Rich Structural Index for Stereoscopic Image Quality Assessment

The human visual system (HVS), affected by viewing distance when perceiving the stereo image information, is of great significance to study of stereoscopic image quality assessment. Many methods of stereoscopic image quality assessment do not have comprehensive consideration for human visual perception characteristics. In accordance with this, we propose a Rich Structural Index (RSI) for Stereoscopic Image objective Quality Assessment (SIQA) method based on multi-scale perception characteristics. To begin with, we put the stereo pair into the image pyramid based on Contrast Sensitivity Function (CSF) to obtain sensitive images of different resolution . Then, we obtain local Luminance and Structural Index (LSI) in a locally adaptive manner on gradient maps which consider the luminance masking and contrast masking. At the same time we use Singular Value Decomposition (SVD) to obtain the Sharpness and Intrinsic Structural Index (SISI) to effectively capture the changes introduced in the image (due to distortion). Meanwhile, considering the disparity edge structures, we use gradient cross-mapping algorithm to obtain Depth Texture Structural Index (DTSI). After that, we apply the standard deviation method for the above results to obtain contrast index of reference and distortion components. Finally, for the loss caused by the randomness of the parameters, we use Support Vector Machine Regression based on Genetic Algorithm (GA-SVR) training to obtain the final quality score. We conducted a comprehensive evaluation with state-of-the-art methods on four open databases. The experimental results show that the proposed method has stable performance and strong competitive advantage.

Researching on influence factorsand value confirmation of elasticmodulus (Eac), layer coefficient (ai)of some types of hot dense asphalt concrete in Vietnam

The method of designing flexible road structures under the guidance of AASHTO 1993 was used in many states in the US and Canada and is being applied by many other countries in Europe and Asia. The layer coefficient ai in the AASHTO design equation represents an empirical relationship between the structural index SN and thickness. The value of the layer coefficients (ai) is specified for each material layer depending on the quality shown mainly through resilient modulus. This paper presents the initial research results of influencing factors and value confirmation of resilient modulus (Eac) and layer coefficients (ai) of some types of hot dense asphalt concrete in Vietnam.

A Constitutive Model for Overconsolidated Structured Soils Using Structural Variable

Due to the influence of soil structure, structured soils exhibit significantly different mechanical behavior compared to the reconstituted soils having the same material. In this work, a theoretical analysis focusing on the mechanical behavior of structured soils is presented. Based on the mechanical behavior of the structured soil, a newly defined variable structural index was used as a measurement of the integrity of soil structure based on the concept of intrinsic compression line of intact structured soils. Furthermore, a novel correlation for the variation in volume of structured soils is established using effective stress and newly defined structural index as the constitutive variables. The novel correlation provided interpretation about the mechanism of compression behavior of the structured soils. Afterwards, the proposed correlation for the variation in volume was extended to triaxial stress state in the framework of subloading surface to include the effect of overconsolidation. Comparisons between the predictions and experimental results validated the proposed constitutive model for structured soils.

Estimation of Depth to Bouguer Anomaly Sources Using Euler Deconvolution Techniques

The geophysical measurement of variations in gravitational field of the Earth for a particular location is carried out through a gravity survey method. These variations termed anomalies can help investigate the subsurface of interest. An investigation was carried out using the airborne satellite-based (EGM08) gravity dataset to reveal the geological information inherent in a location. Qualitative analysis of the gravity dataset by filtering techniques of two-dimensional fast Fourier transform (FFT2D) shows that the area is made up of basement and sedimentary Formations. Further enhancements on the residual anomaly after separation show the sedimentary intrusion into the study area and zones of possible rock minerals of high and low density contrasts. Quantitative interpretations of the study area by 3-D Euler deconvolution depth estimation technique described the depth and locations of gravity bodies that yielded the gravity field. The result of the depth to basement approach was found to be in the depth range of 930 m to 2,686 m (for Structural Index, SI = 0). The research location is a probable area for economic mineral deposits and hydrocarbon exploration.

A Novel Method for Obtaining the Loess Structural Index from Computed Tomography Images: A Case Study from the Lvliang Mountains of the Loess Plateau (China)

The structural index is an important quantitative parameter for revealing the structural properties of loess. However, there is no a widely accepted measurement method for structural index at present. This study aims at presenting a novel method for obtaining the loess structural index (LSI), based on the application of computed tomography (CT) scanning techniques and laboratory physico-mechanical tests. The mountainous area of Lvliang in northwest China was taken as the study area, and Late Pleistocene loess samples were taken from various sites in the region. Several physical parameters were first measured using laboratory tests, including dry density, pore ratio, and liquidity index. CT scanning was used to observe sample microstructures, and a mathematical relationship was established between CT image parameters and the physical property indices, through three dimensions (3D) reconstruction and slice porosity analysis. The results revealed that LSI can be expressed as a non-linear function related to CT image parameters, dry density, and the liquidity index of the loess. Compared with traditional calculation methods, this novel technique calculates the LSI by using an empirical formula, which is less labor-intensive. Such results indicate that the method warrants wide application in the future.

