Particle-Based Fused Rendering

In this chapter, we propose a fused rendering technique that can integrally handle multiple irregular volumes. Although there is a strong requirement for understanding large-scale datasets generated from coupled simulation techniques such as computational structure mechanics (CSM) and computational fluid dynamics (CFD), there is no fused rendering technique to the best of our knowledge. For this purpose, we can employ the particle-based volume rendering (PBVR) technique for each irregular volume dataset. Since the current PBVR technique regards an irregular cell as a planar footprint during depth evaluation, the straightforward employment causes some artifacts especially at the cell boundaries. To solve the problem, we calculate the depth value based on the assumption that the opacity describes the cumulative distribution function (CDF) of a probability variable, w, which shows a length from the entry point in the fragment interval in the cell. In our experiments, we applied our method to numerical simulation results in which two different irregular grid cells are defined in the same space and confirmed its effectiveness with respect to the image quality

Correlation of porosity and properties of recycled fine aggregate concrete with fly ash

In this paper, we presented the experimental discussion of samples of recycled aggregate concrete with replacement of natural fine aggregate by recycled fine aggregate. Three mix kinds were produced and, for each of these three kinds, two levels of water to blinder ratio were used with 0%, 10% and 20% of FA. The result of the tests of drying shrinkage and compressive strength of recycled concrete were used for comparison with tests of mercury intrusion porosimetry (MIP), in which the cumulative pore volume and different intervals of pore volume were studied at ages of 28 and 91 days. Correlation graph of compressive strength and cumulative pore volume might be predicted with given W/B, days and FA of the concrete or none given and drying shrinkage might be predicted with given FA

A study on properties of concrete with dry fly ash and fly ash slurry stored with stirring

In the evaluation of concrete sustainability, what constitutes "sustainable" to one region may vary from another. This often leads to methodological forms of uncertainties that makes the evaluation process more complex. As such, this paper aims to quantify the effect of uncertainties in the regional context on the sustainability evaluation of concrete materials. This is carried out by quantifying the regional context through establishing a weighting scheme and then integrating the obtained weights into the sustainability analysis of concrete materials in tandem with uncertainty analysis. Japan is used as a case study because although it relatively appears as a homogeneous country, its prefectures possess unique characteristics that may make the sustainability evaluation of concrete materials vary across prefectures. Cluster analysis is carried out in the 47 prefectures of Japan using a set of regional context indicators. Five clusters are identified with varying characteristics and these are translated into different weighting schemes. The established weights are used in the sustainability evaluation of concrete materials using multi-criteria decision-making analysis. The results showed that one mix is the most sustainable for four of the clusters and a different mix is the most sustainable for the remaining cluster. When uncertainty analysis is conducted, the effect of the weights in the sustainability evaluation is explained by examining the average scores of the concrete mixes and the variance of the scores across the five clusters. This investigation facilitated the understanding of how regional differences and the uncertainties associated with it impact the evaluation of concrete sustainability

Learning of Art Style Using AI and Its Evaluation Based on Psychological Experiments

[ICEC 2020]19th IFIP TC 14 International Conference, ICEC 2020, Xi'an, China, November 10–13, 2020, ProceedingsPart of the Lecture Notes in Computer Science book series (LNCS, volume 12523)GANs (Generative adversarial networks) is a new AI technology that has the capability of achieving transformation between two image sets. Using GANs we have carried out a comparison between several art sets with different art styles. We have prepared four image sets; a flower image set with Impressionism art style, one with the Western abstract art style, one with Chinese figurative art style, and one with the art style of Naoko Tosa, one of the authors. Using these four sets we have carried out a psychological experiment to evaluate the difference between these four sets. We have found that abstract drawings and figurative drawings are judged to be different, figurative drawings in West and East were judged to be similar, and Naoko Tosa’s artworks are similar to Western abstract artworks

Learning of Art Style Using AI and Its Evaluation Based on Psychological Experiments

GANs (Generative adversarial networks) is a new AI technology that can perform deep learning with less training data and has the capability of achieving transformation between two image sets. Using GAN we have carried out a comparison between several art sets with different art style. We have prepared several image sets; a flower photo set (A), an art image set (B1) of Impressionism drawings, an art image set of abstract paintings (B2), an art image set of Chinese figurative paintings, (B3), and an art image set of abstract images (B4) created by Naoko Tosa, one of the authors. Transformation between set A to each of B was carried out using GAN and four image sets (B1, B2, B3, B4) was obtained. Using these four image sets we have carried out psychological experiment by asking subjects consisting of 23 students to fill in questionnaires. By analyzing the obtained questionnaires, we have found the followings. Abstract drawings and figurative drawings are clearly judged to be different. Figurative drawings in West and East were judged to be similar. Abstract images by Naoko Tosa were judged as similar to Western abstract images. These results show that AI could be used as an analysis tool to reveal differences between art genres

An attempt of dissemination of potential fishing zones prediction map of Japanese common squid in the coastal water, southwestern Hokkaido, Japan

Accurate prediction of potential fishing zones is regarded as one of the most immediate and effective approaches in operational fisheries. It helps fishermen reduce their cost on fuel and also decrease the uncertainty of their fish catches. To predict potential fishing zones of Japanese common squid, we derived fishing positions from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS), combine with bathymetry and model-derived environmental factors from the 4D-VAR data assimilation system and fitted using habitat suitability index (HSI) model. Validations with an independent DMSP/OLS dataset showed better performance of the model in figuring out the squid aggregations than our previous model established with satellite-derived environmental data. Nighttime visible images during June and early July of 2013 derived from Day/Night band (DNB) of Visible Infrared Imaging Radiometer Suite (VIIRS) sensor with a better resolution and quality compared to DMSP/OLS, were also applied for validation and results showed differences of fitness between actual fishing activities and predictions in Japan Sea and Tsugaru Strait

PetaFlow: a global computing-networking-visualisation unitwith social impact

International audienceThe PetaFlow application aims to contribute to the use of high performance computational resources forthe benefit of society. To this goal the emergence of adequate information and communication technologies withrespect to high performance computing-networking-visualisation and their mutual awareness is required. Thedeveloped technology and algorithms are presented and applied to a real global peta-scale data intensive scientificproblem with social and medical importance, i.e. human upper airflow modelling

四面体格子を用いた3次元有限要素法解析結果の可視化技術

京都大学0048新制・論文博士博士(工学)乙第8517号論工博第2838号新制||工||956(附属図書館)UT51-94-J246(主査)教授 英保 茂, 教授 安陪 稔, 教授 池田 克夫学位規則第4条第2項該当Doctor of EngineeringKyoto UniversityDFA

High-quality particle-based volume rendering for large-scale unstructured volume datasets

In this article, we propose a technique for improving the image quality of particle-based volume rendering (PBVR). A large-scale unstructured volume dataset often contains multiple sub-volumes, which cannot be ordered by visibility. PBVR can handle this type of volume dataset. Sampling misses often occur when the transfer function undergoes drastic changes, which can result in poor image quality. To reduce sampling misses caused by the high-frequency transfer function, we develop a new sampling technique called “layered sampling”. To confirm the effectiveness of our technique, we apply the proposed technique to a large-scale unstructured volume dataset subdivided into multiple sub-volumes