easy to find suitable descriptors. This dictionary has been compiled by analyzing existing records, and provides the specialists' know-how of converting free terms to descriptors. Besides the compilation of this dictionary, the characteristics of the assigned descriptors were also clarified. (J.P.N.)

Preserved musical semantic memory in semantic dementia.

Science.gov (United States)

Weinstein, Jessica; Koenig, Phyllis; Gunawardena, Delani; McMillan, Corey; Bonner, Michael; Grossman, Murray

2011-02-01

To understand the scope of semantic impairment in semantic dementia. Case study. Academic medical center. A man with semantic dementia, as demonstrated by clinical, neuropsychological, and imaging studies. Music performance and magnetic resonance imaging results. Despite profoundly impaired semantic memory for words and objects due to left temporal lobe atrophy, this semiprofessional musician was creative and expressive in demonstrating preserved musical knowledge. Long-term representations of words and objects in semantic memory may be dissociated from meaningful knowledge in other domains, such as music.

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.

Hybrid Histogram Descriptor: A Fusion Feature Representation for Image Retrieval.

Science.gov (United States)

Feng, Qinghe; Hao, Qiaohong; Chen, Yuqi; Yi, Yugen; Wei, Ying; Dai, Jiangyan

2018-06-15

Currently, visual sensors are becoming increasingly affordable and fashionable, acceleratingly the increasing number of image data. Image retrieval has attracted increasing interest due to space exploration, industrial, and biomedical applications. Nevertheless, designing effective feature representation is acknowledged as a hard yet fundamental issue. This paper presents a fusion feature representation called a hybrid histogram descriptor (HHD) for image retrieval. The proposed descriptor comprises two histograms jointly: a perceptually uniform histogram which is extracted by exploiting the color and edge orientation information in perceptually uniform regions; and a motif co-occurrence histogram which is acquired by calculating the probability of a pair of motif patterns. To evaluate the performance, we benchmarked the proposed descriptor on RSSCN7, AID, Outex-00013, Outex-00014 and ETHZ-53 datasets. Experimental results suggest that the proposed descriptor is more effective and robust than ten recent fusion-based descriptors under the content-based image retrieval framework. The computational complexity was also analyzed to give an in-depth evaluation. Furthermore, compared with the state-of-the-art convolutional neural network (CNN)-based descriptors, the proposed descriptor also achieves comparable performance, but does not require any training process.

SVM Based Descriptor Selection and Classification of Neurodegenerative Disease Drugs for Pharmacological Modeling.

Science.gov (United States)

Shahid, Mohammad; Shahzad Cheema, Muhammad; Klenner, Alexander; Younesi, Erfan; Hofmann-Apitius, Martin

2013-03-01

Systems pharmacological modeling of drug mode of action for the next generation of multitarget drugs may open new routes for drug design and discovery. Computational methods are widely used in this context amongst which support vector machines (SVM) have proven successful in addressing the challenge of classifying drugs with similar features. We have applied a variety of such SVM-based approaches, namely SVM-based recursive feature elimination (SVM-RFE). We use the approach to predict the pharmacological properties of drugs widely used against complex neurodegenerative disorders (NDD) and to build an in-silico computational model for the binary classification of NDD drugs from other drugs. Application of an SVM-RFE model to a set of drugs successfully classified NDD drugs from non-NDD drugs and resulted in overall accuracy of ∼80 % with 10 fold cross validation using 40 top ranked molecular descriptors selected out of total 314 descriptors. Moreover, SVM-RFE method outperformed linear discriminant analysis (LDA) based feature selection and classification. The model reduced the multidimensional descriptors space of drugs dramatically and predicted NDD drugs with high accuracy, while avoiding over fitting. Based on these results, NDD-specific focused libraries of drug-like compounds can be designed and existing NDD-specific drugs can be characterized by a well-characterized set of molecular descriptors. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cations in Octahedral Sites: A Descriptor for Oxygen Electrocatalysis on Transition-Metal Spinels

Energy Technology Data Exchange (ETDEWEB)

Wei, Chao; Feng, Zhenxing; Scherer, Günther G.; Barber, James; Shao-Horn, Yang; Xu, Zhichuan J. (Nanyang); (ICL); (Oregon State U.); (TUM-CREATE); (MIT)

2017-04-10

Exploring efficient and low-cost electrocatalysts for the oxygen-reduction reaction (ORR) and oxygen-evolution reaction (OER) is critical for developing renewable energy technologies such as fuel cells, metal–air batteries, and water electrolyzers. A rational design of a catalyst can be guided by identifying descriptors that determine its activity. Here, a descriptor study on the ORR/OER of spinel oxides is presented. With a series of MnCo2O4, the Mn in octahedral sites is identified as an active site. This finding is then applied to successfully explain the ORR/OER activities of other transition-metal spinels, including MnxCo3-xO4 (x = 2, 2.5, 3), LixMn2O4 (x = 0.7, 1), XCo2O4 (X = Co, Ni, Zn), and XFe2O4 (X = Mn, Co, Ni). A general principle is concluded that the eg occupancy of the active cation in the octahedral site is the activity descriptor for the ORR/OER of spinels, consolidating the role of electron orbital filling in metal oxide catalysis.

The Relevance Aura of Bibliographic Records.

Science.gov (United States)

Brooks, Terrence A.

1997-01-01

Analyzes relevance assessments of topical descriptors for bibliographic records for two dimensions: (1) a vertical conceptual hierarchy of broad to narrow descriptors, and (2) a horizontal linkage of related terms. The data were analyzed for a semantic distance and semantic direction effect as postulated by the Semantic Distance Model. (Author/LRW)

Branch length similarity entropy-based descriptors for shape representation

Science.gov (United States)

Kwon, Ohsung; Lee, Sang-Hee

2017-11-01

In previous studies, we showed that the branch length similarity (BLS) entropy profile could be successfully used for the shape recognition such as battle tanks, facial expressions, and butterflies. In the present study, we proposed new descriptors, roundness, symmetry, and surface roughness, for the recognition, which are more accurate and fast in the computation than the previous descriptors. The roundness represents how closely a shape resembles to a circle, the symmetry characterizes how much one shape is similar with another when the shape is moved in flip, and the surface roughness quantifies the degree of vertical deviations of a shape boundary. To evaluate the performance of the descriptors, we used the database of leaf images with 12 species. Each species consisted of 10 - 20 leaf images and the total number of images were 160. The evaluation showed that the new descriptors successfully discriminated the leaf species. We believe that the descriptors can be a useful tool in the field of pattern recognition.

Aggregating Local Descriptors for Epigraphs Recognition

OpenAIRE

Amato, Giuseppe; Falchi, Fabrizio; Rabitti, Fausto; Vadicamo, Lucia

2014-01-01

In this paper, we consider the task of recognizing epigraphs in images such as photos taken using mobile devices. Given a set of 17,155 photos related to 14,560 epigraphs, we used a k-NearestNeighbor approach in order to perform the recognition. The contribution of this work is in evaluating state-of-the-art visual object recognition techniques in this specific context. The experimental results conducted show that Vector of Locally Aggregated Descriptors obtained aggregating SIFT descriptors ...

Stargate GTM: Bridging Descriptor and Activity Spaces.

Science.gov (United States)

Gaspar, Héléna A; Baskin, Igor I; Marcou, Gilles; Horvath, Dragos; Varnek, Alexandre

2015-11-23

Predicting the activity profile of a molecule or discovering structures possessing a specific activity profile are two important goals in chemoinformatics, which could be achieved by bridging activity and molecular descriptor spaces. In this paper, we introduce the "Stargate" version of the Generative Topographic Mapping approach (S-GTM) in which two different multidimensional spaces (e.g., structural descriptor space and activity space) are linked through a common 2D latent space. In the S-GTM algorithm, the manifolds are trained simultaneously in two initial spaces using the probabilities in the 2D latent space calculated as a weighted geometric mean of probability distributions in both spaces. S-GTM has the following interesting features: (1) activities are involved during the training procedure; therefore, the method is supervised, unlike conventional GTM; (2) using molecular descriptors of a given compound as input, the model predicts a whole activity profile, and (3) using an activity profile as input, areas populated by relevant chemical structures can be detected. To assess the performance of S-GTM prediction models, a descriptor space (ISIDA descriptors) of a set of 1325 GPCR ligands was related to a B-dimensional (B = 1 or 8) activity space corresponding to pKi values for eight different targets. S-GTM outperforms conventional GTM for individual activities and performs similarly to the Lasso multitask learning algorithm, although it is still slightly less accurate than the Random Forest method.

Descriptors of sensation confirm the multidimensional nature of desire to void.

Science.gov (United States)

Das, Rebekah; Buckley, Jonathan D; Williams, Marie T

2015-02-01

To collect and categorize descriptors of "desire to void" sensation, determine the reliability of descriptor categories and assess whether descriptor categories discriminate between people with and without symptoms of overactive bladder. This observational, repeated measures study involved 64 Australian volunteers (47 female), aged 50 years or more, with and without symptoms of overactive bladder. Descriptors of desire to void sensation were derived from a structured interview (conducted on two occasions, 1 week apart). Descriptors were recorded verbatim and categorized in a three-stage process. Overactive bladder status was determined by the Overactive Bladder Awareness Tool and the Overactive Bladder Symptom Score. McNemar's test assessed the reliability of descriptors volunteered between two occasions and Partial Least Squares Regression determined whether language categories discriminated according to overactive bladder status. Post hoc Chi squared analysis and relative risk calculation determined the size and direction of overactive bladder prediction. Thirteen language categories (Urgency, Fullness, Pressure, Tickle/tingle, Pain/ache, Heavy, Normal, Intense, Sudden, Annoying, Uncomfortable, Anxiety, and Unique somatic) encapsulated 344 descriptors of sensation. Descriptor categories were stable between two interviews. The categories "Urgency" and "Fullness" predicted overactive bladder status. Participants who volunteered "Urgency" descriptors were twice as likely to have overactive bladder and participants who volunteered "Fullness" descriptors were almost three times as likely not to have overactive bladder. The sensation of desire to void is reliably described over sessions separated by a week, the language used reflects multiple dimensions of sensation, and can predict overactive bladder status. © 2013 Wiley Periodicals, Inc.

Evaluating Color Descriptors for Object and Scene Recognition

NARCIS (Netherlands)

van de Sande, K.E.A.; Gevers, T.; Snoek, C.G.M.

2010-01-01

Image category recognition is important to access visual information on the level of objects and scene types. So far, intensity-based descriptors have been widely used for feature extraction at salient points. To increase illumination invariance and discriminative power, color descriptors have been

Improving life sciences information retrieval using semantic web technology.

Science.gov (United States)

Quan, Dennis

2007-05-01

The ability to retrieve relevant information is at the heart of every aspect of research and development in the life sciences industry. Information is often distributed across multiple systems and recorded in a way that makes it difficult to piece together the complete picture. Differences in data formats, naming schemes and network protocols amongst information sources, both public and private, must be overcome, and user interfaces not only need to be able to tap into these diverse information sources but must also assist users in filtering out extraneous information and highlighting the key relationships hidden within an aggregated set of information. The Semantic Web community has made great strides in proposing solutions to these problems, and many efforts are underway to apply Semantic Web techniques to the problem of information retrieval in the life sciences space. This article gives an overview of the principles underlying a Semantic Web-enabled information retrieval system: creating a unified abstraction for knowledge using the RDF semantic network model; designing semantic lenses that extract contextually relevant subsets of information; and assembling semantic lenses into powerful information displays. Furthermore, concrete examples of how these principles can be applied to life science problems including a scenario involving a drug discovery dashboard prototype called BioDash are provided.

Semantic Advertising

OpenAIRE

Zamanzadeh, Ben; Ashish, Naveen; Ramakrishnan, Cartic; Zimmerman, John

2013-01-01

We present the concept of Semantic Advertising which we see as the future of online advertising. Semantic Advertising is online advertising powered by semantic technology which essentially enables us to represent and reason with concepts and the meaning of things. This paper aims to 1) Define semantic advertising, 2) Place it in the context of broader and more widely used concepts such as the Semantic Web and Semantic Search, 3) Provide a survey of work in related areas such as context matchi...

Gabor Weber Local Descriptor for Bovine Iris Recognition

Directory of Open Access Journals (Sweden)

Shengnan Sun

2013-01-01

Full Text Available Iris recognition is a robust biometric technology. This paper proposes a novel local descriptor for bovine iris recognition, named Gabor Weber local descriptor (GWLD. We first compute the Gabor magnitude maps for the input bovine iris image, and then calculate the differential excitation and orientation for each pixel over each Gabor magnitude map. After that, we use these differential excitations and orientations to construct the GWLD histogram representation. Finally, histogram intersection is adopted to measure the similarity between different GWLD histograms. The experimental results on the SEU bovine iris database verify the representation power of our proposed local descriptor.

A group of facial normal descriptors for recognizing 3D identical twins

KAUST Repository

Li, Huibin

2012-09-01

In this paper, to characterize and distinguish identical twins, three popular texture descriptors: i.e. local binary patterns (LBPs), gabor filters (GFs) and local gabor binary patterns (LGBPs) are employed to encode the normal components (x, y and z) of the 3D facial surfaces of identical twins respectively. A group of facial normal descriptors are thus achieved, including Normal Local Binary Patterns descriptor (N-LBPs), Normal Gabor Filters descriptor (N-GFs) and Normal Local Gabor Binary Patterns descriptor (N-LGBPs). All these normal encoding based descriptors are further fed into sparse representation classifier (SRC) for identification. Experimental results on the 3D TEC database demonstrate that these proposed normal encoding based descriptors are very discriminative and efficient, achieving comparable performance to the best of state-of-the-art algorithms. © 2012 IEEE.

Fourier Descriptor Analysis and Unification of Voice Range Profile Contours: Method and Applications

Science.gov (United States)

Pabon, Peter; Ternstrom, Sten; Lamarche, Anick

2011-01-01

Purpose: To describe a method for unified description, statistical modeling, and comparison of voice range profile (VRP) contours, even from diverse sources. Method: A morphologic modeling technique, which is based on Fourier descriptors (FDs), is applied to the VRP contour. The technique, which essentially involves resampling of the curve of the…

Developing descriptors to predict mechanical properties of nanotubes.

Science.gov (United States)

Borders, Tammie L; Fonseca, Alexandre F; Zhang, Hengji; Cho, Kyeongjae; Rusinko, Andrew

2013-04-22

Descriptors and quantitative structure property relationships (QSPR) were investigated for mechanical property prediction of carbon nanotubes (CNTs). 78 molecular dynamics (MD) simulations were carried out, and 20 descriptors were calculated to build quantitative structure property relationships (QSPRs) for Young's modulus and Poisson's ratio in two separate analyses: vacancy only and vacancy plus methyl functionalization. In the first analysis, C(N2)/C(T) (number of non-sp2 hybridized carbons per the total carbons) and chiral angle were identified as critical descriptors for both Young's modulus and Poisson's ratio. Further analysis and literature findings indicate the effect of chiral angle is negligible at larger CNT radii for both properties. Raman spectroscopy can be used to measure C(N2)/C(T), providing a direct link between experimental and computational results. Poisson's ratio approaches two different limiting values as CNT radii increases: 0.23-0.25 for chiral and armchair CNTs and 0.10 for zigzag CNTs (surface defects <3%). In the second analysis, the critical descriptors were C(N2)/C(T), chiral angle, and M(N)/C(T) (number of methyl groups per total carbons). These results imply new types of defects can be represented as a new descriptor in QSPR models. Finally, results are qualified and quantified against experimental data.

RAID: a relation-augmented image descriptor

KAUST Repository

Guerrero, Paul; Mitra, Niloy J.; Wonka, Peter

2016-01-01

As humans, we regularly interpret scenes based on how objects are related, rather than based on the objects themselves. For example, we see a person riding an object X or a plank bridging two objects. Current methods provide limited support to search for content based on such relations. We present RAID, a relation-augmented image descriptor that supports queries based on inter-region relations. The key idea of our descriptor is to encode region-to-region relations as the spatial distribution of point-to-region relationships between two image regions. RAID allows sketch-based retrieval and requires minimal training data, thus making it suited even for querying uncommon relations. We evaluate the proposed descriptor by querying into large image databases and successfully extract nontrivial images demonstrating complex inter-region relations, which are easily missed or erroneously classified by existing methods. We assess the robustness of RAID on multiple datasets even when the region segmentation is computed automatically or very noisy.

RAID: a relation-augmented image descriptor

KAUST Repository

Guerrero, Paul

2016-07-11

As humans, we regularly interpret scenes based on how objects are related, rather than based on the objects themselves. For example, we see a person riding an object X or a plank bridging two objects. Current methods provide limited support to search for content based on such relations. We present RAID, a relation-augmented image descriptor that supports queries based on inter-region relations. The key idea of our descriptor is to encode region-to-region relations as the spatial distribution of point-to-region relationships between two image regions. RAID allows sketch-based retrieval and requires minimal training data, thus making it suited even for querying uncommon relations. We evaluate the proposed descriptor by querying into large image databases and successfully extract nontrivial images demonstrating complex inter-region relations, which are easily missed or erroneously classified by existing methods. We assess the robustness of RAID on multiple datasets even when the region segmentation is computed automatically or very noisy.

Character context: a shape descriptor for Arabic handwriting recognition

Science.gov (United States)

Mudhsh, Mohammed; Almodfer, Rolla; Duan, Pengfei; Xiong, Shengwu

2017-11-01

In the handwriting recognition field, designing good descriptors are substantial to obtain rich information of the data. However, the handwriting recognition research of a good descriptor is still an open issue due to unlimited variation in human handwriting. We introduce a "character context descriptor" that efficiently dealt with the structural characteristics of Arabic handwritten characters. First, the character image is smoothed and normalized, then the character context descriptor of 32 feature bins is built based on the proposed "distance function." Finally, a multilayer perceptron with regularization is used as a classifier. On experimentation with a handwritten Arabic characters database, the proposed method achieved a state-of-the-art performance with recognition rate equal to 98.93% and 99.06% for the 66 and 24 classes, respectively.

Three-Dimensional Model Retrieval Using Dynamic Multi-Descriptor Fusion

Institute of Scientific and Technical Information of China (English)

Jau-Ling Shi; Chang-Hsing Lee; Yao-Wen Hou; Po-Ting Yeh

2017-01-01

In this paper, we propose a dynamic multi-descriptor fusion (DMDF) approach to improving the retrieval accuracy of 3-dimensional (3D) model retrieval systems. First, an independent retrieval list is generated by using each individual descriptor. Second, we propose an automatic relevant/irrelevant models selection (ARMS) approach to selecting the relevant and irrelevant 3D models automatically without any user interaction. A weighted distance, in which the weight associated with each individual descriptor is learnt by using the selected relevant and irrelevant models, is used to measure the similarity between two 3D models. Furthermore, a descriptor-dependent adaptive query point movement (AQPM) approach is employed to update every feature vector. This set of new feature vectors is used to index 3D models in the next search process. Four 3D model databases are used to compare the retrieval accuracy of our proposed DMDF approach with several descriptors as well as some well-known information fusion methods. Experimental results have shown that our proposed DMDF approach provides a promising retrieval result and always yields the best retrieval accuracy.

Semantator: annotating clinical narratives with semantic web ontologies.

Science.gov (United States)

Song, Dezhao; Chute, Christopher G; Tao, Cui

2012-01-01

To facilitate clinical research, clinical data needs to be stored in a machine processable and understandable way. Manual annotating clinical data is time consuming. Automatic approaches (e.g., Natural Language Processing systems) have been adopted to convert such data into structured formats; however, the quality of such automatically extracted data may not always be satisfying. In this paper, we propose Semantator, a semi-automatic tool for document annotation with Semantic Web ontologies. With a loaded free text document and an ontology, Semantator supports the creation/deletion of ontology instances for any document fragment, linking/disconnecting instances with the properties in the ontology, and also enables automatic annotation by connecting to the NCBO annotator and cTAKES. By representing annotations in Semantic Web standards, Semantator supports reasoning based upon the underlying semantics of the owl:disjointWith and owl:equivalentClass predicates. We present discussions based on user experiences of using Semantator.

Correspondence dictionary from free English term to INIS descriptors

International Nuclear Information System (INIS)

1991-12-01

This dictionary is intended for the on-line users of INIS database who select controlled terms (INIS descriptors) starting from free terms. The purpose of terminology control is (1) to reduce the ambiguity of the term use among different subject fields, and (2) to improve the recall by coordinating the synonyms. The controlled terms are collected in the thesaurus, but it is not always easy to find suitable descriptors. This dictionary has been compiled by analyzing existing records, and provides the specialists' know-how of converting free terms to descriptors. The 5,000 records in the physics field were selected, and analyzed by the physicists from the Department of Physics, Ibaraki University. Besides the compilation of this dictionary, the characteristics of the assigned descriptors were also clarified. (J.P.N.)

Shape descriptors for mode-shape recognition and model updating

International Nuclear Information System (INIS)

Wang, W; Mottershead, J E; Mares, C

2009-01-01

The most widely used method for comparing mode shapes from finite elements and experimental measurements is the Modal Assurance Criterion (MAC), which returns a single numerical value and carries no explicit information on shape features. New techniques, based on image processing (IP) and pattern recognition (PR) are described in this paper. The Zernike moment descriptor (ZMD), Fourier descriptor (FD), and wavelet descriptor (WD), presented in this article, are the most popular shape descriptors having properties that include efficiency of expression, robustness to noise, invariance to geometric transformation and rotation, separation of local and global shape features and computational efficiency. The comparison of mode shapes is readily achieved by assembling the shape features of each mode shape into multi-dimensional shape feature vectors (SFVs) and determining the distances separating them.

Qualitative spatial logic descriptors from 3D indoor scenes to generate explanations in natural language.

Science.gov (United States)

Falomir, Zoe; Kluth, Thomas

2018-05-01

The challenge of describing 3D real scenes is tackled in this paper using qualitative spatial descriptors. A key point to study is which qualitative descriptors to use and how these qualitative descriptors must be organized to produce a suitable cognitive explanation. In order to find answers, a survey test was carried out with human participants which openly described a scene containing some pieces of furniture. The data obtained in this survey are analysed, and taking this into account, the QSn3D computational approach was developed which uses a XBox 360 Kinect to obtain 3D data from a real indoor scene. Object features are computed on these 3D data to identify objects in indoor scenes. The object orientation is computed, and qualitative spatial relations between the objects are extracted. These qualitative spatial relations are the input to a grammar which applies saliency rules obtained from the survey study and generates cognitive natural language descriptions of scenes. Moreover, these qualitative descriptors can be expressed as first-order logical facts in Prolog for further reasoning. Finally, a validation study is carried out to test whether the descriptions provided by QSn3D approach are human readable. The obtained results show that their acceptability is higher than 82%.

Prostate malignancy grading using gland-related shape descriptors

Science.gov (United States)

Braumann, Ulf-Dietrich; Scheibe, Patrick; Loeffler, Markus; Kristiansen, Glen; Wernert, Nicolas

2014-03-01

A proof-of-principle study was accomplished assessing the descriptive potential of two simple geometric measures (shape descriptors) applied to sets of segmented glands within images of 125 prostate cancer tissue sections. Respective measures addressing glandular shapes were (i) inverse solidity and (ii) inverse compactness. Using a classifier based on logistic regression, Gleason grades 3 and 4/5 could be differentiated with an accuracy of approx. 95%. Results suggest not only good discriminatory properties, but also robustness against gland segmentation variations. False classifications in part were caused by inadvertent Gleason grade assignments, as a-posteriori re-inspections had turned out.

Semantic processing of EHR data for clinical research.

Science.gov (United States)

Sun, Hong; Depraetere, Kristof; De Roo, Jos; Mels, Giovanni; De Vloed, Boris; Twagirumukiza, Marc; Colaert, Dirk

2015-12-01

There is a growing need to semantically process and integrate clinical data from different sources for clinical research. This paper presents an approach to integrate EHRs from heterogeneous resources and generate integrated data in different data formats or semantics to support various clinical research applications. The proposed approach builds semantic data virtualization layers on top of data sources, which generate data in the requested semantics or formats on demand. This approach avoids upfront dumping to and synchronizing of the data with various representations. Data from different EHR systems are first mapped to RDF data with source semantics, and then converted to representations with harmonized domain semantics where domain ontologies and terminologies are used to improve reusability. It is also possible to further convert data to application semantics and store the converted results in clinical research databases, e.g. i2b2, OMOP, to support different clinical research settings. Semantic conversions between different representations are explicitly expressed using N3 rules and executed by an N3 Reasoner (EYE), which can also generate proofs of the conversion processes. The solution presented in this paper has been applied to real-world applications that process large scale EHR data. Copyright © 2015 Elsevier Inc. All rights reserved.

Ship detection based on rotation-invariant HOG descriptors for airborne infrared images

Science.gov (United States)

Xu, Guojing; Wang, Jinyan; Qi, Shengxiang

2018-03-01

Infrared thermal imagery is widely used in various kinds of aircraft because of its all-time application. Meanwhile, detecting ships from infrared images attract lots of research interests in recent years. In the case of downward-looking infrared imagery, in order to overcome the uncertainty of target imaging attitude due to the unknown position relationship between the aircraft and the target, we propose a new infrared ship detection method which integrates rotation invariant gradient direction histogram (Circle Histogram of Oriented Gradient, C-HOG) descriptors and the support vector machine (SVM) classifier. In details, the proposed method uses HOG descriptors to express the local feature of infrared images to adapt to changes in illumination and to overcome sea clutter effects. Different from traditional computation of HOG descriptor, we subdivide the image into annular spatial bins instead of rectangle sub-regions, and then Radial Gradient Transform (RGT) on the gradient is applied to achieve rotation invariant histogram information. Considering the engineering application of airborne and real-time requirements, we use SVM for training ship target and non-target background infrared sample images to discriminate real ships from false targets. Experimental results show that the proposed method has good performance in both the robustness and run-time for infrared ship target detection with different rotation angles.

[The use of Cantonese pain descriptors among healthy young adults in Hong Kong].

Science.gov (United States)

Chung, W Y; Wong, C H; Yang, J C; Tan, P P

1998-12-01

The interpretation and expression of pain are closely related to an individual's social and cultural background. To convey messages on pain, language and words (pain descriptors) is particularly significant in assessment and evaluation of pain severity and its management. Therefore, the study of pain descriptors is crucial in clinical practice. It was of exploratory-descriptive design. Samples were recruited by convenience. Data were collected by structured self-administered questionnaire. Data obtained included demographic information and pain descriptors used by the subjects in various pain conditions. Data were analyzed by descriptive statistics. Pain descriptors were categorized according to nature, process, intensity, aggravating factors, accompanying symptoms and behavioral manifestation. Total number of pain descriptors (in Cantonese) based on real pain experience was 3017, mean was 3 (n = 986). The commonest used descriptors was the nature of pain (41%). The intensity of pain constituted 20%. There was no significant difference in the number of pain descriptors between male and female. However, there was a significant difference between the type of pain descriptors used (Mfemale = 526, Mmale = 453, Z = -2.9729, p = 0.0029). There were also significant differences in the use of pain descriptors among the various age groups (X2 = 15.0157, df = 4, P = 0.0047) and educational levels (X2 = 11.2443, df = 4, P = 0.0240). The types of descriptors used increased with an increase in age and education levels. This exploratory-descriptive study explores the use of pain descriptors among Chinese young adults in Hong Kong. The result shows that female use more pain descriptors than male. The pain descriptors that female used are mostly of nature type. The similarities and differences in findings with those of the Ho's (1991) are compared.

Semantic content-based recommendations using semantic graphs.

Science.gov (United States)

Guo, Weisen; Kraines, Steven B

2010-01-01

Recommender systems (RSs) can be useful for suggesting items that might be of interest to specific users. Most existing content-based recommendation (CBR) systems are designed to recommend items based on text content, and the items in these systems are usually described with keywords. However, similarity evaluations based on keywords suffer from the ambiguity of natural languages. We present a semantic CBR method that uses Semantic Web technologies to recommend items that are more similar semantically with the items that the user prefers. We use semantic graphs to represent the items and we calculate the similarity scores for each pair of semantic graphs using an inverse graph frequency algorithm. The items having higher similarity scores to the items that are known to be preferred by the user are recommended.

Applied and implied semantics in crystallographic publishing

Directory of Open Access Journals (Sweden)

McMahon Brian

2012-08-01

Full Text Available Abstract Background Crystallography is a data-rich, software-intensive scientific discipline with a community that has undertaken direct responsibility for publishing its own scientific journals. That community has worked actively to develop information exchange standards allowing readers of structure reports to access directly, and interact with, the scientific content of the articles. Results Structure reports submitted to some journals of the International Union of Crystallography (IUCr can be automatically validated and published through an efficient and cost-effective workflow. Readers can view and interact with the structures in three-dimensional visualization applications, and can access the experimental data should they wish to perform their own independent structure solution and refinement. The journals also layer on top of this facility a number of automated annotations and interpretations to add further scientific value. Conclusions The benefits of semantically rich information exchange standards have revolutionised the scholarly publishing process for crystallography, and establish a model relevant to many other physical science disciplines.

Life, Information, Entropy, and Time: Vehicles for Semantic Inheritance.

Science.gov (United States)

Crofts, Antony R

2007-01-01

evolution. The initial interpretational steps include protein synthesis, molecular recognition, and catalytic potential that facilitate structural and functional roles. Combinatorial possibilities are extended through interactions of increasing complexity in the temporal dimension. (3) All living things show a behavior that indicates awareness of time, or chronognosis. The ∼4 billion years of biological evolution have given rise to forms with increasing sophistication in sensory adaptation. This has been linked to the development of an increasing chronognostic range, and an associated increase in combinatorial complexity. (4) Development of a modern human phenotype and the ability to communicate through language, led to the development of archival storage, and invention of the basic skills, institutions and mechanisms that allowed the evolution of modern civilizations. Combinatorial amplification at the supra-phenotypical level arose from the invention of syntax, grammar, numbers, and the subsequent developments of abstraction in writing, algorithms, etc. The translational machineries of the human mind, the "mutation" of ideas therein, and the "conversations" of our social intercourse, have allowed a limited set of symbolic descriptors to evolve into an exponentially expanding semantic heritage. (5) The three postulates above open interesting epistemological questions. An understanding of topics such dualism, the élan vital, the status of hypothesis in science, memetics, the nature of consciousness, the role of semantic processing in the survival of societies, and Popper's three worlds, require recognition of an insubstantial component. By recognizing a necessary linkage between semantic content and a physical machinery, we can bring these perennial problems into the framework of a realistic philosophy. It is suggested, following Popper, that the ∼4 billion years of evolution of the biosphere represents an exploration of the nature of reality at the physicochemical

3D molecular descriptors important for clinical success.

Science.gov (United States)

Kombo, David C; Tallapragada, Kartik; Jain, Rachit; Chewning, Joseph; Mazurov, Anatoly A; Speake, Jason D; Hauser, Terry A; Toler, Steve

2013-02-25

The pharmacokinetic and safety profiles of clinical drug candidates are greatly influenced by their requisite physicochemical properties. In particular, it has been shown that 2D molecular descriptors such as fraction of Sp3 carbon atoms (Fsp3) and number of stereo centers correlate with clinical success. Using the proteomic off-target hit rate of nicotinic ligands, we found that shape-based 3D descriptors such as the radius of gyration and shadow indices discriminate off-target promiscuity better than do Fsp3 and the number of stereo centers. We have deduced the relevant descriptor values required for a ligand to be nonpromiscuous. Investigating the MDL Drug Data Report (MDDR) database as compounds move from the preclinical stage toward the market, we have found that these shape-based 3D descriptors predict clinical success of compounds at preclinical and phase1 stages vs compounds withdrawn from the market better than do Fsp3 and LogD. Further, these computed 3D molecular descriptors correlate well with experimentally observed solubility, which is among well-known physicochemical properties that drive clinical success. We also found that about 84% of launched drugs satisfy either Shadow index or Fsp3 criteria, whereas withdrawn and discontinued compounds fail to meet the same criteria. Our studies suggest that spherical compounds (rather than their elongated counterparts) with a minimal number of aromatic rings may exhibit a high propensity to advance from clinical trials to market.

Modular Chemical Descriptor Language (MCDL: Stereochemical modules

Directory of Open Access Journals (Sweden)

Gakh Andrei A

2011-01-01

Full Text Available Abstract Background In our previous papers we introduced the Modular Chemical Descriptor Language (MCDL for providing a linear representation of chemical information. A subsequent development was the MCDL Java Chemical Structure Editor which is capable of drawing chemical structures from linear representations and generating MCDL descriptors from structures. Results In this paper we present MCDL modules and accompanying software that incorporate unique representation of molecular stereochemistry based on Cahn-Ingold-Prelog and Fischer ideas in constructing stereoisomer descriptors. The paper also contains additional discussions regarding canonical representation of stereochemical isomers, and brief algorithm descriptions of the open source LINDES, Java applet, and Open Babel MCDL processing module software packages. Conclusions Testing of the upgraded MCDL Java Chemical Structure Editor on compounds taken from several large and diverse chemical databases demonstrated satisfactory performance for storage and processing of stereochemical information in MCDL format.

A Semantic Grid Oriented to E-Tourism

Science.gov (United States)

Zhang, Xiao Ming

With increasing complexity of tourism business models and tasks, there is a clear need of the next generation e-Tourism infrastructure to support flexible automation, integration, computation, storage, and collaboration. Currently several enabling technologies such as semantic Web, Web service, agent and grid computing have been applied in the different e-Tourism applications, however there is no a unified framework to be able to integrate all of them. So this paper presents a promising e-Tourism framework based on emerging semantic grid, in which a number of key design issues are discussed including architecture, ontologies structure, semantic reconciliation, service and resource discovery, role based authorization and intelligent agent. The paper finally provides the implementation of the framework.

In silico modelling of permeation enhancement potency in Caco-2 monolayers based on molecular descriptors and random forest

DEFF Research Database (Denmark)

Welling, Søren Havelund; Clemmensen, Line Katrine Harder; Buckley, Stephen T.

2015-01-01

has been developed.The random forest-QSAR model was based upon Caco-2 data for 41 surfactant-like permeation enhancers from Whitehead et al. (2008) and molecular descriptors calculated from their structure.The QSAR model was validated by two test-sets: (i) an eleven compound experimental set with Caco......-2 data and (ii) nine compounds with Caco-2 data from literature. Feature contributions, a recent developed diagnostic tool, was applied to elucidate the contribution of individual molecular descriptors to the predicted potency. Feature contributions provided easy interpretable suggestions...

Short local descriptors from 2D connected pattern spectra

NARCIS (Netherlands)

Bosilj, Petra; Kijak, Ewa; Wilkinson, Michael H. F.; Lefèvre, Sebastien

2015-01-01

We propose a local region descriptor based on connected pattern spectra, and combined with normalized central moments. The descriptors are calculated for MSER regions of the image, and their performance compared against SIFT. The MSER regions were chosen because they can be efficiently selected by

Cooperative Control for Multiple Autonomous Vehicles Using Descriptor Functions

Directory of Open Access Journals (Sweden)

Marta Niccolini

2014-01-01

Full Text Available The paper presents a novel methodology for the control management of a swarm of autonomous vehicles. The vehicles, or agents, may have different skills, and be employed for different missions. The methodology is based on the definition of descriptor functions that model the capabilities of the single agent and each task or mission. The swarm motion is controlled by minimizing a suitable norm of the error between agents’ descriptor functions and other descriptor functions which models the entire mission. The validity of the proposed technique is tested via numerical simulation, using different task assignment scenarios.

Objective scoring of transformed foci in BALB/c 3T3 cell transformation assay by statistical image descriptors.

Science.gov (United States)

Urani, C; Corvi, R; Callegaro, G; Stefanini, F M

2013-09-01

In vitro cell transformation assays (CTAs) have been shown to model important stages of in vivo carcinogenesis and have the potential to predict carcinogenicity in humans. Advantages of CTAs are their ability of revealing both genotoxic and non-genotoxic carcinogens while reducing both experimental costs and the number of animals used. The endpoint of the CTA is foci formation, and requires classification under light microscopy based on morphology. Thus current limitations for the wide adoption of the assay partially depend on a fair degree of subjectivity in foci scoring. An objective evaluation may be obtained after separating foci from background monolayer in the digital image, and quantifying values of statistical descriptors which are selected to capture eye-scored morphological features. The aim of this study was to develop statistical descriptors to be applied to transformed foci of BALB/c 3T3, which cover foci size, multilayering and invasive cell growth into the background monolayer. Proposed descriptors were applied to a database of 407 foci images to explore the numerical features, and to illustrate open problems and potential solutions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Towards an Approach of Semantic Access Control for Cloud Computing

Science.gov (United States)

Hu, Luokai; Ying, Shi; Jia, Xiangyang; Zhao, Kai

With the development of cloud computing, the mutual understandability among distributed Access Control Policies (ACPs) has become an important issue in the security field of cloud computing. Semantic Web technology provides the solution to semantic interoperability of heterogeneous applications. In this paper, we analysis existing access control methods and present a new Semantic Access Control Policy Language (SACPL) for describing ACPs in cloud computing environment. Access Control Oriented Ontology System (ACOOS) is designed as the semantic basis of SACPL. Ontology-based SACPL language can effectively solve the interoperability issue of distributed ACPs. This study enriches the research that the semantic web technology is applied in the field of security, and provides a new way of thinking of access control in cloud computing.

Object classfication from RGB-D images using depth context kernel descriptors

DEFF Research Database (Denmark)

Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

2015-01-01

Context cue is important in object classification. By embedding the depth context cue of image attributes into kernel descriptors, we propose a new set of depth image descriptors called depth context kernel descriptors (DCKD) for RGB-D based object classification. The motivation of DCKD is to use...... the depth consistency of image attributes defined within a neighboring region to improve the robustness of descriptor matching in the kernel space. Moreover, a novel joint spatial-depth pooling (JSDP) scheme, which further partitions image sub-regions using the depth cue and pools features in both 2D image...

Lagrangian descriptors in dissipative systems.

Science.gov (United States)

Junginger, Andrej; Hernandez, Rigoberto

2016-11-09

The reaction dynamics of time-dependent systems can be resolved through a recrossing-free dividing surface associated with the transition state trajectory-that is, the unique trajectory which is bound to the barrier region for all time in response to a given time-dependent potential. A general procedure based on the minimization of Lagrangian descriptors has recently been developed by Craven and Hernandez [Phys. Rev. Lett., 2015, 115, 148301] to construct this particular trajectory without requiring perturbative expansions relative to the naive transition state point at the top of the barrier. The extension of the method to account for dissipation in the equations of motion requires additional considerations established in this paper because the calculation of the Lagrangian descriptor involves the integration of trajectories in forward and backward time. The two contributions are in general very different because the friction term can act as a source (in backward time) or sink (in forward time) of energy, leading to the possibility that information about the phase space structure may be lost due to the dominance of only one of the terms. To compensate for this effect, we introduce a weighting scheme within the Lagrangian descriptor and demonstrate that for thermal Langevin dynamics it preserves the essential phase space structures, while they are lost in the nonweighted case.

A study of expertise effects for products with contradictory semantics

Directory of Open Access Journals (Sweden)

Wang Ching-Yi

2017-01-01

Full Text Available In the design studies, researchers often use the semantic differential method with bipolar adjectives, such as “modern vs. classical” or “simple vs. complex” when investigating the semantics projected by product forms. However, in design practice, some design examples clearly exhibit the simultaneous use of contradictory meanings in product semantics. For example, retro car evokes nostalgia by borrowing characteristics from classical cars. At the same time it exhibits a modern style. However, most studies measure the product semantics mostly by using subjective measurement. There is lack objective measurement for that. In this research, we examined the results of applying the semantic differential method to measure contradiction in product semantics. The results showed that the distributions of semantic differential ratings for the stimuli with contradictory meanings have higher standard deviations. The sensitivity of semantic recognition may depend on participant expertise. The design experts are trained to be good at visual thinking that could easily identify the contradiction semantics between products. In general, successful embedding of contradictory meanings into product forms are based on simple, typical, and rational forms that can display complex, novel, and perceptual images by adding supplementary elements.

Gun bore flaw image matching based on improved SIFT descriptor

Science.gov (United States)

Zeng, Luan; Xiong, Wei; Zhai, You

2013-01-01

In order to increase the operation speed and matching ability of SIFT algorithm, the SIFT descriptor and matching strategy are improved. First, a method of constructing feature descriptor based on sector area is proposed. By computing the gradients histogram of location bins which are parted into 6 sector areas, a descriptor with 48 dimensions is constituted. It can reduce the dimension of feature vector and decrease the complexity of structuring descriptor. Second, it introduce a strategy that partitions the circular region into 6 identical sector areas starting from the dominate orientation. Consequently, the computational complexity is reduced due to cancellation of rotation operation for the area. The experimental results indicate that comparing with the OpenCV SIFT arithmetic, the average matching speed of the new method increase by about 55.86%. The matching veracity can be increased even under some variation of view point, illumination, rotation, scale and out of focus. The new method got satisfied results in gun bore flaw image matching. Keywords: Metrology, Flaw image matching, Gun bore, Feature descriptor

Sparse B-spline polynomial descriptors for human activity recognition

NARCIS (Netherlands)

Oikonomopoulos, Antonios; Pantic, Maja; Patras, Ioannis

2009-01-01

The extraction and quantization of local image and video descriptors for the subsequent creation of visual codebooks is a technique that has proved very effective for image and video retrieval applications. In this paper we build on this concept and propose a new set of visual descriptors that

Geospatial semantic web

CERN Document Server

Zhang, Chuanrong; Li, Weidong

2015-01-01

This book covers key issues related to Geospatial Semantic Web, including geospatial web services for spatial data interoperability; geospatial ontology for semantic interoperability; ontology creation, sharing, and integration; querying knowledge and information from heterogeneous data source; interfaces for Geospatial Semantic Web, VGI (Volunteered Geographic Information) and Geospatial Semantic Web; challenges of Geospatial Semantic Web; and development of Geospatial Semantic Web applications. This book also describes state-of-the-art technologies that attempt to solve these problems such as WFS, WMS, RDF, OWL, and GeoSPARQL, and demonstrates how to use the Geospatial Semantic Web technologies to solve practical real-world problems such as spatial data interoperability.

Color Independent Components Based SIFT Descriptors for Object/Scene Classification

Science.gov (United States)

Ai, Dan-Ni; Han, Xian-Hua; Ruan, Xiang; Chen, Yen-Wei

In this paper, we present a novel color independent components based SIFT descriptor (termed CIC-SIFT) for object/scene classification. We first learn an efficient color transformation matrix based on independent component analysis (ICA), which is adaptive to each category in a database. The ICA-based color transformation can enhance contrast between the objects and the background in an image. Then we compute CIC-SIFT descriptors over all three transformed color independent components. Since the ICA-based color transformation can boost the objects and suppress the background, the proposed CIC-SIFT can extract more effective and discriminative local features for object/scene classification. The comparison is performed among seven SIFT descriptors, and the experimental classification results show that our proposed CIC-SIFT is superior to other conventional SIFT descriptors.

Semantic guidance of eye movements in real-world scenes.

