Direct Representation Research Articles

Direct product-type grid representations for angular coordinates in extended space and their application in the MCTDH approach.

Multi-configurational time-dependent Hartree (MCTDH) calculations using time-dependent grid representations can be used to accurately simulate high-dimensional quantum dynamics on general ab initio potential energy surfaces. Employing the correlation discrete variable representation, sets of direct product type grids are employed in the calculation of the required potential energy matrix elements. This direct product structure can be a problem if the coordinate system includes polar and azimuthal angles that result in singularities in the kinetic energy operator. In the present work, a new direct product-type discrete variable representation (DVR) for arbitrary sets of polar and azimuthal angles is introduced. It employs an extended coordinate space where the range of the polar angles is taken to be [-π, π]. The resulting extended space DVR resolves problems caused by the singularities in the kinetic energy operator without generating a very large spectral width. MCTDH calculations studying the F·CH4 complex are used to investigate important properties of the new scheme. The scheme is found to allow for more efficient integration of the equations of motion compared to the previously employed cot-DVR approach [G. Schiffel and U. Manthe, Chem. Phys. 374, 118 (2010)] and decreases the required central processing unit times by about an order of magnitude.

Signal representations via SIP p-frames and SIP Bessel multipliers in separable Banach spaces

Digital signals are often modeled as functions in Banach spaces, such as the ubiquitous [Formula: see text] spaces. The frame theory in Banach spaces induces flexible representations of signals due to the robustness and redundancy of frames. Nevertheless, the lack of inner product in general Banach spaces limits the direct representations of signals in Banach spaces under a given basis or frame. In this paper, we introduce the concept of semi-inner product (SIP) [Formula: see text]-Bessel multipliers to extend the flexibility of signal representations in separable Banach spaces, where [Formula: see text]. These multipliers are defined as composition of analysis operator of an SIP-I Bessel sequence, a multiplication with a fixed sequence and synthesis operator of an SIP-II Bessel sequence. The basic properties of the SIP [Formula: see text]-Bessel multipliers are investigated. Moreover, as special cases, characterizations of [Formula: see text]-Riesz bases related to signal representations are given, and the multipliers for [Formula: see text]-Riesz bases are discussed. We show that SIP [Formula: see text]-Bessel multipliers for [Formula: see text]-Riesz bases are invertible. Finally, the continuity of SIP [Formula: see text]-Bessel multipliers with respect to their parameters is investigated. The results theoretically show that the SIP [Formula: see text]-Bessel multipliers offer a larger range of freedom than frames on signal representations in Banach spaces.

Corner Detection Using Second-Order Generalized Gaussian Directional Derivative Representations.

Corner detection is a critical component of many image analysis and image understanding tasks, such as object recognition and image matching. Our research indicates that existing corner detection algorithms cannot properly depict the difference between edges and corners and this results in wrong corner detections. In this paper, the capability of second-order generalized (isotropic and anisotropic) Gaussian directional derivative filters to suppress Gaussian noise is evaluated. The second-order generalized Gaussian directional derivative representations of step edge, L-type corner, Y- or T-type corner, X-type corner, and star-type corner are investigated and obtained. A number of properties for edges and corners are discovered which enable us to propose a new image corner detection method. Finally, the criteria on detection accuracy and average repeatability under affine image transformation, JPEG compression, and noise degradation, and the criteria on region repeatability are used to evaluate the proposed detector against nine state-of-the-art methods. The experimental results show that our proposed detector outperforms all the other tested detectors.

Properties of characteristic polynomial and eigenvalues of antiadjacency matrix of directed unicyclic tadpole graph

A directed cyclic graph is a directed graph that has at least one directed cycle graph, that is a cycle graph in which all edges are oriented, so that the direction passes through each vertex once, except the end of vertex. The directed unicyclic tadpole graph is the graph created by concatenating a cycle and a path with an edge from any vertex of to a pendant of for integers m ≥ 3 and n ≥ 1. Antiadjacency matrix is a directed graph representation matrix based on whether or not there is a relation between one vertex and the others. This paper gives the general form of coefficients of characteristic polynomial and eigenvalues of antiadjacency matrix of directed unicyclic tadpole graph. To find the general form of coefficients of characteristic polynomial and eigenvalues of antiadjacency matrix of directed unicyclic tadpole graph we need to do the grouping of induced subgraphs into acyclic and cyclic and verify with related theorems. After that, the characteristic polynomial is factorized and the roots are calculatedto find its eigenvalues. The coefficients of the characteristic polynomial consist of three distinct values and the eigenvalues are divided into odd case and even case.

