CH. Baby Rani^a , N. Vedavathi^b , K.S. Balamurugan^c, G. Dharmaiah^d,*

Frontiers in Heat and Mass Transfer, Vol.14, No.1, pp. 1-11, 2020, DOI:10.5098/hmt.14.6

Abstract The present work provides an analysis of the Dufour, radiation absorption, Hall and ion slip effects on MHD free convective rotating flow of Agwater based nanofluid past a semi-infinite permeable moving plate with constant heat source. In this regard, metal will be considered as nanoparticles with water as base fluid. Governing nonlinear boundary layer equations and boundary conditions are transformed into a system of nonlinear ordinary coupled differential equations and are solved by perturbation technique. Effects of different parameters on skin friction coefficient, local Nusselt number and Local Sherwood number are also discussed. More >

S. Eliza Femi Sherley^1,*, J. M. Karthikeyan¹, N. Bharath Raj¹, R. Prabakaran², A. Abinaya¹, S. V. V. Lakshmi³

Journal on Artificial Intelligence, Vol.4, No.4, pp. 215-227, 2022, DOI:10.32604/jai.2022.034931

Abstract Semantic change detection is extension of change detection task in which it is not only used to identify the changed regions but also to analyze the land area semantic (labels/categories) details before and after the timelines are analyzed. Periodical land change analysis is used for many real time applications for valuation purposes. Majority of the research works are focused on Convolutional Neural Networks (CNN) which tries to analyze changes alone. Semantic information of changes appears to be missing, there by absence of communication between the different semantic timelines and changes detected over the region happens. To overcome this limitation, a… More >

Clément Moreau, Thomas Devogele, Laurent Etienne

Revue Internationale de Géomatique, Vol.29, No.1, pp. 107-128, 2019, DOI:10.3166/rig.2019.00077

Abstract Understanding mobility, whether physical in the spatial sense or virtual in the web navigation sense, raises many challenges in terms of monitoring individuals, spatial planning or activity recommendations. Having access today to many resources on the contextual nature of this mobility, one of the current concerns is to succeed in identifying groups of similar individuals with regard to their mobility. To do this, we propose a semantic trajectory model enriched by ontologies at the level of contextual data and allowing us to calculate the similarity between each episode of individual mobility. Subsequently, an editing distance is used to evaluate in… More >

Dominique Badariotti, Cyril Meyer, Yasmina Ramrani

Revue Internationale de Géomatique, Vol.30, No.2, pp. 181-213, 2020, DOI:10.3166/rig.2021.00109

Abstract In this paper, we propose a model and a methodology for the analysis of urban fabrics, sets of built morphological units articulated together by urban networks. The core of the paper presents the MoGUS model (Model Generator & analyser for Urban Simulation) and its formalization. This model jointly represents the buildings and the viaires networks of a city in a graph, and allows a comparative analysis of the properties of different urban fabrics, using derived indicators. A study plan applied to four types of archetypal urban fabrics (Hippodamean, medieval, radio-concentric, Haussmannic) generated with the MoGUS tool is presented to illustrate… More >

S. Duroudier¹ , S. Chardonnel¹, B. Mericskay² , I. Andre-Poyaud¹ , O. Bedel³ , S. Depeau², T. Devogele⁴, L. Etienne⁴, A. Lepetit², C. Moreau⁴, N. Pelletier² , E. Ployon¹, K. Tabaka¹

Revue Internationale de Géomatique, Vol.30, No.1, pp. 127-148, 2020, DOI:10.3166/rig.2020.00105

Abstract This paper aims at proposing a data quality diagnosis and cleansing data methodology experimented on an individual mobility survey (Mobi’Kids program). The first section presents the theoretical approach to highlight the issue of a data quality diagnosis applied to heterogeneous data collected from mixed methods (GPS tracks, surveys, observations). Secondly, two typologies of major errors are discussed according to their origin (GPS, algorithm, survey) and their nature (completeness, accuracy, consistency). A processing chain is thirdly defined to improve both internal and external data quality in order to the perspective of a replicable methodology.