Science.gov (United States)

Hwang, Alex D; Wang, Hsueh-Cheng; Pomplun, Marc

2011-05-25

The perception of objects in our visual world is influenced by not only their low-level visual features such as shape and color, but also their high-level features such as meaning and semantic relations among them. While it has been shown that low-level features in real-world scenes guide eye movements during scene inspection and search, the influence of semantic similarity among scene objects on eye movements in such situations has not been investigated. Here we study guidance of eye movements by semantic similarity among objects during real-world scene inspection and search. By selecting scenes from the LabelMe object-annotated image database and applying latent semantic analysis (LSA) to the object labels, we generated semantic saliency maps of real-world scenes based on the semantic similarity of scene objects to the currently fixated object or the search target. An ROC analysis of these maps as predictors of subjects' gaze transitions between objects during scene inspection revealed a preference for transitions to objects that were semantically similar to the currently inspected one. Furthermore, during the course of a scene search, subjects' eye movements were progressively guided toward objects that were semantically similar to the search target. These findings demonstrate substantial semantic guidance of eye movements in real-world scenes and show its importance for understanding real-world attentional control. Copyright © 2011 Elsevier Ltd. All rights reserved.

Meaningful Memory in Acute Anorexia Nervosa Patients-Comparing Recall, Learning, and Recognition of Semantically Related and Semantically Unrelated Word Stimuli.

Science.gov (United States)

Terhoeven, Valentin; Kallen, Ursula; Ingenerf, Katrin; Aschenbrenner, Steffen; Weisbrod, Matthias; Herzog, Wolfgang; Brockmeyer, Timo; Friederich, Hans-Christoph; Nikendei, Christoph

2017-03-01

It is unclear whether observed memory impairment in anorexia nervosa (AN) depends on the semantic structure (categorized words) of material to be encoded. We aimed to investigate the processing of semantically related information in AN. Memory performance was assessed in a recall, learning, and recognition test in 27 adult women with AN (19 restricting, 8 binge-eating/purging subtype; average disease duration: 9.32 years) and 30 healthy controls using an extended version of the Rey Auditory Verbal Learning Test, applying semantically related and unrelated word stimuli. Short-term memory (immediate recall, learning), regardless of semantics of the words, was significantly worse in AN patients, whereas long-term memory (delayed recall, recognition) did not differ between AN patients and controls. Semantics of stimuli do not have a better effect on memory recall in AN compared to CO. Impaired short-term versus long-term memory is discussed in relation to dysfunctional working memory in AN. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association.

Robust optimal control design using a differential game approach for open-loop linear quadratic descriptor systems

NARCIS (Netherlands)

Musthofa, M.W.; Salmah, S.; Engwerda, Jacob; Suparwanto, A.

This paper studies the robust optimal control problem for descriptor systems. We applied differential game theory to solve the disturbance attenuation problem. The robust control problem was converted into a reduced ordinary zero-sum game. Within a linear quadratic setting, we solved the problem for

Semantic Multimedia

NARCIS (Netherlands)

S. Staab; A. Scherp; R. Arndt; R. Troncy (Raphael); M. Grzegorzek; C. Saathoff; S. Schenk; L. Hardman (Lynda)

2008-01-01

htmlabstractMultimedia constitutes an interesting field of application for Semantic Web and Semantic Web reasoning, as the access and management of multimedia content and context depends strongly on the semantic descriptions of both. At the same time, multimedia resources constitute complex objects,

Reliability in content analysis: The case of semantic feature norms classification.

Science.gov (United States)

Bolognesi, Marianna; Pilgram, Roosmaryn; van den Heerik, Romy

2017-12-01

Semantic feature norms (e.g., STIMULUS: car → RESPONSE: ) are commonly used in cognitive psychology to look into salient aspects of given concepts. Semantic features are typically collected in experimental settings and then manually annotated by the researchers into feature types (e.g., perceptual features, taxonomic features, etc.) by means of content analyses-that is, by using taxonomies of feature types and having independent coders perform the annotation task. However, the ways in which such content analyses are typically performed and reported are not consistent across the literature. This constitutes a serious methodological problem that might undermine the theoretical claims based on such annotations. In this study, we first offer a review of some of the released datasets of annotated semantic feature norms and the related taxonomies used for content analysis. We then provide theoretical and methodological insights in relation to the content analysis methodology. Finally, we apply content analysis to a new dataset of semantic features and show how the method should be applied in order to deliver reliable annotations and replicable coding schemes. We tackle the following issues: (1) taxonomy structure, (2) the description of categories, (3) coder training, and (4) sustainability of the coding scheme-that is, comparison of the annotations provided by trained versus novice coders. The outcomes of the project are threefold: We provide methodological guidelines for semantic feature classification; we provide a revised and adapted taxonomy that can (arguably) be applied to both concrete and abstract concepts; and we provide a dataset of annotated semantic feature norms.

A Complex Network Approach to Distributional Semantic Models.

Directory of Open Access Journals (Sweden)

Akira Utsumi

Full Text Available A number of studies on network analysis have focused on language networks based on free word association, which reflects human lexical knowledge, and have demonstrated the small-world and scale-free properties in the word association network. Nevertheless, there have been very few attempts at applying network analysis to distributional semantic models, despite the fact that these models have been studied extensively as computational or cognitive models of human lexical knowledge. In this paper, we analyze three network properties, namely, small-world, scale-free, and hierarchical properties, of semantic networks created by distributional semantic models. We demonstrate that the created networks generally exhibit the same properties as word association networks. In particular, we show that the distribution of the number of connections in these networks follows the truncated power law, which is also observed in an association network. This indicates that distributional semantic models can provide a plausible model of lexical knowledge. Additionally, the observed differences in the network properties of various implementations of distributional semantic models are consistently explained or predicted by considering the intrinsic semantic features of a word-context matrix and the functions of matrix weighting and smoothing. Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. The idea underlying the proposed model is that both preferential and random attachments are required to reflect different types of semantic relations in network growth process. We demonstrate that this model provides a better explanation of network behaviors generated by distributional semantic models.

Impact of low alcohol verbal descriptors on perceived strength: An experimental study.

Science.gov (United States)

Vasiljevic, Milica; Couturier, Dominique-Laurent; Marteau, Theresa M

2018-02-01

Low alcohol labels are a set of labels that carry descriptors such as 'low' or 'lighter' to denote alcohol content in beverages. There is growing interest from policymakers and producers in lower strength alcohol products. However, there is a lack of evidence on how the general population perceives verbal descriptors of strength. The present research examines consumers' perceptions of strength (% ABV) and appeal of alcohol products using low or high alcohol verbal descriptors. A within-subjects experimental study in which participants rated the strength and appeal of 18 terms denoting low (nine terms), high (eight terms) and regular (one term) strengths for either (1) wine or (2) beer according to drinking preference. Thousand six hundred adults (796 wine and 804 beer drinkers) sampled from a nationally representative UK panel. Low, Lower, Light, Lighter, and Reduced formed a cluster and were rated as denoting lower strength products than Regular, but higher strength than the cluster with intensifiers consisting of Extra Low, Super Low, Extra Light, and Super Light. Similar clustering in perceived strength was observed amongst the high verbal descriptors. Regular was the most appealing strength descriptor, with the low and high verbal descriptors using intensifiers rated least appealing. The perceived strength and appeal of alcohol products diminished the more the verbal descriptors implied a deviation from Regular. The implications of these findings are discussed in terms of policy implications for lower strength alcohol labelling and associated public health outcomes. Statement of contribution What is already known about this subject? Current UK and EU legislation limits the number of low strength verbal descriptors and the associated alcohol by volume (ABV) to 1.2% ABV and lower. There is growing interest from policymakers and producers to extend the range of lower strength alcohol products above the current cap of 1.2% ABV set out in national legislation. There

Gabor Weber Local Descriptor for Bovine Iris Recognition

OpenAIRE

Sun, Shengnan; Zhao, Lindu; Yang, Shicai

2013-01-01

Iris recognition is a robust biometric technology. This paper proposes a novel local descriptor for bovine iris recognition, named Gabor Weber local descriptor (GWLD). We first compute the Gabor magnitude maps for the input bovine iris image, and then calculate the differential excitation and orientation for each pixel over each Gabor magnitude map. After that, we use these differential excitations and orientations to construct the GWLD histogram representation. Finally, histogram intersectio...

Semantic similarity measure in biomedical domain leverage web search engine.

Science.gov (United States)

Chen, Chi-Huang; Hsieh, Sheau-Ling; Weng, Yung-Ching; Chang, Wen-Yung; Lai, Feipei

2010-01-01

Semantic similarity measure plays an essential role in Information Retrieval and Natural Language Processing. In this paper we propose a page-count-based semantic similarity measure and apply it in biomedical domains. Previous researches in semantic web related applications have deployed various semantic similarity measures. Despite the usefulness of the measurements in those applications, measuring semantic similarity between two terms remains a challenge task. The proposed method exploits page counts returned by the Web Search Engine. We define various similarity scores for two given terms P and Q, using the page counts for querying P, Q and P AND Q. Moreover, we propose a novel approach to compute semantic similarity using lexico-syntactic patterns with page counts. These different similarity scores are integrated adapting support vector machines, to leverage the robustness of semantic similarity measures. Experimental results on two datasets achieve correlation coefficients of 0.798 on the dataset provided by A. Hliaoutakis, 0.705 on the dataset provide by T. Pedersen with physician scores and 0.496 on the dataset provided by T. Pedersen et al. with expert scores.

Exposing SAMOS Data and Vocabularies within the Semantic Web

Science.gov (United States)

Dockery, Nkemdirim; Elya, Jocelyn; Smith, Shawn

2014-05-01

As part of the Ocean Data Interoperability Platform (ODIP), we at the Center for Ocean-Atmospheric Prediction Studies (COAPS) will present the development process for the exposure of quality-controlled data and core vocabularies managed by the Shipboard Automated Meteorological Oceanographic System (SAMOS) initiative using Semantic Web technologies. Participants in the SAMOS initiative collect continuous navigational (position, course, heading, speed), meteorological (winds, pressure, temperature, humidity, radiation), and near-surface oceanographic (sea temperature, salinity) parameters while at sea. One-minute interval observations are packaged and transmitted back to COAPS via daily emails, where they undergo standardized formatting and quality control. The authors will present methods used to expose these daily datasets. The Semantic Web, a vision of the World Wide Web Consortium, focuses on extending the principles of the web from connecting documents to connecting data. The creation of a web of Linked Data that can be used across different applications in a machine-readable way is the ultimate goal. The Resource Description Framework (RDF) is the standard language and format used in the Semantic Web. RDF pages may be queried using the SPARQL Protocol and RDF Query Language (SPARQL). The authors will showcase the development of RDF resources that map SAMOS vocabularies to internationally served vocabularies such as those found in the Natural Environment Research Council (NERC) Vocabulary Server. Each individual SAMOS vocabulary term (data parameter and quality control flag) will be described in an RDF resource page. These RDF resources will define each SAMOS vocabulary term and provide a link to the mapped vocabulary term (or multiple terms) served externally. Along with enhanced retrieval by parameter, time, and location, we will be able to add additional parameters with the confidence that they follow an international standard. The production of RDF

Beyond the VWFA: The orthography-semantics interface in spelling and reading

Science.gov (United States)

Purcell, Jeremy J.; Shea, Jennifer; Rapp, Brenda

2014-01-01

Lexical orthographic information provides the basis for recovering the meanings of words in reading and for generating correct word spellings in writing. Research has provided evidence that an area of the left ventral temporal cortex, a sub-region of what is often referred to as the Visual Word Form Area (VWFA), plays a significant role specifically in lexical orthographic processing. The current investigation goes beyond this previous work by examining the neurotopography of the interface of lexical orthography with semantics. We apply a novel lesion mapping approach with three individuals with acquired dysgraphia and dyslexia who suffered lesions to left ventral temporal cortex. To map cognitive processes to their neural substrates, this lesion mapping approach applies similar logical constraints as used in cognitive neuropsychological research. Using this approach, this investigation: (1) Identifies a region anterior to the VWFA that is important in the interface of orthographic information with semantics for reading and spelling; (2) Determines that, within this Orthography-Semantics Interface Region (OSIR), access to orthography from semantics (spelling) is topographically distinct from access to semantics from orthography (reading); (3) Provides evidence that, within this region, there is modality-specific access to and from lexical semantics for both spoken and written modalities, in both word production and comprehension. Overall, this study contributes to our understanding of the neural architecture at the lexical orthography-semantic-phonological interface within left ventral temporal cortex. PMID:24833190

Semantic evaluations of noise with tonal components in Japan, France, and Germany: a cross-cultural comparison.

Science.gov (United States)

Hansen, Hans; Weber, Reinhard

2009-02-01

An evaluation of tonal components in noise using a semantic differential approach yields several perceptual and connotative factors. This study investigates the effect of culture on these factors with the aid of equivalent listening tests carried out in Japan (n=20), France (n=23), and Germany (n=20). The data's equivalence level is determined by a bias analysis. This analysis gives insight in the cross-cultural validity of the scales used for sound character determination. Three factors were extracted by factor analysis in all cultural subsamples: pleasant, metallic, and power. By employing appropriate target rotations of the factor spaces, the rotated factors were compared and they yield high similarities between the different cultural subsamples. To check cross-cultural differences in means, an item bias analysis was conducted. The a priori assumption of unbiased scales is rejected; the differences obtained are partially linked to bias effects. Acoustical sound descriptors were additionally tested for the semantic dimensions. The high agreement in judgments between the different cultural subsamples contrast the moderate success of the signal parameters to describe the dimensions.

A 3D model retrieval approach based on Bayesian networks lightfield descriptor

Science.gov (United States)

Xiao, Qinhan; Li, Yanjun

2009-12-01

A new 3D model retrieval methodology is proposed by exploiting a novel Bayesian networks lightfield descriptor (BNLD). There are two key novelties in our approach: (1) a BN-based method for building lightfield descriptor; and (2) a 3D model retrieval scheme based on the proposed BNLD. To overcome the disadvantages of the existing 3D model retrieval methods, we explore BN for building a new lightfield descriptor. Firstly, 3D model is put into lightfield, about 300 binary-views can be obtained along a sphere, then Fourier descriptors and Zernike moments descriptors can be calculated out from binaryviews. Then shape feature sequence would be learned into a BN model based on BN learning algorithm; Secondly, we propose a new 3D model retrieval method by calculating Kullback-Leibler Divergence (KLD) between BNLDs. Beneficial from the statistical learning, our BNLD is noise robustness as compared to the existing methods. The comparison between our method and the lightfield descriptor-based approach is conducted to demonstrate the effectiveness of our proposed methodology.

Feature extraction and descriptor calculation methods for automatic georeferencing of Philippines' first microsatellite imagery

Science.gov (United States)

Tupas, M. E. A.; Dasallas, J. A.; Jiao, B. J. D.; Magallon, B. J. P.; Sempio, J. N. H.; Ramos, M. K. F.; Aranas, R. K. D.; Tamondong, A. M.

2017-10-01

The FAST-SIFT corner detector and descriptor extractor combination was used to automatically georeference DIWATA-1 Spaceborne Multispectral Imager images. Features from the Fast Accelerated Segment Test (FAST) algorithm detects corners or keypoints in an image, and these robustly detected keypoints have well-defined positions. Descriptors were computed using Scale-Invariant Feature Transform (SIFT) extractor. FAST-SIFT method effectively SMI same-subscene images detected by the NIR sensor. The method was also tested in stitching NIR images with varying subscene swept by the camera. The slave images were matched to the master image. The keypoints served as the ground control points. Random sample consensus was used to eliminate fall-out matches and ensure accuracy of the feature points from which the transformation parameters were derived. Keypoints are matched based on their descriptor vector. Nearest-neighbor matching is employed based on a metric distance between the descriptors. The metrics include Euclidean and city block, among others. Rough matching outputs not only the correct matches but also the faulty matches. A previous work in automatic georeferencing incorporates a geometric restriction. In this work, we applied a simplified version of the learning method. RANSAC was used to eliminate fall-out matches and ensure accuracy of the feature points. This method identifies if a point fits the transformation function and returns inlier matches. The transformation matrix was solved by Affine, Projective, and Polynomial models. The accuracy of the automatic georeferencing method were determined by calculating the RMSE of interest points, selected randomly, between the master image and transformed slave image.

Varieties of semantic 'access' deficit in Wernicke's aphasia and semantic aphasia.

Science.gov (United States)

Thompson, Hannah E; Robson, Holly; Lambon Ralph, Matthew A; Jefferies, Elizabeth

2015-12-01

Comprehension deficits are common in stroke aphasia, including in cases with (i) semantic aphasia, characterized by poor executive control of semantic processing across verbal and non-verbal modalities; and (ii) Wernicke's aphasia, associated with poor auditory-verbal comprehension and repetition, plus fluent speech with jargon. However, the varieties of these comprehension problems, and their underlying causes, are not well understood. Both patient groups exhibit some type of semantic 'access' deficit, as opposed to the 'storage' deficits observed in semantic dementia. Nevertheless, existing descriptions suggest that these patients might have different varieties of 'access' impairment-related to difficulty resolving competition (in semantic aphasia) versus initial activation of concepts from sensory inputs (in Wernicke's aphasia). We used a case series design to compare patients with Wernicke's aphasia and those with semantic aphasia on Warrington's paradigmatic assessment of semantic 'access' deficits. In these verbal and non-verbal matching tasks, a small set of semantically-related items are repeatedly presented over several cycles so that the target on one trial becomes a distractor on another (building up interference and eliciting semantic 'blocking' effects). Patients with Wernicke's aphasia and semantic aphasia were distinguished according to lesion location in the temporal cortex, but in each group, some individuals had additional prefrontal damage. Both of these aspects of lesion variability-one that mapped onto classical 'syndromes' and one that did not-predicted aspects of the semantic 'access' deficit. Both semantic aphasia and Wernicke's aphasia cases showed multimodal semantic impairment, although as expected, the Wernicke's aphasia group showed greater deficits on auditory-verbal than picture judgements. Distribution of damage in the temporal lobe was crucial for predicting the initially 'beneficial' effects of stimulus repetition: cases with

Complex Correlation Measure: a novel descriptor for Poincaré plot

Directory of Open Access Journals (Sweden)

Gubbi Jayavardhana

2009-08-01

Full Text Available Abstract Background Poincaré plot is one of the important techniques used for visually representing the heart rate variability. It is valuable due to its ability to display nonlinear aspects of the data sequence. However, the problem lies in capturing temporal information of the plot quantitatively. The standard descriptors used in quantifying the Poincaré plot (SD1, SD2 measure the gross variability of the time series data. Determination of advanced methods for capturing temporal properties pose a significant challenge. In this paper, we propose a novel descriptor "Complex Correlation Measure (CCM" to quantify the temporal aspect of the Poincaré plot. In contrast to SD1 and SD2, the CCM incorporates point-to-point variation of the signal. Methods First, we have derived expressions for CCM. Then the sensitivity of descriptors has been shown by measuring all descriptors before and after surrogation of the signal. For each case study, lag-1 Poincaré plots were constructed for three groups of subjects (Arrhythmia, Congestive Heart Failure (CHF and those with Normal Sinus Rhythm (NSR, and the new measure CCM was computed along with SD1 and SD2. ANOVA analysis distribution was used to define the level of significance of mean and variance of SD1, SD2 and CCM for different groups of subjects. Results CCM is defined based on the autocorrelation at different lags of the time series, hence giving an in depth measurement of the correlation structure of the Poincaré plot. A surrogate analysis was performed, and the sensitivity of the proposed descriptor was found to be higher as compared to the standard descriptors. Two case studies were conducted for recognizing arrhythmia and congestive heart failure (CHF subjects from those with NSR, using the Physionet database and demonstrated the usefulness of the proposed descriptors in biomedical applications. CCM was found to be a more significant (p = 6.28E-18 parameter than SD1 and SD2 in discriminating

hERG classification model based on a combination of support vector machine method and GRIND descriptors

DEFF Research Database (Denmark)

Li, Qiyuan; Jorgensen, Flemming Steen; Oprea, Tudor

2008-01-01

and diverse library of 495 compounds. The models combine pharmacophore-based GRIND descriptors with a support vector machine (SVM) classifier in order to discriminate between hERG blockers and nonblockers. Our models were applied at different thresholds from 1 to 40 mu m and achieved an overall accuracy up...

Improved nucleic acid descriptors for siRNA efficacy prediction.

Science.gov (United States)

Sciabola, Simone; Cao, Qing; Orozco, Modesto; Faustino, Ignacio; Stanton, Robert V

2013-02-01

Although considerable progress has been made recently in understanding how gene silencing is mediated by the RNAi pathway, the rational design of effective sequences is still a challenging task. In this article, we demonstrate that including three-dimensional descriptors improved the discrimination between active and inactive small interfering RNAs (siRNAs) in a statistical model. Five descriptor types were used: (i) nucleotide position along the siRNA sequence, (ii) nucleotide composition in terms of presence/absence of specific combinations of di- and trinucleotides, (iii) nucleotide interactions by means of a modified auto- and cross-covariance function, (iv) nucleotide thermodynamic stability derived by the nearest neighbor model representation and (v) nucleic acid structure flexibility. The duplex flexibility descriptors are derived from extended molecular dynamics simulations, which are able to describe the sequence-dependent elastic properties of RNA duplexes, even for non-standard oligonucleotides. The matrix of descriptors was analysed using three statistical packages in R (partial least squares, random forest, and support vector machine), and the most predictive model was implemented in a modeling tool we have made publicly available through SourceForge. Our implementation of new RNA descriptors coupled with appropriate statistical algorithms resulted in improved model performance for the selection of siRNA candidates when compared with publicly available siRNA prediction tools and previously published test sets. Additional validation studies based on in-house RNA interference projects confirmed the robustness of the scoring procedure in prospective studies.

Generative Semantics.

Science.gov (United States)

King, Margaret

The first section of this paper deals with the attempts within the framework of transformational grammar to make semantics a systematic part of linguistic description, and outlines the characteristics of the generative semantics position. The second section takes a critical look at generative semantics in its later manifestations, and makes a case…

Descriptors of natural thermal regimes in streams and their responsiveness to change in the Pacific Northwest of North America

Science.gov (United States)

Arismendi, Ivan; Johnson, Sherri L.; Dunham, Jason B.; Haggerty, Roy

2013-01-01

characteristics or descriptors of thermal regimes in streams. The descriptors we provide herein can be applied across hydro-ecological regions to evaluate spatial and temporal patterns in thermal regimes. Evaluation of coherence and synchrony of different components of thermal regimes can facilitate identification of impacts of regional climate variability or local human or natural influences.

QTLTableMiner++: semantic mining of QTL tables in scientific articles.

Science.gov (United States)

Singh, Gurnoor; Kuzniar, Arnold; van Mulligen, Erik M; Gavai, Anand; Bachem, Christian W; Visser, Richard G F; Finkers, Richard

2018-05-25

A quantitative trait locus (QTL) is a genomic region that correlates with a phenotype. Most of the experimental information about QTL mapping studies is described in tables of scientific publications. Traditional text mining techniques aim to extract information from unstructured text rather than from tables. We present QTLTableMiner ++ (QTM), a table mining tool that extracts and semantically annotates QTL information buried in (heterogeneous) tables of plant science literature. QTM is a command line tool written in the Java programming language. This tool takes scientific articles from the Europe PMC repository as input, extracts QTL tables using keyword matching and ontology-based concept identification. The tables are further normalized using rules derived from table properties such as captions, column headers and table footers. Furthermore, table columns are classified into three categories namely column descriptors, properties and values based on column headers and data types of cell entries. Abbreviations found in the tables are expanded using the Schwartz and Hearst algorithm. Finally, the content of QTL tables is semantically enriched with domain-specific ontologies (e.g. Crop Ontology, Plant Ontology and Trait Ontology) using the Apache Solr search platform and the results are stored in a relational database and a text file. The performance of the QTM tool was assessed by precision and recall based on the information retrieved from two manually annotated corpora of open access articles, i.e. QTL mapping studies in tomato (Solanum lycopersicum) and in potato (S. tuberosum). In summary, QTM detected QTL statements in tomato with 74.53% precision and 92.56% recall and in potato with 82.82% precision and 98.94% recall. QTM is a unique tool that aids in providing QTL information in machine-readable and semantically interoperable formats.

BCL::EMAS — Enantioselective Molecular Asymmetry Descriptor for 3D-QSAR

Directory of Open Access Journals (Sweden)

Mariusz Butkiewicz

2012-08-01

Full Text Available Stereochemistry is an important determinant of a molecule’s biological activity. Stereoisomers can have different degrees of efficacy or even opposing effects when interacting with a target protein. Stereochemistry is a molecular property difficult to represent in 2D-QSAR as it is an inherently three-dimensional phenomenon. A major drawback of most proposed descriptors for 3D-QSAR that encode stereochemistry is that they require a heuristic for defining all stereocenters and rank-ordering its substituents. Here we propose a novel 3D-QSAR descriptor termed Enantioselective Molecular ASymmetry (EMAS that is capable of distinguishing between enantiomers in the absence of such heuristics. The descriptor aims to measure the deviation from an overall symmetric shape of the molecule. A radial-distribution function (RDF determines a signed volume of tetrahedrons of all triplets of atoms and the molecule center. The descriptor can be enriched with atom-centric properties such as partial charge. This descriptor showed good predictability when tested with a dataset of thirty-one steroids commonly used to benchmark stereochemistry descriptors (r² = 0.89, q² = 0.78. Additionally, EMAS improved enrichment of 4.38 versus 3.94 without EMAS in a simulated virtual high-throughput screening (vHTS for inhibitors and substrates of cytochrome P450 (PUBCHEM AID891.

Trust estimation of the semantic web using semantic web clustering

Science.gov (United States)

Shirgahi, Hossein; Mohsenzadeh, Mehran; Haj Seyyed Javadi, Hamid

2017-05-01

Development of semantic web and social network is undeniable in the Internet world these days. Widespread nature of semantic web has been very challenging to assess the trust in this field. In recent years, extensive researches have been done to estimate the trust of semantic web. Since trust of semantic web is a multidimensional problem, in this paper, we used parameters of social network authority, the value of pages links authority and semantic authority to assess the trust. Due to the large space of semantic network, we considered the problem scope to the clusters of semantic subnetworks and obtained the trust of each cluster elements as local and calculated the trust of outside resources according to their local trusts and trust of clusters to each other. According to the experimental result, the proposed method shows more than 79% Fscore that is about 11.9% in average more than Eigen, Tidal and centralised trust methods. Mean of error in this proposed method is 12.936, that is 9.75% in average less than Eigen and Tidal trust methods.

Ligand Electron Density Shape Recognition Using 3D Zernike Descriptors

Science.gov (United States)

Gunasekaran, Prasad; Grandison, Scott; Cowtan, Kevin; Mak, Lora; Lawson, David M.; Morris, Richard J.

We present a novel approach to crystallographic ligand density interpretation based on Zernike shape descriptors. Electron density for a bound ligand is expanded in an orthogonal polynomial series (3D Zernike polynomials) and the coefficients from this expansion are employed to construct rotation-invariant descriptors. These descriptors can be compared highly efficiently against large databases of descriptors computed from other molecules. In this manuscript we describe this process and show initial results from an electron density interpretation study on a dataset containing over a hundred OMIT maps. We could identify the correct ligand as the first hit in about 30 % of the cases, within the top five in a further 30 % of the cases, and giving rise to an 80 % probability of getting the correct ligand within the top ten matches. In all but a few examples, the top hit was highly similar to the correct ligand in both shape and chemistry. Further extensions and intrinsic limitations of the method are discussed.

Improving scale invariant feature transform-based descriptors with shape-color alliance robust feature

Science.gov (United States)

Wang, Rui; Zhu, Zhengdan; Zhang, Liang

2015-05-01

Constructing appropriate descriptors for interest points in image matching is a critical aspect task in computer vision and pattern recognition. A method as an extension of the scale invariant feature transform (SIFT) descriptor called shape-color alliance robust feature (SCARF) descriptor is presented. To address the problem that SIFT is designed mainly for gray images and lack of global information for feature points, the proposed approach improves the SIFT descriptor by means of a concentric-rings model, as well as integrating the color invariant space and shape context with SIFT to construct the SCARF descriptor. The SCARF method developed is more robust than the conventional SIFT with respect to not only the color and photometrical variations but also the measuring similarity as a global variation between two shapes. A comparative evaluation of different descriptors is carried out showing that the SCARF approach provides better results than the other four state-of-the-art related methods.

NOTE - Characterization of genetic variability among common bean genotypes by morphological descriptors

Directory of Open Access Journals (Sweden)

Marilene Santos de Lima

2012-01-01

Full Text Available The purpose of this study was to characterize the genetic variability in 100 genotypes of the Active Germplasm Bank of common bean of the Federal University of Viçosa, by morphological descriptors, classify them in groups of genetic similarity and to identify the degree of relevance of descriptors of genetic divergence. The genotypes were evaluated based on 22 quantitative and qualitative morphological descriptors. The highyielding genotypes V 7936, Gold Gate, LM 95103904, 1829 S 349 Venezuela, and PF 9029975, CNFC 9454 andFe 732015, with upright growth, have potential for use as parents in common bean breeding programs. By genetic divergence analysis, the genotypes were clustered in eight groups of genetic dissimilarity. By methods of principal components, 9 of the 22 descriptors were eliminated, for being redundant or little variable, suggesting that 10-20 morphological descriptors can be used in studies of characterization of genetic variation.

Discrimination Power of Polynomial-Based Descriptors for Graphs by Using Functional Matrices.

Science.gov (United States)

Dehmer, Matthias; Emmert-Streib, Frank; Shi, Yongtang; Stefu, Monica; Tripathi, Shailesh

2015-01-01

In this paper, we study the discrimination power of graph measures that are based on graph-theoretical matrices. The paper generalizes the work of [M. Dehmer, M. Moosbrugger. Y. Shi, Encoding structural information uniquely with polynomial-based descriptors by employing the Randić matrix, Applied Mathematics and Computation, 268(2015), 164-168]. We demonstrate that by using the new functional matrix approach, exhaustively generated graphs can be discriminated more uniquely than shown in the mentioned previous work.

New polynomial-based molecular descriptors with low degeneracy.

Directory of Open Access Journals (Sweden)

Matthias Dehmer

Full Text Available In this paper, we introduce a novel graph polynomial called the 'information polynomial' of a graph. This graph polynomial can be derived by using a probability distribution of the vertex set. By using the zeros of the obtained polynomial, we additionally define some novel spectral descriptors. Compared with those based on computing the ordinary characteristic polynomial of a graph, we perform a numerical study using real chemical databases. We obtain that the novel descriptors do have a high discrimination power.

The retrieval efficiency test of descriptors and free vocabulary terms in INIS on-line search

International Nuclear Information System (INIS)

Ebinuma, Yukio; Takahashi, Satoko

1981-01-01

The test was done for 1) search topics with appropriate descriptors, 2) search topics with considerably broader descriptors, 3) search topics with no appropriate descriptors. As to (1) and (2) the retrieval efficiency was the same both on descriptor system and on keyword system (descriptors + free terms), and the search formulas were easily constructed. As to (3) the descriptor system ensured the recall ratio but decreased the precision ratio. On the other hand the keyword system made the construction of search formulas easy and resulted in good retrieval efficiency. The search system which is available both for full match method of descriptors and truncation method of keywords is desirable because each method can be selected according to the searcher's strategy and search topics. Free-term system seems unnecessary. (author)

Evaluating the effect of annotation size on measures of semantic similarity

KAUST Repository

Kulmanov, Maxat

2017-02-13

Background: Ontologies are widely used as metadata in biological and biomedical datasets. Measures of semantic similarity utilize ontologies to determine how similar two entities annotated with classes from ontologies are, and semantic similarity is increasingly applied in applications ranging from diagnosis of disease to investigation in gene networks and functions of gene products.

The effects of variant descriptors on the potential effectiveness of plain packaging.

Science.gov (United States)

Borland, Ron; Savvas, Steven

2014-01-01

To examine the effects that variant descriptor labels on cigarette packs have on smokers' perceptions of those packs and the cigarettes contained within. As part of two larger web-based studies (each involved 160 young adult ever-smokers 18-29 years old), respondents were shown a computer image of a plain cigarette pack and sets of related variant descriptors. The sets included terms that varied in terms of descriptors of colours as names, flavour strength, degrees of filter venting, filter types, quality, type of cigarette and numbers. For each set, respondents rated the highest and lowest of two or three of the following four characteristics: quality, strongest or weakest in taste, delivers most or least tar/nicotine, and most or least level of harm. There were significant differences on all four ratings. Quality ratings were the least differentiated. Except for colour descriptors, where 'Gold' rated high in quality but medium in other ratings, ratings of quality, harm, strength and delivery were all positively associated when rated on the same descriptors. Descriptor labels on cigarette packs, can affect smokers' perceptions of the characteristics of the cigarettes contained within. Therefore, they are a potential means by which product differentiation can occur. In particular, having variants differing in perceived strength while not differing in deliveries of harmful ingredients is particularly problematic. Any packaging policy should take into account the possibility that variant descriptors can mislead smokers into making inappropriate product attributions.

Uncertainty modeling process for semantic technology

Directory of Open Access Journals (Sweden)

Rommel N. Carvalho

2016-08-01

Full Text Available The ubiquity of uncertainty across application domains generates a need for principled support for uncertainty management in semantically aware systems. A probabilistic ontology provides constructs for representing uncertainty in domain ontologies. While the literature has been growing on formalisms for representing uncertainty in ontologies, there remains little guidance in the knowledge engineering literature for how to design probabilistic ontologies. To address the gap, this paper presents the Uncertainty Modeling Process for Semantic Technology (UMP-ST, a new methodology for modeling probabilistic ontologies. To explain how the methodology works and to verify that it can be applied to different scenarios, this paper describes step-by-step the construction of a proof-of-concept probabilistic ontology. The resulting domain model can be used to support identification of fraud in public procurements in Brazil. While the case study illustrates the development of a probabilistic ontology in the PR-OWL probabilistic ontology language, the methodology is applicable to any ontology formalism that properly integrates uncertainty with domain semantics.

Semantic reasoning with XML-based biomedical information models.

Science.gov (United States)

O'Connor, Martin J; Das, Amar

2010-01-01

The Extensible Markup Language (XML) is increasingly being used for biomedical data exchange. The parallel growth in the use of ontologies in biomedicine presents opportunities for combining the two technologies to leverage the semantic reasoning services provided by ontology-based tools. There are currently no standardized approaches for taking XML-encoded biomedical information models and representing and reasoning with them using ontologies. To address this shortcoming, we have developed a workflow and a suite of tools for transforming XML-based information models into domain ontologies encoded using OWL. In this study, we applied semantics reasoning methods to these ontologies to automatically generate domain-level inferences. We successfully used these methods to develop semantic reasoning methods for information models in the HIV and radiological image domains.

Molecular Descriptors Family on Structure Activity Relationships 3. Antituberculotic Activity of some Polyhydroxyxanthones

Directory of Open Access Journals (Sweden)

Sorana BOLBOACĂ

2005-06-01

Full Text Available The antituberculotic activity of some polyhydroxyxanthones was estimated using the Molecular Descriptors Family on Structure Activity Relationships methodology. From a total number of 298110 real and distinct calculated descriptors, 94843 were significantly different and entered into multiple linear regression analysis. The best performing bi-varied model was obtained by use of all polyhydroxyxanthones. The MDF SAR model was validated splitting the molecules into training and test sets. A correlated correlations analysis was applied in other to compare the MDF SAR models with the previous SAR model. The prediction ability of antituberculotic activity of polyhydroxyxanthones with MDF SAR methodology is sustained by three arguments: leave-one-out procedure, training vs. test procedure, and the correlated correlations analysis. Looking at the bi-varied MDF SAR model, we can conclude that the antituberculotic activity of polyhydroxyxanthones is almost of geometrical nature (99% and is strongly dependent on partial atomic charge and group electronegativity.

Semantic Desktop

Science.gov (United States)

Sauermann, Leo; Kiesel, Malte; Schumacher, Kinga; Bernardi, Ansgar

In diesem Beitrag wird gezeigt, wie der Arbeitsplatz der Zukunft aussehen könnte und wo das Semantic Web neue Möglichkeiten eröffnet. Dazu werden Ansätze aus dem Bereich Semantic Web, Knowledge Representation, Desktop-Anwendungen und Visualisierung vorgestellt, die es uns ermöglichen, die bestehenden Daten eines Benutzers neu zu interpretieren und zu verwenden. Dabei bringt die Kombination von Semantic Web und Desktop Computern besondere Vorteile - ein Paradigma, das unter dem Titel Semantic Desktop bekannt ist. Die beschriebenen Möglichkeiten der Applikationsintegration sind aber nicht auf den Desktop beschränkt, sondern können genauso in Web-Anwendungen Verwendung finden.

Towards a model-based semantic e-Invoicing standard for the Dutch government

NARCIS (Netherlands)

Verhoosel, J.P.C.; Bekkum, M.A. van; Roes, J.B.M.; Krukkert, D.; Schrier, A.

2011-01-01

In this paper we discuss the case of defining a common semantic e-invoicing model for the Dutch government. We have defined a model-based methodology for developing semantic standards and have applied this methodology to the e-invoicing model. This methodology takes into account that multiple

On the Alignment of Shapes Represented by Fourier Descriptors

DEFF Research Database (Denmark)

Sjöstrand, Karl; Ericsson, Anders; Larsen, Rasmus

2006-01-01

The representation of shapes by Fourier descriptors is a time-honored technique that has received relatively little attention lately. Nevertheless, it has many benefits and is applicable for describing a range of medical structures in two dimensions. Delineations in medical applications often...... consist of continuous outlines of structures, where no information of correspondence between samples exist. In this article, we discuss an alignment method that works directly with the functional representation of Fourier descriptors, and that is optimal in a least-squares sense. With corresponding...... represented by common landmarks can be constructed in an automatic fashion. If the aligned Fourier descriptors are inverse transformed from the frequency domain to the spatial domain, a set of roughly aligned landmarks are obtained. The positions of these are then adjusted along the contour of the objects...

Improving scale invariant feature transform with local color contrastive descriptor for image classification

Science.gov (United States)

Guo, Sheng; Huang, Weilin; Qiao, Yu

2017-01-01

Image representation and classification are two fundamental tasks toward version understanding. Shape and texture provide two key features for visual representation and have been widely exploited in a number of successful local descriptors, e.g., scale invariant feature transform (SIFT), local binary pattern descriptor, and histogram of oriented gradient. Unlike these gradient-based descriptors, this paper presents a simple yet efficient local descriptor, named local color contrastive descriptor (LCCD), which captures the contrastive aspects among local regions or color channels for image representation. LCCD is partly inspired by the neural science facts that color contrast plays important roles in visual perception and there exist strong linkages between color and shape. We leverage f-divergence as a robust measure to estimate the contrastive features between different spatial locations and multiple channels. Our descriptor enriches local image representation with both color and contrast information. Due to that LCCD does not explore any gradient information, individual LCCD does not yield strong performance. But we verified experimentally that LCCD can compensate strongly SIFT. Extensive experimental results on image classification show that our descriptor improves the performance of SIFT substantially by combination on three challenging benchmarks, including MIT Indoor-67 database, SUN397, and PASCAL VOC 2007.

Stereo matching based on SIFT descriptor with illumination and camera invariance

Science.gov (United States)

Niu, Haitao; Zhao, Xunjie; Li, Chengjin; Peng, Xiang

2010-10-01

Stereo matching is the process of finding corresponding points in two or more images. The description of interest points is a critical aspect of point correspondence which is vital in stereo matching. SIFT descriptor has been proven to be better on the distinctiveness and robustness than other local descriptors. However, SIFT descriptor does not involve color information of feature point which provides powerfully distinguishable feature in matching tasks. Furthermore, in a real scene, image color are affected by various geometric and radiometric factors,such as gamma correction and exposure. These situations are very common in stereo images. For this reason, the color recorded by a camera is not a reliable cue, and the color consistency assumption is no longer valid between stereo images in real scenes. Hence the performance of other SIFT-based stereo matching algorithms can be severely degraded under the radiometric variations. In this paper, we present a new improved SIFT stereo matching algorithms that is invariant to various radiometric variations between left and right images. Unlike other improved SIFT stereo matching algorithms, we explicitly employ the color formation model with the parameters of lighting geometry, illuminant color and camera gamma in SIFT descriptor. Firstly, we transform the input color images to log-chromaticity color space, thus a linear relationship can be established. Then, we use a log-polar histogram to build three color invariance components for SIFT descriptor. So that our improved SIFT descriptor is invariant to lighting geometry, illuminant color and camera gamma changes between left and right images. Then we can match feature points between two images and use SIFT descriptor Euclidean distance as a geometric measure in our data sets to make it further accurate and robust. Experimental results show that our method is superior to other SIFT-based algorithms including conventional stereo matching algorithms under various

A Color-Texture-Structure Descriptor for High-Resolution Satellite Image Classification

Directory of Open Access Journals (Sweden)

Huai Yu

2016-03-01

Full Text Available Scene classification plays an important role in understanding high-resolution satellite (HRS remotely sensed imagery. For remotely sensed scenes, both color information and texture information provide the discriminative ability in classification tasks. In recent years, substantial performance gains in HRS image classification have been reported in the literature. One branch of research combines multiple complementary features based on various aspects such as texture, color and structure. Two methods are commonly used to combine these features: early fusion and late fusion. In this paper, we propose combining the two methods under a tree of regions and present a new descriptor to encode color, texture and structure features using a hierarchical structure-Color Binary Partition Tree (CBPT, which we call the CTS descriptor. Specifically, we first build the hierarchical representation of HRS imagery using the CBPT. Then we quantize the texture and color features of dense regions. Next, we analyze and extract the co-occurrence patterns of regions based on the hierarchical structure. Finally, we encode local descriptors to obtain the final CTS descriptor and test its discriminative capability using object categorization and scene classification with HRS images. The proposed descriptor contains the spectral, textural and structural information of the HRS imagery and is also robust to changes in illuminant color, scale, orientation and contrast. The experimental results demonstrate that the proposed CTS descriptor achieves competitive classification results compared with state-of-the-art algorithms.

Image feature detectors and descriptors foundations and applications

CERN Document Server

Hassaballah, Mahmoud

2016-01-01

This book provides readers with a selection of high-quality chapters that cover both theoretical concepts and practical applications of image feature detectors and descriptors. It serves as reference for researchers and practitioners by featuring survey chapters and research contributions on image feature detectors and descriptors. Additionally, it emphasizes several keywords in both theoretical and practical aspects of image feature extraction. The keywords include acceleration of feature detection and extraction, hardware implantations, image segmentation, evolutionary algorithm, ordinal measures, as well as visual speech recognition. .