About the Contributors

About the Contributors

Dynamic Complex Network Analysis of PM2.5 Concentrations in the UK, Using Hierarchical Directed Graphs (V1.0.0)

The risk of a broad range of respiratory and heart diseases can be increased by widespread exposure to fine atmospheric particles on account of their capability to have a deep penetration into the blood streams and lung. Globally, studies conducted epidemiologically in Europe and elsewhere provided the evidence base indicating the major role of PM2.5 leading to more than four million deaths annually. Conventional approaches to simulate atmospheric transportation of particles having high dimensionality from both transport and chemical reaction process make exhaustive causal inference difficult. Alternative model reduction methods were adopted, specifically a data-driven directed graph representation, to deduce causal directionality and spatial embeddedness. An undirected correlation and a directed Granger causality network were established through utilizing PM2.5 concentrations in 14 United Kingdom cities for one year. To demonstrate both reduced-order cases, the United Kingdom was split up into two southern and northern connected city communities, with notable spatial embedding in summer and spring. It continued to reach stability to disturbances through the network trophic coherence parameter and by which winter was construed as the most considerable vulnerability. Thanks to our novel graph reduced modeling, we could represent high-dimensional knowledge in a causal inference and stability framework.

Hierarchical, Dense and Dynamic 3D Reconstruction Based on VDB Data Structure for Robotic Manipulation Tasks.

This paper presents a novel approach to implement hierarchical, dense and dynamic reconstruction of 3D objects based on the VDB (Variational Dynamic B + Trees) data structure for robotic applications. The scene reconstruction is done by the integration of depth-images using the Truncated Signed Distance Field (TSDF). The proposed reconstruction method is based on dynamic trees in order to provide similar reconstruction results to the current state-of-the-art methods (i.e., complete volumes, hashing voxels and hierarchical volumes) in terms of execution time but with a direct multi-level representation that remains real-time. This representation provides two major advantages: it is a hierarchical and unbounded space representation. The proposed method is optimally implemented to be used on a GPU architecture, exploiting the parallelism skills of this hardware. A series of experiments will be presented to prove the performance of this approach in a robot arm platform.

Microplane fatigue model MS1 for plain concrete under compression with damage evolution driven by cumulative inelastic shear strain

Mathematical modeling of fatigue behavior of concrete under compressive loading presents a challenging topic that attracts an increasing interest of the scientific community. The present paper proposes a new formulation of the microplane model referred to as MS1 aiming to capture the fundamental inelastic mechanisms that can reflect the tri-axial stress redistribution within a material zone upon cyclic loading at subcritical load levels. The key idea of the proposed approach is to link the fatigue damage evolution to the cumulative inelastic shear strain. In this way the accumulation of fatigue damage under compressive loading owing to internal shear/sliding between aggregates at subcritical load levels can be reflected. The present model is developed within the context of the microplane theory using a homogenization scheme based on the principle of energy equivalence with a direct tensorial representation of the effective elastic stiffness. The paper presents elementary studies of the model behavior accompanied with the evaluation of its capability to capture the response of concrete fatigue under compressive loading. A calibration and validation procedure of the model response is provided based on an accompanying experimental program including normal- and high-strength concretes subjected to several loading scenarios. The model shows the ability to reproduce the concrete behavior under monotonic, cyclic and fatigue loading with consistent set of material parameters.

