找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Web and Wireless Geographical Information Systems; 18th International S Sergio Di Martino,Zhixiang Fang,Ki-Joune Li Conference proceedings

[復制鏈接]
樓主: 延展
21#
發(fā)表于 2025-3-25 04:35:15 | 只看該作者
22#
發(fā)表于 2025-3-25 09:54:18 | 只看該作者
A Social-Spatial Data Approach for Analyzing the Migrant Caravan Phenomenonent analysis and spatiotemporal data exploration. The study reveals significant ethnic polarization and ideological patterns but noticeable regional differences in rural and urban areas. The experimental study shows that our approach provides a valuable experimental framework to study emerging regional phenomena as they appear from social media.
23#
發(fā)表于 2025-3-25 11:45:55 | 只看該作者
24#
發(fā)表于 2025-3-25 18:16:11 | 只看該作者
25#
發(fā)表于 2025-3-25 22:43:07 | 只看該作者
CoolPath: An Application for Recommending Pedestrian Routes with Reduced Heatstroke Riskies have focused on the heat-related analysis or on developing general routing applications for pedestrians, few have aimed at providing routing services for pedestrians specifically to reduce their heatstroke risk. In this research, we propose a novel routing system that can recommend pedestrian ro
26#
發(fā)表于 2025-3-26 03:27:51 | 只看該作者
What Do We Actually Need During Self-localization in an Augmented Environment? makes people understanding their location more intuitively. The signals that can be used for self-localization include landmarks, road names, direction guidance, etc., but these elements cannot all be added on a limited size screen. This paper using eye tracking technology to conduct an experiment,
27#
發(fā)表于 2025-3-26 06:22:19 | 只看該作者
Predicting Indoor Location based on a Hybrid Markov-LSTM Model a novel hybrid Markov-LSTM model to predict the indoor user’s next location, which adopt the multi-order Markov chains (k-MCs) to model the long indoor location sequences and use LSTM to reduce dimension through combining multiple first-order MCs. Finally, we conduct comprehensive experiments on th
28#
發(fā)表于 2025-3-26 09:47:06 | 只看該作者
Massive Spatio-Temporal Mobility Data: An Empirical Experience on Data Management Techniquesphones, GPS handhelds, etc.), has led to a significant increase in the availability of datasets representing mobility phenomena, with high spatial and temporal resolution. Especially in the urban scenario, these datasets can enable the development of “Smart Cities”. Nevertheless, these massive amoun
29#
發(fā)表于 2025-3-26 15:13:57 | 只看該作者
The Integration of OGC SensorThings API and OGC CityGML via Semantic Web Technologyions. While 3D city models, Internet of Things (IoT), and domain models are essential components of smart cities, the integration of IoT resources and 3D city models is a central information backbone for smart city cyber-infrastructures. However, we argue that most of the existing solutions integrat
30#
發(fā)表于 2025-3-26 20:38:42 | 只看該作者
Location Optimization of Urban Emergency Medical Service Stations: A Hierarchical Multi-objective Moreceiving special attention. This paper presents a novel hierarchical multi-objective optimization model that considers the goal of providing effectiveness equal service for all citizens firstly, reducing the total travel cost of emergency medical service missions and the number of overall stations
 關于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結 SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-7 14:35
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權所有 All rights reserved
快速回復 返回頂部 返回列表
神木县| 深泽县| 晋州市| 勐海县| 黎平县| 龙江县| 孟连| 平乐县| 平湖市| 新野县| 花莲县| 无极县| 临汾市| 南京市| 宁城县| 微山县| 桃江县| 鲁山县| 威远县| 黔西县| 台山市| 华容县| 浦城县| 齐河县| 呼玛县| 镇宁| 莎车县| 丹凤县| 平远县| 平潭县| 常州市| 怀来县| 伊吾县| 遵义市| 绥棱县| 周口市| 东乡族自治县| 涟水县| 卓尼县| 沂水县| 黔江区|