A “loop” shape descriptor and its application to automated segmentation of airways from CT scans

Energy Technology Data Exchange (ETDEWEB)

Pu, Jiantao [Department of Radiology, First Affiliated Hospital of Medical College, Xi’an Jiaotong University, Shaanxi 710061, People’s Republic of China, and Departments of Radiology and Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15213 (United States); Jin, Chenwang, E-mail: jcw76@163.com; Yu, Nan; Qian, Yongqiang; Guo, Youmin [Department of Radiology, First Affiliated Hospital of Medical College, Xi’an Jiaotong University, Shaanxi 710061 (China); Wang, Xiaohua [Third Affiliated Hospital, Peking University, Beijing, People’s Republic of China, 100029 (China); Meng, Xin [Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania 15213 (United States)

2015-06-15

Purpose: A novel shape descriptor is presented to aid an automated identification of the airways depicted on computed tomography (CT) images. Methods: Instead of simplifying the tubular characteristic of the airways as an ideal mathematical cylindrical or circular shape, the proposed “loop” shape descriptor exploits the fact that the cross sections of any tubular structure (regardless of its regularity) always appear as a loop. In implementation, the authors first reconstruct the anatomical structures in volumetric CT as a three-dimensional surface model using the classical marching cubes algorithm. Then, the loop descriptor is applied to locate the airways with a concave loop cross section. To deal with the variation of the airway walls in density as depicted on CT images, a multiple threshold strategy is proposed. A publicly available chest CT database consisting of 20 CT scans, which was designed specifically for evaluating an airway segmentation algorithm, was used for quantitative performance assessment. Measures, including length, branch count, and generations, were computed under the aid of a skeletonization operation. Results: For the test dataset, the airway length ranged from 64.6 to 429.8 cm, the generation ranged from 7 to 11, and the branch number ranged from 48 to 312. These results were comparable to the performance of the state-of-the-art algorithms validated on the same dataset. Conclusions: The authors’ quantitative experiment demonstrated the feasibility and reliability of the developed shape descriptor in identifying lung airways.

Semantic heterogeneity: comparing new semantic web approaches with those of digital libraries

OpenAIRE

Krause, Jürgen

2008-01-01

To demonstrate that newer developments in the semantic web community, particularly those based on ontologies (simple knowledge organization system and others) mitigate common arguments from the digital library (DL) community against participation in the Semantic web. The approach is a semantic web discussion focusing on the weak structure of the Web and the lack of consideration given to the semantic content during indexing. The points criticised by the semantic web and ontology approaches ar...

Semantic framework for mapping object-oriented model to semantic web languages.

Science.gov (United States)

Ježek, Petr; Mouček, Roman

2015-01-01

The article deals with and discusses two main approaches in building semantic structures for electrophysiological metadata. It is the use of conventional data structures, repositories, and programming languages on one hand and the use of formal representations of ontologies, known from knowledge representation, such as description logics or semantic web languages on the other hand. Although knowledge engineering offers languages supporting richer semantic means of expression and technological advanced approaches, conventional data structures and repositories are still popular among developers, administrators and users because of their simplicity, overall intelligibility, and lower demands on technical equipment. The choice of conventional data resources and repositories, however, raises the question of how and where to add semantics that cannot be naturally expressed using them. As one of the possible solutions, this semantics can be added into the structures of the programming language that accesses and processes the underlying data. To support this idea we introduced a software prototype that enables its users to add semantically richer expressions into a Java object-oriented code. This approach does not burden users with additional demands on programming environment since reflective Java annotations were used as an entry for these expressions. Moreover, additional semantics need not to be written by the programmer directly to the code, but it can be collected from non-programmers using a graphic user interface. The mapping that allows the transformation of the semantically enriched Java code into the Semantic Web language OWL was proposed and implemented in a library named the Semantic Framework. This approach was validated by the integration of the Semantic Framework in the EEG/ERP Portal and by the subsequent registration of the EEG/ERP Portal in the Neuroscience Information Framework.

Scene text recognition in mobile applications by character descriptor and structure configuration.

Science.gov (United States)

Yi, Chucai; Tian, Yingli

2014-07-01

Text characters and strings in natural scene can provide valuable information for many applications. Extracting text directly from natural scene images or videos is a challenging task because of diverse text patterns and variant background interferences. This paper proposes a method of scene text recognition from detected text regions. In text detection, our previously proposed algorithms are applied to obtain text regions from scene image. First, we design a discriminative character descriptor by combining several state-of-the-art feature detectors and descriptors. Second, we model character structure at each character class by designing stroke configuration maps. Our algorithm design is compatible with the application of scene text extraction in smart mobile devices. An Android-based demo system is developed to show the effectiveness of our proposed method on scene text information extraction from nearby objects. The demo system also provides us some insight into algorithm design and performance improvement of scene text extraction. The evaluation results on benchmark data sets demonstrate that our proposed scheme of text recognition is comparable with the best existing methods.

Contextually guided very-high-resolution imagery classification with semantic segments

Science.gov (United States)

Zhao, Wenzhi; Du, Shihong; Wang, Qiao; Emery, William J.

2017-10-01

Contextual information, revealing relationships and dependencies between image objects, is one of the most important information for the successful interpretation of very-high-resolution (VHR) remote sensing imagery. Over the last decade, geographic object-based image analysis (GEOBIA) technique has been widely used to first divide images into homogeneous parts, and then to assign semantic labels according to the properties of image segments. However, due to the complexity and heterogeneity of VHR images, segments without semantic labels (i.e., semantic-free segments) generated with low-level features often fail to represent geographic entities (such as building roofs usually be partitioned into chimney/antenna/shadow parts). As a result, it is hard to capture contextual information across geographic entities when using semantic-free segments. In contrast to low-level features, "deep" features can be used to build robust segments with accurate labels (i.e., semantic segments) in order to represent geographic entities at higher levels. Based on these semantic segments, semantic graphs can be constructed to capture contextual information in VHR images. In this paper, semantic segments were first explored with convolutional neural networks (CNN) and a conditional random field (CRF) model was then applied to model the contextual information between semantic segments. Experimental results on two challenging VHR datasets (i.e., the Vaihingen and Beijing scenes) indicate that the proposed method is an improvement over existing image classification techniques in classification performance (overall accuracy ranges from 82% to 96%).

Programming the semantic web

CERN Document Server

Segaran, Toby; Taylor, Jamie

2009-01-01

With this book, the promise of the Semantic Web -- in which machines can find, share, and combine data on the Web -- is not just a technical possibility, but a practical reality Programming the Semantic Web demonstrates several ways to implement semantic web applications, using current and emerging standards and technologies. You'll learn how to incorporate existing data sources into semantically aware applications and publish rich semantic data. Each chapter walks you through a single piece of semantic technology and explains how you can use it to solve real problems. Whether you're writing

Descriptor Data Bank (DDB): A Cloud Platform for Multiperspective Modeling of Protein-Ligand Interactions.

Science.gov (United States)

Ashtawy, Hossam M; Mahapatra, Nihar R

2018-01-22

Protein-ligand (PL) interactions play a key role in many life processes such as molecular recognition, molecular binding, signal transmission, and cell metabolism. Examples of interaction forces include hydrogen bonding, hydrophobic effects, steric clashes, electrostatic contacts, and van der Waals attractions. Currently, a large number of hypotheses and perspectives to model these interaction forces are scattered throughout the literature and largely forgotten. Instead, had they been assembled and utilized collectively, they would have substantially improved the accuracy of predicting binding affinity of protein-ligand complexes. In this work, we present Descriptor Data Bank (DDB), a data-driven platform on the cloud for facilitating multiperspective modeling of PL interactions. DDB is an open-access hub for depositing, hosting, executing, and sharing descriptor extraction tools and data for a large number of interaction modeling hypotheses. The platform also implements a machine-learning (ML) toolbox for automatic descriptor filtering and analysis and scoring function (SF) fitting and prediction. The descriptor filtering module is used to filter out irrelevant and/or noisy descriptors and to produce a compact subset from all available features. We seed DDB with 16 diverse descriptor extraction tools developed in-house and collected from the literature. The tools altogether generate over 2700 descriptors that characterize (i) proteins, (ii) ligands, and (iii) protein-ligand complexes. The in-house descriptors we extract are protein-specific which are based on pairwise primary and tertiary alignment of protein structures followed by clustering and trilateration. We built and used DDB's ML library to fit SFs to the in-house descriptors and those collected from the literature. We then evaluated them on several data sets that were constructed to reflect real-world drug screening scenarios. We found that multiperspective SFs that were constructed using a large number

Music Identification System Using MPEG-7 Audio Signature Descriptors

Science.gov (United States)

You, Shingchern D.; Chen, Wei-Hwa; Chen, Woei-Kae

2013-01-01

This paper describes a multiresolution system based on MPEG-7 audio signature descriptors for music identification. Such an identification system may be used to detect illegally copied music circulated over the Internet. In the proposed system, low-resolution descriptors are used to search likely candidates, and then full-resolution descriptors are used to identify the unknown (query) audio. With this arrangement, the proposed system achieves both high speed and high accuracy. To deal with the problem that a piece of query audio may not be inside the system's database, we suggest two different methods to find the decision threshold. Simulation results show that the proposed method II can achieve an accuracy of 99.4% for query inputs both inside and outside the database. Overall, it is highly possible to use the proposed system for copyright control. PMID:23533359

Music Identification System Using MPEG-7 Audio Signature Descriptors

Directory of Open Access Journals (Sweden)

Shingchern D. You

2013-01-01

Full Text Available This paper describes a multiresolution system based on MPEG-7 audio signature descriptors for music identification. Such an identification system may be used to detect illegally copied music circulated over the Internet. In the proposed system, low-resolution descriptors are used to search likely candidates, and then full-resolution descriptors are used to identify the unknown (query audio. With this arrangement, the proposed system achieves both high speed and high accuracy. To deal with the problem that a piece of query audio may not be inside the system’s database, we suggest two different methods to find the decision threshold. Simulation results show that the proposed method II can achieve an accuracy of 99.4% for query inputs both inside and outside the database. Overall, it is highly possible to use the proposed system for copyright control.

Semantic Web integration of Cheminformatics resources with the SADI framework

Directory of Open Access Journals (Sweden)

Chepelev Leonid L

2011-05-01

Full Text Available Abstract Background The diversity and the largely independent nature of chemical research efforts over the past half century are, most likely, the major contributors to the current poor state of chemical computational resource and database interoperability. While open software for chemical format interconversion and database entry cross-linking have partially addressed database interoperability, computational resource integration is hindered by the great diversity of software interfaces, languages, access methods, and platforms, among others. This has, in turn, translated into limited reproducibility of computational experiments and the need for application-specific computational workflow construction and semi-automated enactment by human experts, especially where emerging interdisciplinary fields, such as systems chemistry, are pursued. Fortunately, the advent of the Semantic Web, and the very recent introduction of RESTful Semantic Web Services (SWS may present an opportunity to integrate all of the existing computational and database resources in chemistry into a machine-understandable, unified system that draws on the entirety of the Semantic Web. Results We have created a prototype framework of Semantic Automated Discovery and Integration (SADI framework SWS that exposes the QSAR descriptor functionality of the Chemistry Development Kit. Since each of these services has formal ontology-defined input and output classes, and each service consumes and produces RDF graphs, clients can automatically reason about the services and available reference information necessary to complete a given overall computational task specified through a simple SPARQL query. We demonstrate this capability by carrying out QSAR analysis backed by a simple formal ontology to determine whether a given molecule is drug-like. Further, we discuss parameter-based control over the execution of SADI SWS. Finally, we demonstrate the value of computational resource

Semantic metrics

OpenAIRE

Hu, Bo; Kalfoglou, Yannis; Dupplaw, David; Alani, Harith; Lewis, Paul; Shadbolt, Nigel

2006-01-01

In the context of the Semantic Web, many ontology-related operations, e.g. ontology ranking, segmentation, alignment, articulation, reuse, evaluation, can be boiled down to one fundamental operation: computing the similarity and/or dissimilarity among ontological entities, and in some cases among ontologies themselves. In this paper, we review standard metrics for computing distance measures and we propose a series of semantic metrics. We give a formal account of semantic metrics drawn from a...

Visualization and processing of higher order descriptors for multi-valued data

CERN Document Server

Schultz, Thomas

2015-01-01

Modern imaging techniques and computational simulations yield complex multi-valued data that require higher-order mathematical descriptors. This book addresses topics of importance when dealing with such data, including frameworks for image processing, visualization, and statistical analysis of higher-order descriptors. It also provides examples of the successful use of higher-order descriptors in specific applications and a glimpse of the next generation of diffusion MRI. To do so, it combines contributions on new developments, current challenges in this area, and state-of-the-art surveys.   Compared to the increasing importance of higher-order descriptors in a range of applications, tools for analysis and processing are still relatively hard to come by. Even though application areas such as medical imaging, fluid dynamics, and structural mechanics are very different in nature they face many shared challenges. This book provides an interdisciplinary perspective on this topic with contributions from key rese...

Situational Awareness Applied to Geology Field Mapping using Integration of Semantic Data and Visualization Techniques

Science.gov (United States)

Houser, P. I. Q.

2017-12-01

21st century earth science is data-intensive, characterized by heterogeneous, sometimes voluminous collections representing phenomena at different scales collected for different purposes and managed in disparate ways. However, much of the earth's surface still requires boots-on-the-ground, in-person fieldwork in order to detect the subtle variations from which humans can infer complex structures and patterns. Nevertheless, field experiences can and should be enabled and enhanced by a variety of emerging technologies. The goal of the proposed research project is to pilot test emerging data integration, semantic and visualization technologies for evaluation of their potential usefulness in the field sciences, particularly in the context of field geology. The proposed project will investigate new techniques for data management and integration enabled by semantic web technologies, along with new techniques for augmented reality that can operate on such integrated data to enable in situ visualization in the field. The research objectives include: Develop new technical infrastructure that applies target technologies to field geology; Test, evaluate, and assess the technical infrastructure in a pilot field site; Evaluate the capabilities of the systems for supporting and augmenting field science; and Assess the generality of the system for implementation in new and different types of field sites. Our hypothesis is that these technologies will enable what we call "field science situational awareness" - a cognitive state formerly attained only through long experience in the field - that is highly desirable but difficult to achieve in time- and resource-limited settings. Expected outcomes include elucidation of how, and in what ways, these technologies are beneficial in the field; enumeration of the steps and requirements to implement these systems; and cost/benefit analyses that evaluate under what conditions the investments of time and resources are advisable to construct

Practical Experiences for the Development of Educational Systems in the Semantic Web

Science.gov (United States)

Sánchez Vera, Ma. del Mar; Tomás Fernández Breis, Jesualdo; Serrano Sánchez, José Luis; Prendes Espinosa, Ma. Paz

2013-01-01

Semantic Web technologies have been applied in educational settings for different purposes in recent years, with the type of application being mainly defined by the way in which knowledge is represented and exploited. The basic technology for knowledge representation in Semantic Web settings is the ontology, which represents a common, shareable…

A Novel Fast and Robust Binary Affine Invariant Descriptor for Image Matching

Directory of Open Access Journals (Sweden)

Xiujie Qu

2014-01-01

Full Text Available As the current binary descriptors have disadvantages of high computational complexity, no affine invariance, and the high false matching rate with viewpoint changes, a new binary affine invariant descriptor, called BAND, is proposed. Different from other descriptors, BAND has an irregular pattern, which is based on local affine invariant region surrounding a feature point, and it has five orientations, which are obtained by LBP effectively. Ultimately, a 256 bits binary string is computed by simple random sampling pattern. Experimental results demonstrate that BAND has a good matching result in the conditions of rotating, image zooming, noising, lighting, and small-scale perspective transformation. It has better matching performance compared with current mainstream descriptors, while it costs less time.

How doctors apply semantic components to specify search in work-related information retrieval

DEFF Research Database (Denmark)

Lykke, Marianne; Price, Susan L.; Delcambre, Lois L. M.

2012-01-01

Workplace searching is often context-specific and targets a “right answer” within some domain-specific aspect of the search topic. We have developed the semantic component (SC) model that allows searchers to specify a search within context-specific aspects of the main topic of documents. The goal...

Inquisitive semantics and pragmatics

NARCIS (Netherlands)

Groenendijk, J.; Roelofsen, F.; Larrazabal, J.M.; Zubeldia, L.

2009-01-01

This paper starts with an informal introduction to inquisitive semantics. After that, we present a formal definition of the semantics, and introduce the basic semantic notions of inquisitiveness and informativeness, in terms of wich we define the semantic categories of questions, assertions, and

Dissociating the effects of semantic grouping and rehearsal strategies on event-related brain potentials.

Science.gov (United States)

Schleepen, T M J; Markus, C R; Jonkman, L M

2014-12-01

The application of elaborative encoding strategies during learning, such as grouping items on similar semantic categories, increases the likelihood of later recall. Previous studies have suggested that stimuli that encourage semantic grouping strategies had modulating effects on specific ERP components. However, these studies did not differentiate between ERP activation patterns evoked by elaborative working memory strategies like semantic grouping and more simple strategies like rote rehearsal. Identification of neurocognitive correlates underlying successful use of elaborative strategies is important to understand better why certain populations, like children or elderly people, have problems applying such strategies. To compare ERP activation during the application of elaborative versus more simple strategies subjects had to encode either four semantically related or unrelated pictures by respectively applying a semantic category grouping or a simple rehearsal strategy. Another goal was to investigate if maintenance of semantically grouped vs. ungrouped pictures modulated ERP-slow waves differently. At the behavioral level there was only a semantic grouping benefit in terms of faster responding on correct rejections (i.e. when the memory probe stimulus was not part of the memory set). At the neural level, during encoding semantic grouping only had a modest specific modulatory effect on a fronto-central Late Positive Component (LPC), emerging around 650 ms. Other ERP components (i.e. P200, N400 and a second Late Positive Component) that had been earlier related to semantic grouping encoding processes now showed stronger modulation by rehearsal than by semantic grouping. During maintenance semantic grouping had specific modulatory effects on left and right frontal slow wave activity. These results stress the importance of careful control of strategy use when investigating the neural correlates of elaborative encoding. Copyright © 2014 Elsevier B.V. All rights

Personal semantics: at the crossroads of semantic and episodic memory.

Science.gov (United States)

Renoult, Louis; Davidson, Patrick S R; Palombo, Daniela J; Moscovitch, Morris; Levine, Brian

2012-11-01

Declarative memory is usually described as consisting of two systems: semantic and episodic memory. Between these two poles, however, may lie a third entity: personal semantics (PS). PS concerns knowledge of one's past. Although typically assumed to be an aspect of semantic memory, it is essentially absent from existing models of knowledge. Furthermore, like episodic memory (EM), PS is idiosyncratically personal (i.e., not culturally-shared). We show that, depending on how it is operationalized, the neural correlates of PS can look more similar to semantic memory, more similar to EM, or dissimilar to both. We consider three different perspectives to better integrate PS into existing models of declarative memory and suggest experimental strategies for disentangling PS from semantic and episodic memory. Copyright © 2012 Elsevier Ltd. All rights reserved.

A novel 3D shape descriptor for automatic retrieval of anatomical structures from medical images

Science.gov (United States)

Nunes, Fátima L. S.; Bergamasco, Leila C. C.; Delmondes, Pedro H.; Valverde, Miguel A. G.; Jackowski, Marcel P.

2017-03-01

Content-based image retrieval (CBIR) aims at retrieving from a database objects that are similar to an object provided by a query, by taking into consideration a set of extracted features. While CBIR has been widely applied in the two-dimensional image domain, the retrieval of3D objects from medical image datasets using CBIR remains to be explored. In this context, the development of descriptors that can capture information specific to organs or structures is desirable. In this work, we focus on the retrieval of two anatomical structures commonly imaged by Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) techniques, the left ventricle of the heart and blood vessels. Towards this aim, we developed the Area-Distance Local Descriptor (ADLD), a novel 3D local shape descriptor that employs mesh geometry information, namely facet area and distance from centroid to surface, to identify shape changes. Because ADLD only considers surface meshes extracted from volumetric medical images, it substantially diminishes the amount of data to be analyzed. A 90% precision rate was obtained when retrieving both convex (left ventricle) and non-convex structures (blood vessels), allowing for detection of abnormalities associated with changes in shape. Thus, ADLD has the potential to aid in the diagnosis of a wide range of vascular and cardiac diseases.

Breast density pattern characterization by histogram features and texture descriptors

Directory of Open Access Journals (Sweden)

Pedro Cunha Carneiro

2017-04-01

Full Text Available Abstract Introduction Breast cancer is the first leading cause of death for women in Brazil as well as in most countries in the world. Due to the relation between the breast density and the risk of breast cancer, in medical practice, the breast density classification is merely visual and dependent on professional experience, making this task very subjective. The purpose of this paper is to investigate image features based on histograms and Haralick texture descriptors so as to separate mammographic images into categories of breast density using an Artificial Neural Network. Methods We used 307 mammographic images from the INbreast digital database, extracting histogram features and texture descriptors of all mammograms and selecting them with the K-means technique. Then, these groups of selected features were used as inputs of an Artificial Neural Network to classify the images automatically into the four categories reported by radiologists. Results An average accuracy of 92.9% was obtained in a few tests using only some of the Haralick texture descriptors. Also, the accuracy rate increased to 98.95% when texture descriptors were mixed with some features based on a histogram. Conclusion Texture descriptors have proven to be better than gray levels features at differentiating the breast densities in mammographic images. From this paper, it was possible to automate the feature selection and the classification with acceptable error rates since the extraction of the features is suitable to the characteristics of the images involving the problem.

A Weakest Pre-Expectation Semantics for Mixed-Sign Expectations

OpenAIRE

Kaminski, Benjamin Lucien; Katoen, Joost-Pieter

2017-01-01

We present a weakest-precondition-style calculus for reasoning about the expected values (pre-expectations) of \\emph{mixed-sign unbounded} random variables after execution of a probabilistic program. The semantics of a while-loop is well-defined as the limit of iteratively applying a functional to a zero-element just as in the traditional weakest pre-expectation calculus, even though a standard least fixed point argument is not applicable in this context. A striking feature of our semantics i...

SSWAP: A Simple Semantic Web Architecture and Protocol for semantic web services.

Science.gov (United States)

Gessler, Damian D G; Schiltz, Gary S; May, Greg D; Avraham, Shulamit; Town, Christopher D; Grant, David; Nelson, Rex T

2009-09-23

SSWAP (Simple Semantic Web Architecture and Protocol; pronounced "swap") is an architecture, protocol, and platform for using reasoning to semantically integrate heterogeneous disparate data and services on the web. SSWAP was developed as a hybrid semantic web services technology to overcome limitations found in both pure web service technologies and pure semantic web technologies. There are currently over 2400 resources published in SSWAP. Approximately two dozen are custom-written services for QTL (Quantitative Trait Loci) and mapping data for legumes and grasses (grains). The remaining are wrappers to Nucleic Acids Research Database and Web Server entries. As an architecture, SSWAP establishes how clients (users of data, services, and ontologies), providers (suppliers of data, services, and ontologies), and discovery servers (semantic search engines) interact to allow for the description, querying, discovery, invocation, and response of semantic web services. As a protocol, SSWAP provides the vocabulary and semantics to allow clients, providers, and discovery servers to engage in semantic web services. The protocol is based on the W3C-sanctioned first-order description logic language OWL DL. As an open source platform, a discovery server running at http://sswap.info (as in to "swap info") uses the description logic reasoner Pellet to integrate semantic resources. The platform hosts an interactive guide to the protocol at http://sswap.info/protocol.jsp, developer tools at http://sswap.info/developer.jsp, and a portal to third-party ontologies at http://sswapmeet.sswap.info (a "swap meet"). SSWAP addresses the three basic requirements of a semantic web services architecture (i.e., a common syntax, shared semantic, and semantic discovery) while addressing three technology limitations common in distributed service systems: i.e., i) the fatal mutability of traditional interfaces, ii) the rigidity and fragility of static subsumption hierarchies, and iii) the

Discriminating Power of FISWG Characteristic Descriptors Under Different Forensic Use Cases

NARCIS (Netherlands)

Zeinstra, Christopher Gerard; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan

2016-01-01

FISWG characteristic descriptors are facial features that can be used for evidence evaluation during forensic case work. In this paper we investigate the discriminating power of a biometric system that uses these characteristic descriptors as features under different forensic use cases. We show that

SemanticOrganizer: A Customizable Semantic Repository for Distributed NASA Project Teams

Science.gov (United States)

Keller, Richard M.; Berrios, Daniel C.; Carvalho, Robert E.; Hall, David R.; Rich, Stephen J.; Sturken, Ian B.; Swanson, Keith J.; Wolfe, Shawn R.

2004-01-01

SemanticOrganizer is a collaborative knowledge management system designed to support distributed NASA projects, including diverse teams of scientists, engineers, and accident investigators. The system provides a customizable, semantically structured information repository that stores work products relevant to multiple projects of differing types. SemanticOrganizer is one of the earliest and largest semantic web applications deployed at NASA to date, and has been used in diverse contexts ranging from the investigation of Space Shuttle Columbia's accident to the search for life on other planets. Although the underlying repository employs a single unified ontology, access control and ontology customization mechanisms make the repository contents appear different for each project team. This paper describes SemanticOrganizer, its customization facilities, and a sampling of its applications. The paper also summarizes some key lessons learned from building and fielding a successful semantic web application across a wide-ranging set of domains with diverse users.

Learning semantic and visual similarity for endomicroscopy video retrieval.

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Andre, Barbara; Vercauteren, Tom; Buchner, Anna M; Wallace, Michael B; Ayache, Nicholas

2012-06-01

Content-based image retrieval (CBIR) is a valuable computer vision technique which is increasingly being applied in the medical community for diagnosis support. However, traditional CBIR systems only deliver visual outputs, i.e., images having a similar appearance to the query, which is not directly interpretable by the physicians. Our objective is to provide a system for endomicroscopy video retrieval which delivers both visual and semantic outputs that are consistent with each other. In a previous study, we developed an adapted bag-of-visual-words method for endomicroscopy retrieval, called "Dense-Sift," that computes a visual signature for each video. In this paper, we present a novel approach to complement visual similarity learning with semantic knowledge extraction, in the field of in vivo endomicroscopy. We first leverage a semantic ground truth based on eight binary concepts, in order to transform these visual signatures into semantic signatures that reflect how much the presence of each semantic concept is expressed by the visual words describing the videos. Using cross-validation, we demonstrate that, in terms of semantic detection, our intuitive Fisher-based method transforming visual-word histograms into semantic estimations outperforms support vector machine (SVM) methods with statistical significance. In a second step, we propose to improve retrieval relevance by learning an adjusted similarity distance from a perceived similarity ground truth. As a result, our distance learning method allows to statistically improve the correlation with the perceived similarity. We also demonstrate that, in terms of perceived similarity, the recall performance of the semantic signatures is close to that of visual signatures and significantly better than those of several state-of-the-art CBIR methods. The semantic signatures are thus able to communicate high-level medical knowledge while being consistent with the low-level visual signatures and much shorter than them

Descriptors for ions and ion-pairs for use in linear free energy relationships.

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Abraham, Michael H; Acree, William E

2016-01-22

The determination of Abraham descriptors for single ions is reviewed, and equations are given for the partition of single ions from water to a number of solvents. These ions include permanent anions and cations and ionic species such as carboxylic acid anions, phenoxide anions and protonated base cations. Descriptors for a large number of ions and ionic species are listed, and equations for the prediction of Abraham descriptors for ionic species are given. The application of descriptors for ions and ionic species to physicochemical processes is given; these are to water-solvent partitions, HPLC retention data, immobilised artificial membranes, the Finkelstein reaction and diffusion in water. Applications to biological processes include brain permeation, microsomal degradation of drugs, skin permeation and human intestinal absorption. The review concludes with a section on the determination of descriptors for ion-pairs. Copyright © 2015 Elsevier B.V. All rights reserved.

Varieties of semantic ‘access’ deficit in Wernicke’s aphasia and semantic aphasia

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Robson, Holly; Lambon Ralph, Matthew A.; Jefferies, Elizabeth

2015-01-01

Comprehension deficits are common in stroke aphasia, including in cases with (i) semantic aphasia, characterized by poor executive control of semantic processing across verbal and non-verbal modalities; and (ii) Wernicke’s aphasia, associated with poor auditory–verbal comprehension and repetition, plus fluent speech with jargon. However, the varieties of these comprehension problems, and their underlying causes, are not well understood. Both patient groups exhibit some type of semantic ‘access’ deficit, as opposed to the ‘storage’ deficits observed in semantic dementia. Nevertheless, existing descriptions suggest that these patients might have different varieties of ‘access’ impairment—related to difficulty resolving competition (in semantic aphasia) versus initial activation of concepts from sensory inputs (in Wernicke’s aphasia). We used a case series design to compare patients with Wernicke’s aphasia and those with semantic aphasia on Warrington’s paradigmatic assessment of semantic ‘access’ deficits. In these verbal and non-verbal matching tasks, a small set of semantically-related items are repeatedly presented over several cycles so that the target on one trial becomes a distractor on another (building up interference and eliciting semantic ‘blocking’ effects). Patients with Wernicke’s aphasia and semantic aphasia were distinguished according to lesion location in the temporal cortex, but in each group, some individuals had additional prefrontal damage. Both of these aspects of lesion variability—one that mapped onto classical ‘syndromes’ and one that did not—predicted aspects of the semantic ‘access’ deficit. Both semantic aphasia and Wernicke’s aphasia cases showed multimodal semantic impairment, although as expected, the Wernicke’s aphasia group showed greater deficits on auditory-verbal than picture judgements. Distribution of damage in the temporal lobe was crucial for predicting the initially �

Genetic divergence among Brazilian turmeric germplasm using morpho-agronomical descriptors

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Mário Sérgio Sigrist

2011-01-01

Full Text Available Turmeric (Curcuma longa L. is a vegetatively-propagated crop which is used as a natural dye in the food industryand also presents many biological active compounds. Turmeric conventional breeding is difficult and often limited to germplasmselection. The aim of this study was to evaluate the genetic divergence among turmeric accessions available in Brazil using sevenmorpho-agronomical descriptors. Overall genetic divergence was low, although some divergent genotypes were identified. Fourmain groups of genotypes were identified and could be further used in breeding programs. Canonical variable analysis suggestedthat some descriptors were more important to discriminate accessions and also that one of the descriptors could be discarded. Theresults provided useful insights for better management of the germplasm collection, optimizing conservational and breeding efforts.

Innovative design method of automobile profile based on Fourier descriptor

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Gao, Shuyong; Fu, Chaoxing; Xia, Fan; Shen, Wei

2017-10-01

Aiming at the innovation of the contours of automobile side, this paper presents an innovative design method of vehicle side profile based on Fourier descriptor. The design flow of this design method is: pre-processing, coordinate extraction, standardization, discrete Fourier transform, simplified Fourier descriptor, exchange descriptor innovation, inverse Fourier transform to get the outline of innovative design. Innovative concepts of the innovative methods of gene exchange among species and the innovative methods of gene exchange among different species are presented, and the contours of the innovative design are obtained separately. A three-dimensional model of a car is obtained by referring to the profile curve which is obtained by exchanging xenogeneic genes. The feasibility of the method proposed in this paper is verified by various aspects.

Investigating Correlation between Protein Sequence Similarity and Semantic Similarity Using Gene Ontology Annotations.

Science.gov (United States)

Ikram, Najmul; Qadir, Muhammad Abdul; Afzal, Muhammad Tanvir

2018-01-01

Sequence similarity is a commonly used measure to compare proteins. With the increasing use of ontologies, semantic (function) similarity is getting importance. The correlation between these measures has been applied in the evaluation of new semantic similarity methods, and in protein function prediction. In this research, we investigate the relationship between the two similarity methods. The results suggest absence of a strong correlation between sequence and semantic similarities. There is a large number of proteins with low sequence similarity and high semantic similarity. We observe that Pearson's correlation coefficient is not sufficient to explain the nature of this relationship. Interestingly, the term semantic similarity values above 0 and below 1 do not seem to play a role in improving the correlation. That is, the correlation coefficient depends only on the number of common GO terms in proteins under comparison, and the semantic similarity measurement method does not influence it. Semantic similarity and sequence similarity have a distinct behavior. These findings are of significant effect for future works on protein comparison, and will help understand the semantic similarity between proteins in a better way.

Semantic Indexing of Medical Learning Objects: Medical Students' Usage of a Semantic Network.

Science.gov (United States)

Tix, Nadine; Gießler, Paul; Ohnesorge-Radtke, Ursula; Spreckelsen, Cord

2015-11-11

The Semantically Annotated Media (SAM) project aims to provide a flexible platform for searching, browsing, and indexing medical learning objects (MLOs) based on a semantic network derived from established classification systems. Primarily, SAM supports the Aachen emedia skills lab, but SAM is ready for indexing distributed content and the Simple Knowledge Organizing System standard provides a means for easily upgrading or even exchanging SAM's semantic network. There is a lack of research addressing the usability of MLO indexes or search portals like SAM and the user behavior with such platforms. The purpose of this study was to assess the usability of SAM by investigating characteristic user behavior of medical students accessing MLOs via SAM. In this study, we chose a mixed-methods approach. Lean usability testing was combined with usability inspection by having the participants complete four typical usage scenarios before filling out a questionnaire. The questionnaire was based on the IsoMetrics usability inventory. Direct user interaction with SAM (mouse clicks and pages accessed) was logged. The study analyzed the typical usage patterns and habits of students using a semantic network for accessing MLOs. Four scenarios capturing characteristics of typical tasks to be solved by using SAM yielded high ratings of usability items and showed good results concerning the consistency of indexing by different users. Long-tail phenomena emerge as they are typical for a collaborative Web 2.0 platform. Suitable but nonetheless rarely used keywords were assigned to MLOs by some users. It is possible to develop a Web-based tool with high usability and acceptance for indexing and retrieval of MLOs. SAM can be applied to indexing multicentered repositories of MLOs collaboratively.

A Survey on Challenges of Semantics Application in the Internet of Things Domain

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Harlamova Marina

2017-05-01

Full Text Available The Internet of Things (IoT, a global Internet-based system of computing devices and machines, is one of the most significant trends in the information technology area. An accepted unified communication approach would be a prerequisite for its mass adoption. Semantic technologies (Semantic Web have been advocated as enablers of unified communication. However, while there are particular advancements in research on application of Semantic Web in the IoT domain, the dynamic and complex nature of the IoT often requires case specific solutions hard to be applied widely. In the present survey, the semantic technology challenges in the IoT domain are amalgamated to provide background for further studies in the use of semantic technologies in the IoT.

Getting connected: Both associative and semantic links structure semantic memory for newly learned persons.

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Wiese, Holger; Schweinberger, Stefan R

2015-01-01

The present study examined whether semantic memory for newly learned people is structured by visual co-occurrence, shared semantics, or both. Participants were trained with pairs of simultaneously presented (i.e., co-occurring) preexperimentally unfamiliar faces, which either did or did not share additionally provided semantic information (occupation, place of living, etc.). Semantic information could also be shared between faces that did not co-occur. A subsequent priming experiment revealed faster responses for both co-occurrence/no shared semantics and no co-occurrence/shared semantics conditions, than for an unrelated condition. Strikingly, priming was strongest in the co-occurrence/shared semantics condition, suggesting additive effects of these factors. Additional analysis of event-related brain potentials yielded priming in the N400 component only for combined effects of visual co-occurrence and shared semantics, with more positive amplitudes in this than in the unrelated condition. Overall, these findings suggest that both semantic relatedness and visual co-occurrence are important when novel information is integrated into person-related semantic memory.

A Novel 2.5D Feature Descriptor Compensating for Depth Rotation

DEFF Research Database (Denmark)

Hagelskjær, Frederik; Buch, Anders Glent; Krüger, Norbert

2017-01-01

We introduce a novel type of local image descriptor based on Gabor filter responses. Our method operates on RGB-D images. We use the depth information to compensate for perspective distortions caused by out-of-plane rotations. The descriptor contains the responses of a multi-resolution Gabor bank...

Semantically Interoperable XML Data.

Science.gov (United States)

Vergara-Niedermayr, Cristobal; Wang, Fusheng; Pan, Tony; Kurc, Tahsin; Saltz, Joel

2013-09-01

XML is ubiquitously used as an information exchange platform for web-based applications in healthcare, life sciences, and many other domains. Proliferating XML data are now managed through latest native XML database technologies. XML data sources conforming to common XML schemas could be shared and integrated with syntactic interoperability. Semantic interoperability can be achieved through semantic annotations of data models using common data elements linked to concepts from ontologies. In this paper, we present a framework and software system to support the development of semantic interoperable XML based data sources that can be shared through a Grid infrastructure. We also present our work on supporting semantic validated XML data through semantic annotations for XML Schema, semantic validation and semantic authoring of XML data. We demonstrate the use of the system for a biomedical database of medical image annotations and markups.

Semantically Interoperable XML Data

Science.gov (United States)

Vergara-Niedermayr, Cristobal; Wang, Fusheng; Pan, Tony; Kurc, Tahsin; Saltz, Joel

2013-01-01

XML is ubiquitously used as an information exchange platform for web-based applications in healthcare, life sciences, and many other domains. Proliferating XML data are now managed through latest native XML database technologies. XML data sources conforming to common XML schemas could be shared and integrated with syntactic interoperability. Semantic interoperability can be achieved through semantic annotations of data models using common data elements linked to concepts from ontologies. In this paper, we present a framework and software system to support the development of semantic interoperable XML based data sources that can be shared through a Grid infrastructure. We also present our work on supporting semantic validated XML data through semantic annotations for XML Schema, semantic validation and semantic authoring of XML data. We demonstrate the use of the system for a biomedical database of medical image annotations and markups. PMID:25298789

From acoustic descriptors to evoked quality of car door sounds.

Science.gov (United States)

Bezat, Marie-Céline; Kronland-Martinet, Richard; Roussarie, Vincent; Ystad, Sølvi

2014-07-01

This article describes the first part of a study aiming at adapting the mechanical car door construction to the drivers' expectancies in terms of perceived quality of cars deduced from car door sounds. A perceptual cartography of car door sounds is obtained from various listening tests aiming at revealing both ecological and analytical properties linked to evoked car quality. In the first test naive listeners performed absolute evaluations of five ecological properties (i.e., solidity, quality, weight, closure energy, and success of closure). Then experts in the area of automobile doors categorized the sounds according to organic constituents (lock, joints, door panel), in particular whether or not the lock mechanism could be perceived. Further, a sensory panel of naive listeners identified sensory descriptors such as classical descriptors or onomatopoeia that characterize the sounds, hereby providing an analytic description of the sounds. Finally, acoustic descriptors were calculated after decomposition of the signal into a lock and a closure component by the Empirical Mode Decomposition (EMD) method. A statistical relationship between the acoustic descriptors and the perceptual evaluations of the car door sounds could then be obtained through linear regression analysis.

Semantic Role Labeling

CERN Document Server

Palmer, Martha; Xue, Nianwen

2011-01-01

This book is aimed at providing an overview of several aspects of semantic role labeling. Chapter 1 begins with linguistic background on the definition of semantic roles and the controversies surrounding them. Chapter 2 describes how the theories have led to structured lexicons such as FrameNet, VerbNet and the PropBank Frame Files that in turn provide the basis for large scale semantic annotation of corpora. This data has facilitated the development of automatic semantic role labeling systems based on supervised machine learning techniques. Chapter 3 presents the general principles of applyin

Semantic similarity between ontologies at different scales

Energy Technology Data Exchange (ETDEWEB)

Zhang, Qingpeng; Haglin, David J.

2016-04-01

In the past decade, existing and new knowledge and datasets has been encoded in different ontologies for semantic web and biomedical research. The size of ontologies is often very large in terms of number of concepts and relationships, which makes the analysis of ontologies and the represented knowledge graph computational and time consuming. As the ontologies of various semantic web and biomedical applications usually show explicit hierarchical structures, it is interesting to explore the trade-offs between ontological scales and preservation/precision of results when we analyze ontologies. This paper presents the first effort of examining the capability of this idea via studying the relationship between scaling biomedical ontologies at different levels and the semantic similarity values. We evaluate the semantic similarity between three Gene Ontology slims (Plant, Yeast, and Candida, among which the latter two belong to the same kingdom—Fungi) using four popular measures commonly applied to biomedical ontologies (Resnik, Lin, Jiang-Conrath, and SimRel). The results of this study demonstrate that with proper selection of scaling levels and similarity measures, we can significantly reduce the size of ontologies without losing substantial detail. In particular, the performance of Jiang-Conrath and Lin are more reliable and stable than that of the other two in this experiment, as proven by (a) consistently showing that Yeast and Candida are more similar (as compared to Plant) at different scales, and (b) small deviations of the similarity values after excluding a majority of nodes from several lower scales. This study provides a deeper understanding of the application of semantic similarity to biomedical ontologies, and shed light on how to choose appropriate semantic similarity measures for biomedical engineering.

Bridging the semantic gap in sports

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Li, Baoxin; Errico, James; Pan, Hao; Sezan, M. Ibrahim

2003-01-01

One of the major challenges facing current media management systems and the related applications is the so-called "semantic gap" between the rich meaning that a user desires and the shallowness of the content descriptions that are automatically extracted from the media. In this paper, we address the problem of bridging this gap in the sports domain. We propose a general framework for indexing and summarizing sports broadcast programs. The framework is based on a high-level model of sports broadcast video using the concept of an event, defined according to domain-specific knowledge for different types of sports. Within this general framework, we develop automatic event detection algorithms that are based on automatic analysis of the visual and aural signals in the media. We have successfully applied the event detection algorithms to different types of sports including American football, baseball, Japanese sumo wrestling, and soccer. Event modeling and detection contribute to the reduction of the semantic gap by providing rudimentary semantic information obtained through media analysis. We further propose a novel approach, which makes use of independently generated rich textual metadata, to fill the gap completely through synchronization of the information-laden textual data with the basic event segments. An MPEG-7 compliant prototype browsing system has been implemented to demonstrate semantic retrieval and summarization of sports video.

UML 2 Semantics and Applications

CERN Document Server

Lano, Kevin

2009-01-01

A coherent and integrated account of the leading UML 2 semantics work and the practical applications of UML semantics development With contributions from leading experts in the field, the book begins with an introduction to UML and goes on to offer in-depth and up-to-date coverage of: The role of semantics Considerations and rationale for a UML system model Definition of the UML system model UML descriptive semantics Axiomatic semantics of UML class diagrams The object constraint language Axiomatic semantics of state machines A coalgebraic semantic framework for reasoning about interaction des

Probabilistic Latent Semantic Analyses (PLSA in Bibliometric Analysis for Technology Forecasting

Directory of Open Access Journals (Sweden)

Wang Zan

2007-03-01

Full Text Available Due to the availability of internet-based abstract services and patent databases, bibliometric analysis has become one of key technology forecasting approaches. Recently, latent semantic analysis (LSA has been applied to improve the accuracy in document clustering. In this paper, a new LSA method, probabilistic latent semantic analysis (PLSA which uses probabilistic methods and algebra to search latent space in the corpus is further applied in document clustering. The results show that PLSA is more accurate than LSA and the improved iteration method proposed by authors can simplify the computing process and improve the computing efficiency

The semantic representation of prejudice and stereotypes.

Science.gov (United States)

Bhatia, Sudeep

2017-07-01

We use a theory of semantic representation to study prejudice and stereotyping. Particularly, we consider large datasets of newspaper articles published in the United States, and apply latent semantic analysis (LSA), a prominent model of human semantic memory, to these datasets to learn representations for common male and female, White, African American, and Latino names. LSA performs a singular value decomposition on word distribution statistics in order to recover word vector representations, and we find that our recovered representations display the types of biases observed in human participants using tasks such as the implicit association test. Importantly, these biases are strongest for vector representations with moderate dimensionality, and weaken or disappear for representations with very high or very low dimensionality. Moderate dimensional LSA models are also the best at learning race, ethnicity, and gender-based categories, suggesting that social category knowledge, acquired through dimensionality reduction on word distribution statistics, can facilitate prejudiced and stereotyped associations. Copyright © 2017 Elsevier B.V. All rights reserved.