Role of epicuticular wax in the regulation of plant growth and health as measured by spectral indices

ABSTRACT Using remote sensing technology for exploring the trait of interest can provide better results without damaging the plants and are comparatively economic. Traditional methods are available for quantification of different pigments and chemicals present in plants, yet these methods do not allow repeated measurements on the same plant throughout development. The reflected values from plant surfaces are a direct representation of plant physiology including plant morphological factors. The hyperspectral imaging indices for vegetation and water-stressed canopies provided a better indication of each genotype proficiency, thus improving their selection efficiency. The presence of epicuticular wax (EW) influences the reflectance from leaf surface which depends on the presence of leaf pigments including carotenoids, photosynthetic light use efficiency biochemical structures, and water content as they absorb the incident light necessary for photosynthesis. The results obtained suggested decrease carotenoid reflectance index (CRI) and photochemical reflectance index (PRI) values for high wax lines indicating the low concentration of stress-related pigments thus improving plant health and extended maturation. The high waxy lines decreased for plant senescence reflectance index (PSRI) and reduce canopy stress at grain filling and maturation growth stages. A positive correlation between high epicuticular wax (EW) and yield was found confirming previous study. A positive correlation between high epicuticular wax (EW) lines and yield indicated its important role in preventing yield losses under drought conditions.

A 200-μW Interface for High-Resolution Eddy-Current Displacement Sensors

This article presents a low-power eddy-current sensor interface for touch applications. It is based on a bang-bang digital phase-locked loop (DPLL) that converts the displacement of a metal target into digital information. The PLL consists of a digitally controlled oscillator (DCO) built around a sensing coil and a capacitive DAC, a comparator-based bang-bang phase/frequency detector (PFD), and a digital loop filter (DLF). The PLL locks the DCO to a reference frequency, making its digital input a direct representation of the sensing coil inductance. To compensate for the coil inductance tolerances, the DCO's center frequency can be trimmed by a second capacitive DAC. This approach obviates the need for a reference coil. When combined with a 5-mm-diameter sensing coil located 500 μm from a metal target, the interface achieves a displacement resolution of 6.7 nm (rms) in a 3-kHz bandwidth. It consumes 200 μW from a 1.8-V power supply, which represents the best-reported tradeoff between power consumption, bandwidth, and resolution.

A neuronal blueprint for directional mechanosensation in larval zebrafish

Animals have a remarkable ability to use local cues to orient in space in the absence of a panoramic fixed reference frame. Here we use the mechanosensory lateral line in larval zebrafish to understand rheotaxis, an innate oriented swimming evoked by water currents. We generated a comprehensive light-microscopy cell-resolution projectome of lateralis afferent neurons (LANs) and used clustering techniques for morphological classification. We find surprising structural constancy among LANs. Laser-mediated microlesions indicate that precise topographic mapping of lateral-line receptors is not essential for rheotaxis. Recording neuronal-activity during controlled mechanical stimulation of neuromasts reveals unequal representation of water-flow direction in the hindbrain. We explored potential circuit architectures constrained by anatomical and functional data to suggest a parsimonious model under which the integration of lateralized signals transmitted by direction-selective LANs underlies the encoding of water-flow direction in the brain. These data provide a new framework to understand how animals use local mechanical cues to orient in space.

Shape-Driven EIT Reconstruction Using Fourier Representations.

Shape-driven approaches have been proposed as an effective strategy for the electrical impedance tomography (EIT) reconstruction problem in recent years. In order to augment the shape-driven approaches, we propose a new method that transforms the shape to be reconstructed as basic primitives directly modeled by using Fourier representations. To allow automatic topological changes between the basic primitives and surrounding objects simultaneously, Boolean operations are employed. The Boolean operations with direct representation of primitives can be utilized for dimensionality and ill-posedness reduction, enabling feasible shape and topology optimization with shape-driven approaches. As a proof of principle, we leverage the proposed method for two dimensional shape reconstruction in EIT with various conductivity distributions. We demonstrate that our method is able to improve EIT reconstructions by enabling accurate shape and topology optimization.

