scholarly journals A Zonal Displacement Approach via Grid Point Weighting in Building Generalization

2021 ◽  
Vol 10 (2) ◽  
pp. 105
Author(s):  
Kadir Sahbaz ◽  
Melih Basaraner
Keyword(s):  
Quality Evaluation ◽  
Grid Point ◽  
Voronoi Tessellation ◽  
Evaluation Criteria ◽  
Visual Assessment ◽  
Positional Accuracy ◽  
Grid Points ◽  
Delaunay Triangles ◽  
Displacement Approach ◽  
Comparison Measures

When generalizing a group of objects, displacement is an essential operation to resolve the conflicts arising between them due to enlargement of their symbol sizes and reduction of available map space. Although there are many displacement methods, most of them are rather complicated. Therefore, more practical methods are still needed. In this article, a new building displacement approach is proposed. For this purpose, buildings are grouped and zones are created for them in the blocks via Voronoi tessellation and buffering. Linear patterns are then detected through buffer analyses and the respective zones are narrowed to be able to preserve these patterns. After all the buildings are displaced inside their zones, grid points are generated and then weighted through kernel density estimation and buffer analyses to find suitable locations. Accordingly, the buildings are displaced toward the computed locations iteratively. The proposed approach directly enforces minimum distance and positional accuracy constraints while several indirect mechanisms are used for preserving spatial patterns and relationships. For the quality evaluation of the displacement, the angle, length and shape comparison measures are introduced, computed based on the (Delaunay) triangles or the azimuth comparison measure of the connection lines, generated for the buildings. The quality evaluation criteria are yielded according to the visual assessment of the displacement quality and the quantitative analysis of the measures. The findings demonstrate that the proposed approach is quite effective and practical for zonal building displacement.

Objective Video Quality Method Based on Mutual Information and Human Visual System

2012 ◽  
Vol 58 (2) ◽  
pp. 147-152
Author(s):  
Michal Mardiak ◽  
Jaroslav Polec
Keyword(s):  
Mutual Information ◽  
Visual System ◽  
Human Visual System ◽  
Quality Evaluation ◽  
Video Quality ◽  
Evaluation Criteria ◽  
Test Sequence ◽  
Quality Metric ◽  
Two Stages ◽  
Video Quality Metric

Objective Video Quality Method Based on Mutual Information and Human Visual SystemIn this paper we present the objective video quality metric based on mutual information and Human Visual System. The calculation of proposed metric consists of two stages. In the first stage of quality evaluation whole original and test sequence are pre-processed by the Human Visual System. In the second stage we calculate mutual information which has been utilized as the quality evaluation criteria. The mutual information was calculated between the frame from original sequence and the corresponding frame from test sequence. For this testing purpose we choose Foreman video at CIF resolution. To prove reliability of our metric were compared it with some commonly used objective methods for measuring the video quality. The results show that presented objective video quality metric based on mutual information and Human Visual System provides relevant results in comparison with results of other objective methods so it is suitable candidate for measuring the video quality.

scholarly journals Image-based textile decoding

2020 ◽  
pp. 1-14
Author(s):  
Siqiang Chen ◽  
Masahiro Toyoura ◽  
Takamasa Terada ◽  
Xiaoyang Mao ◽  
Gang Xu
Keyword(s):  
Deep Learning ◽  
Grid Point ◽  
Intermediate Representation ◽  
Training Set ◽  
Binary Matrix ◽  
The Matrix ◽  
Correct Pattern ◽  
Grid Points ◽  
Textile Fabric ◽  
Direct Correspondence

A textile fabric consists of countless parallel vertical yarns (warps) and horizontal yarns (wefts). While common looms can weave repetitive patterns, Jacquard looms can weave the patterns without repetition restrictions. A pattern in which the warps and wefts cross on a grid is defined in a binary matrix. The binary matrix can define which warp and weft is on top at each grid point of the Jacquard fabric. The process can be regarded as encoding from pattern to textile. In this work, we propose a decoding method that generates a binary pattern from a textile fabric that has been already woven. We could not use a deep neural network to learn the process based solely on the training set of patterns and observed fabric images. The crossing points in the observed image were not completely located on the grid points, so it was difficult to take a direct correspondence between the fabric images and the pattern represented by the matrix in the framework of deep learning. Therefore, we propose a method that can apply the framework of deep learning viau the intermediate representation of patterns and images. We show how to convert a pattern into an intermediate representation and how to reconvert the output into a pattern and confirm its effectiveness. In this experiment, we confirmed that 93% of correct pattern was obtained by decoding the pattern from the actual fabric images and weaving them again.

