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8,604 results on '"Fang, Jing"'

203. CrowdEstimator: Approximating Crowd Sizes with Multi-modal Data for Internet-of-Things Services

Author

Wu, Fang-Jing and Solmaz, Gürkan

Subjects
Electrical Engineering and Systems Science - Systems and Control, Computer Science - Networking and Internet Architecture
Abstract

Crowd mobility has been paid attention for the Internet-of-things (IoT) applications. This paper addresses the crowd estimation problem and builds an IoT service to share the crowd estimation results across different systems. The crowd estimation problem is to approximate the crowd size in a targeted area using the observed information (e.g., Wi-Fi data). This paper exploits Wi-Fi probe request packets ("Wi-Fi probes" for short) broadcasted by mobile devices to solve this problem. However, using only Wi-Fi probes to estimate the crowd size may result in inaccurate results due to various environmental uncertainties which may lead to crowd overestimation or underestimation. Moreover, the ground-truth is unavailable because the coverage of Wi-Fi signals is time-varying and invisible. This paper introduces auxiliary sensors, stereoscopic cameras, to collect the near ground-truth at a specified calibration choke point. Two calibration algorithms are proposed to solve the crowd estimation problem. The key idea is to calibrate the Wi-Fi-only crowd estimation based on the correlations between the two types of data modalities. Then, to share the calibrated results across systems required by different stakeholders, our system is integrated with the FIWARE-based IoT platform. To verify the proposed system, we have launched an indoor pilot study in the Wellington Railway Station and an outdoor pilot study in the Christchurch Re:START Mall in New Zealand. The large-scale pilot studies show that stereoscopic cameras can reach minimum accuracy of 85\% and high precision detection for providing the near ground-truth. The proposed calibration algorithms reduce estimation errors by 43.68% on average compared to the Wi-Fi-only approach., Comment: This work was funded by the joint project collaborations between NEC New Zealand and NEC Laboratories Europe and between NEC Laboratories Europe GmbH and Technische Universitat Dortmund, and has been partially funded by the European Union's Horizon 2020 Programme under Grant Agreement No. CNECT-ICT-643943 FIESTA-IoT: Federated Interoperable Semantic IoT Testbeds and Applications. Proc. of ACM MobiSys'18, 2018

Published
2019
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207. Toward Understanding Crowd Mobility in Smart Cities through the Internet of Things

Author

Solmaz, Gürkan, Wu, Fang-Jing, Cirillo, Flavio, Kovacs, Ernö, Santana, Juan Ramón, Sánchez, Luis, Sotres, Pablo, and Muñoz, Luis

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

Understanding crowd mobility behaviors would be a key enabler for crowd management in smart cities, benefiting various sectors such as public safety, tourism and transportation. This article discusses the existing challenges and the recent advances to overcome them and allow sharing information across stakeholders of crowd management through Internet of Things (IoT) technologies. The article proposes the usage of the new federated interoperable semantic IoT platform (FIESTA-IoT), which is considered as "a system of systems". The platform can support various IoT applications for crowd management in smart cities. In particular, the article discusses two integrated IoT systems for crowd mobility: 1) Crowd Mobility Analytics System, 2) Crowd Counting and Location System (from the SmartSantander testbed). Pilot studies are conducted in Gold Coast, Australia and Santander, Spain to fulfill various requirements such as providing online and offline crowd mobility analyses with various sensors in different regions. The analyses provided by these systems are shared across applications in order to provide insights and support crowd management in smart city environments., Comment: This work is published in IEEE Communications Magazine, This work has been partially funded by the Spanish Government (MINECO) under Grant Agreement No. TEC2015-71329-C2-1-R ADVICE project and by the EU Horizon 2020 Programme under Grant Agreements No. 731993 AUTOPILOT, 643943 FIESTA-IoT, and 643275 FESTIVAL projects

Published
2019
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208. Adversarial Objects Against LiDAR-Based Autonomous Driving Systems

Author

Cao, Yulong, Xiao, Chaowei, Yang, Dawei, Fang, Jing, Yang, Ruigang, Liu, Mingyan, and Li, Bo