Semantic memory in object use.

Science.gov (United States)

Silveri, Maria Caterina; Ciccarelli, Nicoletta

2009-10-01

We studied five patients with semantic memory disorders, four with semantic dementia and one with herpes simplex virus encephalitis, to investigate the involvement of semantic conceptual knowledge in object use. Comparisons between patients who had semantic deficits of different severity, as well as the follow-up, showed that the ability to use objects was largely preserved when the deficit was mild but progressively decayed as the deficit became more severe. Naming was generally more impaired than object use. Production tasks (pantomime execution and actual object use) and comprehension tasks (pantomime recognition and action recognition) as well as functional knowledge about objects were impaired when the semantic deficit was severe. Semantic and unrelated errors were produced during object use, but actions were always fluent and patients performed normally on a novel tools task in which the semantic demand was minimal. Patients with severe semantic deficits scored borderline on ideational apraxia tasks. Our data indicate that functional semantic knowledge is crucial for using objects in a conventional way and suggest that non-semantic factors, mainly non-declarative components of memory, might compensate to some extent for semantic disorders and guarantee some residual ability to use very common objects independently of semantic knowledge.

Accumulation of different visual feature descriptors in a coherent framework

DEFF Research Database (Denmark)

Jessen, J.B.; Pilz, F.; Kraft, Dirk

2011-01-01

We present a temporal accumulation scheme which disambiguates different kinds of visual 3D descriptors within one coherent framework. The accumulation consists of a twofold process: First, by means of a Bayesian filtering outliers become eliminated and second, the precision of the extracted infor...... information becomes enhanced by means of an unscented Kalman filtering process. It is a particular property of our algorithm to be able to deal with different kinds of visual descriptors by the very same mechanism. We show quantitative and qualitative results.......We present a temporal accumulation scheme which disambiguates different kinds of visual 3D descriptors within one coherent framework. The accumulation consists of a twofold process: First, by means of a Bayesian filtering outliers become eliminated and second, the precision of the extracted...

Exploring and linking biomedical resources through multidimensional semantic spaces.

Science.gov (United States)

Berlanga, Rafael; Jiménez-Ruiz, Ernesto; Nebot, Victoria

2012-01-25

The semantic integration of biomedical resources is still a challenging issue which is required for effective information processing and data analysis. The availability of comprehensive knowledge resources such as biomedical ontologies and integrated thesauri greatly facilitates this integration effort by means of semantic annotation, which allows disparate data formats and contents to be expressed under a common semantic space. In this paper, we propose a multidimensional representation for such a semantic space, where dimensions regard the different perspectives in biomedical research (e.g., population, disease, anatomy and protein/genes). This paper presents a novel method for building multidimensional semantic spaces from semantically annotated biomedical data collections. This method consists of two main processes: knowledge and data normalization. The former one arranges the concepts provided by a reference knowledge resource (e.g., biomedical ontologies and thesauri) into a set of hierarchical dimensions for analysis purposes. The latter one reduces the annotation set associated to each collection item into a set of points of the multidimensional space. Additionally, we have developed a visual tool, called 3D-Browser, which implements OLAP-like operators over the generated multidimensional space. The method and the tool have been tested and evaluated in the context of the Health-e-Child (HeC) project. Automatic semantic annotation was applied to tag three collections of abstracts taken from PubMed, one for each target disease of the project, the Uniprot database, and the HeC patient record database. We adopted the UMLS Meta-thesaurus 2010AA as the reference knowledge resource. Current knowledge resources and semantic-aware technology make possible the integration of biomedical resources. Such an integration is performed through semantic annotation of the intended biomedical data resources. This paper shows how these annotations can be exploited for

The structure of semantic person memory: evidence from semantic priming in person recognition.

Science.gov (United States)

Wiese, Holger

2011-11-01

This paper reviews research on the structure of semantic person memory as examined with semantic priming. In this experimental paradigm, a familiarity decision on a target face or written name is usually faster when it is preceded by a related as compared to an unrelated prime. This effect has been shown to be relatively short lived and susceptible to interfering items. Moreover, semantic priming can cross stimulus domains, such that a written name can prime a target face and vice versa. However, it remains controversial whether representations of people are stored in associative networks based on co-occurrence, or in more abstract semantic categories. In line with prominent cognitive models of face recognition, which explain semantic priming by shared semantic information between prime and target, recent research demonstrated that priming could be obtained from purely categorically related, non-associated prime/target pairs. Although strategic processes, such as expectancy and retrospective matching likely contribute, there is also evidence for a non-strategic contribution to priming, presumably related to spreading activation. Finally, a semantic priming effect has been demonstrated in the N400 event-related potential (ERP) component, which may reflect facilitated access to semantic information. It is concluded that categorical relatedness is one organizing principle of semantic person memory. ©2011 The British Psychological Society.

Meinongian Semantics and Artificial Intelligence

Directory of Open Access Journals (Sweden)

William J. Rapaport

2013-12-01

Full Text Available This essay describes computational semantic networks for a philosophical audience and surveys several approaches to semantic-network semantics. In particular, propositional semantic networks (exemplified by SNePS are discussed; it is argued that only a fully intensional, Meinongian semantics is appropriate for them; and several Meinongian systems are presented.

Bag of frequencies: a descriptor of pulmonary nodules in Computed Tomography images

NARCIS (Netherlands)

Ciompi, F.; Jacobs, C.; Scholten, E.T.; Wille, M.M.W.; Jong, P.A. de; Prokop, M.; Ginneken, B. van

2015-01-01

We present a novel descriptor for the characterization of pulmonary nodules in computed tomography (CT) images. The descriptor encodes information on nodule morphology and has scale-invariant and rotation-invariant properties. Information on nodule morphology is captured by sampling intensity

Geospatial Semantics and the Semantic Web

CERN Document Server

Ashish, Naveen

2011-01-01

The availability of geographic and geospatial information and services, especially on the open Web has become abundant in the last several years with the proliferation of online maps, geo-coding services, geospatial Web services and geospatially enabled applications. The need for geospatial reasoning has significantly increased in many everyday applications including personal digital assistants, Web search applications, local aware mobile services, specialized systems for emergency response, medical triaging, intelligence analysis and more. Geospatial Semantics and the Semantic Web: Foundation

SU-D-207B-02: Early Grade Classification in Meningioma Patients Combining Radiomics and Semantics Data

International Nuclear Information System (INIS)

Coroller, T; Bi, W; Abedalthagafi, M; Aizer, A; Wu, W; Greenwald, N; Beroukhim, R; Al-Mefty, O; Santagata, S; Dunn, I; Alexander, B; Huang, R; Aerts, H

2016-01-01

Purpose: The clinical management of meningioma is guided by its grade and biologic behavior. Currently, diagnosis of tumor grade follows surgical resection and histopathologic review. Reliable techniques for pre-operative determination of tumor behavior are needed. We investigated the association between imaging features extracted from preoperative gadolinium-enhanced T1-weighted MRI and meningioma grade. Methods: We retrospectively examined the pre-operative MRI for 139 patients with de novo WHO grade I (63%) and grade II (37%) meningiomas. We investigated the predictive power of ten semantic radiologic features as determined by a neuroradiologist, fifteen radiomic features, and tumor location. Conventional (volume and diameter) imaging features were added for comparison. AUC was computed for continuous and χ 2 for discrete variables. Classification was done using random forest. Performance was evaluated using cross validation (1000 iterations, 75% training and 25% validation). All p-values were adjusted for multiple testing. Results: Significant association was observed between meningioma grade and tumor location (p<0.001) and two semantic features including intra-tumoral heterogeneity (p<0.001) and overt hemorrhage (p=0.01). Conventional (AUC 0.61–0.67) and eleven radiomic (AUC 0.60–0.70) features were significant from random (p<0.05, Noether test). Median AUC values for classification of tumor grade were 0.57, 0.71, 0.72 and 0.77 respectively for conventional, radiomic, location, and semantic features after using random forest. By combining all imaging data (semantic, radiomic, and location), the median AUC was 0.81, which offers superior predicting power to that of conventional imaging descriptors for meningioma as well as radiomic features alone (p<0.05, permutation test). Conclusion: We demonstrate a strong association between radiologic features and meningioma grade. Pre-operative prediction of tumor behavior based on imaging features offers promise

SU-D-207B-02: Early Grade Classification in Meningioma Patients Combining Radiomics and Semantics Data

Energy Technology Data Exchange (ETDEWEB)

Coroller, T; Bi, W; Abedalthagafi, M; Aizer, A; Wu, W; Greenwald, N; Beroukhim, R; Al-Mefty, O; Santagata, S; Dunn, I; Alexander, B; Huang, R; Aerts, H [Dana Farber Cancer Institute, Brigham and Womens Hospital, Harvard Medical School (United States)

2016-06-15

Purpose: The clinical management of meningioma is guided by its grade and biologic behavior. Currently, diagnosis of tumor grade follows surgical resection and histopathologic review. Reliable techniques for pre-operative determination of tumor behavior are needed. We investigated the association between imaging features extracted from preoperative gadolinium-enhanced T1-weighted MRI and meningioma grade. Methods: We retrospectively examined the pre-operative MRI for 139 patients with de novo WHO grade I (63%) and grade II (37%) meningiomas. We investigated the predictive power of ten semantic radiologic features as determined by a neuroradiologist, fifteen radiomic features, and tumor location. Conventional (volume and diameter) imaging features were added for comparison. AUC was computed for continuous and χ{sup 2} for discrete variables. Classification was done using random forest. Performance was evaluated using cross validation (1000 iterations, 75% training and 25% validation). All p-values were adjusted for multiple testing. Results: Significant association was observed between meningioma grade and tumor location (p<0.001) and two semantic features including intra-tumoral heterogeneity (p<0.001) and overt hemorrhage (p=0.01). Conventional (AUC 0.61–0.67) and eleven radiomic (AUC 0.60–0.70) features were significant from random (p<0.05, Noether test). Median AUC values for classification of tumor grade were 0.57, 0.71, 0.72 and 0.77 respectively for conventional, radiomic, location, and semantic features after using random forest. By combining all imaging data (semantic, radiomic, and location), the median AUC was 0.81, which offers superior predicting power to that of conventional imaging descriptors for meningioma as well as radiomic features alone (p<0.05, permutation test). Conclusion: We demonstrate a strong association between radiologic features and meningioma grade. Pre-operative prediction of tumor behavior based on imaging features offers

Structural protein descriptors in 1-dimension and their sequence-based predictions.

Science.gov (United States)

Kurgan, Lukasz; Disfani, Fatemeh Miri

2011-09-01

The last few decades observed an increasing interest in development and application of 1-dimensional (1D) descriptors of protein structure. These descriptors project 3D structural features onto 1D strings of residue-wise structural assignments. They cover a wide-range of structural aspects including conformation of the backbone, burying depth/solvent exposure and flexibility of residues, and inter-chain residue-residue contacts. We perform first-of-its-kind comprehensive comparative review of the existing 1D structural descriptors. We define, review and categorize ten structural descriptors and we also describe, summarize and contrast over eighty computational models that are used to predict these descriptors from the protein sequences. We show that the majority of the recent sequence-based predictors utilize machine learning models, with the most popular being neural networks, support vector machines, hidden Markov models, and support vector and linear regressions. These methods provide high-throughput predictions and most of them are accessible to a non-expert user via web servers and/or stand-alone software packages. We empirically evaluate several recent sequence-based predictors of secondary structure, disorder, and solvent accessibility descriptors using a benchmark set based on CASP8 targets. Our analysis shows that the secondary structure can be predicted with over 80% accuracy and segment overlap (SOV), disorder with over 0.9 AUC, 0.6 Matthews Correlation Coefficient (MCC), and 75% SOV, and relative solvent accessibility with PCC of 0.7 and MCC of 0.6 (0.86 when homology is used). We demonstrate that the secondary structure predicted from sequence without the use of homology modeling is as good as the structure extracted from the 3D folds predicted by top-performing template-based methods.

Deconstructing field-induced ketene isomerization through Lagrangian descriptors.

Science.gov (United States)

Craven, Galen T; Hernandez, Rigoberto

2016-02-07

The time-dependent geometrical separatrices governing state transitions in field-induced ketene isomerization are constructed using the method of Lagrangian descriptors. We obtain the stable and unstable manifolds of time-varying transition states as dynamic phase space objects governing configurational changes when the ketene molecule is subjected to an oscillating electric field. The dynamics of the isomerization reaction are modeled through classical trajectory studies on the Gezelter-Miller potential energy surface and an approximate dipole moment model which is coupled to a time-dependent electric field. We obtain a representation of the reaction geometry, over varying field strengths and oscillation frequencies, by partitioning an initial phase space into basins labeled according to which product state is reached at a given time. The borders between these basins are in agreement with those obtained using Lagrangian descriptors, even in regimes exhibiting chaotic dynamics. Major outcomes of this work are: validation and extension of a transition state theory framework built from Lagrangian descriptors, elaboration of the applicability for this theory to periodically- and aperiodically-driven molecular systems, and prediction of regimes in which isomerization of ketene and its derivatives may be controlled using an external field.

Centrality as a Method for the Evaluation of Semantic Resources for Disaster Risk Reduction

Directory of Open Access Journals (Sweden)

Otakar Čerba

2017-08-01

Full Text Available Clear and straightforward communication is a key aspect of all human activities related to crisis management. Since crisis management activities involve professionals from various disciplines using different terminology, clear and straightforward communication is difficult to achieve. Semantics as a broad science can help to overcome communication difficulties. This research focuses on the evaluation of available semantic resources including ontologies, thesauri, and controlled vocabularies for disaster risk reduction as part of crisis management. The main idea of the study is that the most appropriate source of broadly understandable terminology is such a semantic resource, which is accepted by—or at least connected to the majority of other resources. Important is not only the number of interconnected resources, but also the concrete position of the resource in the complex network of Linked Data resources. Although this is usually done by user experience, objective methods of resource semantic centrality can be applied. This can be described by centrality methods used mainly in graph theory. This article describes the calculation of four types of centrality methods (Outdegree, Indegree, Closeness, and Betweenness applied to 160 geographic concepts published as Linked Data and related to disaster risk reduction. Centralities were calculated for graph structures containing particular semantic resources as nodes and identity links as edges. The results show that (with some discussed exceptions the datasets with high values of centrality serve as important information resources, but they also include more concepts from preselected 160 geographic concepts. Therefore, they could be considered as the most suitable resources of terminology to make communication in the domain easier. The main research goal is to automate the semantic resources evaluation and to apply a well-known theoretical method (centrality to the semantic issues of Linked Data. It

Semantic Contours in Tracks Based on Emotional Tags

DEFF Research Database (Denmark)

Petersen, Michael Kai; Hansen, Lars Kai; Butkus, Andrius

2009-01-01

Outlining a high level cognitive approach to how we select media based on affective user preferences, we model the latent semantics of lyrics as patterns of emotional components. Using a selection of affective last.fm tags as top-down emotional buoys, we apply LSA latent semantic analysis to bottom......-up represent the correlation of terms and song lyrics in a vector space that reflects the emotional context. Analyzing the resulting patterns of affective components, by comparing them against last.fm tag clouds describing the corresponding songs, we propose that it might be feasible to automatically generate...

CNTRO: A Semantic Web Ontology for Temporal Relation Inferencing in Clinical Narratives.

Science.gov (United States)

Tao, Cui; Wei, Wei-Qi; Solbrig, Harold R; Savova, Guergana; Chute, Christopher G

2010-11-13

Using Semantic-Web specifications to represent temporal information in clinical narratives is an important step for temporal reasoning and answering time-oriented queries. Existing temporal models are either not compatible with the powerful reasoning tools developed for the Semantic Web, or designed only for structured clinical data and therefore are not ready to be applied on natural-language-based clinical narrative reports directly. We have developed a Semantic-Web ontology which is called Clinical Narrative Temporal Relation ontology. Using this ontology, temporal information in clinical narratives can be represented as RDF (Resource Description Framework) triples. More temporal information and relations can then be inferred by Semantic-Web based reasoning tools. Experimental results show that this ontology can represent temporal information in real clinical narratives successfully.

Verbal and non-verbal semantic impairment: From fluent primary progressive aphasia to semantic dementia

Directory of Open Access Journals (Sweden)

Mirna Lie Hosogi Senaha

Full Text Available Abstract Selective disturbances of semantic memory have attracted the interest of many investigators and the question of the existence of single or multiple semantic systems remains a very controversial theme in the literature. Objectives: To discuss the question of multiple semantic systems based on a longitudinal study of a patient who presented semantic dementia from fluent primary progressive aphasia. Methods: A 66 year-old woman with selective impairment of semantic memory was examined on two occasions, undergoing neuropsychological and language evaluations, the results of which were compared to those of three paired control individuals. Results: In the first evaluation, physical examination was normal and the score on the Mini-Mental State Examination was 26. Language evaluation revealed fluent speech, anomia, disturbance in word comprehension, preservation of the syntactic and phonological aspects of the language, besides surface dyslexia and dysgraphia. Autobiographical and episodic memories were relatively preserved. In semantic memory tests, the following dissociation was found: disturbance of verbal semantic memory with preservation of non-verbal semantic memory. Magnetic resonance of the brain revealed marked atrophy of the left anterior temporal lobe. After 14 months, the difficulties in verbal semantic memory had become more severe and the semantic disturbance, limited initially to the linguistic sphere, had worsened to involve non-verbal domains. Conclusions: Given the dissociation found in the first examination, we believe there is sufficient clinical evidence to refute the existence of a unitary semantic system.

Design of an Optimal Preview Controller for Linear Discrete-Time Descriptor Noncausal Multirate Systems

Directory of Open Access Journals (Sweden)

Mengjuan Cao

2014-01-01

Full Text Available The linear discrete-time descriptor noncausal multirate system is considered for the presentation of a new design approach for optimal preview control. First, according to the characteristics of causal controllability and causal observability, the descriptor noncausal system is constructed into a descriptor causal closed-loop system. Second, by using the characteristics of the causal system and elementary transformation, the descriptor causal closed-loop system is transformed into a normal system. Then, taking advantage of the discrete lifting technique, the normal multirate system is converted to a single-rate system. By making use of the standard preview control method, we construct the descriptor augmented error system. The quadratic performance index for the multirate system is given, which can be changed into one for the single-rate system. In addition, a new single-rate system is obtained, the optimal control law of which is given. Returning to the original system, the optimal preview controller for linear discrete-time descriptor noncausal multirate systems is derived. The stabilizability and detectability of the lifted single-rate system are discussed in detail. The optimal preview control design techniques are illustrated by simulation results for a simple example.

Montague semantics

NARCIS (Netherlands)

Janssen, T.M.V.

2012-01-01

Montague semantics is a theory of natural language semantics and of its relation with syntax. It was originally developed by the logician Richard Montague (1930-1971) and subsequently modified and extended by linguists, philosophers, and logicians. The most important features of the theory are its

Region descriptors for automatic classification of small sea targets in infrared video

NARCIS (Netherlands)

Mouthaan, M.M.; Broek, S.P. van den; Hendriks, E.A.; Schwering, P.B.W.

2011-01-01

We evaluate the performance of different key-point detectors and region descriptors when used for automatic classification of small sea targets in infrared video. In our earlier research performed on this subject as well as in other literature, many different region descriptors have been proposed.

From Data to Semantic Information

Directory of Open Access Journals (Sweden)

Luciano Floridi

2003-06-01

Full Text Available Abstract: There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information (SDI as meaningful data, in favour of the Dretske-Grice approach: meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth-values do not supervene on semantic information, and misinformation (that is, false semantic information is not a type of semantic information, but pseudo-information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo-information. As a consequence, SDI is revised to include a necessary truth-condition. The last section summarises the main results of the paper and indicates the important implications of the revised definition for the analysis of the deflationary theories of truth, the standard definition of knowledge and the classic, quantitative theory of semantic information.

Foundations of semantic web technologies

CERN Document Server

Hitzler, Pascal; Rudolph, Sebastian

2009-01-01

The Quest for Semantics Building Models Calculating with Knowledge Exchanging Information Semanic Web Technologies RESOURCE DESCRIPTION LANGUAGE (RDF)Simple Ontologies in RDF and RDF SchemaIntroduction to RDF Syntax for RDF Advanced Features Simple Ontologies in RDF Schema Encoding of Special Data Structures An ExampleRDF Formal Semantics Why Semantics? Model-Theoretic Semantics for RDF(S) Syntactic Reasoning with Deduction Rules The Semantic Limits of RDF(S)WEB ONTOLOGY LANGUAGE (OWL) Ontologies in OWL OWL Syntax and Intuitive Semantics OWL Species The Forthcoming OWL 2 StandardOWL Formal Sem

Recommendation of standardized health learning contents using archetypes and semantic web technologies.

Science.gov (United States)

Legaz-García, María del Carmen; Martínez-Costa, Catalina; Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás

2012-01-01

Linking Electronic Healthcare Records (EHR) content to educational materials has been considered a key international recommendation to enable clinical engagement and to promote patient safety. This would suggest citizens to access reliable information available on the web and to guide them properly. In this paper, we describe an approach in that direction, based on the use of dual model EHR standards and standardized educational contents. The recommendation method will be based on the semantic coverage of the learning content repository for a particular archetype, which will be calculated by applying semantic web technologies like ontologies and semantic annotations.

Temperature and relative humidity influence the ripening descriptors of Camembert-type cheeses throughout ripening.

Science.gov (United States)

Leclercq-Perlat, M-N; Sicard, M; Perrot, N; Trelea, I C; Picque, D; Corrieu, G

2015-02-01

Ripening descriptors are the main factors that determine consumers' preferences of soft cheeses. Six descriptors were defined to represent the sensory changes in Camembert cheeses: Penicillium camemberti appearance, cheese odor and rind color, creamy underrind thickness and consistency, and core hardness. To evaluate the effects of the main process parameters on these descriptors, Camembert cheeses were ripened under different temperatures (8, 12, and 16°C) and relative humidity (RH; 88, 92, and 98%). The sensory descriptors were highly dependent on the temperature and RH used throughout ripening in a ripening chamber. All sensory descriptor changes could be explained by microorganism growth, pH, carbon substrate metabolism, and cheese moisture, as well as by microbial enzymatic activities. On d 40, at 8°C and 88% RH, all sensory descriptors scored the worst: the cheese was too dry, its odor and its color were similar to those of the unripe cheese, the underrind was driest, and the core was hardest. At 16°C and 98% RH, the odor was strongly ammonia and the color was dark brown, and the creamy underrind represented the entire thickness of the cheese but was completely runny, descriptors indicative of an over ripened cheese. Statistical analysis showed that the best ripening conditions to achieve an optimum balance between cheese sensory qualities and marketability were 13±1°C and 94±1% RH. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Region-Based Image Retrieval Using an Object Ontology and Relevance Feedback

Directory of Open Access Journals (Sweden)

Kompatsiaris Ioannis

2004-01-01

Full Text Available An image retrieval methodology suited for search in large collections of heterogeneous images is presented. The proposed approach employs a fully unsupervised segmentation algorithm to divide images into regions and endow the indexing and retrieval system with content-based functionalities. Low-level descriptors for the color, position, size, and shape of each region are subsequently extracted. These arithmetic descriptors are automatically associated with appropriate qualitative intermediate-level descriptors, which form a simple vocabulary termed object ontology. The object ontology is used to allow the qualitative definition of the high-level concepts the user queries for (semantic objects, each represented by a keyword and their relations in a human-centered fashion. When querying for a specific semantic object (or objects, the intermediate-level descriptor values associated with both the semantic object and all image regions in the collection are initially compared, resulting in the rejection of most image regions as irrelevant. Following that, a relevance feedback mechanism, based on support vector machines and using the low-level descriptors, is invoked to rank the remaining potentially relevant image regions and produce the final query results. Experimental results and comparisons demonstrate, in practice, the effectiveness of our approach.

Dense Descriptors for Optical Flow Estimation: A Comparative Study

Directory of Open Access Journals (Sweden)

Ahmadreza Baghaie

2017-02-01

Full Text Available Estimating the displacements of intensity patterns between sequential frames is a very well-studied problem, which is usually referred to as optical flow estimation. The first assumption among many of the methods in the field is the brightness constancy during movements of pixels between frames. This assumption is proven to be not true in general, and therefore, the use of photometric invariant constraints has been studied in the past. One other solution can be sought by use of structural descriptors rather than pixels for estimating the optical flow. Unlike sparse feature detection/description techniques and since the problem of optical flow estimation tries to find a dense flow field, a dense structural representation of individual pixels and their neighbors is computed and then used for matching and optical flow estimation. Here, a comparative study is carried out by extending the framework of SIFT-flow to include more dense descriptors, and comprehensive comparisons are given. Overall, the work can be considered as a baseline for stimulating more interest in the use of dense descriptors for optical flow estimation.

An Advanced Rotation Invariant Descriptor for SAR Image Registration

Directory of Open Access Journals (Sweden)

Yuming Xiang

2017-07-01

Full Text Available The Scale-Invariant Feature Transform (SIFT algorithm and its many variants have been widely used in Synthetic Aperture Radar (SAR image registration. The SIFT-like algorithms maintain rotation invariance by assigning a dominant orientation for each keypoint, while the calculation of dominant orientation is not robust due to the effect of speckle noise in SAR imagery. In this paper, we propose an advanced local descriptor for SAR image registration to achieve rotation invariance without assigning a dominant orientation. Based on the improved intensity orders, we first divide a circular neighborhood into several sub-regions. Second, rotation-invariant ratio orientation histograms of each sub-region are proposed by accumulating the ratio values of different directions in a rotation-invariant coordinate system. The proposed descriptor is composed of the concatenation of the histograms of each sub-region. In order to increase the distinctiveness of the proposed descriptor, multiple image neighborhoods are aggregated. Experimental results on several satellite SAR images have shown an improvement in the matching performance over other state-of-the-art algorithms.

Basic semantics of product sounds

NARCIS (Netherlands)

Özcan Vieira, E.; Van Egmond, R.

2012-01-01

Product experience is a result of sensory and semantic experiences with product properties. In this paper, we focus on the semantic attributes of product sounds and explore the basic components for product sound related semantics using a semantic differential paradigmand factor analysis. With two

Retrieval from semantic memory.

NARCIS (Netherlands)

Noordman-Vonk, Wietske

1977-01-01

The present study has been concerned with the retrieval of semantic information. Retrieving semantic information is a fundamental process in almost any kind of cognitive behavior. The introduction presented the main experimental paradigms and results found in the literature on semantic memory as

Towards Universal Semantic Tagging

NARCIS (Netherlands)

Abzianidze, Lasha; Bos, Johan

2017-01-01

The paper proposes the task of universal semantic tagging---tagging word tokens with language-neutral, semantically informative tags. We argue that the task, with its independent nature, contributes to better semantic analysis for wide-coverage multilingual text. We present the initial version of

Semantic Search in E-Discovery: An Interdisciplinary Approach

NARCIS (Netherlands)

Graus, D.; Ren, Z.; de Rijke, M.; van Dijk, D.; Henseler, H.; van der Knaap, N.

2013-01-01

We propose an interdisciplinary approach to applying and evaluating semantic search in the e-discovery setting. By combining expertise from the fields of law and criminology with that of information retrieval and extraction, we move beyond "algorithm-centric" evaluation, towards evaluating the

Process-oriented semantic web search

CERN Document Server

Tran, DT

2011-01-01

The book is composed of two main parts. The first part is a general study of Semantic Web Search. The second part specifically focuses on the use of semantics throughout the search process, compiling a big picture of Process-oriented Semantic Web Search from different pieces of work that target specific aspects of the process.In particular, this book provides a rigorous account of the concepts and technologies proposed for searching resources and semantic data on the Semantic Web. To collate the various approaches and to better understand what the notion of Semantic Web Search entails, this bo

Semantic SenseLab: Implementing the vision of the Semantic Web in neuroscience.

Science.gov (United States)

Samwald, Matthias; Chen, Huajun; Ruttenberg, Alan; Lim, Ernest; Marenco, Luis; Miller, Perry; Shepherd, Gordon; Cheung, Kei-Hoi

2010-01-01

Integrative neuroscience research needs a scalable informatics framework that enables semantic integration of diverse types of neuroscience data. This paper describes the use of the Web Ontology Language (OWL) and other Semantic Web technologies for the representation and integration of molecular-level data provided by several of SenseLab suite of neuroscience databases. Based on the original database structure, we semi-automatically translated the databases into OWL ontologies with manual addition of semantic enrichment. The SenseLab ontologies are extensively linked to other biomedical Semantic Web resources, including the Subcellular Anatomy Ontology, Brain Architecture Management System, the Gene Ontology, BIRNLex and UniProt. The SenseLab ontologies have also been mapped to the Basic Formal Ontology and Relation Ontology, which helps ease interoperability with many other existing and future biomedical ontologies for the Semantic Web. In addition, approaches to representing contradictory research statements are described. The SenseLab ontologies are designed for use on the Semantic Web that enables their integration into a growing collection of biomedical information resources. We demonstrate that our approach can yield significant potential benefits and that the Semantic Web is rapidly becoming mature enough to realize its anticipated promises. The ontologies are available online at http://neuroweb.med.yale.edu/senselab/. 2009 Elsevier B.V. All rights reserved.

Considering the role of semantic memory in episodic future thinking: evidence from semantic dementia.

Science.gov (United States)

Irish, Muireann; Addis, Donna Rose; Hodges, John R; Piguet, Olivier

2012-07-01

Semantic dementia is a progressive neurodegenerative condition characterized by the profound and amodal loss of semantic memory in the context of relatively preserved episodic memory. In contrast, patients with Alzheimer's disease typically display impairments in episodic memory, but with semantic deficits of a much lesser magnitude than in semantic dementia. Our understanding of episodic memory retrieval in these cohorts has greatly increased over the last decade, however, we know relatively little regarding the ability of these patients to imagine and describe possible future events, and whether episodic future thinking is mediated by divergent neural substrates contingent on dementia subtype. Here, we explored episodic future thinking in patients with semantic dementia (n=11) and Alzheimer's disease (n=11), in comparison with healthy control participants (n=10). Participants completed a battery of tests designed to probe episodic and semantic thinking across past and future conditions, as well as standardized tests of episodic and semantic memory. Further, all participants underwent magnetic resonance imaging. Despite their relatively intact episodic retrieval for recent past events, the semantic dementia cohort showed significant impairments for episodic future thinking. In contrast, the group with Alzheimer's disease showed parallel deficits across past and future episodic conditions. Voxel-based morphometry analyses confirmed that atrophy in the left inferior temporal gyrus and bilateral temporal poles, regions strongly implicated in semantic memory, correlated significantly with deficits in episodic future thinking in semantic dementia. Conversely, episodic future thinking performance in Alzheimer's disease correlated with atrophy in regions associated with episodic memory, namely the posterior cingulate, parahippocampal gyrus and frontal pole. These distinct neuroanatomical substrates contingent on dementia group were further qualified by correlational

New molecular descriptors based on local properties at the molecular surface and a boiling-point model derived from them.

Science.gov (United States)

Ehresmann, Bernd; de Groot, Marcel J; Alex, Alexander; Clark, Timothy

2004-01-01

New molecular descriptors based on statistical descriptions of the local ionization potential, local electron affinity, and the local polarizability at the surface of the molecule are proposed. The significance of these descriptors has been tested by calculating them for the Maybridge database in addition to our set of 26 descriptors reported previously. The new descriptors show little correlation with those already in use. Furthermore, the principal components of the extended set of descriptors for the Maybridge data show that especially the descriptors based on the local electron affinity extend the variance in our set of descriptors, which we have previously shown to be relevant to physical properties. The first nine principal components are shown to be most significant. As an example of the usefulness of the new descriptors, we have set up a QSPR model for boiling points using both the old and new descriptors.

A Semantic Reasoning Method Towards Ontological Model for Automated Learning Analysis

OpenAIRE

Okoye, Kingsley; Tawil, Abdel-Rahman; Naeem, Usman; Lamine, Elyes

2015-01-01

Semantic reasoning can help solve the problem of regulating the evolving and static measures of knowledge at theoretical and technological levels. The technique has been proven to enhance the capability of process models by making inferences, retaining and applying what they have learned as well as discovery of new processes. The work in this paper propose a semantic rule-based approach directed towards discovering learners interaction patterns within a learning knowledge base, and then respo...

High Performance Descriptive Semantic Analysis of Semantic Graph Databases

Energy Technology Data Exchange (ETDEWEB)

Joslyn, Cliff A.; Adolf, Robert D.; al-Saffar, Sinan; Feo, John T.; Haglin, David J.; Mackey, Greg E.; Mizell, David W.

2011-06-02

As semantic graph database technology grows to address components ranging from extant large triple stores to SPARQL endpoints over SQL-structured relational databases, it will become increasingly important to be able to understand their inherent semantic structure, whether codified in explicit ontologies or not. Our group is researching novel methods for what we call descriptive semantic analysis of RDF triplestores, to serve purposes of analysis, interpretation, visualization, and optimization. But data size and computational complexity makes it increasingly necessary to bring high performance computational resources to bear on this task. Our research group built a novel high performance hybrid system comprising computational capability for semantic graph database processing utilizing the large multi-threaded architecture of the Cray XMT platform, conventional servers, and large data stores. In this paper we describe that architecture and our methods, and present the results of our analyses of basic properties, connected components, namespace interaction, and typed paths such for the Billion Triple Challenge 2010 dataset.

Descriptors for antimicrobial peptides

DEFF Research Database (Denmark)

Jenssen, Håvard

2011-01-01

of these are currently being used in quantitative structure--activity relationship (QSAR) studies for AMP optimization. Additionally, some key commercial computational tools are discussed, and both successful and less successful studies are referenced, illustrating some of the challenges facing AMP scientists. Through...... examples of different peptide QSAR studies, this review highlights some of the missing links and illuminates some of the questions that would be interesting to challenge in a more systematic fashion. Expert opinion: Computer-aided peptide QSAR using molecular descriptors may provide the necessary edge...

Tracking image features with PCA-SURF descriptors

CSIR Research Space (South Africa)

Pancham, A

2015-05-01

Full Text Available IAPR International Conference on Machine Vision Applications, May 18-22, 2015, Tokyo, JAPAN Tracking Image Features with PCA-SURF Descriptors Ardhisha Pancham CSIR, UKZN South Africa apancham@csir.co.za Daniel Withey CSIR South Africa...

Dual descriptors within the framework of spin-polarized density functional theory.

Science.gov (United States)

Chamorro, E; Pérez, P; Duque, M; De Proft, F; Geerlings, P

2008-08-14

Spin-polarized density functional theory (SP-DFT) allows both the analysis of charge-transfer (e.g., electrophilic and nucleophilic reactivity) and of spin-polarization processes (e.g., photophysical changes arising from electron transitions). In analogy with the dual descriptor introduced by Morell et al. [J. Phys. Chem. A 109, 205 (2005)], we introduce new dual descriptors intended to simultaneously give information of the molecular regions where the spin-polarization process linking states of different multiplicity will drive electron density and spin density changes. The electronic charge and spin rearrangement in the spin forbidden radiative transitions S(0)-->T(n,pi(*)) and S(0)-->T(pi,pi(*)) in formaldehyde and ethylene, respectively, have been used as benchmark examples illustrating the usefulness of the new spin-polarization dual descriptors. These quantities indicate those regions where spin-orbit coupling effects are at work in such processes. Additionally, the qualitative relationship between the topology of the spin-polarization dual descriptors and the vertical singlet triplet energy gap in simple substituted carbene series has been also discussed. It is shown that the electron density and spin density rearrangements arise in agreement with spectroscopic experimental evidence and other theoretical results on the selected target systems.

Analysis Relationship Among Descriptor, References and Citation to Contruct the Inherent Structure of Document Collection

International Nuclear Information System (INIS)

Hasibuan, Zainal A.; Mustangimah

2001-01-01

There are many characteristics can be used to identify a document which cover characteristics of the documents, cited documents, and citing documents This research explored the inherent structure of a document collection as one of main components of information retrieval system. The characteristics examined are: descriptors, references (cited documents), and citations (citing documents). Three independent variables were studied: co-descriptor, bibliographic coupling, and co-citation. A test collection was constructed by searching on a single descriptor i nformation retrieval i n the CD-ROM version of Education Resource Information Clearinghouse (ERIC), covering the period 1981 through 1985. Descriptors were extracted from ERIC; cited and citing documents associated with the test collection were derived from Social Sciences Citation Index (SSCI), covering the period 1981 through 1990. Three hypothesis were tested in this study, that are: (1) the higher the frequency of co-descriptors between documents, the higher the frequencies of their bibliographic coupling and co-citation; (2) the higher the frequency of bibliographic coupling between documents, the higher the frequencies of their co-citation and co-descriptors; and (3) the higher the frequency of co-citation between documents, the higher the frequencies of their co-descriptors and bibliographic coupling. The results showed that all of three hypothesis are supported statistically and there is a significant linear relationship among the observed variables. It is mean that there is a significant relationship among descriptors, references, and citation, so that it can be used to construct the inherent structure of document collection in order to improve information retrieval system performance

Design of an optimal preview controller for linear discrete-time descriptor systems with state delay

Science.gov (United States)

Cao, Mengjuan; Liao, Fucheng

2015-04-01

In this paper, the linear discrete-time descriptor system with state delay is studied, and a design method for an optimal preview controller is proposed. First, by using the discrete lifting technique, the original system is transformed into a general descriptor system without state delay in form. Then, taking advantage of the first-order forward difference operator, we construct a descriptor augmented error system, including the state vectors of the lifted system, error vectors, and desired target signals. Rigorous mathematical proofs are given for the regularity, stabilisability, causal controllability, and causal observability of the descriptor augmented error system. Based on these, the optimal preview controller with preview feedforward compensation for the original system is obtained by using the standard optimal regulator theory of the descriptor system. The effectiveness of the proposed method is shown by numerical simulation.

Quality Assurance of UMLS Semantic Type Assignments Using SNOMED CT Hierarchies.

Science.gov (United States)

Gu, H; Chen, Y; He, Z; Halper, M; Chen, L

2016-01-01

The Unified Medical Language System (UMLS) is one of the largest biomedical terminological systems, with over 2.5 million concepts in its Metathesaurus repository. The UMLS's Semantic Network (SN) with its collection of 133 high-level semantic types serves as an abstraction layer on top of the Metathesaurus. In particular, the SN elaborates an aspect of the Metathesaurus's concepts via the assignment of one or more types to each concept. Due to the scope and complexity of the Metathesaurus, errors are all but inevitable in this semantic-type assignment process. To develop a semi-automated methodology to help assure the quality of semantic-type assignments within the UMLS. The methodology uses a cross-validation strategy involving SNOMED CT's hierarchies in combination with UMLS semantic types. Semantically uniform, disjoint concept groups are generated programmatically by partitioning the collection of all concepts in the same SNOMED CT hierarchy according to their respective semantic-type assignments in the UMLS. Domain experts are then called upon to review the concepts in any group having a small number of concepts. It is our hypothesis that a semantic-type assignment combination applicable only to a very small number of concepts in a SNOMED CT hierarchy is an indicator of potential problems. The methodology was applied to the UMLS 2013AA release along with the SNOMED CT from January 2013. An overall error rate of 33% was found for concepts proposed by the quality-assurance methodology. Supporting our hypothesis, that number was four times higher than the error rate found in control samples. The results show that the quality-assurance methodology can aid in effective and efficient identification of UMLS semantic-type assignment errors.

A Defense of Semantic Minimalism

Science.gov (United States)

Kim, Su

2012-01-01

Semantic Minimalism is a position about the semantic content of declarative sentences, i.e., the content that is determined entirely by syntax. It is defined by the following two points: "Point 1": The semantic content is a complete/truth-conditional proposition. "Point 2": The semantic content is useful to a theory of…

Fourier descriptor classification of differential eddy current probe impedance plane trajectories

International Nuclear Information System (INIS)

Lord, W.; Satish, S.R.

1984-01-01

This chapter describes the use of a parametric model for representing the two-dimensional eddy current impedance plane trajectory. The main advantage of this approach is the ability to reconstruct the trajectory from the model coefficients. Fourier descriptors are used to facilitate defect classification. The Fourier descriptors are obtained by expanding the complex contour function in a Fourier series. Functions of Fourier coefficients which are invariant under transformation of the trajectory are derived and incorporated into a feature vector. Defect classification is obtained by using the K-Means algorithm to cluster the feature vectors. It is demonstrated that the Fourier descriptor approach represents a powerful tool which have several advantages over nonparametric approaches including its insensitivity to drift in the eddy current instrument as well as variations in the probe speed

Artificial intelligence systems based on texture descriptors for vaccine development.

Science.gov (United States)

Nanni, Loris; Brahnam, Sheryl; Lumini, Alessandra

2011-02-01

The aim of this work is to analyze and compare several feature extraction methods for peptide classification that are based on the calculation of texture descriptors starting from a matrix representation of the peptide. This texture-based representation of the peptide is then used to train a support vector machine classifier. In our experiments, the best results are obtained using local binary patterns variants and the discrete cosine transform with selected coefficients. These results are better than those previously reported that employed texture descriptors for peptide representation. In addition, we perform experiments that combine standard approaches based on amino acid sequence. The experimental section reports several tests performed on a vaccine dataset for the prediction of peptides that bind human leukocyte antigens and on a human immunodeficiency virus (HIV-1). Experimental results confirm the usefulness of our novel descriptors. The matlab implementation of our approaches is available at http://bias.csr.unibo.it/nanni/TexturePeptide.zip.

Assigning Main Orientation to an EOH Descriptor on Multispectral Images.

Science.gov (United States)

Li, Yong; Shi, Xiang; Wei, Lijun; Zou, Junwei; Chen, Fang

2015-07-01

This paper proposes an approach to compute an EOH (edge-oriented histogram) descriptor with main orientation. EOH has a better matching ability than SIFT (scale-invariant feature transform) on multispectral images, but does not assign a main orientation to keypoints. Alternatively, it tends to assign the same main orientation to every keypoint, e.g., zero degrees. This limits EOH to matching keypoints between images of translation misalignment only. Observing this limitation, we propose assigning to keypoints the main orientation that is computed with PIIFD (partial intensity invariant feature descriptor). In the proposed method, SIFT keypoints are detected from images as the extrema of difference of Gaussians, and every keypoint is assigned to the main orientation computed with PIIFD. Then, EOH is computed for every keypoint with respect to its main orientation. In addition, an implementation variant is proposed for fast computation of the EOH descriptor. Experimental results show that the proposed approach performs more robustly than the original EOH on image pairs that have a rotation misalignment.

Using ontology-based semantic similarity to facilitate the article screening process for systematic reviews.