Spatio-temporal variability of temperature and potential evapotranspiration over India

2016 ◽  
Vol 7 (4) ◽  
pp. 810-822 ◽  
Author(s):  
P. Sonali ◽  
D. Nagesh Kumar
Keyword(s):  
Hydrological Cycle ◽  
Potential Evapotranspiration ◽  
Grid Point ◽  
Rank Correlation ◽  
Trend Detection ◽  
Detection Analysis ◽  
Change Impact ◽  
Spatio Temporal ◽  
Grid Points ◽  
Significant Factors

Worldwide, major changes in the climate are expected due to global warming, which leads to temperature variations. To assess the climate change impact on the hydrological cycle, a spatio-temporal change detection study of potential evapotranspiration (PET) along with maximum and minimum temperatures (Tmax and Tmin) over India have been performed for the second half of the 20th century (1950–2005) both at monthly and seasonal scale. From the observed monthly climatology of PET over India, high values of PET are envisioned during the months of March, April, May and June. Temperature is one of the significant factors in explaining changes in PET. Hence seasonal correlations of PET with Tmax and Tmin were analyzed using Spearman rank correlation. Correlation of PET with Tmax was found to be higher compared to that with Tmin. Seasonal variability of trend at each grid point over India was studied for Tmax, Tmin and PET separately. Trend Free Pre-Whitening and Modified Mann Kendall approaches, which consider the effect of serial correlation, were employed for the trend detection analysis. A significant trend was observed in Tmin compared to Tmax and PET. Significant upward trends in Tmax, Tmin and PET were observed over most of the grid points in the interior peninsular region.

Exact Subthreshold Integration with Continuous Spike Times in Discrete-Time Neural Network Simulations

2007 ◽  
Vol 19 (1) ◽  
pp. 47-79 ◽  
Author(s):  
Abigail Morrison ◽  
Sirko Straube ◽  
Hans Ekkehard Plesser ◽  
Markus Diesmann
Keyword(s):  
Grid Point ◽  
Propagation Delay ◽  
Integration Scheme ◽  
The Novel ◽  
Neuron Models ◽  
Exact Integration ◽  
Wide Range ◽  
Network Simulations ◽  
Adequate Representation ◽  
Grid Points

Very large networks of spiking neurons can be simulated efficiently in parallel under the constraint that spike times are bound to an equidistant time grid. Within this scheme, the subthreshold dynamics of a wide class of integrate-and-fire-type neuron models can be integrated exactly from one grid point to the next. However, the loss in accuracy caused by restricting spike times to the grid can have undesirable consequences, which has led to interest in interpolating spike times between the grid points to retrieve an adequate representation of network dynamics. We demonstrate that the exact integration scheme can be combined naturally with off-grid spike events found by interpolation. We show that by exploiting the existence of a minimal synaptic propagation delay, the need for a central event queue is removed, so that the precision of event-driven simulation on the level of single neurons is combined with the efficiency of time-driven global scheduling. Further, for neuron models with linear subthreshold dynamics, even local event queuing can be avoided, resulting in much greater efficiency on the single-neuron level. These ideas are exemplified by two implementations of a widely used neuron model. We present a measure for the efficiency of network simulations in terms of their integration error and show that for a wide range of input spike rates, the novel techniques we present are both more accurate and faster than standard techniques.