Collective labor relations and juridification: A marriage proposal

Contributing to debates over relations between the collective and juridified regulation of labor, this article analyzes a rich case study in the Israeli construction sector to claim that juridification can spur unions and employers’ associations to initiate strategic and inclusive change. By subsuming processes of juridification into traditional IR frameworks and embracing its logic and practices, the corporatist social partners broaden the relevance of collective labor relations to workers otherwise excluded from direct union representation. In this way, while not increasing union density or improving wages, these ‘traditional’ IR actors reassert their monopolistic control over worker and employer representation, as well as over the sectoral labor market.

Investigating Neural Representation of Finger-Movement Directions Using Electroencephalography Independent Components

There are few EEG studies on finger movement directions because ocular artifacts also convey directional information, which makes it hard to separate the contribution of EEG from that of the ocular artifacts. To overcome this issue, we designed an experiment in which EEG’s temporal dynamics and spatial information are evaluated together to improve the performance of brain-computer interface (BCI) for classifying finger movement directions. Six volunteers participated in the study. We examined their EEG using decoding analyses. Independent components (ICs) that represented brain-source signals successfully classified the directions of the finger movements with higher rates than chance level. The weight analyses of the classifiers revealed that maximal performance of the classification was recorded at the latencies prior to the onset of finger movements. The weight analyses also revealed the relevant cortical areas including the right lingual, left posterior cingulate, left inferior temporal gyrus, and right precuneus, which indicated the involvement of the visuospatial processing. We concluded that combining spatial distribution and temporal dynamics of the scalp EEG may improve BCI performance.

Teorijski problemi periodizacije književnosti

An overview of epochs and directions is not the history of literature, because history cannot be reduced to summary representations of periods and directions. The greatest writers, the creators of history, are above and beyond the directions and schools. Directions and schools appear and disappear legally, so they are imposed as a subject of literary-historical and theoretical study. The periodization system establishes a certain scientific orientation in a multitude of literary facts, past and present. The paper highlights the theoretical problem of periodization of literature, as a central problem of theoretical examinations of literary phenomena.

Метод оценки единичных показателей качества материалов, изделий, конструкций зданий и сооружений на опасных производственных объектах с использованием S-образных кривых

The article considers the issue of establishing a mathematical dependence in the form of an S-shaped curve for quantifying the quality of buildings and structures at hazardous production facilities with subsequent automation of the quality assessment calculation mechanism based on the obtained mathematical model. It is proposed to take a piecewise nonlinear dependence described by a polynomial of odd degree as the basis of an S-shaped curve. Using the least squares method, the equation of the S-shaped curve of the quality assessment M from the value of a single quality indicator p_(i ) is obtained. The software «Qualimetric Unit Quality Estimation» has been developed, which allows to carry out a quantitative assessment of the quality of a single indicator by the method of qualimetry, as well as to give a direct visual representation in the form of a graph. The process of calculating the quality assessment of the selected single indicator reduces the time for calculating and analyzing the results, increases the efficiency of the procedure for assessing the quality of materials, products, structures of buildings and structures at hazardous production facilities.

Recovery of surfaces and functions in high dimensions: sampling theory and links to neural networks.

Several imaging algorithms including patch-based image denoising, image time series recovery, and convolutional neural networks can be thought of as methods that exploit the manifold structure of signals. While the empirical performance of these algorithms is impressive, the understanding of recovery of the signals and functions that live on manifold is less understood. In this paper, we focus on the recovery of signals that live on a union of surfaces. In particular, we consider signals living on a union of smooth band-limited surfaces in high dimensions. We show that an exponential mapping transforms the data to a union of low-dimensional subspaces. Using this relation, we introduce a sampling theoretical framework for the recovery of smooth surfaces from few samples and the learning of functions living on smooth surfaces. The low-rank property of the features is used to determine the number of measurements needed to recover the surface. Moreover, the low-rank property of the features also provides an efficient approach, which resembles a neural network, for the local representation of multidimensional functions on the surface. The direct representation of such a function in high dimensions often suffers from the curse of dimensionality; the large number of parameters would translate to the need for extensive training data. The low-rank property of the features can significantly reduce the number of parameters, which makes the computational structure attractive for learning and inference from limited labeled training data.