Science.gov (United States)

Ji, Xiaonan; Ritter, Alan; Yen, Po-Yin

2017-05-01

Systematic Reviews (SRs) are utilized to summarize evidence from high quality studies and are considered the preferred source of evidence-based practice (EBP). However, conducting SRs can be time and labor intensive due to the high cost of article screening. In previous studies, we demonstrated utilizing established (lexical) article relationships to facilitate the identification of relevant articles in an efficient and effective manner. Here we propose to enhance article relationships with background semantic knowledge derived from Unified Medical Language System (UMLS) concepts and ontologies. We developed a pipelined semantic concepts representation process to represent articles from an SR into an optimized and enriched semantic space of UMLS concepts. Throughout the process, we leveraged concepts and concept relations encoded in biomedical ontologies (SNOMED-CT and MeSH) within the UMLS framework to prompt concept features of each article. Article relationships (similarities) were established and represented as a semantic article network, which was readily applied to assist with the article screening process. We incorporated the concept of active learning to simulate an interactive article recommendation process, and evaluated the performance on 15 completed SRs. We used work saved over sampling at 95% recall (WSS95) as the performance measure. We compared the WSS95 performance of our ontology-based semantic approach to existing lexical feature approaches and corpus-based semantic approaches, and found that we had better WSS95 in most SRs. We also had the highest average WSS95 of 43.81% and the highest total WSS95 of 657.18%. We demonstrated using ontology-based semantics to facilitate the identification of relevant articles for SRs. Effective concepts and concept relations derived from UMLS ontologies can be utilized to establish article semantic relationships. Our approach provided a promising performance and can easily apply to any SR topics in the

Density-Based Clustering with Geographical Background Constraints Using a Semantic Expression Model

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Qingyun Du

2016-05-01

Full Text Available A semantics-based method for density-based clustering with constraints imposed by geographical background knowledge is proposed. In this paper, we apply an ontological approach to the DBSCAN (Density-Based Geospatial Clustering of Applications with Noise algorithm in the form of knowledge representation for constraint clustering. When used in the process of clustering geographic information, semantic reasoning based on a defined ontology and its relationships is primarily intended to overcome the lack of knowledge of the relevant geospatial data. Better constraints on the geographical knowledge yield more reasonable clustering results. This article uses an ontology to describe the four types of semantic constraints for geographical backgrounds: “No Constraints”, “Constraints”, “Cannot-Link Constraints”, and “Must-Link Constraints”. This paper also reports the implementation of a prototype clustering program. Based on the proposed approach, DBSCAN can be applied with both obstacle and non-obstacle constraints as a semi-supervised clustering algorithm and the clustering results are displayed on a digital map.

Subliminal semantic priming in speech.

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Jérôme Daltrozzo

Full Text Available Numerous studies have reported subliminal repetition and semantic priming in the visual modality. We transferred this paradigm to the auditory modality. Prime awareness was manipulated by a reduction of sound intensity level. Uncategorized prime words (according to a post-test were followed by semantically related, unrelated, or repeated target words (presented without intensity reduction and participants performed a lexical decision task (LDT. Participants with slower reaction times in the LDT showed semantic priming (faster reaction times for semantically related compared to unrelated targets and negative repetition priming (slower reaction times for repeated compared to semantically related targets. This is the first report of semantic priming in the auditory modality without conscious categorization of the prime.

Open semantic analysis: The case of word level semantics in Danish

DEFF Research Database (Denmark)

Nielsen, Finn Årup; Hansen, Lars Kai

2017-01-01

The present research is motivated by the need for accessible and efficient tools for automated semantic analysis in Danish. We are interested in tools that are completely open, so they can be used by a critical public, in public administration, non-governmental organizations and businesses. We...... describe data-driven models for Danish semantic relatedness, word intrusion and sentiment prediction. Open Danish corpora were assembled and unsupervised learning implemented for explicit semantic analysis and with Gensim’s Word2vec model. We evaluate the performance of the two models on three different...... annotated word datasets. We test the semantic representations’ alignment with single word sentiment using supervised learning. We find that logistic regression and large random forests perform well with Word2vec features....

Locator-Checker-Scaler Object Tracking Using Spatially Ordered and Weighted Patch Descriptor.

Science.gov (United States)

Kim, Han-Ul; Kim, Chang-Su

2017-08-01

In this paper, we propose a simple yet effective object descriptor and a novel tracking algorithm to track a target object accurately. For the object description, we divide the bounding box of a target object into multiple patches and describe them with color and gradient histograms. Then, we determine the foreground weight of each patch to alleviate the impacts of background information in the bounding box. To this end, we perform random walk with restart (RWR) simulation. We then concatenate the weighted patch descriptors to yield the spatially ordered and weighted patch (SOWP) descriptor. For the object tracking, we incorporate the proposed SOWP descriptor into a novel tracking algorithm, which has three components: locator, checker, and scaler (LCS). The locator and the scaler estimate the center location and the size of a target, respectively. The checker determines whether it is safe to adjust the target scale in a current frame. These three components cooperate with one another to achieve robust tracking. Experimental results demonstrate that the proposed LCS tracker achieves excellent performance on recent benchmarks.

Using ontological inference and hierarchical matchmaking to overcome semantic heterogeneity in remote sensing-based biodiversity monitoring

Science.gov (United States)

Nieland, Simon; Kleinschmit, Birgit; Förster, Michael

2015-05-01

Ontology-based applications hold promise in improving spatial data interoperability. In this work we use remote sensing-based biodiversity information and apply semantic formalisation and ontological inference to show improvements in data interoperability/comparability. The proposed methodology includes an observation-based, "bottom-up" engineering approach for remote sensing applications and gives a practical example of semantic mediation of geospatial products. We apply the methodology to three different nomenclatures used for remote sensing-based classification of two heathland nature conservation areas in Belgium and Germany. We analysed sensor nomenclatures with respect to their semantic formalisation and their bio-geographical differences. The results indicate that a hierarchical and transparent nomenclature is far more important for transferability than the sensor or study area. The inclusion of additional information, not necessarily belonging to a vegetation class description, is a key factor for the future success of using semantics for interoperability in remote sensing.

SM4MQ: A Semantic Model for Multidimensional Queries

DEFF Research Database (Denmark)

Varga, Jovan; Dobrokhotova, Ekaterina; Romero, Oscar

2017-01-01

On-Line Analytical Processing (OLAP) is a data analysis approach to support decision-making. On top of that, Exploratory OLAP is a novel initiative for the convergence of OLAP and the Semantic Web (SW) that enables the use of OLAP techniques on SW data. Moreover, OLAP approaches exploit different......, sharing, and reuse on the SW. As OLAP is based on the underlying multidimensional (MD) data model we denote such queries as MD queries and define SM4MQ: A Semantic Model for Multidimensional Queries. Furthermore, we propose a method to automate the exploitation of queries by means of SPARQL. We apply...

IN SILICO EVALUATION OF ANGIOTENSIN II RECEPTOR ANTAGONIST’S PLASMA PROTEIN BINDING USING COMPUTED MOLECULAR DESCRIPTORS

Directory of Open Access Journals (Sweden)

Jadranka Odović

2014-03-01

Full Text Available The discovery of new pharmacologically active substances and drugs modeling led to necessity of predicting drugs properties and its ADME data. Angiotensin II receptor antagonists are a group of pharmaceuticals which modulate the renin-angiotensin-aldosterone system and today represent the most commonly prescribed anti-hypertensive drugs. The aim of this study was to compare different molecular properties of seven angiotensin II receptor antagonists / blockers (ARBs, (eprosartan, irbesartan, losartan, olmesartan, telmisartan, valsartan and their plasma protein binding (PPB data. Several ARBs molecular descriptors were calculated using software package Molinspiration Depiction Software as well as Virtual Computational Chemistry Laboratory (electronic descriptor – PSA, constitutional parameter – Mw, geometric descriptor – Vol, lipophilicity descriptors - logP values, aqueous solubility data – logS. The correlations between all collected descriptors and plasma protein binding data obtained from relevant literature were established. In the simple linear regression poor correlations were obtained in relationships between PPB data and all calculated molecular descriptors. In the next stage of the study multiple linear regression (MLR was used for correlation of PPB data with two different descriptors as independent variables. The best correlation (R2=0.70 with P<0.05 was established between PPB data and molecular weight with addition of volume values as independent variables. The possible application of computed molecular descriptors in drugs protein binding evaluation can be of great importance in drug research.

Quantitative structure-retention relationships of pesticides in reversed-phase high-performance liquid chromatography based on WHIM and GETAWAY molecular descriptors

Energy Technology Data Exchange (ETDEWEB)

D' Archivio, Angelo Antonio [Dipartimento di Chimica, Ingegneria Chimica e Materiali, Universita degli Studi di L' Aquila, Via Vetoio, 67010 Coppito, L' Aquila (Italy)], E-mail: darchivi@univaq.it; Maggi, Maria Anna; Mazzeo, Pietro; Ruggieri, Fabrizio [Dipartimento di Chimica, Ingegneria Chimica e Materiali, Universita degli Studi di L' Aquila, Via Vetoio, 67010 Coppito, L' Aquila (Italy)

2008-11-03

The ability of the Weighted Holistic Invariant Molecular (WHIM) and GEometry, Topology, and Atom-Weights AssemblY (GETAWAY) descriptors to represent the effect of molecular structure on the retention of pesticides in reversed-phase high-performance liquid chromatography (RP-HPLC) is investigated. To this end, two retention data sets previously collected in water-acetonitrile mobile phase are re-examined. The first data set (data-set-1) consists of retention data of 26 neutral compounds belonging to widely used pesticide classes, collected within the mobile phase composition range 40-65% (v/v) acetonitrile. The second data set (data-set-2) describes retention of phenoxy acid herbicides and structurally related compounds (benzoic acid and phenylacetic acid derivatives), as a whole covering the pK{sub a} range 2.3-4.3, as a function of mobile phase composition, ranging between 30 and 70% (v/v) acetonitrile, and pH, ranging between 2 and 5. For each data set, the mobile phase attributes are combined with WHIM or GETAWAY descriptors into 'mixed' predictive models in order to attempt retention modelling within the whole mobile phase composition range of analytical interest. Six- or seven-dimensional multilinear models, preliminarily selected using a genetic algorithm, were improved using a multi-layer artificial neural network (ANN) learned by back propagation. ANN performance was tested on three molecules not used in the learning stage and by leave-more-out cross validation. The results reveal that while WHIM descriptors seem not adequate to model retention of solutes of data-set-1, GETAWAY descriptors provide a satisfactory retention model. On the other hand WHIM and GETAWAY descriptors applied to data-set-2 provide a similar performance, even if slightly worse as compared with the above case. Accuracy of retention modelling in these cases is comparable or slightly poorer as compared with the results previously obtained by combining quantum chemical

Quantitative structure-retention relationships of pesticides in reversed-phase high-performance liquid chromatography based on WHIM and GETAWAY molecular descriptors

International Nuclear Information System (INIS)

D'Archivio, Angelo Antonio; Maggi, Maria Anna; Mazzeo, Pietro; Ruggieri, Fabrizio

2008-01-01

The ability of the Weighted Holistic Invariant Molecular (WHIM) and GEometry, Topology, and Atom-Weights AssemblY (GETAWAY) descriptors to represent the effect of molecular structure on the retention of pesticides in reversed-phase high-performance liquid chromatography (RP-HPLC) is investigated. To this end, two retention data sets previously collected in water-acetonitrile mobile phase are re-examined. The first data set (data-set-1) consists of retention data of 26 neutral compounds belonging to widely used pesticide classes, collected within the mobile phase composition range 40-65% (v/v) acetonitrile. The second data set (data-set-2) describes retention of phenoxy acid herbicides and structurally related compounds (benzoic acid and phenylacetic acid derivatives), as a whole covering the pK a range 2.3-4.3, as a function of mobile phase composition, ranging between 30 and 70% (v/v) acetonitrile, and pH, ranging between 2 and 5. For each data set, the mobile phase attributes are combined with WHIM or GETAWAY descriptors into 'mixed' predictive models in order to attempt retention modelling within the whole mobile phase composition range of analytical interest. Six- or seven-dimensional multilinear models, preliminarily selected using a genetic algorithm, were improved using a multi-layer artificial neural network (ANN) learned by back propagation. ANN performance was tested on three molecules not used in the learning stage and by leave-more-out cross validation. The results reveal that while WHIM descriptors seem not adequate to model retention of solutes of data-set-1, GETAWAY descriptors provide a satisfactory retention model. On the other hand WHIM and GETAWAY descriptors applied to data-set-2 provide a similar performance, even if slightly worse as compared with the above case. Accuracy of retention modelling in these cases is comparable or slightly poorer as compared with the results previously obtained by combining quantum chemical descriptors or usual

Adventures in semantic publishing: exemplar semantic enhancements of a research article.

Directory of Open Access Journals (Sweden)

David Shotton

2009-04-01

Full Text Available Scientific innovation depends on finding, integrating, and re-using the products of previous research. Here we explore how recent developments in Web technology, particularly those related to the publication of data and metadata, might assist that process by providing semantic enhancements to journal articles within the mainstream process of scholarly journal publishing. We exemplify this by describing semantic enhancements we have made to a recent biomedical research article taken from PLoS Neglected Tropical Diseases, providing enrichment to its content and increased access to datasets within it. These semantic enhancements include provision of live DOIs and hyperlinks; semantic markup of textual terms, with links to relevant third-party information resources; interactive figures; a re-orderable reference list; a document summary containing a study summary, a tag cloud, and a citation analysis; and two novel types of semantic enrichment: the first, a Supporting Claims Tooltip to permit "Citations in Context", and the second, Tag Trees that bring together semantically related terms. In addition, we have published downloadable spreadsheets containing data from within tables and figures, have enriched these with provenance information, and have demonstrated various types of data fusion (mashups with results from other research articles and with Google Maps. We have also published machine-readable RDF metadata both about the article and about the references it cites, for which we developed a Citation Typing Ontology, CiTO (http://purl.org/net/cito/. The enhanced article, which is available at http://dx.doi.org/10.1371/journal.pntd.0000228.x001, presents a compelling existence proof of the possibilities of semantic publication. We hope the showcase of examples and ideas it contains, described in this paper, will excite the imaginations of researchers and publishers, stimulating them to explore the possibilities of semantic publishing for their own

Pascal Semantics by a Combination of Denotational Semantics and High-level Petri Nets

DEFF Research Database (Denmark)

Jensen, Kurt; Schmidt, Erik Meineche

1986-01-01

This paper describes the formal semantics of a subset of PASCAL, by means of a semantic model based on a combination of denotational semantics and high-level Petri nets. It is our intention that the paper can be used as part of the written material for an introductory course in computer science....

Where does it break? or : Why the semantic web is not just "research as usual"

NARCIS (Netherlands)

Van Harmelen, Frank

2006-01-01

Work on the Semantic Web is all too often phrased as a technological challenge: how to improve the precision of search engines, how to personalise web-sites, how to integrate weakly-structured data-sources, etc. This suggests that we will be able to realise the Semantic Web by merely applying (and

New descriptors of T-wave morphology are independent of heart rate

DEFF Research Database (Denmark)

Andersen, Mads Peter; Xue, Joel Q; Graff, Claus

2008-01-01

from daytime Holter recordings. Duration parameters (QT, ToTe, TpTe, and others), a number of basic T-wave morphology parameters (amplitude, area, and others) as well as advanced morphology descriptors (asymmetry, flatness, and others) were measured automatically. Heart rate dependence was examined...... by means of analysis of covariance. The results showed clear heart rate dependence for the QT interval (R(2) = 0.53-0.57) and a moderate degree of heart rate dependence for the basic morphology parameters (amplitude, area, and others) (R(2) = 0.17-0.42). Both the advanced T-wave descriptors (asymmetry......T-wave morphology descriptors are sensitive to drug-induced changes and may be a useful addition to the QT interval in cardiac safety trials. Intrasubject heart rate dependence of T-wave morphology was investigated in a sample of 39 healthy individuals. Ten-second electrocardiograms were obtained...

Syntax-driven semantic frame composition in Lexicalized Tree Adjoining Grammars

Directory of Open Access Journals (Sweden)

Laura Kallmeyer

2014-01-01

Full Text Available The grammar framework presented in this paper combines Lexicalized Tree Adjoining Grammar (LTAG with a (decompositional frame semantics. We introduce elementary constructions as pairs of elementary LTAG trees and decompositional frames. The linking between syntax and semantics can largely be captured by such constructions since in LTAG, elementary trees represent full argument projections. Substitution and adjunction in the syntax then trigger the unification of the associated semantic frames, which are formally defined as base-labelled feature structures. Moreover, the system of elementary constructions is specified in a metagrammar by means of tree and frame descriptions. This metagrammatical factorization gives rise to a fine-grained decomposition of the semantic contributions of syntactic building blocks, and it allows us to separate lexical from constructional contributions and to carve out generalizations across constructions. In the second half of the paper, we apply the framework to the analysis of directed motion expressions and of the dative alternation in English, two well-known examples of the interaction between lexical and constructional meaning.

Quantitative structure-activity relationship study of antioxidative peptide by using different sets of amino acids descriptors

Science.gov (United States)

Li, Yao-Wang; Li, Bo; He, Jiguo; Qian, Ping

2011-07-01

A database consisting of 214 tripeptides which contain either His or Tyr residue was applied to study quantitative structure-activity relationships (QSAR) of antioxidative tripeptides. Partial Least-Squares Regression analysis (PLSR) was conducted using parameters individually of each amino acid descriptor, including Divided Physico-chemical Property Scores (DPPS), Hydrophobic, Electronic, Steric, and Hydrogen (HESH), Vectors of Hydrophobic, Steric, and Electronic properties (VHSE), Molecular Surface-Weighted Holistic Invariant Molecular (MS-WHIM), isotropic surface area-electronic charge index (ISA-ECI) and Z-scale, to describe antioxidative tripeptides as X-variables and antioxidant activities measured with ferric thiocyanate methods were as Y-variable. After elimination of outliers by Hotelling's T 2 method and residual analysis, six significant models were obtained describing the entire data set. According to cumulative squared multiple correlation coefficients ( R2), cumulative cross-validation coefficients ( Q2) and relative standard deviation for calibration set (RSD c), the qualities of models using DPPS, HESH, ISA-ECI, and VHSE descriptors are better ( R2 > 0.6, Q2 > 0.5, RSD c 0.44). Furthermore, the predictive ability of models using DPPS descriptor is best among the six descriptors systems (cumulative multiple correlation coefficient for predict set ( Rext2) > 0.7). It was concluded that the DPPS is better to describe the amino acid of antioxidative tripeptides. The results of DPPS descriptor reveal that the importance of the center amino acid and the N-terminal amino acid are far more than the importance of the C-terminal amino acid for antioxidative tripeptides. The hydrophobic (positively to activity) and electronic (negatively to activity) properties of the N-terminal amino acid are suggested to play the most important significance to activity, followed by the hydrogen bond (positively to activity) of the center amino acid. The N-terminal amino acid

Finding the Best Feature Detector-Descriptor Combination

DEFF Research Database (Denmark)

Dahl, Anders Lindbjerg; Aanæs, Henrik; Pedersen, Kim Steenstrup

2011-01-01

, not statistically significantly better than some other methods. As a byproduct of this investigation, we have also tested various DAISY type descriptors, and found that the difference among their performance is statistically insignificant using this dataset. Furthermore, we have not been able to produce results...

Auditing the Assignments of Top-Level Semantic Types in the UMLS Semantic Network to UMLS Concepts.

Science.gov (United States)

He, Zhe; Perl, Yehoshua; Elhanan, Gai; Chen, Yan; Geller, James; Bian, Jiang

2017-11-01

The Unified Medical Language System (UMLS) is an important terminological system. By the policy of its curators, each concept of the UMLS should be assigned the most specific Semantic Types (STs) in the UMLS Semantic Network (SN). Hence, the Semantic Types of most UMLS concepts are assigned at or near the bottom (leaves) of the UMLS Semantic Network. While most ST assignments are correct, some errors do occur. Therefore, Quality Assurance efforts of UMLS curators for ST assignments should concentrate on automatically detected sets of UMLS concepts with higher error rates than random sets. In this paper, we investigate the assignments of top-level semantic types in the UMLS semantic network to concepts, identify potential erroneous assignments, define four categories of errors, and thus provide assistance to curators of the UMLS to avoid these assignments errors. Human experts analyzed samples of concepts assigned 10 of the top-level semantic types and categorized the erroneous ST assignments into these four logical categories. Two thirds of the concepts assigned these 10 top-level semantic types are erroneous. Our results demonstrate that reviewing top-level semantic type assignments to concepts provides an effective way for UMLS quality assurance, comparing to reviewing a random selection of semantic type assignments.

Performance Evaluation of State-of-the-Art Local Feature Detectors and Descriptors in the Context of Longitudinal Registration of Retinal Images.

Science.gov (United States)

Saha, Sajib K; Xiao, Di; Frost, Shaun; Kanagasingam, Yogesan

2018-02-17

In this paper we systematically evaluate the performance of several state-of-the-art local feature detectors and descriptors in the context of longitudinal registration of retinal images. Longitudinal (temporal) registration facilitates to track the changes in the retina that has happened over time. A wide number of local feature detectors and descriptors exist and many of them have already applied for retinal image registration, however, no comparative evaluation has been made so far to analyse their respective performance. In this manuscript we evaluate the performance of the widely known and commonly used detectors such as Harris, SIFT, SURF, BRISK, and bifurcation and cross-over points. As of descriptors SIFT, SURF, ALOHA, BRIEF, BRISK and PIIFD are used. Longitudinal retinal image datasets containing a total of 244 images are used for the experiment. The evaluation reveals some potential findings including more robustness of SURF and SIFT keypoints than the commonly used bifurcation and cross-over points, when detected on the vessels. SIFT keypoints can be detected with a reliability of 59% for without pathology images and 45% for with pathology images. For SURF keypoints these values are respectively 58% and 47%. ALOHA descriptor is best suited to describe SURF keypoints, which ensures an overall matching accuracy, distinguishability of 83%, 93% and 78%, 83% for without pathology and with pathology images respectively.

Semantic role labeling for protein transport predicates

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Martin James H

2008-06-01

Full Text Available Abstract Background Automatic semantic role labeling (SRL is a natural language processing (NLP technique that maps sentences to semantic representations. This technique has been widely studied in the recent years, but mostly with data in newswire domains. Here, we report on a SRL model for identifying the semantic roles of biomedical predicates describing protein transport in GeneRIFs – manually curated sentences focusing on gene functions. To avoid the computational cost of syntactic parsing, and because the boundaries of our protein transport roles often did not match up with syntactic phrase boundaries, we approached this problem with a word-chunking paradigm and trained support vector machine classifiers to classify words as being at the beginning, inside or outside of a protein transport role. Results We collected a set of 837 GeneRIFs describing movements of proteins between cellular components, whose predicates were annotated for the semantic roles AGENT, PATIENT, ORIGIN and DESTINATION. We trained these models with the features of previous word-chunking models, features adapted from phrase-chunking models, and features derived from an analysis of our data. Our models were able to label protein transport semantic roles with 87.6% precision and 79.0% recall when using manually annotated protein boundaries, and 87.0% precision and 74.5% recall when using automatically identified ones. Conclusion We successfully adapted the word-chunking classification paradigm to semantic role labeling, applying it to a new domain with predicates completely absent from any previous studies. By combining the traditional word and phrasal role labeling features with biomedical features like protein boundaries and MEDPOST part of speech tags, we were able to address the challenges posed by the new domain data and subsequently build robust models that achieved F-measures as high as 83.1. This system for extracting protein transport information from Gene

Proposal for standardised ultrasound descriptors of abnormally invasive placenta (AIP)

DEFF Research Database (Denmark)

Collins, Sally L; Ashcroft, Anna; Braun, Thorsten

2016-01-01

on subjective interpretation of imaging signs. There is no accepted consensus on the definition of the commonly used ultrasound markers for AIP. The studies included in a recently published systematic review of antenatal sonographic diagnosis of AIP were analysed for the ultrasound descriptors. Different...... were examined for wording used to describe AIP signs. These were extracted and grouped by ultrasound modality, and synonymous or identical terms identified. The group agreed on six unified descriptors for 2D greyscale signs, four for 2D colour Doppler and one for 3D power Doppler. Four papers included...

Alignment-independent comparison of binding sites based on DrugScore potential fields encoded by 3D Zernike descriptors.

Science.gov (United States)

Nisius, Britta; Gohlke, Holger

2012-09-24

Analyzing protein binding sites provides detailed insights into the biological processes proteins are involved in, e.g., into drug-target interactions, and so is of crucial importance in drug discovery. Herein, we present novel alignment-independent binding site descriptors based on DrugScore potential fields. The potential fields are transformed to a set of information-rich descriptors using a series expansion in 3D Zernike polynomials. The resulting Zernike descriptors show a promising performance in detecting similarities among proteins with low pairwise sequence identities that bind identical ligands, as well as within subfamilies of one target class. Furthermore, the Zernike descriptors are robust against structural variations among protein binding sites. Finally, the Zernike descriptors show a high data compression power, and computing similarities between binding sites based on these descriptors is highly efficient. Consequently, the Zernike descriptors are a useful tool for computational binding site analysis, e.g., to predict the function of novel proteins, off-targets for drug candidates, or novel targets for known drugs.

Exploring the role of quantum chemical descriptors in modeling acute toxicity of diverse chemicals to Daphnia magna.

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Reenu; Vikas

2015-09-01

Various quantum-mechanically computed molecular and thermodynamic descriptors along with physico-chemical, electrostatic and topological descriptors are compared while developing quantitative structure-activity relationships (QSARs) for the acute toxicity of 252 diverse organic chemicals towards Daphnia magna. QSAR models based on the quantum-chemical descriptors, computed with routinely employed advanced semi-empirical and ab-initio methods, along with the electron-correlation contribution (CORR) of the descriptors, are analyzed for the external predictivity of the acute toxicity. The models with reliable internal stability and external predictivity are found to be based on the HOMO energy along with the physico-chemical, electrostatic and topological descriptors. Besides this, the total energy and electron-correlation energy are also observed as highly reliable descriptors, suggesting that the intra-molecular interactions between the electrons play an important role in the origin of the acute toxicity, which is in fact an unexplored phenomenon. The models based on quantum-chemical descriptors such as chemical hardness, absolute electronegativity, standard Gibbs free energy and enthalpy are also observed to be reliable. A comparison of the robust models based on the quantum-chemical descriptors computed with various quantum-mechanical methods suggests that the advanced semi-empirical methods such as PM7 can be more reliable than the ab-initio methods which are computationally more expensive. Copyright © 2015 Elsevier Inc. All rights reserved.

Semantics, contrastive linguistics and parallel corpora

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Violetta Koseska

2014-09-01

Full Text Available Semantics, contrastive linguistics and parallel corpora In view of the ambiguity of the term “semantics”, the author shows the differences between the traditional lexical semantics and the contemporary semantics in the light of various semantic schools. She examines semantics differently in connection with contrastive studies where the description must necessary go from the meaning towards the linguistic form, whereas in traditional contrastive studies the description proceeded from the form towards the meaning. This requirement regarding theoretical contrastive studies necessitates construction of a semantic interlanguage, rather than only singling out universal semantic categories expressed with various language means. Such studies can be strongly supported by parallel corpora. However, in order to make them useful for linguists in manual and computer translations, as well as in the development of dictionaries, including online ones, we need not only formal, often automatic, annotation of texts, but also semantic annotation - which is unfortunately manual. In the article we focus on semantic annotation concerning time, aspect and quantification of names and predicates in the whole semantic structure of the sentence on the example of the “Polish-Bulgarian-Russian parallel corpus”.

Propuesta de descriptores para Acca sellowiana (Berg. Burret

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María Puppo

2014-12-01

Full Text Available Guayabo del país o goiaba serrana [Acca sellowiana (Berg. Burret] es uno de los recursos fitogenéticos subutilizados más valiosos de Uruguay y Brasil. Este árbol de fruto comestible, es endémico de una estrecha región sudamericana que abarca el noreste uruguayo y sur de Brasil, donde su cultivo se limita al uso doméstico o a pequeños huertos comerciales. El uso de los materiales de la especie se ve limitado por el desconocimiento de la diversidad presente tanto en poblaciones naturales como en materiales cultivados. El objetivo de este trabajo fue la elaboración de una lista de descriptores que permita la caracterización y evaluación de los materiales para la conservación, uso sostenible e incorporación de diversidad en los programas de mejoramiento genético. Se elaboró una lista preliminar de 41 descriptores morfo-fenológicos de hoja, flor y fruto, que se aplicó in situ a 204 individuos pertenecientes a cuatro poblaciones silvestres del noreste del Uruguay. Con el método de Máxima Verosimilitud Restringida se estimaron los componentes de la varianza entre poblaciones (s²P, entre individuos dentro de poblaciones (s²I(P, entre muestras dentro de individuo (s²M(IP y sus intervalos de confianza utilizando un Modelo Lineal Mixto. Para la determinación del poder discriminante de las variables cuantitativas se adoptó como criterio estadístico la comparación de IC (límite inferior ICs²I(P>límite superior ICs²M(IP y se calculó la razón entre s²I(P/s²M(IP. Para las variables cualitativas se calculó el estadístico F para la determinación de las diferencias significativas entre individuos con el objetivo de identificar descriptores discriminantes de individuos. También se determinaron las variables que discriminan poblaciones. Se validaron siete descriptores cualitativos (forma de fruto, posición de los sépalos, color de pulpa, color interno de la cáscara, dureza de cáscara, clases de distancia estigma-estambres y

Prediction of monomer reactivity in radical copolymerizations from transition state quantum chemical descriptors

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Zhengde Tan

2013-01-01

Full Text Available In comparison with the Q-e scheme, the Revised Patterns Scheme: the U, V Version (the U-V scheme has greatly improved both its accessibility and its accuracy in interpreting and predicting the reactivity of a monomer in free-radical copolymerizations. Quantitative structure-activity relationship (QSAR models were developed to predict the reactivity parameters u and v of the U-V scheme, by applying genetic algorithm (GA and support vector machine (SVM techniques. Quantum chemical descriptors used for QSAR models were calculated from transition state species with structures C¹H3 - C²HR³• or •C¹H2 - C²H2R³ (formed from vinyl monomers C¹H²=C²HR³ + H•, using density functional theory (DFT, at the UB3LYP level of theory with 6-31G(d basis set. The optimum support vector regression (SVR model of the reactivity parameter u based on Gaussian radial basis function (RBF kernel (C = 10, ε = 10- 5 and γ = 1.0 produced root-mean-square (rms errors for the training, validation and prediction sets being 0.220, 0.326 and 0.345, respectively. The optimal SVR model for v with the RBF kernel (C = 20, ε = 10- 4 and γ = 1.2 produced rms errors for the training set of 0.123, the validation set of 0.206 and the prediction set of 0.238. The feasibility of applying the transition state quantum chemical descriptors to develop SVM models for reactivity parameters u and v in the U-V scheme has been demonstrated.

Relationship between Dyspnea Descriptors and Underlying Causes of the Symptom; a Cross-sectional Study.

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Sajadi, Seyyed Mohammad Ali; Majidi, Alireza; Abdollahimajd, Fahimeh; Jalali, Fatemeh

2017-01-01

History taking and physical examination help clinicians identify the patient's problem and effectively treat it. This study aimed to evaluate the descriptors of dyspnea in patients presenting to emergency department (ED) with asthma, congestive heart failure (CHF), and chronic obstructive pulmonary disease (COPD). This cross-sectional study was conducted on all patients presenting to ED with chief complaint of dyspnea, during 2 years. The patients were asked to describe their dyspnea by choosing three items from the valid and reliable questionnaire or articulating their sensation. The relationship between dyspnea descriptors and underlying cause of symptom was evaluated using SPSS version 16. 312 patients with the mean age of 60.96±17.01 years were evaluated (53.2% male). Most of the patients were > 65 years old (48.7%) and had basic level of education (76.9%). "My breath doesn't go out all the way" with 83.1%, "My chest feels tight " with 45.8%, and "I feel that my airway is obstructed" with 40.7%, were the most frequent dyspnea descriptors in asthma patients. "My breathing requires work" with 46.3%, "I feel that I am suffocating" with 31.5%, and "My breath doesn't go out all the way" with 29.6%, were the most frequent dyspnea descriptors in COPD patients. "My breathing is heavy" with 74.4%, "A hunger for more air" with 24.4%, and "I cannot get enough air" with 23.2%, were the most frequent dyspnea descriptors in CHF patients. Except for "My breath does not go in all the way", there was significant correlation between studied dyspnea descriptors and underlying disease (p = 0.001 for all analyses). It seems that dyspnea descriptors along with other findings from history and physical examination could be helpful in differentiating the causes of the symptom in patients presenting to ED suffering from dyspnea.

Semantic web for dummies

CERN Document Server

Pollock, Jeffrey T

2009-01-01

Semantic Web technology is already changing how we interact with data on the Web. By connecting random information on the Internet in new ways, Web 3.0, as it is sometimes called, represents an exciting online evolution. Whether you're a consumer doing research online, a business owner who wants to offer your customers the most useful Web site, or an IT manager eager to understand Semantic Web solutions, Semantic Web For Dummies is the place to start! It will help you:Know how the typical Internet user will recognize the effects of the Semantic WebExplore all the benefits the data Web offers t

Dependence of QSAR models on the selection of trial descriptor sets: a demonstration using nanotoxicity endpoints of decorated nanotubes.

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Shao, Chi-Yu; Chen, Sing-Zuo; Su, Bo-Han; Tseng, Yufeng J; Esposito, Emilio Xavier; Hopfinger, Anton J

2013-01-28

Little attention has been given to the selection of trial descriptor sets when designing a QSAR analysis even though a great number of descriptor classes, and often a greater number of descriptors within a given class, are now available. This paper reports an effort to explore interrelationships between QSAR models and descriptor sets. Zhou and co-workers (Zhou et al., Nano Lett. 2008, 8 (3), 859-865) designed, synthesized, and tested a combinatorial library of 80 surface modified, that is decorated, multi-walled carbon nanotubes for their composite nanotoxicity using six endpoints all based on a common 0 to 100 activity scale. Each of the six endpoints for the 29 most nanotoxic decorated nanotubes were incorporated as the training set for this study. The study reported here includes trial descriptor sets for all possible combinations of MOE, VolSurf, and 4D-fingerprints (FP) descriptor classes, as well as including and excluding explicit spatial contributions from the nanotube. Optimized QSAR models were constructed from these multiple trial descriptor sets. It was found that (a) both the form and quality of the best QSAR models for each of the endpoints are distinct and (b) some endpoints are quite dependent upon 4D-FP descriptors of the entire nanotube-decorator complex. However, other endpoints yielded equally good models only using decorator descriptors with and without the decorator-only 4D-FP descriptors. Lastly, and most importantly, the quality, significance, and interpretation of a QSAR model were found to be critically dependent on the trial descriptor sets used within a given QSAR endpoint study.

Assigning Main Orientation to an EOH Descriptor on Multispectral Images

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Yong Li

2015-07-01

Full Text Available This paper proposes an approach to compute an EOH (edge-oriented histogram descriptor with main orientation. EOH has a better matching ability than SIFT (scale-invariant feature transform on multispectral images, but does not assign a main orientation to keypoints. Alternatively, it tends to assign the same main orientation to every keypoint, e.g., zero degrees. This limits EOH to matching keypoints between images of translation misalignment only. Observing this limitation, we propose assigning to keypoints the main orientation that is computed with PIIFD (partial intensity invariant feature descriptor. In the proposed method, SIFT keypoints are detected from images as the extrema of difference of Gaussians, and every keypoint is assigned to the main orientation computed with PIIFD. Then, EOH is computed for every keypoint with respect to its main orientation. In addition, an implementation variant is proposed for fast computation of the EOH descriptor. Experimental results show that the proposed approach performs more robustly than the original EOH on image pairs that have a rotation misalignment.

Cavity Versus Ligand Shape Descriptors: Application to Urokinase Binding Pockets.

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Cerisier, Natacha; Regad, Leslie; Triki, Dhoha; Camproux, Anne-Claude; Petitjean, Michel

2017-11-01

We analyzed 78 binding pockets of the human urokinase plasminogen activator (uPA) catalytic domain extracted from a data set of crystallized uPA-ligand complexes. These binding pockets were computed with an original geometric method that does NOT involve any arbitrary parameter, such as cutoff distances, angles, and so on. We measured the deviation from convexity of each pocket shape with the pocket convexity index (PCI). We defined a new pocket descriptor called distributional sphericity coefficient (DISC), which indicates to which extent the protein atoms of a given pocket lie on the surface of a sphere. The DISC values were computed with the freeware PCI. The pocket descriptors and their high correspondences with ligand descriptors are crucial for polypharmacology prediction. We found that the protein heavy atoms lining the urokinases binding pockets are either located on the surface of their convex hull or lie close to this surface. We also found that the radii of the urokinases binding pockets and the radii of their ligands are highly correlated (r = 0.9).

The contribution of executive control to semantic cognition: Convergent evidence from semantic aphasia and executive dysfunction.

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Thompson, Hannah E; Almaghyuli, Azizah; Noonan, Krist A; Barak, Ohr; Lambon Ralph, Matthew A; Jefferies, Elizabeth

2018-01-03

Semantic cognition, as described by the controlled semantic cognition (CSC) framework (Rogers et al., , Neuropsychologia, 76, 220), involves two key components: activation of coherent, generalizable concepts within a heteromodal 'hub' in combination with modality-specific features (spokes), and a constraining mechanism that manipulates and gates this knowledge to generate time- and task-appropriate behaviour. Executive-semantic goal representations, largely supported by executive regions such as frontal and parietal cortex, are thought to allow the generation of non-dominant aspects of knowledge when these are appropriate for the task or context. Semantic aphasia (SA) patients have executive-semantic deficits, and these are correlated with general executive impairment. If the CSC proposal is correct, patients with executive impairment should not only exhibit impaired semantic cognition, but should also show characteristics that align with those observed in SA. This possibility remains largely untested, as patients selected on the basis that they show executive impairment (i.e., with 'dysexecutive syndrome') have not been extensively tested on tasks tapping semantic control and have not been previously compared with SA cases. We explored conceptual processing in 12 patients showing symptoms consistent with dysexecutive syndrome (DYS) and 24 SA patients, using a range of multimodal semantic assessments which manipulated control demands. Patients with executive impairments, despite not being selected to show semantic impairments, nevertheless showed parallel patterns to SA cases. They showed strong effects of distractor strength, cues and miscues, and probe-target distance, plus minimal effects of word frequency on comprehension (unlike semantic dementia patients with degradation of conceptual knowledge). This supports a component process account of semantic cognition in which retrieval is shaped by control processes, and confirms that deficits in SA patients reflect

Putting semantics into the semantic web: how well can it capture biology?

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Kazic, Toni

2006-01-01

Could the Semantic Web work for computations of biological interest in the way it's intended to work for movie reviews and commercial transactions? It would be wonderful if it could, so it's worth looking to see if its infrastructure is adequate to the job. The technologies of the Semantic Web make several crucial assumptions. I examine those assumptions; argue that they create significant problems; and suggest some alternative ways of achieving the Semantic Web's goals for biology.

Towards Compatible and Interderivable Semantic Specifications for the Scheme Programming Language, Part I: Denotational Semantics, Natural Semantics, and Abstract Machines

DEFF Research Database (Denmark)

Danvy, Olivier

2008-01-01

We derive two big-step abstract machines, a natural semantics, and the valuation function of a denotational semantics based on the small-step abstract machine for Core Scheme presented by Clinger at PLDI'98. Starting from a functional implementation of this small-step abstract machine, (1) we fuse...... its transition function with its driver loop, obtaining the functional implementation of a big-step abstract machine; (2) we adjust this big-step abstract machine so that it is in defunctionalized form, obtaining the functional implementation of a second big-step abstract machine; (3) we...... refunctionalize this adjusted abstract machine, obtaining the functional implementation of a natural semantics in continuation style; and (4) we closure-unconvert this natural semantics, obtaining a compositional continuation-passing evaluation function which we identify as the functional implementation...

Temporal Representation in Semantic Graphs

Energy Technology Data Exchange (ETDEWEB)

Levandoski, J J; Abdulla, G M

2007-08-07

A wide range of knowledge discovery and analysis applications, ranging from business to biological, make use of semantic graphs when modeling relationships and concepts. Most of the semantic graphs used in these applications are assumed to be static pieces of information, meaning temporal evolution of concepts and relationships are not taken into account. Guided by the need for more advanced semantic graph queries involving temporal concepts, this paper surveys the existing work involving temporal representations in semantic graphs.

Flow Logics and Operational Semantics

DEFF Research Database (Denmark)

Nielson, Flemming; Nielson, Hanne Riis

1998-01-01

Flow logic is a “fast prototyping” approach to program analysis that shows great promise of being able to deal with a wide variety of languages and calculi for computation. However, seemingly innocent choices in the flow logic as well as in the operational semantics may inhibit proving the analys...... correct. Our main conclusion is that environment based semantics is more flexible than either substitution based semantics or semantics making use of structural congruences (like alpha-renaming)....

Fast human pose estimation using 3D Zernike descriptors

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Berjón, Daniel; Morán, Francisco

2012-03-01

Markerless video-based human pose estimation algorithms face a high-dimensional problem that is frequently broken down into several lower-dimensional ones by estimating the pose of each limb separately. However, in order to do so they need to reliably locate the torso, for which they typically rely on time coherence and tracking algorithms. Their losing track usually results in catastrophic failure of the process, requiring human intervention and thus precluding their usage in real-time applications. We propose a very fast rough pose estimation scheme based on global shape descriptors built on 3D Zernike moments. Using an articulated model that we configure in many poses, a large database of descriptor/pose pairs can be computed off-line. Thus, the only steps that must be done on-line are the extraction of the descriptors for each input volume and a search against the database to get the most likely poses. While the result of such process is not a fine pose estimation, it can be useful to help more sophisticated algorithms to regain track or make more educated guesses when creating new particles in particle-filter-based tracking schemes. We have achieved a performance of about ten fps on a single computer using a database of about one million entries.

Semantic word category processing in semantic dementia and posterior cortical atrophy.

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Shebani, Zubaida; Patterson, Karalyn; Nestor, Peter J; Diaz-de-Grenu, Lara Z; Dawson, Kate; Pulvermüller, Friedemann

2017-08-01

There is general agreement that perisylvian language cortex plays a major role in lexical and semantic processing; but the contribution of additional, more widespread, brain areas in the processing of different semantic word categories remains controversial. We investigated word processing in two groups of patients whose neurodegenerative diseases preferentially affect specific parts of the brain, to determine whether their performance would vary as a function of semantic categories proposed to recruit those brain regions. Cohorts with (i) Semantic Dementia (SD), who have anterior temporal-lobe atrophy, and (ii) Posterior Cortical Atrophy (PCA), who have predominantly parieto-occipital atrophy, performed a lexical decision test on words from five different lexico-semantic categories: colour (e.g., yellow), form (oval), number (seven), spatial prepositions (under) and function words (also). Sets of pseudo-word foils matched the target words in length and bi-/tri-gram frequency. Word-frequency was matched between the two visual word categories (colour and form) and across the three other categories (number, prepositions, and function words). Age-matched healthy individuals served as controls. Although broad word processing deficits were apparent in both patient groups, the deficit was strongest for colour words in SD and for spatial prepositions in PCA. The patterns of performance on the lexical decision task demonstrate (a) general lexicosemantic processing deficits in both groups, though more prominent in SD than in PCA, and (b) differential involvement of anterior-temporal and posterior-parietal cortex in the processing of specific semantic categories of words. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

A semantic web approach applied to integrative bioinformatics experimentation: a biological use case with genomics data.