An extended WASPAS approach for teaching quality evaluation based on pythagorean fuzzy reducible weighted Maclaurin symmetric mean

2022 ◽  
pp. 1-32
Author(s):  
Dongmei Wei ◽  
Yuan Rong ◽  
Harish Garg
Keyword(s):  
Quality Evaluation ◽  
Evaluation Criteria ◽  
Teaching Quality ◽  
Teaching Management ◽  
Maclaurin Symmetric Mean ◽  
School Teaching ◽  
Decision Outcomes ◽  
Multiple Input ◽  
Product Assessment ◽  
Fuzzy Assessment

Teaching quality evaluation (TQE) can not only improve teachers’ teaching skills, but also provide an important reference for school teaching management departments to formulate teaching reform measures and strengthen teaching management. TQE is a process of grading and ranking a given teachers based on the comprehensive consideration of multiple evaluation criteria by expert. The Maclaurin symmetric mean (MSM), as a powerful aggregation function, can capture the correlation among multiple input data more efficient. Although multitude weighted MSM operators have been developed to handle the Pythagorean fuzzy decision issues, these above operators do not possess the idempotency and reducibility during the procedure of information fusion. To conquer these defects, we present the Pythagorean fuzzy reducible weighted MSM (PFRWMSM) operator and Pythagorean fuzzy reducible weighted geometric MSM (PFRWGMSM) operator to fuse Pythagorean fuzzy assessment information. Meanwhile, several worthwhile properties and especial cases of the developed operators are explored at length. Afterwards, we develop a novel Pythagorean fuzzy entropy based upon knowledge measure to ascertain the weights of attribute. Furthermore, an extended weighted aggregated sum product assessment (WASPAS) method is developed by combining the PFRWMSM operator, PFRWGMSM operator and entropy to settle the decision problems of unknown weight information. The efficiency of the proffered method is demonstrated by a teaching quality evaluation issue, as well as the discussion of sensitivity analysis for decision outcomes. Consequently, a comparative study of the presented method with the extant Pythagorean fuzzy approaches is conducted to display the superiority of the propounded approach.

Technological Evaluation and Optimization of E-Learning Systems Components

2011 ◽  
pp. 150-173 ◽  
Author(s):  
Eugenijus Kurilovas ◽  
Valentina Dagiene
Keyword(s):  
Quality Evaluation ◽  
Evaluation Criteria ◽  
Learning Objects ◽  
Learning Systems ◽  
Main Research ◽  
Evaluation Models ◽  
E Learning ◽  
Multiple Criteria Evaluation ◽  
Technological Evaluation ◽  
Learning Software

The main research objective of the chapter is to provide an analysis of the technological quality evaluation models and make a proposal for a method suitable for the multiple criteria evaluation (decision making) and optimization of the components of e-learning systems (i.e. learning software), including Learning Objects, Learning Object Repositories, and Virtual Learning Environments. Both the learning software ‘internal quality’ and ‘quality in use’ technological evaluation criteria are analyzed in the chapter and are incorporated into comprehensive quality evaluation models. The learning software quality evaluation criteria are further investigated in terms of their optimal parameters, and an additive utility function based on experts’ judgements, including multicriteria evaluation, numerical ratings, and weights, is applied to optimize the learning software according to particular learners’ needs.

scholarly journals Quality evaluation of briquettes made from wood waste

2012 ◽  
Vol 58 (No. 1) ◽  
pp. 30-35 ◽  
Author(s):  
M. Brožek ◽  
A. Nováková ◽  
M. Kolářová
Keyword(s):  
Quality Evaluation ◽  
Evaluation Criteria ◽  
Calorific Value ◽  
Wood Dust ◽  
Gross Calorific Value ◽  
Pine Sawdust ◽  
Fine Grained ◽  
Technology Products ◽  
Mechanical Durability ◽  
Total Moisture Content