Crystal and molecular structure of bis(N-(diethylcarbamothioyl)cyclohexane carboxamido)copper(II) complex

Herein, we describe the synthesis and characterization of bis(N-(diethylcarbamothioyl)cyclohexane carboxamido)copper(II) complex, cis-[Cu(L-κ2S,O)2], has been prepared by the reaction of N-(diethyl carbamothioyl)cyclohexanecarboxamide ligand with copper(II) acetate. The green colored crystals of the complex were obtained by slow evaporation of their dichloromethane:ethanol solution (2:1, v:v). The crystal structure of cis-[Cu(L-κ2S,O)2] was obtained by single-crystal X-ray diffraction. The crystal structure reveals an monoclinic C2 (no. 5) space group with cell parameters a = 14.848(3) Å, b = 10.543(2) Å, c = 10.511(2) Å, β = 123.84(3)°, V = 1366.7(7) Å3, Z = 2, T = 153(2) K, μ(MoKα) = 0.979 mm-1, Dcalc = 1.327 g/cm3, 4979 reflections measured (6.6° ≤ 2Θ ≤ 50.68°), 2243 unique (Rint = 0.0223, Rsigma = 0.0444) which were used in all calculations. The final R1 was 0.0225 (>2sigma(I)) and wR2 was 0.0490 (all data). The angular structural index parameter, τ4, is equal to 0.40, which confirms the distorted square planar geometry for the title compound. The puckering parameters (q2 = 0.015(3) Å, q3 = 0.576(3) Å, QT = 0.577(3) Å, θ = 1.6(3)° and φ = 20(11)°) of the title complex show that the cyclohexane ring adopts a chair conformation. The two ethyl groups of the diethyl amine group have anti-orientation with respect to one another. The crystal packing shows the molecules stacked in parallel sheets along [010], accompanied by C3-H3A···O1ⁱ (i -x, +y, 1-z) intermolecular contact.

Automated and qualitative structural evaluation of floor plans for remodeling of apartment housing

Many floor plans are proposed during the early stage of an apartment housing remodeling project as it involves a multitude of entities with different stakes. Consequently, the process to converge the opinions per the individual's preference on an agreed remodeling floor plan becomes repetitive and time consuming. For these reasons, structural evaluation of each proposed conceptual plan is often bypassed and postponed until a finalized floor plan is determined. An automated structural evaluation application for architectural floor plans of apartment housing with the load-bearing wall system is developed on this necessity. The application reads the conceptual drawings and returns various supportive information regarding structural performance, almost instantly. The outputs from the application include the amount of removed, remaining, and new bearing walls, 3D views of each wall component overlaid on the floor plans and their dimensions, area moment of inertia (AMOI) of the walls, torsional resistance of the floor plans, and other supportive indices. For easy and intuitive communication with the users, an abstract and simple quantitative value, structural index (SI), is suggested and included as one of the outputs in the application. In order to validate the developed automated application, a case study is conducted with an ongoing remodeling project, and the results, accuracy, and processing time are compared with the conventional hand calculation method. The application is accurate with errors of less than 1.3%, while the processing speed is nearly seven times faster. With the developed application, the designers could evaluate their conceptual drawings in almost real time. In addition, the stakeholders would communicate in a more straightforward language with the outputs of the application, such as the AMOI evaluation and SI results. Consequently, it is anticipated that the decision-making process during the early stage of a remodeling project would be expedited with the help of the developed automated application.

Scalable structural index construction for JSON analytics

JavaScript Object Notation (JSON) and its variants have gained great popularity in recent years. Unfortunately, the performance of their analytics is often dragged down by the expensive JSON parsing. To address this, recent work has shown that building bitwise indices on JSON data, called structural indices , can greatly accelerate querying. Despite its promise, the existing structural index construction does not scale well as records become larger and more complex, due to its (inherently) sequential construction process and the involvement of costly memory copies that grow as the nesting level increases. To address the above issues, this work introduces Pison - a more memory-efficient structural index constructor with supports of intra-record parallelism. First, Pison features a redesign of the bottleneck step in the existing solution. The new design is not only simpler but more memory-efficient. More importantly, Pison is able to build structural indices for a single bulky record in parallel, enabled by a group of customized parallelization techniques. Finally, Pison is also optimized for better data locality, which is especially critical in the scenario of bulky record processing. Our evaluation using real-world JSON datasets shows that Pison achieves 9.8X speedup (on average) over the existing structural index construction solution for bulky records and 4.6X speedup (on average) of end-to-end performance (indexing plus querying) over a state-of-the-art SIMD-based JSON parser on a 16-core machine.