NARCIS (Netherlands)

Post, L.J.G.; Roos, M.; Marshall, M.S.; van Driel, R.; Breit, T.M.

2007-01-01

The numerous public data resources make integrative bioinformatics experimentation increasingly important in life sciences research. However, it is severely hampered by the way the data and information are made available. The semantic web approach enhances data exchange and integration by providing

Scientific Knowledge Discovery in Complex Semantic Networks of Geophysical Systems

Science.gov (United States)

Fox, P.

2012-04-01

The vast majority of explorations of the Earth's systems are limited in their ability to effectively explore the most important (often most difficult) problems because they are forced to interconnect at the data-element, or syntactic, level rather than at a higher scientific, or semantic, level. Recent successes in the application of complex network theory and algorithms to climate data, raise expectations that more general graph-based approaches offer the opportunity for new discoveries. In the past ~ 5 years in the natural sciences there has substantial progress in providing both specialists and non-specialists the ability to describe in machine readable form, geophysical quantities and relations among them in meaningful and natural ways, effectively breaking the prior syntax barrier. The corresponding open-world semantics and reasoning provide higher-level interconnections. That is, semantics provided around the data structures, using semantically-equipped tools, and semantically aware interfaces between science application components allowing for discovery at the knowledge level. More recently, formal semantic approaches to continuous and aggregate physical processes are beginning to show promise and are soon likely to be ready to apply to geoscientific systems. To illustrate these opportunities, this presentation presents two application examples featuring domain vocabulary (ontology) and property relations (named and typed edges in the graphs). First, a climate knowledge discovery pilot encoding and exploration of CMIP5 catalog information with the eventual goal to encode and explore CMIP5 data. Second, a multi-stakeholder knowledge network for integrated assessments in marine ecosystems, where the data is highly inter-disciplinary.

Awareness of breathing: the structure of language descriptors of respiratory sensations.

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Petersen, Sibylle; Orth, Bernhard; Ritz, Thomas

2008-01-01

Recent research suggests that dyspnea is not a single sensation but a multidimensional construct reflected in different verbal descriptors that can provide useful diagnostic information. In this study superordinated clusters of dyspnea were investigated in combination with a dimensional approach. We examined the use of 20 respiratory symptom descriptors by healthy volunteers who completed a protocol of seven experimental conditions: Quiet breathing, breath holding, paced breathing, climbing stairs, resistive load breathing, voluntary hyperinflation, and voluntary hyperventilation. We analyzed the ratings of these descriptors with multidimensional scaling (MDS) and cluster analysis. While similarities with prior studies were found on a lower fusion level, we were able to demonstrate the usefulness of interpreting higher fusion levels with four clusters related to work of breathing, coordination, suffocation, and struggling for air, merging into two superordinated clusters, effort and air hunger that are compatible with widely accepted primary components of dyspnea. MDS results also suggested that future studies should consider further breathing sensations related to cognitive control of breathing.

SemantEco: a semantically powered modular architecture for integrating distributed environmental and ecological data

Science.gov (United States)

Patton, Evan W.; Seyed, Patrice; Wang, Ping; Fu, Linyun; Dein, F. Joshua; Bristol, R. Sky; McGuinness, Deborah L.

2014-01-01

We aim to inform the development of decision support tools for resource managers who need to examine large complex ecosystems and make recommendations in the face of many tradeoffs and conflicting drivers. We take a semantic technology approach, leveraging background ontologies and the growing body of linked open data. In previous work, we designed and implemented a semantically enabled environmental monitoring framework called SemantEco and used it to build a water quality portal named SemantAqua. Our previous system included foundational ontologies to support environmental regulation violations and relevant human health effects. In this work, we discuss SemantEco’s new architecture that supports modular extensions and makes it easier to support additional domains. Our enhanced framework includes foundational ontologies to support modeling of wildlife observation and wildlife health impacts, thereby enabling deeper and broader support for more holistically examining the effects of environmental pollution on ecosystems. We conclude with a discussion of how, through the application of semantic technologies, modular designs will make it easier for resource managers to bring in new sources of data to support more complex use cases.

Semantic Web Primer

NARCIS (Netherlands)

Antoniou, Grigoris; Harmelen, Frank van

2004-01-01

The development of the Semantic Web, with machine-readable content, has the potential to revolutionize the World Wide Web and its use. A Semantic Web Primer provides an introduction and guide to this still emerging field, describing its key ideas, languages, and technologies. Suitable for use as a

Quantization, Frobenius and Bi algebras from the Categorical Framework of Quantum Mechanics to Natural Language Semantics

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Sadrzadeh, Mehrnoosh

2017-07-01

Compact Closed categories and Frobenius and Bi algebras have been applied to model and reason about Quantum protocols. The same constructions have also been applied to reason about natural language semantics under the name: ``categorical distributional compositional'' semantics, or in short, the ``DisCoCat'' model. This model combines the statistical vector models of word meaning with the compositional models of grammatical structure. It has been applied to natural language tasks such as disambiguation, paraphrasing and entailment of phrases and sentences. The passage from the grammatical structure to vectors is provided by a functor, similar to the Quantization functor of Quantum Field Theory. The original DisCoCat model only used compact closed categories. Later, Frobenius algebras were added to it to model long distance dependancies such as relative pronouns. Recently, bialgebras have been added to the pack to reason about quantifiers. This paper reviews these constructions and their application to natural language semantics. We go over the theory and present some of the core experimental results.

Wernicke's Aphasia Reflects a Combination of Acoustic-Phonological and Semantic Control Deficits: A Case-Series Comparison of Wernicke's Aphasia, Semantic Dementia and Semantic Aphasia

Science.gov (United States)

Robson, Holly; Sage, Karen; Lambon Ralph, Matthew A.

2012-01-01

Wernicke's aphasia (WA) is the classical neurological model of comprehension impairment and, as a result, the posterior temporal lobe is assumed to be critical to semantic cognition. This conclusion is potentially confused by (a) the existence of patient groups with semantic impairment following damage to other brain regions (semantic dementia and…

COTARD SYNDROME IN SEMANTIC DEMENTIA

Science.gov (United States)

Mendez, Mario F.; Ramírez-Bermúdez, Jesús

2011-01-01

Background Semantic dementia is a neurodegenerative disorder characterized by the loss of meaning of words or concepts. semantic dementia can offer potential insights into the mechanisms of content-specific delusions. Objective The authors present a rare case of semantic dementia with Cotard syndrome, a delusion characterized by nihilism or self-negation. Method The semantic deficits and other features of semantic dementia were evaluated in relation to the patient's Cotard syndrome. Results Mrs. A developed the delusional belief that she was wasting and dying. This occurred after she lost knowledge for her somatic discomforts and sensations and for the organs that were the source of these sensations. Her nihilistic beliefs appeared to emerge from her misunderstanding of her somatic sensations. Conclusion This unique patient suggests that a mechanism for Cotard syndrome is difficulty interpreting the nature and source of internal pains and sensations. We propose that loss of semantic knowledge about one's own body may lead to the delusion of nihilism or death. PMID:22054629

Hierarchical Semantic Model of Geovideo

Directory of Open Access Journals (Sweden)

XIE Xiao

2015-05-01

Full Text Available The public security incidents were getting increasingly challenging with regard to their new features, including multi-scale mobility, multistage dynamic evolution, as well as spatiotemporal concurrency and uncertainty in the complex urban environment. However, the existing video models, which were used/designed for independent archive or local analysis of surveillance video, have seriously inhibited emergency response to the urgent requirements.Aiming at the explicit representation of change mechanism in video, the paper proposed a novel hierarchical geovideo semantic model using UML. This model was characterized by the hierarchical representation of both data structure and semantics based on the change-oriented three domains (feature domain, process domain and event domain instead of overall semantic description of video streaming; combining both geographical semantics and video content semantics, in support of global semantic association between multiple geovideo data. The public security incidents by video surveillance are inspected as an example to illustrate the validity of this model.

Mapping the Structure of Semantic Memory

Science.gov (United States)

Morais, Ana Sofia; Olsson, Henrik; Schooler, Lael J.

2013-01-01

Aggregating snippets from the semantic memories of many individuals may not yield a good map of an individual's semantic memory. The authors analyze the structure of semantic networks that they sampled from individuals through a new snowball sampling paradigm during approximately 6 weeks of 1-hr daily sessions. The semantic networks of individuals…

Causality in the semantics of Esterel : revisited

NARCIS (Netherlands)

Mousavi, M.R.; Klin, B.; Sobocinski, P.

2010-01-01

We re-examine the challenges concerning causality in the semantics of Esterel and show that they pertain to the known issues in the semantics of Structured Operational Semantics with negative premises. We show that the solutions offered for the semantics of SOS also provide answers to the semantic

Semantic Representatives of the Concept

Directory of Open Access Journals (Sweden)

Elena N. Tsay

2013-01-01

Full Text Available In the article concept as one of the principle notions of cognitive linguistics is investigated. Considering concept as culture phenomenon, having language realization and ethnocultural peculiarities, the description of the concept “happiness” is presented. Lexical and semantic paradigm of the concept of happiness correlates with a great number of lexical and semantic variants. In the work semantic representatives of the concept of happiness, covering supreme spiritual values are revealed and semantic interpretation of their functioning in the Biblical discourse is given.

System semantics of explanatory dictionaries

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Volodymyr Shyrokov

2015-11-01

Full Text Available System semantics of explanatory dictionaries Some semantic properties of the language to be followed from the structure of lexicographical systems of big explanatory dictionaries are considered. The hyperchains and hypercycles are determined as the definite kind of automorphisms of the lexicographical system of explanatory dictionary. Some semantic consequencies following from the principles of lexicographic closure and lexicographic completeness are investigated using the hyperchains and hypercycles formalism. The connection between the hypercyle properties of the lexicographical system semantics and Goedel’s incompleteness theorem is discussed.

Semantic Categories in the Domain of Motion Verbs by Adult Speakers of Danish, German, and Turkish

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Jessen, Moiken

2013-12-01

Full Text Available Languages differ in the ways they divide the world. This study applies cluster analysis to understand how and why languages differ in the way they express motion events. It further lays out what the parameters of the structure of the semantic space of motion are, based on data collected from participants who were adult speakers of Danish, German, and Turkish. The participants described 37 video clips depicting a large variety of motion events. The results of the study show that the segmentation of the semantic space displays a great deal of variation across all three groups. Turkish differs from German and Danish with respect to the features used to segment the semantic space – namely by using vector orientation. German and Danish differ greatly with respect to (a how fine-grained the distinctions made are, and (b how motion verbs with a common Germanic root are distributed across the semantic space. Consequently, this study illustrates that the parameters applied for categorization by speakers are, to some degree, related to typological membership, in relation to Talmy's typological framework for the expression of motion events. Finally, the study shows that the features applied for categorization differ across languages and that typological membership is not necessarily a predictor of elaboration of the motion verb lexicon.

Externally predictive quantitative modeling of supercooled liquid vapor pressure of polychlorinated-naphthalenes through electron-correlation based quantum-mechanical descriptors.

Science.gov (United States)

Vikas; Chayawan

2014-01-01

For predicting physico-chemical properties related to environmental fate of molecules, quantitative structure-property relationships (QSPRs) are valuable tools in environmental chemistry. For developing a QSPR, molecular descriptors computed through quantum-mechanical methods are generally employed. The accuracy of a quantum-mechanical method, however, rests on the amount of electron-correlation estimated by the method. In this work, single-descriptor QSPRs for supercooled liquid vapor pressure of chloronaphthalenes and polychlorinated-naphthalenes are developed using molecular descriptors based on the electron-correlation contribution of the quantum-mechanical descriptor. The quantum-mechanical descriptors for which the electron-correlation contribution is analyzed include total-energy, mean polarizability, dipole moment, frontier orbital (HOMO/LUMO) energy, and density-functional theory (DFT) based descriptors, namely, absolute electronegativity, chemical hardness, and electrophilicity index. A total of 40 single-descriptor QSPRs were developed using molecular descriptors computed with advanced semi-empirical (SE) methods, namely, RM1, PM7, and ab intio methods, namely, Hartree-Fock and DFT. The developed QSPRs are validated using state-of-the-art external validation procedures employing an external prediction set. From the comparison of external predictivity of the models, it is observed that the single-descriptor QSPRs developed using total energy and correlation energy are found to be far more robust and predictive than those developed using commonly employed descriptors such as HOMO/LUMO energy and dipole moment. The work proposes that if real external predictivity of a QSPR model is desired to be explored, particularly, in terms of intra-molecular interactions, correlation-energy serves as a more appropriate descriptor than the polarizability. However, for developing QSPRs, computationally inexpensive advanced SE methods such as PM7 can be more reliable than

Plant Identification Based on Leaf Midrib Cross-Section Images Using Fractal Descriptors.

Directory of Open Access Journals (Sweden)

Núbia Rosa da Silva

Full Text Available The correct identification of plants is a common necessity not only to researchers but also to the lay public. Recently, computational methods have been employed to facilitate this task, however, there are few studies front of the wide diversity of plants occurring in the world. This study proposes to analyse images obtained from cross-sections of leaf midrib using fractal descriptors. These descriptors are obtained from the fractal dimension of the object computed at a range of scales. In this way, they provide rich information regarding the spatial distribution of the analysed structure and, as a consequence, they measure the multiscale morphology of the object of interest. In Biology, such morphology is of great importance because it is related to evolutionary aspects and is successfully employed to characterize and discriminate among different biological structures. Here, the fractal descriptors are used to identify the species of plants based on the image of their leaves. A large number of samples are examined, being 606 leaf samples of 50 species from Brazilian flora. The results are compared to other imaging methods in the literature and demonstrate that fractal descriptors are precise and reliable in the taxonomic process of plant species identification.

Cross border semantic interoperability for clinical research: the EHR4CR semantic resources and services

Science.gov (United States)

Daniel, Christel; Ouagne, David; Sadou, Eric; Forsberg, Kerstin; Gilchrist, Mark Mc; Zapletal, Eric; Paris, Nicolas; Hussain, Sajjad; Jaulent, Marie-Christine; MD, Dipka Kalra

2016-01-01

With the development of platforms enabling the use of routinely collected clinical data in the context of international clinical research, scalable solutions for cross border semantic interoperability need to be developed. Within the context of the IMI EHR4CR project, we first defined the requirements and evaluation criteria of the EHR4CR semantic interoperability platform and then developed the semantic resources and supportive services and tooling to assist hospital sites in standardizing their data for allowing the execution of the project use cases. The experience gained from the evaluation of the EHR4CR platform accessing to semantically equivalent data elements across 11 European participating EHR systems from 5 countries demonstrated how far the mediation model and mapping efforts met the expected requirements of the project. Developers of semantic interoperability platforms are beginning to address a core set of requirements in order to reach the goal of developing cross border semantic integration of data. PMID:27570649

The Semantic Web Revisited

OpenAIRE

Shadbolt, Nigel; Berners-Lee, Tim; Hall, Wendy

2006-01-01

The original Scientific American article on the Semantic Web appeared in 2001. It described the evolution of a Web that consisted largely of documents for humans to read to one that included data and information for computers to manipulate. The Semantic Web is a Web of actionable information--information derived from data through a semantic theory for interpreting the symbols.This simple idea, however, remains largely unrealized. Shopbots and auction bots abound on the Web, but these are esse...

Semantic Search of Web Services

Science.gov (United States)

Hao, Ke

2013-01-01

This dissertation addresses semantic search of Web services using natural language processing. We first survey various existing approaches, focusing on the fact that the expensive costs of current semantic annotation frameworks result in limited use of semantic search for large scale applications. We then propose a vector space model based service…

ProtDCal: A program to compute general-purpose-numerical descriptors for sequences and 3D-structures of proteins.

Science.gov (United States)

Ruiz-Blanco, Yasser B; Paz, Waldo; Green, James; Marrero-Ponce, Yovani

2015-05-16

The exponential growth of protein structural and sequence databases is enabling multifaceted approaches to understanding the long sought sequence-structure-function relationship. Advances in computation now make it possible to apply well-established data mining and pattern recognition techniques to these data to learn models that effectively relate structure and function. However, extracting meaningful numerical descriptors of protein sequence and structure is a key issue that requires an efficient and widely available solution. We here introduce ProtDCal, a new computational software suite capable of generating tens of thousands of features considering both sequence-based and 3D-structural descriptors. We demonstrate, by means of principle component analysis and Shannon entropy tests, how ProtDCal's sequence-based descriptors provide new and more relevant information not encoded by currently available servers for sequence-based protein feature generation. The wide diversity of the 3D-structure-based features generated by ProtDCal is shown to provide additional complementary information and effectively completes its general protein encoding capability. As demonstration of the utility of ProtDCal's features, prediction models of N-linked glycosylation sites are trained and evaluated. Classification performance compares favourably with that of contemporary predictors of N-linked glycosylation sites, in spite of not using domain-specific features as input information. ProtDCal provides a friendly and cross-platform graphical user interface, developed in the Java programming language and is freely available at: http://bioinf.sce.carleton.ca/ProtDCal/ . ProtDCal introduces local and group-based encoding which enhances the diversity of the information captured by the computed features. Furthermore, we have shown that adding structure-based descriptors contributes non-redundant additional information to the features-based characterization of polypeptide systems. This

LAIR: A Language for Automated Semantics-Aware Text Sanitization based on Frame Semantics

DEFF Research Database (Denmark)

Hedegaard, Steffen; Houen, Søren; Simonsen, Jakob Grue

2009-01-01

We present \\lair{}: A domain-specific language that enables users to specify actions to be taken upon meeting specific semantic frames in a text, in particular to rephrase and redact the textual content. While \\lair{} presupposes superficial knowledge of frames and frame semantics, it requires on...... with automated redaction of web pages for subjectively undesirable content; initial experiments suggest that using a small language based on semantic recognition of undesirable terms can be highly useful as a supplement to traditional methods of text sanitization.......We present \\lair{}: A domain-specific language that enables users to specify actions to be taken upon meeting specific semantic frames in a text, in particular to rephrase and redact the textual content. While \\lair{} presupposes superficial knowledge of frames and frame semantics, it requires only...... limited prior programming experience. It neither contain scripting or I/O primitives, nor does it contain general loop constructions and is not Turing-complete. We have implemented a \\lair{} compiler and integrated it in a pipeline for automated redaction of web pages. We detail our experience...

PROFEAT Update: A Protein Features Web Server with Added Facility to Compute Network Descriptors for Studying Omics-Derived Networks.

Science.gov (United States)

Zhang, P; Tao, L; Zeng, X; Qin, C; Chen, S Y; Zhu, F; Yang, S Y; Li, Z R; Chen, W P; Chen, Y Z

2017-02-03

The studies of biological, disease, and pharmacological networks are facilitated by the systems-level investigations using computational tools. In particular, the network descriptors developed in other disciplines have found increasing applications in the study of the protein, gene regulatory, metabolic, disease, and drug-targeted networks. Facilities are provided by the public web servers for computing network descriptors, but many descriptors are not covered, including those used or useful for biological studies. We upgraded the PROFEAT web server http://bidd2.nus.edu.sg/cgi-bin/profeat2016/main.cgi for computing up to 329 network descriptors and protein-protein interaction descriptors. PROFEAT network descriptors comprehensively describe the topological and connectivity characteristics of unweighted (uniform binding constants and molecular levels), edge-weighted (varying binding constants), node-weighted (varying molecular levels), edge-node-weighted (varying binding constants and molecular levels), and directed (oriented processes) networks. The usefulness of the network descriptors is illustrated by the literature-reported studies of the biological networks derived from the genome, interactome, transcriptome, metabolome, and diseasome profiles. Copyright © 2016 Elsevier Ltd. All rights reserved.

Feature Detector and Descriptor for Medical Images

Science.gov (United States)

Sargent, Dusty; Chen, Chao-I.; Tsai, Chang-Ming; Wang, Yuan-Fang; Koppel, Daniel

2009-02-01

The ability to detect and match features across multiple views of a scene is a crucial first step in many computer vision algorithms for dynamic scene analysis. State-of-the-art methods such as SIFT and SURF perform successfully when applied to typical images taken by a digital camera or camcorder. However, these methods often fail to generate an acceptable number of features when applied to medical images, because such images usually contain large homogeneous regions with little color and intensity variation. As a result, tasks like image registration and 3D structure recovery become difficult or impossible in the medical domain. This paper presents a scale, rotation and color/illumination invariant feature detector and descriptor for medical applications. The method incorporates elements of SIFT and SURF while optimizing their performance on medical data. Based on experiments with various types of medical images, we combined, adjusted, and built on methods and parameter settings employed in both algorithms. An approximate Hessian based detector is used to locate scale invariant keypoints and a dominant orientation is assigned to each keypoint using a gradient orientation histogram, providing rotation invariance. Finally, keypoints are described with an orientation-normalized distribution of gradient responses at the assigned scale, and the feature vector is normalized for contrast invariance. Experiments show that the algorithm detects and matches far more features than SIFT and SURF on medical images, with similar error levels.

Semantic dementia without surface dyslexia in Spanish: unimpaired reading with impaired semantics.

Science.gov (United States)

Wilson, Maximiliano A; Martínez-Cuitiño, Macarena

2012-01-01

Surface dyslexia has been attributed to an overreliance on the sub-lexical route for reading. Typically, surface dyslexic patients commit regularisation errors when reading irregular words. Also, semantic dementia has often been associated with surface dyslexia, leading to some explanations of the reading impairment that stress the role of semantics in irregular word reading. Nevertheless, some patients have been reported with unimpaired ability to read irregular words, even though they show severe comprehension impairment. We present the case of M.B., the first Spanish-speaking semantic dementia patient to be reported who shows unimpaired reading of non-words, regular words, and - most strikingly - irregular loan words. M.B. has severely impaired comprehension of the same words he reads correctly (whether regular or irregular). We argue that M.B.'s pattern of performance shows that irregular words can be correctly read even with impaired semantic knowledge corresponding to those words.

A generalized notion of semantic independence

DEFF Research Database (Denmark)

Fränzle, Martin; Stengel, Bernhard von; Wittmüss, Arne

1995-01-01

For programs represented semantically as relations, a concept of semantic independence is defined that is more general than previously stated notions. It allows for shared input variables and irrelevant interference due to nondeterminism.......For programs represented semantically as relations, a concept of semantic independence is defined that is more general than previously stated notions. It allows for shared input variables and irrelevant interference due to nondeterminism....

Morphological descriptors and micro satellite diversity among scarlet ...

African Journals Online (AJOL)

Solanum aethiopicum L. groups is an important leaf and fruit vegetable, largely consumed in sub Saharan Africa. Genetic variation pattern among 35 accessions belonging to S. aethiopicum groups and sources of donor parents were investigated using morphological descriptors and SSR marker pairs. The Principal ...

On the universal structure of human lexical semantics.

Science.gov (United States)

Youn, Hyejin; Sutton, Logan; Smith, Eric; Moore, Cristopher; Wilkins, Jon F; Maddieson, Ian; Croft, William; Bhattacharya, Tanmoy

2016-02-16

How universal is human conceptual structure? The way concepts are organized in the human brain may reflect distinct features of cultural, historical, and environmental background in addition to properties universal to human cognition. Semantics, or meaning expressed through language, provides indirect access to the underlying conceptual structure, but meaning is notoriously difficult to measure, let alone parameterize. Here, we provide an empirical measure of semantic proximity between concepts using cross-linguistic dictionaries to translate words to and from languages carefully selected to be representative of worldwide diversity. These translations reveal cases where a particular language uses a single "polysemous" word to express multiple concepts that another language represents using distinct words. We use the frequency of such polysemies linking two concepts as a measure of their semantic proximity and represent the pattern of these linkages by a weighted network. This network is highly structured: Certain concepts are far more prone to polysemy than others, and naturally interpretable clusters of closely related concepts emerge. Statistical analysis of the polysemies observed in a subset of the basic vocabulary shows that these structural properties are consistent across different language groups, and largely independent of geography, environment, and the presence or absence of a literary tradition. The methods developed here can be applied to any semantic domain to reveal the extent to which its conceptual structure is, similarly, a universal attribute of human cognition and language use.

Comparing Refinements for Failure and Bisimulation Semantics

NARCIS (Netherlands)

Eshuis, H.; Fokkinga, M.M.

2002-01-01

Refinement in bisimulation semantics is defined differently from refinement in failure semantics: in bisimulation semantics refinement is based on simulations between labelled transition systems, whereas in failure semantics refinement is based on inclusions between failure systems. There exist

Semantics-based Automated Web Testing

Directory of Open Access Journals (Sweden)

Hai-Feng Guo

2015-08-01

Full Text Available We present TAO, a software testing tool performing automated test and oracle generation based on a semantic approach. TAO entangles grammar-based test generation with automated semantics evaluation using a denotational semantics framework. We show how TAO can be incorporated with the Selenium automation tool for automated web testing, and how TAO can be further extended to support automated delta debugging, where a failing web test script can be systematically reduced based on grammar-directed strategies. A real-life parking website is adopted throughout the paper to demonstrate the effectivity of our semantics-based web testing approach.

Graph-Based Semantic Web Service Composition for Healthcare Data Integration.

Science.gov (United States)

Arch-Int, Ngamnij; Arch-Int, Somjit; Sonsilphong, Suphachoke; Wanchai, Paweena

2017-01-01

Within the numerous and heterogeneous web services offered through different sources, automatic web services composition is the most convenient method for building complex business processes that permit invocation of multiple existing atomic services. The current solutions in functional web services composition lack autonomous queries of semantic matches within the parameters of web services, which are necessary in the composition of large-scale related services. In this paper, we propose a graph-based Semantic Web Services composition system consisting of two subsystems: management time and run time. The management-time subsystem is responsible for dependency graph preparation in which a dependency graph of related services is generated automatically according to the proposed semantic matchmaking rules. The run-time subsystem is responsible for discovering the potential web services and nonredundant web services composition of a user's query using a graph-based searching algorithm. The proposed approach was applied to healthcare data integration in different health organizations and was evaluated according to two aspects: execution time measurement and correctness measurement.

Benchmarking semantic web technology

CERN Document Server

García-Castro, R

2009-01-01

This book addresses the problem of benchmarking Semantic Web Technologies; first, from a methodological point of view, proposing a general methodology to follow in benchmarking activities over Semantic Web Technologies and, second, from a practical point of view, presenting two international benchmarking activities that involved benchmarking the interoperability of Semantic Web technologies using RDF(S) as the interchange language in one activity and OWL in the other.The book presents in detail how the different resources needed for these interoperability benchmarking activities were defined:

Bayesian screening for active compounds in high-dimensional chemical spaces combining property descriptors and molecular fingerprints.

Science.gov (United States)

Vogt, Martin; Bajorath, Jürgen

2008-01-01

Bayesian classifiers are increasingly being used to distinguish active from inactive compounds and search large databases for novel active molecules. We introduce an approach to directly combine the contributions of property descriptors and molecular fingerprints in the search for active compounds that is based on a Bayesian framework. Conventionally, property descriptors and fingerprints are used as alternative features for virtual screening methods. Following the approach introduced here, probability distributions of descriptor values and fingerprint bit settings are calculated for active and database molecules and the divergence between the resulting combined distributions is determined as a measure of biological activity. In test calculations on a large number of compound activity classes, this methodology was found to consistently perform better than similarity searching using fingerprints and multiple reference compounds or Bayesian screening calculations using probability distributions calculated only from property descriptors. These findings demonstrate that there is considerable synergy between different types of property descriptors and fingerprints in recognizing diverse structure-activity relationships, at least in the context of Bayesian modeling.

Semantic Web and Contextual Information: Semantic Network Analysis of Online Journalistic Texts

Science.gov (United States)

Lim, Yon Soo

This study examines why contextual information is important to actualize the idea of semantic web, based on a case study of a socio-political issue in South Korea. For this study, semantic network analyses were conducted regarding English-language based 62 blog posts and 101 news stories on the web. The results indicated the differences of the meaning structures between blog posts and professional journalism as well as between conservative journalism and progressive journalism. From the results, this study ascertains empirical validity of current concerns about the practical application of the new web technology, and discusses how the semantic web should be developed.

Perbandingan Hasil Deteksi Plagiarisme Dokumen dengan Metode Jaro-Winkler Distance dan Metode Latent Semantic Analysis

Directory of Open Access Journals (Sweden)

Tinaliah Tinaliah

2018-01-01

Full Text Available Various methods are applied in the application of plagiarism detection to help check the similarity of a document. Jaro-Winkler Distance can measure the distance between two strings. However, this method basically depends on the position of the word. Latent Semantic Analysis emphasizes the words contained in the document regardless of its linguistic character. This study compares the results of plagiarism detection using the Jaro-Winkler Distance and the Latent Semantic Analysis method. From comparing results of  Jaro-Winkler Distance method and Latent Semantic Analysis method, Jaro-Winkler Distance method is better than Latent Semantic Analysis method if using the same test data. Jaro-Winkler Distance method will give plagiarism result 100% and Latent Semantic Analysis method will give plagiarism result 97,14%. Beragam metode diterapkan dalam aplikasi deteksi plagiarisme untuk membantu mengecek tingkat kesamaan sebuah dokumen. Metode Jaro-Winkler Distance dapat mengukur kesamaan antara dua buah string dan sangat bergantung pada urutan atau posisi kata. Latent Semantic Analysis mementingkan kata-kata yang terkandung di dalam dokumen tanpa memperhatikan karakter linguistiknya. Penelitian ini melakukan perbandingan hasil deteksi plagiarisme dengan menggunakan metode Jaro-Winkler Distance dan metode Latent Semantic Analysis. Hasil pendeteksian plagiarisme dokumen menggunakan metode Jaro-Winkler Distance memberikan hasil yang lebih baik daripada metode Latent Semantic Analysis, yaitu jika data yang dibandingkan sama persis maka akan menghasilkan nilai plagiat sebesar 100%, sedangkan metode Latent Semantic Analysis menghasilkan nilai plagiat sebesar 97,14%.

Observer Bias: An Interaction of Temperament Traits with Biases in the Semantic Perception of Lexical Material

Science.gov (United States)

Trofimova, Ira

2014-01-01

The lexical approach is a method in differential psychology that uses people's estimations of verbal descriptors of human behavior in order to derive the structure of human individuality. The validity of the assumptions of this method about the objectivity of people's estimations is rarely questioned. Meanwhile the social nature of language and the presence of emotionality biases in cognition are well-recognized in psychology. A question remains, however, as to whether such an emotionality-capacities bias is strong enough to affect semantic perception of verbal material. For the lexical approach to be valid as a method of scientific investigations, such biases should not exist in semantic perception of the verbal material that is used by this approach. This article reports on two studies investigating differences between groups contrasted by 12 temperament traits (i.e. by energetic and other capacities, as well as emotionality) in the semantic perception of very general verbal material. Both studies contrasted the groups by a variety of capacities: endurance, lability and emotionality separately in physical, social-verbal and mental aspects of activities. Hypotheses of “background emotionality” and a “projection through capacities” were supported. Non-evaluative criteria for categorization (related to complexity, organization, stability and probability of occurrence of objects) followed the polarity of evaluative criteria, and did not show independence from this polarity. Participants with stronger physical or social endurance gave significantly more positive ratings to a variety of concepts, and participants with faster physical tempo gave more positive ratings to timing-related concepts. The results suggest that people's estimations of lexical material related to human behavior have emotionality, language- and dynamical capacities-related biases and therefore are unreliable. This questions the validity of the lexical approach as a method for the objective

Delay-Dependent Finite-Time H∞ Controller Design for a Kind of Nonlinear Descriptor Systems via a T-S Fuzzy Model

Directory of Open Access Journals (Sweden)

Baoyan Zhu

2015-01-01

Full Text Available Delay-dependent finite-time H∞ controller design problems are investigated for a kind of nonlinear descriptor system via a T-S fuzzy model in this paper. The solvable conditions of finite-time H∞ controller are given to guarantee that the loop-closed system is impulse-free and finite-time bounded and holds the H∞ performance to a prescribed disturbance attenuation level γ. The method given is the ability to eliminate the impulsive behavior caused by descriptor systems in a finite-time interval, which confirms the existence and uniqueness of solutions in the interval. By constructing a nonsingular matrix, we overcome the difficulty that results in an infeasible linear matrix inequality (LMI. Using the FEASP solver and GEVP solver of the LMI toolbox, we perform simulations to validate the proposed methods for a nonlinear descriptor system via the T-S fuzzy model, which shows the application of the T-S fuzzy method in studying the finite-time control problem of a nonlinear system. Meanwhile the method was also applied to the biological economy system to eliminate impulsive behavior at the bifurcation value, stabilize the loop-closed system in a finite-time interval, and achieve a H∞ performance level.

Evaluating descriptors for the lateral translocation of membrane proteins.

Science.gov (United States)

Domanova, Olga; Borbe, Stefan; Mühlfeld, Stefanie; Becker, Martin; Kubitz, Ralf; Häussinger, Dieter; Berlage, Thomas

2011-01-01

Microscopic images of tissue sections are used for diagnosis and monitoring of therapy, by analysis of protein patterns correlating to disease states. Spatial protein distribution is influenced by protein translocation between different membrane compartments and quantified by comparison of microscopic images of biological samples. Cholestatic liver diseases are characterized by translocation of transport proteins, and quantification of their dislocation offers new diagnostic options. However, reliable and unbiased tools are lacking. The nowadays used manual method is slow, subjective and error-prone. We have developed a new workflow based on automated image analysis and improved it by the introduction of scale-free descriptors for the translocation quantification. This fast and unbiased method can substitute the manual analysis, and the suggested descriptors perform better than the earlier used statistical variance.

A new texture descriptor based on local micro-pattern for detection of architectural distortion in mammographic images

Science.gov (United States)

de Oliveira, Helder C. R.; Moraes, Diego R.; Reche, Gustavo A.; Borges, Lucas R.; Catani, Juliana H.; de Barros, Nestor; Melo, Carlos F. E.; Gonzaga, Adilson; Vieira, Marcelo A. C.

2017-03-01

This paper presents a new local micro-pattern texture descriptor for the detection of Architectural Distortion (AD) in digital mammography images. AD is a subtle contraction of breast parenchyma that may represent an early sign of breast cancer. Due to its subtlety and variability, AD is more difficult to detect compared to microcalcifications and masses, and is commonly found in retrospective evaluations of false-negative mammograms. Several computer-based systems have been proposed for automatic detection of AD, but their performance are still unsatisfactory. The proposed descriptor, Local Mapped Pattern (LMP), is a generalization of the Local Binary Pattern (LBP), which is considered one of the most powerful feature descriptor for texture classification in digital images. Compared to LBP, the LMP descriptor captures more effectively the minor differences between the local image pixels. Moreover, LMP is a parametric model which can be optimized for the desired application. In our work, the LMP performance was compared to the LBP and four Haralick's texture descriptors for the classification of 400 regions of interest (ROIs) extracted from clinical mammograms. ROIs were selected and divided into four classes: AD, normal tissue, microcalcifications and masses. Feature vectors were used as input to a multilayer perceptron neural network, with a single hidden layer. Results showed that LMP is a good descriptor to distinguish AD from other anomalies in digital mammography. LMP performance was slightly better than the LBP and comparable to Haralick's descriptors (mean classification accuracy = 83%).

Semantic Keys and Reading

Directory of Open Access Journals (Sweden)

Zev bar-Lev

2016-12-01

Full Text Available Semantic Keys are elements (word-parts of written language that give an iconic, general representation of the whole word’s meaning. In written Sino-Japanese the “radical” or semantic components play this role. For example, the character meaning ‘woman, female’ is the Semantic Key of the character for Ma ‘Mama’ (alongside the phonetic component Ma, which means ‘horse’ as a separate character. The theory of semantic Keys in both graphic and phonemic aspects is called qTheory or nanosemantics. The most innovative aspect of the present article is the hypothesis that, in languages using alphabetic writing systems, the role of Semantic Key is played by consonants, more specifically the first consonant. Thus, L meaning ‘LIFT’ is the Semantic Key of English Lift, Ladle, Lofty, aLps, eLevator, oLympus; Spanish Leva, Lecantarse, aLto, Lengua; Arabic aLLah, and Hebrew① ªeL-ºaL ‘upto-above’ (the Israeli airline, Polish Lot ‘flight’ (the Polish airline; Hebrew ªeL, ªeLohim ‘God’, and haLLeluyah ‘praise-ye God’ (using Parallels, ‘Lift up God’. Evidence for the universality of the theory is shown by many examples drawn from various languages, including Indo-European Semitic, Chinese and Japanese. The theory reveals hundreds of relationships within and between languages, related and unrelated, that have been “Hiding in Plain Sight”, to mention just one example: the Parallel between Spanish Pan ‘bread’ and Mandarin Fan ‘rice’.

Interpreting semantic clustering effects in free recall.

Science.gov (United States)

Manning, Jeremy R; Kahana, Michael J

2012-07-01

The order in which participants choose to recall words from a studied list of randomly selected words provides insights into how memories of the words are represented, organised, and retrieved. One pervasive finding is that when a pair of semantically related words (e.g., "cat" and "dog") is embedded in the studied list, the related words are often recalled successively. This tendency to successively recall semantically related words is termed semantic clustering (Bousfield, 1953; Bousfield & Sedgewick, 1944; Cofer, Bruce, & Reicher, 1966). Measuring semantic clustering effects requires making assumptions about which words participants consider to be similar in meaning. However, it is often difficult to gain insights into individual participants' internal semantic models, and for this reason researchers typically rely on standardised semantic similarity metrics. Here we use simulations to gain insights into the expected magnitudes of semantic clustering effects given systematic differences between participants' internal similarity models and the similarity metric used to quantify the degree of semantic clustering. Our results provide a number of useful insights into the interpretation of semantic clustering effects in free recall.

Snapshots for Semantic Maps

National Research Council Canada - National Science Library

Nielsen, Curtis W; Ricks, Bob; Goodrich, Michael A; Bruemmer, David; Few, Doug; Walton, Miles

2004-01-01

.... Semantic maps are a relatively new approach to information presentation. Semantic maps provide more detail about an environment than typical maps because they are augmented by icons or symbols that provide meaning for places or objects of interest...

Towards Compatible and Interderivable Semantic Specifications for the Scheme Programming Language, Part I: Denotational Semantics, Natural Semantics, and Abstract Machines

DEFF Research Database (Denmark)

Danvy, Olivier

2009-01-01

We derive two big-step abstract machines, a natural semantics, and the valuation function of a denotational semantics based on the small-step abstract machine for Core Scheme presented by Clinger at PLDI'98. Starting from a functional implementation of this small-step abstract machine, (1) we fus...

Modelling of retention of pesticides in reversed-phase high-performance liquid chromatography: Quantitative structure-retention relationships based on solute quantum-chemical descriptors and experimental (solvatochromic and spin-probe) mobile phase descriptors

International Nuclear Information System (INIS)

D'Archivio, Angelo Antonio; Ruggieri, Fabrizio; Mazzeo, Pietro; Tettamanti, Enzo

2007-01-01

A quantitative structure-retention relationship (QSRR) analysis based on multilinear regression (MLR) and artificial neural networks (ANNs) is carried out to model the combined effect of solute structure and eluent composition on the retention behaviour of pesticides in isocratic reversed-phase high-performance liquid chromatography (RP-HPLC). The octanol-water partition coefficient and four quantum chemical descriptors (the total dipole moment, the mean polarizability, the anisotropy of the polarizability and a descriptor of hydrogen-bonding based on the atomic charges on acidic and basic chemical functionalities) are considered as solute descriptors. In order to identify suitable mobile phase descriptors, encoding composition-dependent properties of both methanol- and acetonitrile-containing mobile phases, the Kamlet-Taft solvatochromic parameters (polarity-dipolarity, hydrogen-bond acidity and hydrogen-bond basicity, π * , α and β, respectively) and the 14 N hyperfine-splitting constant (a N ) of a spin-probe dissolved in the eluent are examined. A satisfactory description of mobile phase properties influencing the solute retention is provided by a N and β or alternatively π * and β. The two seven-parameter models resulting from combination of a N and β, or π * and β, with the solute descriptors were tested on a set of 26 pesticides representative of 10 different chemical classes in a wide range of mobile phase composition (30-60% (v/v) water-methanol and 30-70% (v/v) water-acetonitrile). Within the explored experimental range, the acidity of the eluent, as quantified by α, is almost constant, and this parameter is in fact irrelevant. The results reveal that a N and π * , that can be considered as interchangeable mobile phase descriptors, are the most influent variables in the respective models. The predictive ability of the proposed models, as tested on an external data set, is quite good (Q 2 close to 0.94) when a MLR approach is used, but the

Modelling of retention of pesticides in reversed-phase high-performance liquid chromatography: Quantitative structure-retention relationships based on solute quantum-chemical descriptors and experimental (solvatochromic and spin-probe) mobile phase descriptors

Energy Technology Data Exchange (ETDEWEB)

D' Archivio, Angelo Antonio [Dipartimento di Chimica, Ingegneria Chimica e Materiali, Universita degli Studi di L' Aquila, Via Vetoio, 67010 Coppito, L' Aquila (Italy)]. E-mail: darchivi@univaq.it; Ruggieri, Fabrizio [Dipartimento di Chimica, Ingegneria Chimica e Materiali, Universita degli Studi di L' Aquila, Via Vetoio, 67010 Coppito, L' Aquila (Italy); Mazzeo, Pietro [Dipartimento di Chimica, Ingegneria Chimica e Materiali, Universita degli Studi di L' Aquila, Via Vetoio, 67010 Coppito, L' Aquila (Italy); Tettamanti, Enzo [Dipartimento di Scienze Biomediche Comparate, Universita di Teramo, P.zzale A. Moro 45, 64100 Teramo (Italy)

2007-06-19

A quantitative structure-retention relationship (QSRR) analysis based on multilinear regression (MLR) and artificial neural networks (ANNs) is carried out to model the combined effect of solute structure and eluent composition on the retention behaviour of pesticides in isocratic reversed-phase high-performance liquid chromatography (RP-HPLC). The octanol-water partition coefficient and four quantum chemical descriptors (the total dipole moment, the mean polarizability, the anisotropy of the polarizability and a descriptor of hydrogen-bonding based on the atomic charges on acidic and basic chemical functionalities) are considered as solute descriptors. In order to identify suitable mobile phase descriptors, encoding composition-dependent properties of both methanol- and acetonitrile-containing mobile phases, the Kamlet-Taft solvatochromic parameters (polarity-dipolarity, hydrogen-bond acidity and hydrogen-bond basicity, {pi} {sup *}, {alpha} and {beta}, respectively) and the {sup 14}N hyperfine-splitting constant (a {sub N}) of a spin-probe dissolved in the eluent are examined. A satisfactory description of mobile phase properties influencing the solute retention is provided by a {sub N} and {beta} or alternatively {pi} {sup *} and {beta}. The two seven-parameter models resulting from combination of a {sub N} and {beta}, or {pi} {sup *} and {beta}, with the solute descriptors were tested on a set of 26 pesticides representative of 10 different chemical classes in a wide range of mobile phase composition (30-60% (v/v) water-methanol and 30-70% (v/v) water-acetonitrile). Within the explored experimental range, the acidity of the eluent, as quantified by {alpha}, is almost constant, and this parameter is in fact irrelevant. The results reveal that a {sub N} and {pi} {sup *}, that can be considered as interchangeable mobile phase descriptors, are the most influent variables in the respective models. The predictive ability of the proposed models, as tested on an

Examining lateralized semantic access using pictures.