At logging and at the subsequent wood and wood semi-products treatment the fine grained loose waste arises, e.g. wood dust, saw dust, shavings, chips, bark etc. One of possibilities of its meaningful utilization is the briquetting technology, products of which are briquettes determined for energetic utilization (combustion). In the paper the experimental results are published. The briquettes quality evaluation was their aim. For the briquetting tests bark (pine), shavings (about 90% spruce + 10% pine), sawdust (spruce), birch chips and poplar chips were used. The basic physical-mechanical properties were the evaluation criteria. Following properties were determined: gross calorific value, total moisture content, density, rupture force, length, diameter, density and mechanical durability.

scholarly journals Derivation of a planetary ionospheric storm index

2008 ◽  
Vol 26 (9) ◽  
pp. 2645-2648 ◽  
Author(s):  
T. L. Gulyaeva ◽  
I. Stanislawska
Keyword(s):  
Solar Cycle ◽  
Extreme Values ◽  
Grid Point ◽  
Radiant Energy ◽  
Electron Content ◽  
Vertical Total Electron Content ◽  
Ionospheric Storm ◽  
Total Electron ◽  
Grid Points ◽  
Storm Index

Abstract. The planetary ionospheric storm index, Wp, is deduced from the numerical global ionospheric GPS-IONEX maps of the vertical total electron content, TEC, for more than half a solar cycle, 1999–2008. The TEC values are extracted from the 600 grid points of the map at latitudes 60° N to 60° S with a step of 5° and longitudes 0° to 345° E with a step of 15° providing the data for 00:00 to 23:00 h of local time. The local effects of the solar radiant energy are filtered out by normalizing of the TEC in terms of the solar zenith angle χ at a particular time and the local noon value χ0. The degree of perturbation, DTEC, is computed as log of TEC relative to quiet reference median for 27 days prior to the day of observation. The W-index map is generated by segmentation of DTEC with the relevant thresholds specified earlier for foF2 so that 1 or −1 stands for the quiet state, 2 or −2 for the moderate disturbance, 3 or −3 for the moderate ionospheric storm, and 4 or −4 for intense ionospheric storm at each grid point of the map. The planetary ionospheric storm Wp index is obtained from the W-index map as a latitudinal average of the distance between maximum positive and minimum negative W-index weighted by the latitude/longitude extent of the extreme values on the map. The threshold Wp exceeding 4.0 index units and the peak value Wpmax≥6.0 specify the duration and the power of the planetary ionosphere-plasmasphere storm. It is shown that the occurrence of the Wp storms is growing with the phase of the solar cycle being twice as much as the number of the magnetospheric storms with Dst≤−100 nT and Ap≥100 nT.

3‐D eikonal solvers: First‐arrival traveltimes

Geophysics ◽  
2002 ◽  
Vol 67 (4) ◽  
pp. 1225-1231 ◽  
Author(s):  
Seongjai Kim
Keyword(s):  
Grid Point ◽  
Level Set Methods ◽  
Second Order ◽  
Normal Velocity ◽  
Fast Marching Method ◽  
Fast Marching ◽  
Maximum Angle ◽  
First Arrival ◽  
Grid Points ◽  
Marching Method

The article is concerned with the development and comparison of three different algorithms for the computation of first‐arrival traveltimes: the fast marching method (FMM), the group marching method (GMM), and a second‐order finite‐difference eikonal solver. GMM is introduced as a variant of FMM. It proceeds the solution by advancing a selected group of grid points at a time, rather than sorting the solution in the narrow band to march forward a single grid point. The second‐order eikonal solver studied in the article is an expanding‐box, essentially nonoscillatory scheme for which the stability is enforced by the introduction of a down ‘n’ out marching and a post‐sweeping iteration. Techniques such as the maximum angle condition, the average normal velocity, and cache‐based implementation are introduced for the algorithms to improve the numerical accuracy and efficiency. The algorithms are implemented for solving the eikonal equation in 3‐D isotropic media, and their performances are compared. GMM is numerically verified to be faster than FMM. However, the second‐order algorithm turns out to be superior to these first‐order level‐set methods in both accuracy and efficiency; the incorporation of average normal velocity improves accuracy dramatically for the second‐order scheme.

Sign in / Sign up

Export Citation Format

Share Document