RÉSUMÉ
Cet article a pour objectif de… More >

Gauthier Fillières-Riveau¹ , Jean-Marie Favreau¹ , Vincent Barra¹ , Guillaume Touya²

Revue Internationale de Géomatique, Vol.30, No.1, pp. 105-126, 2020, DOI:10.3166/rig.2020.00104

Abstract Photo-realistic tactile maps are one of the tools used by visually impaired people to understand their immediate urban environment, particularly in the context of mobility, for crossing crossroads for example. These maps are nowadays mainly hand-made. In this article, we propose an approach to produce a semantic segmentation of precision aerial imagery, a central step in this manufacturing process. The different elements of interest such as sidewalks, pedestrian crossings, or central islands are thus located and traced in the urban space. We present in particular how the augmentation of this imagery by vector data from OpenStreetMap leads to significant results… More >

Claire Prudhomme¹ , Ana Roxin² , Christophe Cruz² , Frank Boochs¹

Revue Internationale de Géomatique, Vol.30, No.1, pp. 37-65, 2020, DOI:10.3166/rig.2020.00102

Abstract Disaster management requires collaborative preparedness among the various stakeholders. Collaborative exercises aim to train stakeholders to apply the plans prepared and to identify potential problems and areas for improvement. As these exercises are costly, computer simulation is an interesting tool to optimize preparation through a wider variety of contexts. However, research on simulation and disaster management focuses on a particular problem rather than on the overall optimization of the plans prepared. This limitation is explained by the challenge of creating a simulation model that can represent and adapt to a wide variety of plans from various disciplines. The work presented… More >

Jin Zhao, Yi Wang^*, Zhengwei Ma

Structural Durability & Health Monitoring, Vol.17, No.2, pp. 159-173, 2023, DOI:10.32604/sdhm.2023.09601

Abstract Viscoelastic damper is an effective passive damping device, which can reduce the seismic response of the structure by increasing the damping and dissipating the vibration energy of structures. It has a wide application prospect in actual structural vibration control because of simple device and economical material. In view of the poor seismic behaviors of assembled frame structure connections, various energy dissipation devices are proposed to improve the seismic performance. The finite element numerical analysis method is adopted to analyze relevant energy dissipation structural parameters. The response spectrum of a 7-story assembled frame structure combined the ordinary steel support, ordinary viscoelastic… More >

A. Manju¹, A. Revathi², M. Arivukarasi¹, S. Hariharan³, V. Umarani⁴, Shih-Yu Chen^5,*, Jin Wang⁶

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 905-920, 2023, DOI:10.32604/iasc.2023.038444

Abstract With the proliferation of the internet, big data continues to grow exponentially, and video has become the largest source. Video big data introduces many technological challenges, including compression, storage, transmission, analysis, and recognition. The increase in the number of multimedia resources has brought an urgent need to develop intelligent methods to organize and process them. The integration between Semantic link Networks and multimedia resources provides a new prospect for organizing them with their semantics. The tags and surrounding texts of multimedia resources are used to measure their semantic association. Two evaluation methods including clustering and retrieval are performed to measure… More >

Zimeng Yang, Qiulan Wu, Feng Zhang^*, Xuefei Chen, Weiqiang Wang, Xueshen Zhang

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 491-506, 2023, DOI:10.32604/iasc.2023.037558

Abstract Semantic segmentation of remote sensing images is one of the core tasks of remote sensing image interpretation. With the continuous development of artificial intelligence technology, the use of deep learning methods for interpreting remote-sensing images has matured. Existing neural networks disregard the spatial relationship between two targets in remote sensing images. Semantic segmentation models that combine convolutional neural networks (CNNs) and graph convolutional neural networks (GCNs) cause a lack of feature boundaries, which leads to the unsatisfactory segmentation of various target feature boundaries. In this paper, we propose a new semantic segmentation model for remote sensing images (called DGCN hereinafter),… More >