Science.gov (United States)

Lovseth, Kyle; Atchley, Ruth Ann

2010-03-01

A divided visual field (DVF) experiment examined the semantic processing strategies employed by the cerebral hemispheres to determine if strategies observed with written word stimuli generalize to other media for communicating semantic information. We employed picture stimuli and vary the degree of semantic relatedness between the picture pairs. Participants made an on-line semantic relatedness judgment in response to sequentially presented pictures. We found that when pictures are presented to the right hemisphere responses are generally more accurate than the left hemisphere for semantic relatedness judgments for picture pairs. Furthermore, consistent with earlier DVF studies employing words, we conclude that the RH is better at accessing or maintaining access to information that has a weak or more remote semantic relationship. We also found evidence of faster access for pictures presented to the LH in the strongly-related condition. Overall, these results are consistent with earlier DVF word studies that argue that the cerebral hemispheres each play an important and separable role during semantic retrieval. Copyright 2009 Elsevier Inc. All rights reserved.

A Denotational Semantics for Logic Programming

DEFF Research Database (Denmark)

Frandsen, Gudmund Skovbjerg

A fully abstract denotational semantics for logic programming has not been constructed yet. In this paper we present a denotational semantics that is almost fully abstract. We take the meaning of a logic program to be an element in a Plotkin power domain of substitutions. In this way our result...... shows that standard domain constructions suffice, when giving a semantics for logic programming. Using the well-known fixpoint semantics of logic programming we have to consider two different fixpoints in order to obtain information about both successful and failed computations. In contrast, our...... semantics is uniform in that the (single) meaning of a logic program contains information about both successful, failed and infinite computations. Finally, based on the full abstractness result, we argue that the detail level of substitutions is needed in any denotational semantics for logic programming....

Advances in structural damage assessment using strain measurements and invariant shape descriptors

Science.gov (United States)

Patki, Amol Suhas

to the area surrounding the damage, while damage in orthotropic materials tends to have more global repercussions. This calls for analysis of full-field strain distributions adding to the complexity of post-damage life estimation. This study explores shape descriptors used in the field of medical imagery, military targeting and biometric recognition for obtaining a qualitative and quantitative comparison between full-field strain data recorded from damaged composite panels using sophisticated experimental techniques. These descriptors are capable of decomposing images with 103 to 106 pixels into a feature vector with only a few hundred elements. This ability of shape descriptors to achieve enormous reduction in strain data, while providing unique representation, makes them a practical choice for the purpose of structural damage assessment. Consequently, it is relatively easy to statistically compare the shape descriptors of the full-field strain maps using similarity measures rather than the strain maps themselves. However, the wide range of geometric and design features in engineering components pose difficulties in the application of traditional shape description techniques. Thus a new shape descriptor is developed which is applicable to a wide range of specimen geometries. This work also illustrates how shape description techniques can be applied to full-field finite element model validations and updating.

WEATHER FORECAST DATA SEMANTIC ANALYSIS IN F-LOGIC

Directory of Open Access Journals (Sweden)

Ana Meštrović

2007-06-01

Full Text Available This paper addresses the semantic analysis problem in a spoken dialog system developed for the domain of weather forecasts. The main goal of semantic analysis is to extract the meaning from the spoken utterances and to transform it into a domain database format. In this work a semantic database for the domain of weather forecasts is represented using the F-logic formalism. Semantic knowledge is captured through semantic categories a semantic dictionary using phrases and output templates. Procedures for semantic analysis of Croatian weather data combine parsing techniques for Croatian language and slot filling approach. Semantic analysis is conducted in three phases. In the first phase the main semantic category for the input utterance is determined. The lattices are used for hierarchical semantic relation representation and main category derivation. In the second phase semantic units are analyzed and knowledge slots in the database are filled. Since some slot values of input data are missing in the third phase, incomplete data is updated with missing values. All rules for semantic analysis are defined in the F-logic and implemented using the FLORA-2 system. The results of semantic analysis evaluation in terms of frame and slot error rates are presented.

CASL The Common Algebraic Specification Language Semantics

DEFF Research Database (Denmark)

Haxthausen, Anne

1998-01-01

This is version 1.0 of the CASL Language Summary, annotated by the CoFI Semantics Task Group with the semantics of constructs. This is the first complete but possibly imperfect version of the semantics. It was compiled prior to the CoFI workshop at Cachan in November 1998.......This is version 1.0 of the CASL Language Summary, annotated by the CoFI Semantics Task Group with the semantics of constructs. This is the first complete but possibly imperfect version of the semantics. It was compiled prior to the CoFI workshop at Cachan in November 1998....

75 FR 2879 - Use of Tobacco Marketing Descriptors to Convey Modified Risk; Request for Comments

Science.gov (United States)

2010-01-19

... information, research, and ideas on tobacco product marketing descriptors that may be considered similar to...] Use of Tobacco Marketing Descriptors to Convey Modified Risk; Request for Comments AGENCY: Food and... authority to regulate the manufacture, marketing, and distribution of tobacco products to protect the public...

Semantic Web status model

CSIR Research Space (South Africa)

Gerber, AJ

2006-06-01

Full Text Available Semantic Web application areas are experiencing intensified interest due to the rapid growth in the use of the Web, together with the innovation and renovation of information content technologies. The Semantic Web is regarded as an integrator across...

UltiMatch-NL: a Web service matchmaker based on multiple semantic filters.

Science.gov (United States)

Mohebbi, Keyvan; Ibrahim, Suhaimi; Zamani, Mazdak; Khezrian, Mojtaba

2014-01-01

In this paper, a Semantic Web service matchmaker called UltiMatch-NL is presented. UltiMatch-NL applies two filters namely Signature-based and Description-based on different abstraction levels of a service profile to achieve more accurate results. More specifically, the proposed filters rely on semantic knowledge to extract the similarity between a given pair of service descriptions. Thus it is a further step towards fully automated Web service discovery via making this process more semantic-aware. In addition, a new technique is proposed to weight and combine the results of different filters of UltiMatch-NL, automatically. Moreover, an innovative approach is introduced to predict the relevance of requests and Web services and eliminate the need for setting a threshold value of similarity. In order to evaluate UltiMatch-NL, the repository of OWLS-TC is used. The performance evaluation based on standard measures from the information retrieval field shows that semantic matching of OWL-S services can be significantly improved by incorporating designed matching filters.

UltiMatch-NL: A Web Service Matchmaker Based on Multiple Semantic Filters

Science.gov (United States)

Mohebbi, Keyvan; Ibrahim, Suhaimi; Zamani, Mazdak; Khezrian, Mojtaba

2014-01-01

In this paper, a Semantic Web service matchmaker called UltiMatch-NL is presented. UltiMatch-NL applies two filters namely Signature-based and Description-based on different abstraction levels of a service profile to achieve more accurate results. More specifically, the proposed filters rely on semantic knowledge to extract the similarity between a given pair of service descriptions. Thus it is a further step towards fully automated Web service discovery via making this process more semantic-aware. In addition, a new technique is proposed to weight and combine the results of different filters of UltiMatch-NL, automatically. Moreover, an innovative approach is introduced to predict the relevance of requests and Web services and eliminate the need for setting a threshold value of similarity. In order to evaluate UltiMatch-NL, the repository of OWLS-TC is used. The performance evaluation based on standard measures from the information retrieval field shows that semantic matching of OWL-S services can be significantly improved by incorporating designed matching filters. PMID:25157872

Quantization, Frobenius and Bi Algebras from the Categorical Framework of Quantum Mechanics to Natural Language Semantics

Directory of Open Access Journals (Sweden)

Mehrnoosh Sadrzadeh

2017-07-01

Full Text Available Compact Closed categories and Frobenius and Bi algebras have been applied to model and reason about Quantum protocols. The same constructions have also been applied to reason about natural language semantics under the name: “categorical distributional compositional” semantics, or in short, the “DisCoCat” model. This model combines the statistical vector models of word meaning with the compositional models of grammatical structure. It has been applied to natural language tasks such as disambiguation, paraphrasing and entailment of phrases and sentences. The passage from the grammatical structure to vectors is provided by a functor, similar to the Quantization functor of Quantum Field Theory. The original DisCoCat model only used compact closed categories. Later, Frobenius algebras were added to it to model long distance dependancies such as relative pronouns. Recently, bialgebras have been added to the pack to reason about quantifiers. This paper reviews these constructions and their application to natural language semantics. We go over the theory and present some of the core experimental results.

Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation

KAUST Repository

2016-08-29

In this note, the joint state and parameters estimation problem for nonlinear multi-input multi-output descriptor systems is considered. Asymptotic convergence of the adaptive descriptor observer is established by a sufficient set of linear matrix inequalities for the noise-free systems. The noise corrupted systems are also considered and it is shown that the state and parameters estimation errors are bounded for bounded noises. In addition, if the noises are bounded and have zero mean, then the estimation errors asymptotically converge to zero in the mean. The performance of the proposed adaptive observer is illustrated by a numerical example.

Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation

KAUST Repository

Unknown author

2016-01-01

In this note, the joint state and parameters estimation problem for nonlinear multi-input multi-output descriptor systems is considered. Asymptotic convergence of the adaptive descriptor observer is established by a sufficient set of linear matrix inequalities for the noise-free systems. The noise corrupted systems are also considered and it is shown that the state and parameters estimation errors are bounded for bounded noises. In addition, if the noises are bounded and have zero mean, then the estimation errors asymptotically converge to zero in the mean. The performance of the proposed adaptive observer is illustrated by a numerical example.

Large scale healthcare data integration and analysis using the semantic web.

Science.gov (United States)

Timm, John; Renly, Sondra; Farkash, Ariel

2011-01-01

Healthcare data interoperability can only be achieved when the semantics of the content is well defined and consistently implemented across heterogeneous data sources. Achieving these objectives of interoperability requires the collaboration of experts from several domains. This paper describes tooling that integrates Semantic Web technologies with common tools to facilitate cross-domain collaborative development for the purposes of data interoperability. Our approach is divided into stages of data harmonization and representation, model transformation, and instance generation. We applied our approach on Hypergenes, an EU funded project, where we use our method to the Essential Hypertension disease model using a CDA template. Our domain expert partners include clinical providers, clinical domain researchers, healthcare information technology experts, and a variety of clinical data consumers. We show that bringing Semantic Web technologies into the healthcare interoperability toolkit increases opportunities for beneficial collaboration thus improving patient care and clinical research outcomes.

Semantic Memory in the Clinical Progression of Alzheimer Disease.

Science.gov (United States)

Tchakoute, Christophe T; Sainani, Kristin L; Henderson, Victor W

2017-09-01

Semantic memory measures may be useful in tracking and predicting progression of Alzheimer disease. We investigated relationships among semantic memory tasks and their 1-year predictive value in women with Alzheimer disease. We conducted secondary analyses of a randomized clinical trial of raloxifene in 42 women with late-onset mild-to-moderate Alzheimer disease. We assessed semantic memory with tests of oral confrontation naming, category fluency, semantic recognition and semantic naming, and semantic density in written narrative discourse. We measured global cognition (Alzheimer Disease Assessment Scale, cognitive subscale), dementia severity (Clinical Dementia Rating sum of boxes), and daily function (Activities of Daily Living Inventory) at baseline and 1 year. At baseline and 1 year, most semantic memory scores correlated highly or moderately with each other and with global cognition, dementia severity, and daily function. Semantic memory task performance at 1 year had worsened one-third to one-half standard deviation. Factor analysis of baseline test scores distinguished processes in semantic and lexical retrieval (semantic recognition, semantic naming, confrontation naming) from processes in lexical search (semantic density, category fluency). The semantic-lexical retrieval factor predicted global cognition at 1 year. Considered separately, baseline confrontation naming and category fluency predicted dementia severity, while semantic recognition and a composite of semantic recognition and semantic naming predicted global cognition. No individual semantic memory test predicted daily function. Semantic-lexical retrieval and lexical search may represent distinct aspects of semantic memory. Semantic memory processes are sensitive to cognitive decline and dementia severity in Alzheimer disease.

A Denotational Semantics for Communicating Unstructured Code

Directory of Open Access Journals (Sweden)

Nils Jähnig

2015-03-01

Full Text Available An important property of programming language semantics is that they should be compositional. However, unstructured low-level code contains goto-like commands making it hard to define a semantics that is compositional. In this paper, we follow the ideas of Saabas and Uustalu to structure low-level code. This gives us the possibility to define a compositional denotational semantics based on least fixed points to allow for the use of inductive verification methods. We capture the semantics of communication using finite traces similar to the denotations of CSP. In addition, we examine properties of this semantics and give an example that demonstrates reasoning about communication and jumps. With this semantics, we lay the foundations for a proof calculus that captures both, the semantics of unstructured low-level code and communication.

A Semantics for Distributed Execution of Statemate

DEFF Research Database (Denmark)

Fränzle, Martin; Niehaus, Jürgen; Metzner, Alexander

2003-01-01

We present a semantics for the statechart variant implemented in the Statemate product of i-Logix. Our semantics enables distributed code generation for Statemate models in the context of rapid prototyping for embedded control applications. We argue that it seems impossible to efficiently generate......, the changes made regarding the interaction of distributed model parts are similar to the interaction between the model and its environment in the original semantics, thus giving designers a familiar execution model. The semantics has been implemented in Grace, a framework for rapid prototyping code generation...... distributed code using the original Statemate semantics. The new, distributed semantics has the advantages that, first, it enables the generation of efficient distributed code, second, it preserves many aspects of the original semantics for those parts of a model that are not distributed, and third...

morphological descriptors and micro satellite diversity among scarlet ...

African Journals Online (AJOL)

Prof. Adipala Ekwamu

distinctness, similarities and overlap among groups. The Kumba and Aculeatum groups are related for multi- locular characteristic of the fruits. The Nei's coefficients for morphological descriptors and SSR data indicated that S. aethiopicum groups showed a wide genetic base. MM1102 and MM457 showed high relatedness ...

Inter-deriving Semantic Artifacts for Object-Oriented Programming

DEFF Research Database (Denmark)

Danvy, Olivier; Johannsen, Jacob

2008-01-01

.e., big-step operational semantics) specified in Abadi and Cardelli's monograph. This abstract machine therefore embodies the soundness of Abadi and Cardelli's reduction semantics and natural semantics relative to each other. To move closer to actual implementations, which use environments rather than......We present a new abstract machine for Abadi and Cardelli's untyped calculus of objects. What is special about this semantic artifact (i.e., man-made construct) is that is mechanically corresponds to both the reduction semantics (i.e., small-step operational semantics) and the natural semantics (i...... actual substitutions, we then represent object methods as closures and in the same inter-derivational spirit, we present three new semantic artifacts: a reduction semantics for a version of Abadi and Cardelli's untyped calculus of objects with explicit substitutions, an environment-based abstract machine...

Quality of semantic standards

NARCIS (Netherlands)

Folmer, Erwin Johan Albert

2012-01-01

Little scientific literature addresses the issue of quality of semantic standards, albeit a problem with high economic and social impact. Our problem survey, including 34 semantic Standard Setting Organizations (SSOs), gives evidence that quality of standards can be improved, but for improvement a

Morphological Cues for Lexical Semantics

National Research Council Canada - National Science Library

Light, Marc

1996-01-01

Most natural language processing tasks require lexical semantic information such as verbal argument structure and selectional restrictions, corresponding nominal semantic class, verbal aspectual class...

Language networks associated with computerized semantic indices.

Science.gov (United States)

Pakhomov, Serguei V S; Jones, David T; Knopman, David S

2015-01-01

Tests of generative semantic verbal fluency are widely used to study organization and representation of concepts in the human brain. Previous studies demonstrated that clustering and switching behavior during verbal fluency tasks is supported by multiple brain mechanisms associated with semantic memory and executive control. Previous work relied on manual assessments of semantic relatedness between words and grouping of words into semantic clusters. We investigated a computational linguistic approach to measuring the strength of semantic relatedness between words based on latent semantic analysis of word co-occurrences in a subset of a large online encyclopedia. We computed semantic clustering indices and compared them to brain network connectivity measures obtained with task-free fMRI in a sample consisting of healthy participants and those differentially affected by cognitive impairment. We found that semantic clustering indices were associated with brain network connectivity in distinct areas including fronto-temporal, fronto-parietal and fusiform gyrus regions. This study shows that computerized semantic indices complement traditional assessments of verbal fluency to provide a more complete account of the relationship between brain and verbal behavior involved organization and retrieval of lexical information from memory. Copyright © 2014 Elsevier Inc. All rights reserved.

Fine-coarse semantic processing in schizophrenia: a reversed pattern of hemispheric dominance.

Science.gov (United States)

Zeev-Wolf, Maor; Goldstein, Abraham; Levkovitz, Yechiel; Faust, Miriam

2014-04-01

Left lateralization for language processing is a feature of neurotypical brains. In individuals with schizophrenia, lack of left lateralization is associated with the language impairments manifested in this population. Beeman׳s fine-coarse semantic coding model asserts left hemisphere specialization in fine (i.e., conventionalized) semantic coding and right hemisphere specialization in coarse (i.e., non-conventionalized) semantic coding. Applying this model to schizophrenia would suggest that language impairments in this population are a result of greater reliance on coarse semantic coding. We investigated this hypothesis and examined whether a reversed pattern of hemispheric involvement in fine-coarse semantic coding along the time course of activation could be detected in individuals with schizophrenia. Seventeen individuals with schizophrenia and 30 neurotypical participants were presented with two word expressions of four types: literal, conventional metaphoric, unrelated (exemplars of fine semantic coding) and novel metaphoric (an exemplar of coarse semantic coding). Expressions were separated by either a short (250 ms) or long (750 ms) delay. Findings indicate that whereas during novel metaphor processing, controls displayed a left hemisphere advantage at 250 ms delay and right hemisphere advantage at 750 ms, individuals with schizophrenia displayed the opposite. For conventional metaphoric and unrelated expressions, controls showed left hemisphere advantage across times, while individuals with schizophrenia showed a right hemisphere advantage. Furthermore, whereas individuals with schizophrenia were less accurate than control at judging literal, conventional metaphoric and unrelated expressions they were more accurate when judging novel metaphors. Results suggest that individuals with schizophrenia display a reversed pattern of lateralization for semantic coding which causes them to rely more heavily on coarse semantic coding. Thus, for individuals with

On the Existence of Semantic Working Memory: Evidence for Direct Semantic Maintenance

Science.gov (United States)

Shivde, Geeta; Anderson, Michael C.

2011-01-01

Despite widespread acknowledgment of the importance of online semantic maintenance, there has been astonishingly little work that clearly establishes this construct. We review the extant work relevant to short-term retention of meaning and show that, although consistent with semantic working memory, most data can be accommodated in other ways.…

Density functional theory fragment descriptors to quantify the reactivity of a molecular family: application to amino acids.

Science.gov (United States)

Senet, P; Aparicio, F

2007-04-14

By using the exact density functional theory, one demonstrates that the value of the local electronic softness of a molecular fragment is directly related to the polarization charge (Coulomb hole) induced by a test electron removed (or added) from (at) the fragment. Our finding generalizes to a chemical group a formal relation between these molecular descriptors recently obtained for an atom in a molecule using an approximate atomistic model [P. Senet and M. Yang, J. Chem. Sci. 117, 411 (2005)]. In addition, a practical ab initio computational scheme of the Coulomb hole and related local descriptors of reactivity of a molecular family having in common a similar fragment is presented. As a blind test, the method is applied to the lateral chains of the 20 isolated amino acids. One demonstrates that the local softness of the lateral chain is a quantitative measure of the similarity of the amino acids. It predicts the separation of amino acids in different biochemical groups (aliphatic, basic, acidic, sulfur contained, and aromatic). The present approach may find applications in quantitative structure activity relationship methodology.

Semantic Coherence Facilitates Distributional Learning.

Science.gov (United States)

Ouyang, Long; Boroditsky, Lera; Frank, Michael C

2017-04-01

Computational models have shown that purely statistical knowledge about words' linguistic contexts is sufficient to learn many properties of words, including syntactic and semantic category. For example, models can infer that "postman" and "mailman" are semantically similar because they have quantitatively similar patterns of association with other words (e.g., they both tend to occur with words like "deliver," "truck," "package"). In contrast to these computational results, artificial language learning experiments suggest that distributional statistics alone do not facilitate learning of linguistic categories. However, experiments in this paradigm expose participants to entirely novel words, whereas real language learners encounter input that contains some known words that are semantically organized. In three experiments, we show that (a) the presence of familiar semantic reference points facilitates distributional learning and (b) this effect crucially depends both on the presence of known words and the adherence of these known words to some semantic organization. Copyright © 2016 Cognitive Science Society, Inc.

Molecular Descriptors Family on Structure Activity Relationships 1. Review of the Methodology

Directory of Open Access Journals (Sweden)

Lorentz JÄNTSCHI

2005-01-01

Full Text Available This review cumulates the knowledge about the use of Molecular Descriptors Family usage on Structure Activity Relationships. The methodology is augmented through the general Structure Activity Relationships methodology. The obtained models in a series of five papers are quantitatively analyzed by comparing with previous reported results by using of the correlated correlations tests. The scores for a series of 13 data sets unpublished yet results are presented. Two unrestricted online access portals to the Molecular Descriptors Family Structure Activity Relationship models results are given.

Semantic Query Processing : Estimating Relational Purity

NARCIS (Netherlands)

Kalo, Jan-Christoph; Lofi, C.; Maseli, René Pascal; Balke, Wolf-Tilo; Leyer, M.

2017-01-01

The use of semantic information found in structured knowledge bases has become an integral part of the processing pipeline of modern intelligent in-
formation systems. However, such semantic information is frequently insuffi-cient to capture the rich semantics demanded by the applications, and

Hierarchical layered and semantic-based image segmentation using ergodicity map

Science.gov (United States)

Yadegar, Jacob; Liu, Xiaoqing

2010-04-01

Image segmentation plays a foundational role in image understanding and computer vision. Although great strides have been made and progress achieved on automatic/semi-automatic image segmentation algorithms, designing a generic, robust, and efficient image segmentation algorithm is still challenging. Human vision is still far superior compared to computer vision, especially in interpreting semantic meanings/objects in images. We present a hierarchical/layered semantic image segmentation algorithm that can automatically and efficiently segment images into hierarchical layered/multi-scaled semantic regions/objects with contextual topological relationships. The proposed algorithm bridges the gap between high-level semantics and low-level visual features/cues (such as color, intensity, edge, etc.) through utilizing a layered/hierarchical ergodicity map, where ergodicity is computed based on a space filling fractal concept and used as a region dissimilarity measurement. The algorithm applies a highly scalable, efficient, and adaptive Peano- Cesaro triangulation/tiling technique to decompose the given image into a set of similar/homogenous regions based on low-level visual cues in a top-down manner. The layered/hierarchical ergodicity map is built through a bottom-up region dissimilarity analysis. The recursive fractal sweep associated with the Peano-Cesaro triangulation provides efficient local multi-resolution refinement to any level of detail. The generated binary decomposition tree also provides efficient neighbor retrieval mechanisms for contextual topological object/region relationship generation. Experiments have been conducted within the maritime image environment where the segmented layered semantic objects include the basic level objects (i.e. sky/land/water) and deeper level objects in the sky/land/water surfaces. Experimental results demonstrate the proposed algorithm has the capability to robustly and efficiently segment images into layered semantic objects

Lagrangian descriptors of driven chemical reaction manifolds.

Science.gov (United States)

Craven, Galen T; Junginger, Andrej; Hernandez, Rigoberto

2017-08-01

The persistence of a transition state structure in systems driven by time-dependent environments allows the application of modern reaction rate theories to solution-phase and nonequilibrium chemical reactions. However, identifying this structure is problematic in driven systems and has been limited by theories built on series expansion about a saddle point. Recently, it has been shown that to obtain formally exact rates for reactions in thermal environments, a transition state trajectory must be constructed. Here, using optimized Lagrangian descriptors [G. T. Craven and R. Hernandez, Phys. Rev. Lett. 115, 148301 (2015)PRLTAO0031-900710.1103/PhysRevLett.115.148301], we obtain this so-called distinguished trajectory and the associated moving reaction manifolds on model energy surfaces subject to various driving and dissipative conditions. In particular, we demonstrate that this is exact for harmonic barriers in one dimension and this verification gives impetus to the application of Lagrangian descriptor-based methods in diverse classes of chemical reactions. The development of these objects is paramount in the theory of reaction dynamics as the transition state structure and its underlying network of manifolds directly dictate reactivity and selectivity.

Pragmatics for formal semantics

DEFF Research Database (Denmark)

Danvy, Olivier

2011-01-01

This tech talk describes how to write and how to inter-derive formal semantics for sequential programming languages. The progress reported here is (1) concrete guidelines to write each formal semantics to alleviate their proof obligations, and (2) simple calculational tools to obtain a formal...

A reasonable Semantic Web

NARCIS (Netherlands)

Hitzler, Pascal; Van Harmelen, Frank

2010-01-01

The realization of Semantic Web reasoning is central to substantiating the Semantic Web vision. However, current mainstream research on this topic faces serious challenges, which forces us to question established lines of research and to rethink the underlying approaches. We argue that reasoning for

Compositional descriptor-based recommender system for the materials discovery

Science.gov (United States)

Seko, Atsuto; Hayashi, Hiroyuki; Tanaka, Isao

2018-06-01

Structures and properties of many inorganic compounds have been collected historically. However, it only covers a very small portion of possible inorganic crystals, which implies the presence of numerous currently unknown compounds. A powerful machine-learning strategy is mandatory to discover new inorganic compounds from all chemical combinations. Herein we propose a descriptor-based recommender-system approach to estimate the relevance of chemical compositions where crystals can be formed [i.e., chemically relevant compositions (CRCs)]. In addition to data-driven compositional similarity used in the literature, the use of compositional descriptors as a prior knowledge is helpful for the discovery of new compounds. We validate our recommender systems in two ways. First, one database is used to construct a model, while another is used for the validation. Second, we estimate the phase stability for compounds at expected CRCs using density functional theory calculations.

Episodic memory, semantic memory, and amnesia.

Science.gov (United States)

Squire, L R; Zola, S M

1998-01-01

Episodic memory and semantic memory are two types of declarative memory. There have been two principal views about how this distinction might be reflected in the organization of memory functions in the brain. One view, that episodic memory and semantic memory are both dependent on the integrity of medial temporal lobe and midline diencephalic structures, predicts that amnesic patients with medial temporal lobe/diencephalic damage should be proportionately impaired in both episodic and semantic memory. An alternative view is that the capacity for semantic memory is spared, or partially spared, in amnesia relative to episodic memory ability. This article reviews two kinds of relevant data: 1) case studies where amnesia has occurred early in childhood, before much of an individual's semantic knowledge has been acquired, and 2) experimental studies with amnesic patients of fact and event learning, remembering and knowing, and remote memory. The data provide no compelling support for the view that episodic and semantic memory are affected differently in medial temporal lobe/diencephalic amnesia. However, episodic and semantic memory may be dissociable in those amnesic patients who additionally have severe frontal lobe damage.

Gricean Semantics and Vague Speaker-Meaning

OpenAIRE

Schiffer, Stephen

2017-01-01

Presentations of Gricean semantics, including Stephen Neale’s in “Silent Reference,” totally ignore vagueness, even though virtually every utterance is vague. I ask how Gricean semantics might be adjusted to accommodate vague speaker-meaning. My answer is that it can’t accommodate it: the Gricean program collapses in the face of vague speaker-meaning. The Gricean might, however, fi nd some solace in knowing that every other extant meta-semantic and semantic program is in the same boat.

Modeling the Interaction Between Semantic Agents and Semantic Web Services Using MDA Approach

NARCIS (Netherlands)

Kardas, Geylani; Göknil, Arda; Dikenelli, Oguz; Topaloglu, N. Yasemin

2007-01-01

In this paper, we present our metamodeling approach for integrating semantic web services and semantic web enabled agents under Model Driven Architecture (MDA) view which defines a conceptual framework to realize model driven development. We believe that agents must have well designed environment

A Model for Semantic IS Standards

NARCIS (Netherlands)

Folmer, Erwin Johan Albert; Oude Luttighuis, Paul; van Hillegersberg, Jos

2011-01-01

We argue that, in order to suggest improvements of any kind to semantic information system (IS) standards, better understanding of the conceptual structure of semantic IS standard is required. This study develops a model for semantic IS standard, based on literature and expert knowledge. The model

Clinical descriptors for the recognition of central sensitization pain in patients with knee osteoarthritis

DEFF Research Database (Denmark)

Lluch, Enrique; Nijs, Jo; Courtney, Carol A

2018-01-01

BACKGROUND: Despite growing awareness of the contribution of central pain mechanisms to knee osteoarthritis pain in a subgroup of patients, routine evaluation of central sensitization is yet to be incorporated into clinical practice. AIM: The objective of this perspective is to design a set...... of clinical descriptors for the recognition of central sensitization in patients with knee osteoarthritis that can be implemented in clinical practice. METHODS: A narrative review of original research papers was conducted by nine clinicians and researchers from seven different countries to reach agreement...... hyperalgesia, hypoesthesia and reduced vibration sense. CONCLUSIONS: This article describes a set of clinically relevant descriptors that might indicate the presence of central sensitization in patients with knee osteoarthritis in clinical practice. Although based on research data, the descriptors proposed...

Semantic-based surveillance video retrieval.

Science.gov (United States)

Hu, Weiming; Xie, Dan; Fu, Zhouyu; Zeng, Wenrong; Maybank, Steve

2007-04-01

Visual surveillance produces large amounts of video data. Effective indexing and retrieval from surveillance video databases are very important. Although there are many ways to represent the content of video clips in current video retrieval algorithms, there still exists a semantic gap between users and retrieval systems. Visual surveillance systems supply a platform for investigating semantic-based video retrieval. In this paper, a semantic-based video retrieval framework for visual surveillance is proposed. A cluster-based tracking algorithm is developed to acquire motion trajectories. The trajectories are then clustered hierarchically using the spatial and temporal information, to learn activity models. A hierarchical structure of semantic indexing and retrieval of object activities, where each individual activity automatically inherits all the semantic descriptions of the activity model to which it belongs, is proposed for accessing video clips and individual objects at the semantic level. The proposed retrieval framework supports various queries including queries by keywords, multiple object queries, and queries by sketch. For multiple object queries, succession and simultaneity restrictions, together with depth and breadth first orders, are considered. For sketch-based queries, a method for matching trajectories drawn by users to spatial trajectories is proposed. The effectiveness and efficiency of our framework are tested in a crowded traffic scene.

Preserving differential privacy under finite-precision semantics.

Directory of Open Access Journals (Sweden)

Ivan Gazeau

2013-06-01

Full Text Available The approximation introduced by finite-precision representation of continuous data can induce arbitrarily large information leaks even when the computation using exact semantics is secure. Such leakage can thus undermine design efforts aimed at protecting sensitive information. We focus here on differential privacy, an approach to privacy that emerged from the area of statistical databases and is now widely applied also in other domains. In this approach, privacy is protected by the addition of noise to a true (private value. To date, this approach to privacy has been proved correct only in the ideal case in which computations are made using an idealized, infinite-precision semantics. In this paper, we analyze the situation at the implementation level, where the semantics is necessarily finite-precision, i.e. the representation of real numbers and the operations on them, are rounded according to some level of precision. We show that in general there are violations of the differential privacy property, and we study the conditions under which we can still guarantee a limited (but, arguably, totally acceptable variant of the property, under only a minor degradation of the privacy level. Finally, we illustrate our results on two cases of noise-generating distributions: the standard Laplacian mechanism commonly used in differential privacy, and a bivariate version of the Laplacian recently introduced in the setting of privacy-aware geolocation.

IBRI-CASONTO: Ontology-based semantic search engine

Directory of Open Access Journals (Sweden)

Awny Sayed

2017-11-01

Full Text Available The vast availability of information, that added in a very fast pace, in the data repositories creates a challenge in extracting correct and accurate information. Which has increased the competition among developers in order to gain access to technology that seeks to understand the intent researcher and contextual meaning of terms. While the competition for developing an Arabic Semantic Search systems are still in their infancy, and the reason could be traced back to the complexity of Arabic Language. It has a complex morphological, grammatical and semantic aspects, as it is a highly inflectional and derivational language. In this paper, we try to highlight and present an Ontological Search Engine called IBRI-CASONTO for Colleges of Applied Sciences, Oman. Our proposed engine supports both Arabic and English language. It is also employed two types of search which are a keyword-based search and a semantics-based search. IBRI-CASONTO is based on different technologies such as Resource Description Framework (RDF data and Ontological graph. The experiments represent in two sections, first it shows a comparison among Entity-Search and the Classical-Search inside the IBRI-CASONTO itself, second it compares the Entity-Search of IBRI-CASONTO with currently used search engines, such as Kngine, Wolfram Alpha and the most popular engine nowadays Google, in order to measure their performance and efficiency.

Semantic models for adaptive interactive systems

CERN Document Server

Hussein, Tim; Lukosch, Stephan; Ziegler, Jürgen; Calvary, Gaëlle

2013-01-01

Providing insights into methodologies for designing adaptive systems based on semantic data, and introducing semantic models that can be used for building interactive systems, this book showcases many of the applications made possible by the use of semantic models.Ontologies may enhance the functional coverage of an interactive system as well as its visualization and interaction capabilities in various ways. Semantic models can also contribute to bridging gaps; for example, between user models, context-aware interfaces, and model-driven UI generation. There is considerable potential for using

Some Novel Techniques in Operational Semantics

DEFF Research Database (Denmark)

Mosses, Peter David

2003-01-01

Several novel techniques for use in operational semantics are presented. They were developed in connection with a modular vatriant of the conventional Structural Operational Semantics framework, but can also be exploited when modularity is of no great concern. Gives a simple introduction to the m......Several novel techniques for use in operational semantics are presented. They were developed in connection with a modular vatriant of the conventional Structural Operational Semantics framework, but can also be exploited when modularity is of no great concern. Gives a simple introduction...

Partial solvation parameters and LSER molecular descriptors

International Nuclear Information System (INIS)

Panayiotou, Costas

2012-01-01

Graphical abstract: The one-to-one correspondence of LSER molecular descriptors and partial solvation parameters (PSPs) for propionic acid. Highlights: ► Quantum-mechanics based development of a new QSPR predictive method. ► One-to-one correspondence of partial solvation parameters and LSER molecular descriptors. ► Development of alternative routes for the determination of partial solvation parameters and solubility parameters. ► Expansion and enhancement of solubility parameter approach. - Abstract: The partial solvation parameters (PSP) have been defined recently, on the basis of the insight derived from modern quantum chemical calculations, in an effort to overcome some of the inherent restrictions of the original definition of solubility parameter and expand its range of applications. The present work continues along these lines and introduces two new solvation parameters, the van der Waals and the polarity/refractivity ones, which may replace both of the former dispersion and polar PSPs. Thus, one may use either the former scheme of PSPs (dispersion, polar, acidic, and basic) or, equivalently, the new scheme (van der Waals, polarity/refractivity, acidic, basic). The new definitions are made in a simple and straightforward manner and, thus, the strength and appeal of the widely accepted concept of solubility parameter is preserved. The inter-relations of the various PSPs are critically discussed and their values are tabulated for a variety of common substances. The advantage of the new scheme of PSPs is the bridge that makes with the corresponding Abraham’s LSER descriptors. With this bridge, one may exchange information between PSPs, LSER experimental scales, and quantum mechanics calculations such as via the COSMO-RS theory. The proposed scheme is a predictive one and it is applicable to, both, homo-solvated and hetero-solvated compounds. The new scheme is tested for the calculation of activity coefficients at infinite dilution, for octanol

Semantic HyperMultimedia Adaptation Schemes and Applications

CERN Document Server

Bieliková, Mária; Mylonas, Phivos; Tsapatsoulis, Nicolas

2013-01-01

Nowadays, more and more users are witnessing the impact of Hypermedia/Multimedia as well as the penetration of social applications in their life. Parallel to the evolution of the Internet and Web, several Hypermedia/Multimedia schemes and technologies bring semantic-based intelligent, personalized and adaptive services to the end users. More and more techniques are applied in media systems in order to be user/group-centric, adapting to different content and context features of a single or a community user. In respect to all the above, researchers need to explore and study the plethora of challenges that emergent personalisation and adaptation technologies bring to the new era. This edited volume aims to increase the awareness of researchers in this area. All contributions provide an in-depth investigation on research and deployment issues, regarding already introduced schemes and applications in Semantic Hyper/Multimedia and Social Media Adaptation. Moreover, the authors provide survey-based articles, so as p...

The neural substrates of semantic memory deficits in early Alzheimer's disease: Clues from semantic priming effects and FDG-PET

International Nuclear Information System (INIS)

Giffard, B.; Laisney, M.; Mezenge, F.; De la Sayette, V.; Eustache, F.; Desgranges, B.

2008-01-01

The neural substrates responsible for semantic dysfunction during the early stages of AD have yet to be clearly identified. After a brief overview of the literature on normal and pathological semantic memory, we describe a new approach, designed to provide fresh insights into semantic deficits in AD. We mapped the correlations between resting-state brain glucose utilisation measured by FDG-PET and semantic priming scores in a group of 17 AD patients. The priming task, which yields a particularly pure measurement of semantic memory, was composed of related pairs of words sharing an attribute relationship (e.g. tiger-stripe). The priming scores correlated positively with the metabolism of the superior temporal areas on both sides, especially the right side, and this correlation was shown to be specific to the semantic priming effect.This pattern of results is discussed in the light of recent theoretical models of semantic memory, and suggests that a dysfunction of the right superior temporal cortex may contribute to early semantic deficits, characterised by the loss of specific features of concepts in AD. (authors)

Object Tracking Using Adaptive Covariance Descriptor and Clustering-Based Model Updating for Visual Surveillance

Directory of Open Access Journals (Sweden)

Lei Qin

2014-05-01

Full Text Available We propose a novel approach for tracking an arbitrary object in video sequences for visual surveillance. The first contribution of this work is an automatic feature extraction method that is able to extract compact discriminative features from a feature pool before computing the region covariance descriptor. As the feature extraction method is adaptive to a specific object of interest, we refer to the region covariance descriptor computed using the extracted features as the adaptive covariance descriptor. The second contribution is to propose a weakly supervised method for updating the object appearance model during tracking. The method performs a mean-shift clustering procedure among the tracking result samples accumulated during a period of time and selects a group of reliable samples for updating the object appearance model. As such, the object appearance model is kept up-to-date and is prevented from contamination even in case of tracking mistakes. We conducted comparing experiments on real-world video sequences, which confirmed the effectiveness of the proposed approaches. The tracking system that integrates the adaptive covariance descriptor and the clustering-based model updating method accomplished stable object tracking on challenging video sequences.

Using probabilistic model as feature descriptor on a smartphone device for autonomous navigation of unmanned ground vehicles

Science.gov (United States)

Desai, Alok; Lee, Dah-Jye

2013-12-01

There has been significant research on the development of feature descriptors in the past few years. Most of them do not emphasize real-time applications. This paper presents the development of an affine invariant feature descriptor for low resource applications such as UAV and UGV that are equipped with an embedded system with a small microprocessor, a field programmable gate array (FPGA), or a smart phone device. UAV and UGV have proven suitable for many promising applications such as unknown environment exploration, search and rescue operations. These applications required on board image processing for obstacle detection, avoidance and navigation. All these real-time vision applications require a camera to grab images and match features using a feature descriptor. A good feature descriptor will uniquely describe a feature point thus allowing it to be correctly identified and matched with its corresponding feature point in another image. A few feature description algorithms are available for a resource limited system. They either require too much of the device's resource or too much simplification on the algorithm, which results in reduction in performance. This research is aimed at meeting the needs of these systems without sacrificing accuracy. This paper introduces a new feature descriptor called PRObabilistic model (PRO) for UGV navigation applications. It is a compact and efficient binary descriptor that is hardware-friendly and easy for implementation.

Social Semantics for an Effective Enterprise

Science.gov (United States)

Berndt, Sarah; Doane, Mike

2012-01-01

An evolution of the Semantic Web, the Social Semantic Web (s2w), facilitates knowledge sharing with "useful information based on human contributions, which gets better as more people participate." The s2w reaches beyond the search box to move us from a collection of hyperlinked facts, to meaningful, real time context. When focused through the lens of Enterprise Search, the Social Semantic Web facilitates the fluid transition of meaningful business information from the source to the user. It is the confluence of human thought and computer processing structured with the iterative application of taxonomies, folksonomies, ontologies, and metadata schemas. The importance and nuances of human interaction are often deemphasized when focusing on automatic generation of semantic markup, which results in dissatisfied users and unrealized return on investment. Users consistently qualify the value of information sets through the act of selection, making them the de facto stakeholders of the Social Semantic Web. Employers are the ultimate beneficiaries of s2w utilization with a better informed, more decisive workforce; one not achieved with an IT miracle technology, but by improved human-computer interactions. Johnson Space Center Taxonomist Sarah Berndt and Mike Doane, principal owner of Term Management, LLC discuss the planning, development, and maintenance stages for components of a semantic system while emphasizing the necessity of a Social Semantic Web for the Enterprise. Identification of risks and variables associated with layering the successful implementation of a semantic system are also modeled.

Web service composition: a semantic web and automated planning technique application

Directory of Open Access Journals (Sweden)

Jaime Alberto Guzmán Luna

2008-09-01

Full Text Available This article proposes applying semantic web and artificial intelligence planning techniques to a web services composition model dealing with problems of ambiguity in web service description and handling incomplete web information. The model uses an OWL-S services and implements a planning technique which handles open world semantics in its reasoning process to resolve these problems. This resulted in a web services composition system incorporating a module for interpreting OWL-S services and converting them into a planning problem in PDDL (a planning module handling incomplete information and an execution service module concurrently interacting with the planner for executing each composition plan service.

The contribution of executive control to semantic cognition: Convergent evidence from semantic aphasia and executive dysfunction

OpenAIRE

Thompson, Hannah E; Almaghyuli, Azizah; Noonan, Krist A.; Barak, Ohr; Lambon Ralph, Matthew; Jefferies, Elizabeth

2018-01-01

Semantic cognition, as described by the Controlled Semantic Cognition (CSC) framework (Rogers, Patterson, Jefferies, & Lambon Ralph, 2015), involves two key components: activation of coherent, generalizable concepts within a heteromodal ‘hub’ in combination with modality-specific features (spokes), and a constraining mechanism that manipulates and gates this knowledge to generate time- and task- appropriate behaviour. Executive-semantic goal representations, largely supported by executive...

Semantic Shifts Found In The Translated Version Of Rick Riordan’s Percy Jackson & The Olympians:The Titan’s Curse

OpenAIRE

A.G, Aida Caroline

2015-01-01

The thesis entitled “Semantic Shifts Found In The Translated Version Of Rick Riordan’s Percy Jackson & The Olympians: The Titan’s Curse.” This thesis explains about definition, function, process, principle, types, and shift of translation which specifically discusses about semantic (meaning) shifts that occur in the target text. The theory applied in analyzing the related data is the one proposed by Nida and Taber (1969). This theory explains about two types of semantic shift which is shift f...