ТЕНДЕНЦІЇ РОЗВИТКУ ЖІНОЧОЇ НОВЕЛІСТИКИ КАТАРУ КІНЦЯ XX – ПОЧАТКУ XXIСТОЛІТ Ь(НА ПРИКЛАДІ ЗБІРКИ ДАЛЯЛЬ ХАЛІФИ "Я – КВІТКА БІЛОГО ЖАСМИНУ")

This paper deals with the investigation of Qatari women's short story at the end of the 20th – the beginning of the 21st centuries. The author determines the contribution of women's literary output in the development of the short story genre in Qatari literature. In the late ‘70s and ‘80s, Qatari short story had a great development due to the works of such writers as Kaltham Jabr, Umm Aktham, Nura Al Saad, Ḥeṣṣa al-Jabir and Mayisa al-Khalifi. In their works, they began to depict the inner world of the characters and abandoned the direct representation of reality. As a result, they modernized the form of a short story. The short story collections "The Pain of an Arab Woman" ("وجع امرأة عربية", 1993 р.) by Kaltham Jabr and "Newspaper Seller" ("بائع الجرائد", 1989 р.) by Nura Al Saad attracted great attention of Arab critics with their novelty. In their opinion, they became a leap in the development of Qatari short story. Among the representatives of the generation of the 1990s and 2000s, the short story collections of Huda al-Naimi, Nurah Faraj, and Dalal Khalifah stand out. The themes and stylistic features of their short stories have been briefly outlined. Dalal Khalifa's short story collection "I am a Flower of White Jasmine" ("أنا الياسمينة البيضاء", 2002 р.) was chosen for a more detailed analysis, taking into consideration the significant contribution of Dalal Khalifah to the development of prose genres in Qatari literature. In short stories from this collection Dalal Khalifah reveals the inner conflicts of the individual due to the skillful use of modernist narrative techniques.

Certain Investigations on Melanoma Detection Using Non-Subsampled Bendlet Transform with Different Classifiers

Skin is the largest organ and outer enclosure of the integumentary system that protects the human body from pathogens. Among various cancers in the world, skin cancer is one of the most commonly diagnosed cancer which can be either melanoma or non-melanoma. Melanoma cancers are very fatal compared with non-melanoma cancers but the chances of survival rate are high when diagnosed and treated earlier. The main aim of this work is to analyze and investigate the performance of Non-Subsampled Bendlet Transform (NSBT) on various classifiers for detecting melanoma from dermoscopic images. NSBT is a multiscale and multidirectional transform based on second order shearlet system which precisely classifies the curvature over other directional representation systems. Here two-phase classification is employed using k-Nearest Neighbour (kNN), Naive Bayes (NB), Decision Trees (DT) and Support Vector Machines (SVM). The first phase classification is used to classify the images of PH2 database into normal and abnormal images and the second phase classification classifies the abnormal images into benign and malignant. Experimental result shows the improvement in classification accuracy, sensitivity and specificity compared with the state of art methods.

Stratified opposition-based initialization for variable-length chromosome shortest path problem evolutionary algorithms

Initialization is the first and a major step in the implementation of evolutionary algorithms (EAs). Although there are many common general methods to initialize EAs such as the pseudo-random number generator (PRNG), there is no single method that can fit every problem. This study provides a new, flexible, diversity-aware, and easy-to-implement initialization method for a genetic algorithm for the shortest path problem. The proposed algorithm, called stratified opposition-based sampling (SOBS), considers phenotype and genotype diversity while striving to achieve the best fitness for the initialization population. SOBS does not depend on a specific type of sampling, because the main goal is to stratify the sampling space. SOBS aims at an initial population with higher fitness and diversity in the phenotype and genotype. To investigate the performance of SOBS, four network models were used to simulate real-world networks. Compared with the most frequently used initialization method, that is, PRNG, SOBS provides more accurate solutions, better running time with less memory usage, and an initial population with higher fitness. Statistical analysis showed that SOBS yields solutions with higher accuracy in 68–100% of the time. Although this study was focused on the genetic algorithm, it can be applied to other population-based EAs that solve the shortest path problem and use the same direct population representation such as particle swarm optimization (PSO).