Psychologizing the Semantics of Fiction

Directory of Open Access Journals (Sweden)

John Woods

2010-04-01

Full Text Available Psychologiser la sémantique de la fictionLes théoriciens sémantistes de la fiction cherchent typiquement à expliquer nos relations sémantiques au fictionnel dans le contexte plus général des théories de la référence, privilégiant une explication de la sémantique sur le psychologique. Dans cet article, nous défendons une dépendance inverse. Par l’éclaircissement de nos relations psychologiques au fictionnel, nous trouverons un guide pour savoir comment développer une sémantique de la fiction. S’ensuivra une esquisse de la sémantique.Semantic theorists of fiction typically look for an account of our semantic relations to the fictional within general-purpose theories of reference, privileging an explanation of the semantic over the psychological. In this paper, we counsel a reverse dependency. In sorting out our psychological relations to the fictional, there is useful guidance about how to proceed with the semantics of fiction. A sketch of the semantics follows.

Jigsaw Semantics

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Paul J. E. Dekker

2010-12-01

Full Text Available In the last decade the enterprise of formal semantics has been under attack from several philosophical and linguistic perspectives, and it has certainly suffered from its own scattered state, which hosts quite a variety of paradigms which may seem to be incompatible. It will not do to try and answer the arguments of the critics, because the arguments are often well-taken. The negative conclusions, however, I believe are not. The only adequate reply seems to be a constructive one, which puts several pieces of formal semantics, in particular dynamic semantics, together again. In this paper I will try and sketch an overview of tasks, techniques, and results, which serves to at least suggest that it is possible to develop a coherent overall picture of undeniably important and structural phenomena in the interpretation of natural language. The idea is that the concept of meanings as truth conditions after all provides an excellent start for an integrated study of the meaning and use of natural language, and that an extended notion of goal directed pragmatics naturally complements this picture. None of the results reported here are really new, but we think it is important to re-collect them.ReferencesAsher, Nicholas & Lascarides, Alex. 1998. ‘Questions in Dialogue’. Linguistics and Philosophy 23: 237–309.http://dx.doi.org/10.1023/A:1005364332007Borg, Emma. 2007. ‘Minimalism versus contextualism in semantics’. In Gerhard Preyer & Georg Peter (eds. ‘Context-Sensitivity and Semantic Minimalism’, pp. 339–359. Oxford: Oxford University Press.Cappelen, Herman & Lepore, Ernest. 1997. ‘On an Alleged Connection between Indirect Quotation and Semantic Theory’. Mind and Language 12: pp. 278–296.Cappelen, Herman & Lepore, Ernie. 2005. Insensitive Semantics. Oxford: Blackwell.http://dx.doi.org/10.1002/9780470755792Dekker, Paul. 2002. ‘Meaning and Use of Indefinite Expressions’. Journal of Logic, Language and Information 11: pp. 141–194

Semantic tagging of and semantic enhancements to systematics papers: ZooKeys working examples

NARCIS (Netherlands)

Penev, L.; Agosti, D.; Georgiev, T.; Catapano, T.; Miller, J.; Blagoderov, V.; Roberts, D.; Smith, V.S.; Brake, I.; Ryrcroft, S.; Scott, B.; Johnson, N.F.; Morris, R.A.; Sautter, G.; Chavan, V.; Robertson, T.; Remsen, D.; Stoev, P.; Parr, C.; Knapp, S.; Kress, W.J.; Thompson, F.C.; Erwin, T.

2010-01-01

The concept of semantic tagging and its potential for semantic enhancements to taxonomic papers is outlined and illustrated by four exemplar papers published in the present issue of ZooKeys. The four papers were created in different ways: (i) written in Microsoft Word and submitted as non-tagged

Topics in Semantics-based Program Manipulation

DEFF Research Database (Denmark)

Grobauer, Bernt

four articles in the field of semantics-based techniques for program manipulation: three articles are about partial evaluation, a method for program specialization; the fourth article treats an approach to automatic cost analysis. Partial evaluation optimizes programs by specializing them with respect...... article in this dissertation describes how the second Futamura projection can be achieved for type-directed partial evaluation (TDPE), a relatively recent approach to partial evaluation: We derive an ML implementation of the second Futamura projection for TDPE. Due to the differences between ‘traditional...... denotational semantics—allows us to relate various possible semantics to each other both conceptually and formally. We thus are able to explain goal-directed evaluation using an intuitive list-based semantics, while using a continuation semantics for semantics-based compilation through partial evaluation...

Inter-deriving Semantic Artifacts for Object-Oriented Programming

DEFF Research Database (Denmark)

Danvy, Olivier; Johannsen, Jacob

2008-01-01

We present a new abstract machine for Abadi and Cardelli's untyped calculus of objects. What is special about this semantic artifact (i.e., man-made construct) is that is mechanically corresponds to both the reduction semantics (i.e., small-step operational semantics) and the natural semantics (i...... actual substitutions, we then represent object methods as closures and in the same inter-derivational spirit, we present three new semantic artifacts: a reduction semantics for a version of Abadi and Cardelli's untyped calculus of objects with explicit substitutions, an environment-based abstract machine...

Object tracking on mobile devices using binary descriptors

Science.gov (United States)

Savakis, Andreas; Quraishi, Mohammad Faiz; Minnehan, Breton

2015-03-01

With the growing ubiquity of mobile devices, advanced applications are relying on computer vision techniques to provide novel experiences for users. Currently, few tracking approaches take into consideration the resource constraints on mobile devices. Designing efficient tracking algorithms and optimizing performance for mobile devices can result in better and more efficient tracking for applications, such as augmented reality. In this paper, we use binary descriptors, including Fast Retina Keypoint (FREAK), Oriented FAST and Rotated BRIEF (ORB), Binary Robust Independent Features (BRIEF), and Binary Robust Invariant Scalable Keypoints (BRISK) to obtain real time tracking performance on mobile devices. We consider both Google's Android and Apple's iOS operating systems to implement our tracking approach. The Android implementation is done using Android's Native Development Kit (NDK), which gives the performance benefits of using native code as well as access to legacy libraries. The iOS implementation was created using both the native Objective-C and the C++ programing languages. We also introduce simplified versions of the BRIEF and BRISK descriptors that improve processing speed without compromising tracking accuracy.

A Universal 3D Voxel Descriptor for Solid-State Material Informatics with Deep Convolutional Neural Networks.

Science.gov (United States)

Kajita, Seiji; Ohba, Nobuko; Jinnouchi, Ryosuke; Asahi, Ryoji

2017-12-05

Material informatics (MI) is a promising approach to liberate us from the time-consuming Edisonian (trial and error) process for material discoveries, driven by machine-learning algorithms. Several descriptors, which are encoded material features to feed computers, were proposed in the last few decades. Especially to solid systems, however, their insufficient representations of three dimensionality of field quantities such as electron distributions and local potentials have critically hindered broad and practical successes of the solid-state MI. We develop a simple, generic 3D voxel descriptor that compacts any field quantities, in such a suitable way to implement convolutional neural networks (CNNs). We examine the 3D voxel descriptor encoded from the electron distribution by a regression test with 680 oxides data. The present scheme outperforms other existing descriptors in the prediction of Hartree energies that are significantly relevant to the long-wavelength distribution of the valence electrons. The results indicate that this scheme can forecast any functionals of field quantities just by learning sufficient amount of data, if there is an explicit correlation between the target properties and field quantities. This 3D descriptor opens a way to import prominent CNNs-based algorithms of supervised, semi-supervised and reinforcement learnings into the solid-state MI.

The contribution of executive control to semantic cognition: Convergent evidence from semantic aphasia and executive dysfunction

OpenAIRE

Thompson, Hannah; Almaghyuli, Azizah; Noonan, Krist A.; barak, Ohr; Lambon Ralph, Matthew A.; Jefferies, Elizabeth

2018-01-01

Semantic cognition, as described by the controlled semantic cognition (CSC) framework (Rogers et al., 2015, Neuropsychologia, 76, 220), involves two key components: activation of coherent, generalizable concepts within a heteromodal ‘hub’ in combination with modality-specific features (spokes), and a constraining mechanism that manipulates and gates this knowledge to generate time- and task-appropriate behaviour. Executive–semantic goal representations, largely supported by executive regions ...

Survey of semantic modeling techniques

Energy Technology Data Exchange (ETDEWEB)

Smith, C.L.

1975-07-01

The analysis of the semantics of programing languages was attempted with numerous modeling techniques. By providing a brief survey of these techniques together with an analysis of their applicability for answering semantic issues, this report attempts to illuminate the state-of-the-art in this area. The intent is to be illustrative rather than thorough in the coverage of semantic models. A bibliography is included for the reader who is interested in pursuing this area of research in more detail.

Semantic multimedia analysis and processing

CERN Document Server

Spyrou, Evaggelos; Mylonas, Phivos

2014-01-01

Broad in scope, Semantic Multimedia Analysis and Processing provides a complete reference of techniques, algorithms, and solutions for the design and the implementation of contemporary multimedia systems. Offering a balanced, global look at the latest advances in semantic indexing, retrieval, analysis, and processing of multimedia, the book features the contributions of renowned researchers from around the world. Its contents are based on four fundamental thematic pillars: 1) information and content retrieval, 2) semantic knowledge exploitation paradigms, 3) multimedia personalization, and 4)

Neural correlates underlying musical semantic memory.

Science.gov (United States)

Groussard, M; Viader, F; Landeau, B; Desgranges, B; Eustache, F; Platel, H

2009-07-01

Numerous functional imaging studies have examined the neural basis of semantic memory mainly using verbal and visuospatial materials. Musical material also allows an original way to explore semantic memory processes. We used PET imaging to determine the neural substrates that underlie musical semantic memory using different tasks and stimuli. The results of three PET studies revealed a greater involvement of the anterior part of the temporal lobe. Concerning clinical observations and our neuroimaging data, the musical lexicon (and most widely musical semantic memory) appears to be sustained by a temporo-prefrontal cerebral network involving right and left cerebral regions.

Flexible recruitment of semantic richness: Context modulates body-object interaction effects in lexical-semantic processing

Directory of Open Access Journals (Sweden)

Cody eTousignant

2012-03-01

Full Text Available Body-object interaction (BOI is a semantic richness variable that measures the perceived ease with which the human body can physically interact with a word’s referent. Lexical and semantic processing is facilitated when words are associated with relatively more bodily experience (high BOI words, e.g., belt. To date, BOI effects have been examined in only one semantic decision context (is it imageable?. It has been argued that semantic processing is dynamic and can be modulated by context. We examined these influences by testing how task knowledge modulated BOI effects. We presented the same stimuli (high- and low-BOI entity words and a set of action words in each of four action/entity semantic categorization tasks (SCTs. Task framing was manipulated: participants were told about one (actions or entities or both (actions and entities categories of words in the decision task. Facilitatory BOI effects were observed when participants knew that ‘entity’ was part of the decision category, regardless of whether the high- and low-BOI entity words appeared on the affirmative or negative side of the decision. That BOI information was only useful when participants had expectations that object words would be presented suggests a strong role for the decision context in lexical-semantic processing, and supports a dynamic view of conceptual knowledge.

Scandinavian Semantics and the Human Body

DEFF Research Database (Denmark)

Levisen, Carsten

2015-01-01

, it is demonstrated that Scandinavian and English systems differ significantly in some aspects of the way in which the construe the human body with words. The study ventures an innovative combination of methods, pairing the Natural Semantic Metalanguage (NSM) approach to linguistic and conceptual analysis......This paper presents an ethnolinguistic analysis of how the space between the head and the body is construed in Scandinavian semantic systems vis-a-vis the semantic system of English. With an extensive case study of neck-related meanings in Danish, and with cross-Scandinavian reference...... with empirical evidence from the Evolution of Semantic Systems (EoSS) project. This combination of empirical and interpretative tools helps to integrate evidence from semantics and semiotics, pinning out in great detail the intricacies of the meanings of particular body words. The paper concludes that body words...

Visualizing the semantic structure in classical music works.

Science.gov (United States)

Chan, Wing-Yi; Qu, Huamin; Mak, Wai-Ho

2010-01-01

A major obstacle in the appreciation of classical music is that extensive training is required to understand musical structure and compositional techniques toward comprehending the thoughts behind the musical work. In this paper, we propose an innovative visualization solution to reveal the semantic structure in classical orchestral works such that users can gain insights into musical structure and appreciate the beauty of music. We formulate the semantic structure into macrolevel layer interactions, microlevel theme variations, and macro-micro relationships between themes and layers to abstract the complicated construction of a musical composition. The visualization has been applied with success in understanding some classical music works as supported by highly promising user study results with the general audience and very positive feedback from music students and experts, demonstrating its effectiveness in conveying the sophistication and beauty of classical music to novice users with informative and intuitive displays.

Inter-deriving Semantic Artifacts for Object-Oriented Programming

DEFF Research Database (Denmark)

Danvy, Olivier; Johannsen, Jacob

2010-01-01

We present a new abstract machine for Abadi and Cardelli's untyped non-imperative calculus of objects.  This abstract machine mechanically corresponds to both the reduction semantics (i.e., small-step operational semantics) and the natural semantics (i.e., big-step operational semantics) specified...

CASL - The CoFI Algebraic Specification Language - Semantics

DEFF Research Database (Denmark)

Haxthausen, Anne

1999-01-01

This is version 1.0 of the CASL Language Summary, annotated by the CoFI Semantics Task Group with the semantics of constructs. This is the second complete but possibly imperfect version of the semantics. It was compiled prior to the CoFI workshop in Amsterdam in March 1999.......This is version 1.0 of the CASL Language Summary, annotated by the CoFI Semantics Task Group with the semantics of constructs. This is the second complete but possibly imperfect version of the semantics. It was compiled prior to the CoFI workshop in Amsterdam in March 1999....

Structure-Activity Relationships on the Molecular Descriptors Family Project at the End

Directory of Open Access Journals (Sweden)

Lorentz JÄNTSCHI

2007-12-01

Full Text Available Molecular Descriptors Family (MDF on the Structure-Activity Relationships (SAR, a promising approach in investigation and quantification of the link between 2D and 3D structural information and the activity, and its potential in the analysis of the biological active compounds is summarized. The approach, attempts to correlate molecular descriptors family generated and calculated on a set of biological active compounds with their observed activity. The estimation as well as prediction abilities of the approach are presented. The obtained MDF SAR models can be used to predict the biological activity of unknown substrates in a series of compounds.

Using semantic analysis to improve speech recognition performance

OpenAIRE

Erdoğan, Hakan; Erdogan, Hakan; Sarıkaya, Ruhi; Sarikaya, Ruhi; Chen, Stanley F.; Gao, Yuqing; Picheny, Michael

2005-01-01

Although syntactic structure has been used in recent work in language modeling, there has not been much effort in using semantic analysis for language models. In this study, we propose three new language modeling techniques that use semantic analysis for spoken dialog systems. We call these methods concept sequence modeling, two-level semantic-lexical modeling, and joint semantic-lexical modeling. These models combine lexical information with varying amounts of semantic information, using ann...

Co-clustering for Weblogs in Semantic Space

DEFF Research Database (Denmark)

Zong, Yu; Xu, Guandong; Dolog, Peter

2010-01-01

Web clustering is an approach for aggregating web objects into various groups according to underlying relationships among them. Finding co-clusters of web objects in semantic space is an interesting topic in the context of web usage mining, which is able to capture the underlying user navigational...... interest and content preference simultaneously. In this paper we will present a novel web co-clustering algorithm named Co-Clustering in Semantic space (COCS) to simultaneously partition web users and pages via a latent semantic analysis approach. In COCS, we first, train the latent semantic space...... of weblog data by using Probabilistic Latent Semantic Analysis (PLSA) model, and then, project all weblog data objects into this semantic space with probability distribution to capture the relationship among web pages and web users, at last, propose a clustering algorithm to generate the co...

Discovery and Selection of Semantic Web Services

CERN Document Server

Wang, Xia

2013-01-01

For advanced web search engines to be able not only to search for semantically related information dispersed over different web pages, but also for semantic services providing certain functionalities, discovering semantic services is the key issue. Addressing four problems of current solution, this book presents the following contributions. A novel service model independent of semantic service description models is proposed, which clearly defines all elements necessary for service discovery and selection. It takes service selection as its gist and improves efficiency. Corresponding selection algorithms and their implementation as components of the extended Semantically Enabled Service-oriented Architecture in the Web Service Modeling Environment are detailed. Many applications of semantic web services, e.g. discovery, composition and mediation, can benefit from a general approach for building application ontologies. With application ontologies thus built, services are discovered in the same way as with single...

Action representation: crosstalk between semantics and pragmatics.

Science.gov (United States)

Prinz, Wolfgang

2014-03-01

Marc Jeannerod pioneered a representational approach to movement and action. In his approach, motor representations provide both, declarative knowledge about action and procedural knowledge for action (action semantics and action pragmatics, respectively). Recent evidence from language comprehension and action simulation supports the claim that action pragmatics and action semantics draw on common representational resources, thus challenging the traditional divide between declarative and procedural action knowledge. To account for these observations, three kinds of theoretical frameworks are discussed: (i) semantics is grounded in pragmatics, (ii) pragmatics is anchored in semantics, and (iii) pragmatics is part and parcel of semantics. © 2013 Elsevier Ltd. All rights reserved.

Semantic policy and adversarial modeling for cyber threat identification and avoidance

Science.gov (United States)

DeFrancesco, Anton; McQueary, Bruce

2009-05-01

Today's enterprise networks undergo a relentless barrage of attacks from foreign and domestic adversaries. These attacks may be perpetrated with little to no funding, but may wreck incalculable damage upon the enterprises security, network infrastructure, and services. As more services come online, systems that were once in isolation now provide information that may be combined dynamically with information from other systems to create new meaning on the fly. Security issues are compounded by the potential to aggregate individual pieces of information and infer knowledge at a higher classification than any of its constituent parts. To help alleviate these challenges, in this paper we introduce the notion of semantic policy and discuss how it's use is evolving from a robust approach to access control to preempting and combating attacks in the cyber domain, The introduction of semantic policy and adversarial modeling to network security aims to ask 'where is the network most vulnerable', 'how is the network being attacked', and 'why is the network being attacked'. The first aspect of our approach is integration of semantic policy into enterprise security to augment traditional network security with an overall awareness of policy access and violations. This awareness allows the semantic policy to look at the big picture - analyzing trends and identifying critical relations in system wide data access. The second aspect of our approach is to couple adversarial modeling with semantic policy to move beyond reactive security measures and into a proactive identification of system weaknesses and areas of vulnerability. By utilizing Bayesian-based methodologies, the enterprise wide meaning of data and semantic policy is applied to probability and high-level risk identification. This risk identification will help mitigate potential harm to enterprise networks by enabling resources to proactively isolate, lock-down, and secure systems that are most vulnerable.

The use of reproductive vigor descriptors in studying genetic ...

African Journals Online (AJOL)

The use of reproductive vigor descriptors in studying genetic variability in nine Tunisian faba bean ( Vicia faba L.) populations. ... The dendrogram based on Nei's genetic distance of the 9 populations using UPGMA method, show some genetic drift between populations. Key words: Faba bean, agromorphological traits, ...

Feedback nash equilibria for linear quadratic descriptor differential games

NARCIS (Netherlands)

Engwerda, J.C.; Salmah, S.

2012-01-01

In this paper, we consider the non-cooperative linear feedback Nash quadratic differential game with an infinite planning horizon for descriptor systems of index one. The performance function is assumed to be indefinite. We derive both necessary and sufficient conditions under which this game has a

Feedback Nash Equilibria for Linear Quadratic Descriptor Differential Games

NARCIS (Netherlands)

Engwerda, J.C.; Salmah, Y.

2010-01-01

In this note we consider the non-cooperative linear feedback Nash quadratic differential game with an infinite planning horizon for descriptor systems of index one. The performance function is assumed to be indefinite. We derive both necessary and sufficient conditions under which this game has a

Challenges as enablers for high quality Linked Data: insights from the Semantic Publishing Challenge

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Anastasia Dimou

2017-01-01

Full Text Available While most challenges organized so far in the Semantic Web domain are focused on comparing tools with respect to different criteria such as their features and competencies, or exploiting semantically enriched data, the Semantic Web Evaluation Challenges series, co-located with the ESWC Semantic Web Conference, aims to compare them based on their output, namely the produced dataset. The Semantic Publishing Challenge is one of these challenges. Its goal is to involve participants in extracting data from heterogeneous sources on scholarly publications, and producing Linked Data that can be exploited by the community itself. This paper reviews lessons learned from both (i the overall organization of the Semantic Publishing Challenge, regarding the definition of the tasks, building the input dataset and forming the evaluation, and (ii the results produced by the participants, regarding the proposed approaches, the used tools, the preferred vocabularies and the results produced in the three editions of 2014, 2015 and 2016. We compared these lessons to other Semantic Web Evaluation Challenges. In this paper, we (i distill best practices for organizing such challenges that could be applied to similar events, and (ii report observations on Linked Data publishing derived from the submitted solutions. We conclude that higher quality may be achieved when Linked Data is produced as a result of a challenge, because the competition becomes an incentive, while solutions become better with respect to Linked Data publishing best practices when they are evaluated against the rules of the  challenge.

A Semantic Analysis Method for Scientific and Engineering Code

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Stewart, Mark E. M.

1998-01-01

This paper develops a procedure to statically analyze aspects of the meaning or semantics of scientific and engineering code. The analysis involves adding semantic declarations to a user's code and parsing this semantic knowledge with the original code using multiple expert parsers. These semantic parsers are designed to recognize formulae in different disciplines including physical and mathematical formulae and geometrical position in a numerical scheme. In practice, a user would submit code with semantic declarations of primitive variables to the analysis procedure, and its semantic parsers would automatically recognize and document some static, semantic concepts and locate some program semantic errors. A prototype implementation of this analysis procedure is demonstrated. Further, the relationship between the fundamental algebraic manipulations of equations and the parsing of expressions is explained. This ability to locate some semantic errors and document semantic concepts in scientific and engineering code should reduce the time, risk, and effort of developing and using these codes.

The Semantics of Plurals: A Defense of Singularism

Science.gov (United States)

Florio, Salvatore

2010-01-01

In this dissertation, I defend "semantic singularism", which is the view that syntactically plural terms, such as "they" or "Russell and Whitehead", are semantically singular. A semantically singular term is a term that denotes a single entity. Semantic singularism is to be distinguished from "syntactic singularism", according to which…

SOCIAL METRICS APPLIED TO SMART TOURISM

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O. Cervantes

2016-09-01

Full Text Available We present a strategy to make productive use of semantically-related social data, from a user-centered semantic network, in order to help users (tourists and citizens in general to discover cultural heritage, points of interest and available services in a smart city. This data can be used to personalize recommendations in a smart tourism application. Our approach is based on flow centrality metrics typically used in social network analysis: flow betweenness, flow closeness and eccentricity. These metrics are useful to discover relevant nodes within the network yielding nodes that can be interpreted as suggestions (venues or services to users. We describe the semantic network built on graph model, as well as social metrics algorithms used to produce recommendations. We also present challenges and results from a prototypical implementation applied to the case study of the City of Puebla, Mexico.

Social Metrics Applied to Smart Tourism

Science.gov (United States)

Cervantes, O.; Gutiérrez, E.; Gutiérrez, F.; Sánchez, J. A.

2016-09-01

We present a strategy to make productive use of semantically-related social data, from a user-centered semantic network, in order to help users (tourists and citizens in general) to discover cultural heritage, points of interest and available services in a smart city. This data can be used to personalize recommendations in a smart tourism application. Our approach is based on flow centrality metrics typically used in social network analysis: flow betweenness, flow closeness and eccentricity. These metrics are useful to discover relevant nodes within the network yielding nodes that can be interpreted as suggestions (venues or services) to users. We describe the semantic network built on graph model, as well as social metrics algorithms used to produce recommendations. We also present challenges and results from a prototypical implementation applied to the case study of the City of Puebla, Mexico.

Improved Prediction of Blood-Brain Barrier Permeability Through Machine Learning with Combined Use of Molecular Property-Based Descriptors and Fingerprints.

Science.gov (United States)

Yuan, Yaxia; Zheng, Fang; Zhan, Chang-Guo

2018-03-21

Blood-brain barrier (BBB) permeability of a compound determines whether the compound can effectively enter the brain. It is an essential property which must be accounted for in drug discovery with a target in the brain. Several computational methods have been used to predict the BBB permeability. In particular, support vector machine (SVM), which is a kernel-based machine learning method, has been used popularly in this field. For SVM training and prediction, the compounds are characterized by molecular descriptors. Some SVM models were based on the use of molecular property-based descriptors (including 1D, 2D, and 3D descriptors) or fragment-based descriptors (known as the fingerprints of a molecule). The selection of descriptors is critical for the performance of a SVM model. In this study, we aimed to develop a generally applicable new SVM model by combining all of the features of the molecular property-based descriptors and fingerprints to improve the accuracy for the BBB permeability prediction. The results indicate that our SVM model has improved accuracy compared to the currently available models of the BBB permeability prediction.

Multi Voxel Descriptor for 3D Texture Retrieval

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Hero Yudo Martono

2016-08-01

Full Text Available In this paper, we present a new feature descriptors  which exploit voxels for 3D textured retrieval system when models vary either by geometric shape or texture or both. First, we perform pose normalisation to modify arbitrary 3D models  in order to have same orientation. We then map the structure of 3D models into voxels. This purposes to make all the 3D models have the same dimensions. Through this voxels, we can capture information from a number of ways.  First, we build biner voxel histogram and color voxel histogram.  Second, we compute distance from centre voxel into other voxels and generate histogram. Then we also compute fourier transform in spectral space.  For capturing texture feature, we apply voxel tetra pattern. Finally, we merge all features by linear combination. For experiment, we use standard evaluation measures such as Nearest Neighbor (NN, First Tier (FT, Second Tier (ST, Average Dynamic Recall (ADR. Dataset in SHREC 2014  and its evaluation program is used to verify the proposed method. Experiment result show that the proposed method  is more accurate when compared with some methods of state-of-the-art.

Towards a Reactive Semantic Execution Environment

Science.gov (United States)

Komazec, Srdjan; Facca, Federico Michele

Managing complex and distributed software systems built on top of the service-oriented paradigm has never been more challenging. While Semantic Web Service technologies offer a promising set of languages and tools as a foundation to resolve the heterogeneity and scalability issues, they are still failing to provide an autonomic execution environment. In this paper we present an approach based on Semantic Web Services to enable the monitoring and self-management of a Semantic Execution Environment (SEE), a brokerage system for Semantic Web Services. Our approach is founded on the event-triggered reactivity paradigm in order to facilitate environment control, thus contributing to its autonomicity, robustness and flexibility.

Semantic Observation Integration

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Werner Kuhn

2012-09-01

Full Text Available Although the integration of sensor-based information into analysis and decision making has been a research topic for many years, semantic interoperability has not yet been reached. The advent of user-generated content for the geospatial domain, Volunteered Geographic Information (VGI, makes it even more difficult to establish semantic integration. This paper proposes a novel approach to integrating conventional sensor information and VGI, which is exploited in the context of detecting forest fires. In contrast to common logic-based semantic descriptions, we present a formal system using algebraic specifications to unambiguously describe the processing steps from natural phenomena to value-added information. A generic ontology of observations is extended and profiled for forest fire detection in order to illustrate how the sensing process, and transformations between heterogeneous sensing systems, can be represented as mathematical functions and grouped into abstract data types. We discuss the required ontological commitments and a possible generalization.

Insensitive Enough Semantics

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Richard Vallée

2006-06-01

Full Text Available According to some philosophers, sentences like (1 “It is raining” and (2 “John is ready” are context sensitive sentences even if they do not contain indexicals or demonstratives. That view initiated a context sensitivity frenzy. Cappelen and Lepore (2005 summarize the frenzy by the slogan “Every sentence is context sensitive” (Insensitive Semantics, p. 6, note 5. They suggest a view they call Minimalism according to which the truth conditions of utterances of sentences like (1/(2 are exactly what Convention T gives you. I will distinguish different propositions, and refocus semantics on sentences. As distinct from what the protagonists in the ongoing debate think, I argue that the content or truth conditions of utterances of both context sensitive sentences and sentences like (1/(2 are not interesting from a semantic point of view, and that the problem sentences like (1/(2 raises is not about context sensitivity or context insensitivity of sentences, but relevance of the content of utterances.

The influence of rTMS over prefrontal and motor areas in a morphological task: grammatical vs. semantic effects.

Science.gov (United States)

Gerfo, Emanuele Lo; Oliveri, Massimiliano; Torriero, Sara; Salerno, Silvia; Koch, Giacomo; Caltagirone, Carlo

2008-01-31

We investigated the differential role of two frontal regions in the processing of grammatical and semantic knowledge. Given the documented specificity of the prefrontal cortex for the grammatical class of verbs, and of the primary motor cortex for the semantic class of action words, we sought to investigate whether the prefrontal cortex is also sensitive to semantic effects, and whether the motor cortex is also sensitive to grammatical class effects. We used repetitive transcranial magnetic stimulation (rTMS) to suppress the excitability of a portion of left prefontal cortex (first experiment) and of the motor area (second experiment). In the first experiment we found that rTMS applied to the left prefrontal cortex delays the processing of action verbs' retrieval, but is not critical for retrieval of state verbs and state nouns. In the second experiment we found that rTMS applied to the left motor cortex delays the processing of action words, both name and verbs, while it is not critical for the processing of state words. These results support the notion that left prefrontal and motor cortex are involved in the process of action word retrieval. Left prefrontal cortex subserves processing of both grammatical and semantic information, whereas motor cortex contributes to the processing of semantic representation of action words without any involvement in the representation of grammatical categories.

Obscure phenomena in statistical analysis of quantitative structure-activity relationships. Part 1: Multicollinearity of physicochemical descriptors.

Science.gov (United States)

Mager, P P; Rothe, H

1990-10-01

Multicollinearity of physicochemical descriptors leads to serious consequences in quantitative structure-activity relationship (QSAR) analysis, such as incorrect estimators and test statistics of regression coefficients of the ordinary least-squares (OLS) model applied usually to QSARs. Beside the diagnosis of the known simple collinearity, principal component regression analysis (PCRA) also allows the diagnosis of various types of multicollinearity. Only if the absolute values of PCRA estimators are order statistics that decrease monotonically, the effects of multicollinearity can be circumvented. Otherwise, obscure phenomena may be observed, such as good data recognition but low predictive model power of a QSAR model.

Towards measuring the semantic capacity of a physical medium demonstrated with elementary cellular automata.

Science.gov (United States)

Dittrich, Peter

2018-02-01

The organic code concept and its operationalization by molecular codes have been introduced to study the semiotic nature of living systems. This contribution develops further the idea that the semantic capacity of a physical medium can be measured by assessing its ability to implement a code as a contingent mapping. For demonstration and evaluation, the approach is applied to a formal medium: elementary cellular automata (ECA). The semantic capacity is measured by counting the number of ways codes can be implemented. Additionally, a link to information theory is established by taking multivariate mutual information for quantifying contingency. It is shown how ECAs differ in their semantic capacities, how this is related to various ECA classifications, and how this depends on how a meaning is defined. Interestingly, if the meaning should persist for a certain while, the highest semantic capacity is found in CAs with apparently simple behavior, i.e., the fixed-point and two-cycle class. Synergy as a predictor for a CA's ability to implement codes can only be used if context implementing codes are common. For large context spaces with sparse coding contexts synergy is a weak predictor. Concluding, the approach presented here can distinguish CA-like systems with respect to their ability to implement contingent mappings. Applying this to physical systems appears straight forward and might lead to a novel physical property indicating how suitable a physical medium is to implement a semiotic system. Copyright © 2017 Elsevier B.V. All rights reserved.

The Problem of Naturalizing Semantics.

Science.gov (United States)

Sullivan, Arthur

2000-01-01

Investigates conceptual barriers prevalent in the works of both proponents and opponents of semantic naturalism. Searches for a tenable definition of naturalism according to which one can be a realist, a non-reductionist, and a naturalist about semantic content. (Author/VWL)

Compiling Dictionaries Using Semantic Domains*

Directory of Open Access Journals (Sweden)

Ronald Moe

2011-10-01

Full Text Available

Abstract: The task of providing dictionaries for all the world's languages is prodigious, re-quiring efficient techniques. The text corpus method cannot be used for minority languages lacking texts. To meet the need, the author has constructed a list of 1 600 semantic domains, which he has successfully used to collect words. In a workshop setting, a group of speakers can collect as many as 17 000 words in ten days. This method results in a classified word list that can be efficiently expanded into a full dictionary. The method works because the mental lexicon is a giant web or-ganized around key concepts. A semantic domain can be defined as an important concept together with the words directly related to it by lexical relations. A person can utilize the mental web to quickly jump from word to word within a domain. The author is developing a template for each domain to aid in collecting words and in de-scribing their semantics. Investigating semantics within the context of a domain yields many in-sights. The method permits the production of both alphabetically and semantically organized dic-tionaries. The list of domains is intended to be universal in scope and applicability. Perhaps due to universals of human experience and universals of linguistic competence, there are striking simi-larities in various lists of semantic domains developed for languages around the world. Using a standardized list of domains to classify multiple dictionaries opens up possibilities for cross-lin-guistic research into semantic and lexical universals.

Keywords: SEMANTIC DOMAINS, SEMANTIC FIELDS, SEMANTIC CATEGORIES, LEX-ICAL RELATIONS, SEMANTIC PRIMITIVES, DOMAIN TEMPLATES, MENTAL LEXICON, SEMANTIC UNIVERSALS, MINORITY LANGUAGES, LEXICOGRAPHY

Opsomming: Samestelling van woordeboeke deur gebruikmaking van se-mantiese domeine. Die taak van die voorsiening van woordeboeke aan al die tale van die wêreld is geweldig en vereis doeltreffende tegnieke. Die

Linking Disparate Datasets of the Earth Sciences with the SemantEco Annotator

Science.gov (United States)

Seyed, P.; Chastain, K.; McGuinness, D. L.

2013-12-01

Use of Semantic Web technologies for data management in the Earth sciences (and beyond) has great potential but is still in its early stages, since the challenges of translating data into a more explicit or semantic form for immediate use within applications has not been fully addressed. In this abstract we help address this challenge by introducing the SemantEco Annotator, which enables anyone, regardless of expertise, to semantically annotate tabular Earth Science data and translate it into linked data format, while applying the logic inherent in community-standard vocabularies to guide the process. The Annotator was conceived under a desire to unify dataset content from a variety of sources under common vocabularies, for use in semantically-enabled web applications. Our current use case employs linked data generated by the Annotator for use in the SemantEco environment, which utilizes semantics to help users explore, search, and visualize water or air quality measurement and species occurrence data through a map-based interface. The generated data can also be used immediately to facilitate discovery and search capabilities within 'big data' environments. The Annotator provides a method for taking information about a dataset, that may only be known to its maintainers, and making it explicit, in a uniform and machine-readable fashion, such that a person or information system can more easily interpret the underlying structure and meaning. Its primary mechanism is to enable a user to formally describe how columns of a tabular dataset relate and/or describe entities. For example, if a user identifies columns for latitude and longitude coordinates, we can infer the data refers to a point that can be plotted on a map. Further, it can be made explicit that measurements of 'nitrate' and 'NO3-' are of the same entity through vocabulary assignments, thus more easily utilizing data sets that use different nomenclatures. The Annotator provides an extensive and searchable

Semantic Business Process Modeling

OpenAIRE

Markovic, Ivan

2010-01-01

This book presents a process-oriented business modeling framework based on semantic technologies. The framework consists of modeling languages, methods, and tools that allow for semantic modeling of business motivation, business policies and rules, and business processes. Quality of the proposed modeling framework is evaluated based on the modeling content of SAP Solution Composer and several real-world business scenarios.

Discrete-Time Sliding-Mode Control of Uncertain Systems with Time-Varying Delays via Descriptor Approach

Directory of Open Access Journals (Sweden)

Maode Yan

2008-01-01

Full Text Available This paper considers the problem of robust discrete-time sliding-mode control (DT-SMC design for a class of uncertain linear systems with time-varying delays. By applying a descriptor model transformation and Moon's inequality for bounding cross terms, a delay-dependent sufficient condition for the existence of stable sliding surface is given in terms of linear matrix inequalities (LMIs. Based on this existence condition, the synthesized sliding mode controller can guarantee the sliding-mode reaching condition of the specified discrete-time sliding surface for all admissible uncertainties and time-varying delays. An illustrative example verifies the effectiveness of the proposed method.

MBR-SIFT: A mirror reflected invariant feature descriptor using a binary representation for image matching.

Directory of Open Access Journals (Sweden)

Mingzhe Su

Full Text Available The traditional scale invariant feature transform (SIFT method can extract distinctive features for image matching. However, it is extremely time-consuming in SIFT matching because of the use of the Euclidean distance measure. Recently, many binary SIFT (BSIFT methods have been developed to improve matching efficiency; however, none of them is invariant to mirror reflection. To address these problems, in this paper, we present a horizontal or vertical mirror reflection invariant binary descriptor named MBR-SIFT, in addition to a novel image matching approach. First, 16 cells in the local region around the SIFT keypoint are reorganized, and then the 128-dimensional vector of the SIFT descriptor is transformed into a reconstructed vector according to eight directions. Finally, the MBR-SIFT descriptor is obtained after binarization and reverse coding. To improve the matching speed and accuracy, a fast matching algorithm that includes a coarse-to-fine two-step matching strategy in addition to two similarity measures for the MBR-SIFT descriptor are proposed. Experimental results on the UKBench dataset show that the proposed method not only solves the problem of mirror reflection, but also ensures desirable matching accuracy and speed.

MBR-SIFT: A mirror reflected invariant feature descriptor using a binary representation for image matching.

Science.gov (United States)

Su, Mingzhe; Ma, Yan; Zhang, Xiangfen; Wang, Yan; Zhang, Yuping

2017-01-01

The traditional scale invariant feature transform (SIFT) method can extract distinctive features for image matching. However, it is extremely time-consuming in SIFT matching because of the use of the Euclidean distance measure. Recently, many binary SIFT (BSIFT) methods have been developed to improve matching efficiency; however, none of them is invariant to mirror reflection. To address these problems, in this paper, we present a horizontal or vertical mirror reflection invariant binary descriptor named MBR-SIFT, in addition to a novel image matching approach. First, 16 cells in the local region around the SIFT keypoint are reorganized, and then the 128-dimensional vector of the SIFT descriptor is transformed into a reconstructed vector according to eight directions. Finally, the MBR-SIFT descriptor is obtained after binarization and reverse coding. To improve the matching speed and accuracy, a fast matching algorithm that includes a coarse-to-fine two-step matching strategy in addition to two similarity measures for the MBR-SIFT descriptor are proposed. Experimental results on the UKBench dataset show that the proposed method not only solves the problem of mirror reflection, but also ensures desirable matching accuracy and speed.

Semantic annotation in biomedicine: the current landscape.

Science.gov (United States)

Jovanović, Jelena; Bagheri, Ebrahim

2017-09-22

The abundance and unstructured nature of biomedical texts, be it clinical or research content, impose significant challenges for the effective and efficient use of information and knowledge stored in such texts. Annotation of biomedical documents with machine intelligible semantics facilitates advanced, semantics-based text management, curation, indexing, and search. This paper focuses on annotation of biomedical entity mentions with concepts from relevant biomedical knowledge bases such as UMLS. As a result, the meaning of those mentions is unambiguously and explicitly defined, and thus made readily available for automated processing. This process is widely known as semantic annotation, and the tools that perform it are known as semantic annotators.Over the last dozen years, the biomedical research community has invested significant efforts in the development of biomedical semantic annotation technology. Aiming to establish grounds for further developments in this area, we review a selected set of state of the art biomedical semantic annotators, focusing particularly on general purpose annotators, that is, semantic annotation tools that can be customized to work with texts from any area of biomedicine. We also examine potential directions for further improvements of today's annotators which could make them even more capable of meeting the needs of real-world applications. To motivate and encourage further developments in this area, along the suggested and/or related directions, we review existing and potential practical applications and benefits of semantic annotators.

Determination of descriptors for polycyclic aromatic hydrocarbons and related compounds by chromatographic methods and liquid-liquid partition in totally organic biphasic systems.

Science.gov (United States)

Ariyasena, Thiloka C; Poole, Colin F

2014-09-26

Retention factors on several columns and at various temperatures using gas chromatography and from reversed-phase liquid chromatography on a SunFire C18 column with various mobile phase compositions containing acetonitrile, methanol and tetrahydrofuran as strength adjusting solvents are combined with liquid-liquid partition coefficients in totally organic biphasic systems to calculate descriptors for 23 polycyclic aromatic hydrocarbons and eighteen related compounds of environmental interest. The use of a consistent protocol for the above measurements provides descriptors that are more self consistent for the estimation of physicochemical properties (octanol-water, air-octanol, air-water, aqueous solubility, and subcooled liquid vapor pressure). The descriptor in this report tend to have smaller values for the L and E descriptors and random differences in the B and S descriptors compared with literature sources. A simple atom fragment constant model is proposed for the estimation of descriptors from structure for polycyclic aromatic hydrocarbons. The new descriptors show no bias in the prediction of the air-water partition coefficient for polycyclic aromatic hydrocarbons unlike the literature values. Copyright © 2014 Elsevier B.V. All rights reserved.

The paca that roared: Immediate cumulative semantic interference among newly acquired words.

Science.gov (United States)

Oppenheim, Gary M

2018-08-01

With 40,000 words in the average vocabulary, how can speakers find the specific words that they want so quickly and easily? Cumulative semantic interference in language production provides a clue: when naming a large series of pictures, with a few mammals sprinkled about, naming each subsequent mammal becomes slower and more error-prone. Such interference mirrors predictions from an incremental learning algorithm applied to meaning-driven retrieval from an established vocabulary, suggesting retrieval benefits from a constant, implicit, re-optimization process (Oppenheim et al., 2010). But how quickly would a new mammal (e.g. paca) engage in this re-optimization? In this experiment, 18 participants studied 3 novel and 3 familiar exemplars from each of six semantic categories, and immediately performed a timed picture-naming task. Consistent with the learning model's predictions, naming latencies revealed immediate cumulative semantic interference in all directions: from new words to new words, from new words to old words, from old words to new words, and from old words to old words. Repeating the procedure several days later produced similar-magnitude effects, demonstrating that newly acquired words can be immediately semantically integrated, at least to the extent necessary to produce typical cumulative semantic interference. These findings extend the Dark Side model's scope to include novel word production, and are considered in terms of mechanisms for lexical selection. Copyright © 2018 Elsevier B.V. All rights reserved.

Towards a formal semantics for Ada 9X

Science.gov (United States)

Guaspari, David; Mchugh, John; Wolfgang, Polak; Saaltink, Mark

1995-01-01

The Ada 9X language precision team was formed during the revisions of Ada 83, with the goal of analyzing the proposed design, identifying problems, and suggesting improvements, through the use of mathematical models. This report defines a framework for formally describing Ada 9X, based on Kahn's 'natural semantics', and applies the framework to portions of the language. The proposals for exceptions and optimization freedoms are also analyzed, using a different technique.