Subjects
Computer Science - Cryptography and Security, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Deep neural networks (DNNs) are found to be vulnerable against adversarial examples, which are carefully crafted inputs with a small magnitude of perturbation aiming to induce arbitrarily incorrect predictions. Recent studies show that adversarial examples can pose a threat to real-world security-critical applications: a "physical adversarial Stop Sign" can be synthesized such that the autonomous driving cars will misrecognize it as others (e.g., a speed limit sign). However, these image-space adversarial examples cannot easily alter 3D scans of widely equipped LiDAR or radar on autonomous vehicles. In this paper, we reveal the potential vulnerabilities of LiDAR-based autonomous driving detection systems, by proposing an optimization based approach LiDAR-Adv to generate adversarial objects that can evade the LiDAR-based detection system under various conditions. We first show the vulnerabilities using a blackbox evolution-based algorithm, and then explore how much a strong adversary can do, using our gradient-based approach LiDAR-Adv. We test the generated adversarial objects on the Baidu Apollo autonomous driving platform and show that such physical systems are indeed vulnerable to the proposed attacks. We also 3D-print our adversarial objects and perform physical experiments to illustrate that such vulnerability exists in the real world. Please find more visualizations and results on the anonymous website: https://sites.google.com/view/lidar-adv.

Published
2019

217. Prevalence of Self-Reported Hypertension and Antihypertensive Medication Use Among Adults--United States, 2017-2021

Author

Sekkarie, Ahlia, Fang, Jing, Hayes, Donald, and Loustalot, Fleetwood

Subjects
Heart diseases -- Drug therapy, Stroke (Disease) -- Drug therapy, Adults -- Analysis, Antihypertensive drugs -- Analysis, Hypertension -- Drug therapy, African Americans -- Analysis, Health
Abstract

Introduction Hypertension, or high blood pressure, is a major risk factor for heart disease and stroke (1). Hypertension affects approximately one in two U.S. adults aged [greater than or equal [...]

Published
2024

230. Fructose-1,6-bisphosphatase 1 functions as a protein phosphatase to dephosphorylate histone H3 and suppresses PPARα-regulated gene transcription and tumour growth

Author

Wang, Zheng, Li, Min, Jiang, Hongfei, Luo, Shudi, Shao, Fei, Xia, Yan, Yang, Mengke, Ren, Xiangle, Liu, Tong, Yan, Meisi, Qian, Xu, He, Haiyan, Guo, Dong, Duan, Yuran, Wu, Ke, Wang, Lei, Ji, Guimei, Shen, Yuli, Li, Lin, Zheng, Peixiang, Dong, Bofei, Fang, Jing, Zheng, Min, Liang, Tingbo, Li, Haitao, Yu, Rilei, Xu, Daqian, and Lu, Zhimin

Published
2022
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237. Network Information Utilization Technology Based on Information Retrieval Technology

Author

Fang, Jing, Liu, Jun, Chen, Youchen, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Hung, Jason C., editor, Chang, Jia-Wei, editor, Pei, Yan, editor, and Wu, Wei-Chen, editor

Published
2022
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238. Identifying Flight Trajectory Patterns via a Density-Aided Hierarchical Clustering Algorithm

Author

Zhang, Zhuxi, Chen, Yichong, Fang, Jing, Zhou, Xueyang, An, Yuhang, Zhu, Xi, Chinese Society of Aeronautics and Astronautics, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, and Zhang, Junjie James, Series Editor

Published
2022
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249. Effects of chronic renal failure on intestinal mucosal barrier and expression of autophagy related proteins in rats

Author

ZHANG Zi-yuan, FANG Jing-ai, LI Su-fen, HU Ya-ling, ZHANG Xiao-dong, LIU Wen-yuan, LIU Xue-jun

Subjects
autophagy, chronic renal failure, intestinal mucosal barrier, Medicine
Abstract

Objective To observe the injury of intestinal mucosal barrier and the expression of autophagy protein in colon tissue of rats with chronic renal failure. Methods Thirty SPF healthy male SD rats were randomly divided into sham operation group (10 rats) and model group (20 rats). The model group was given adenine 200 mg/(kg·d) by gavage for 4 weeks after left nephrectomy. The general conditions of rats were observed. Serum, renal tissue and colon tissue samples were collected at 4 and 8 weeks after gavage. The levels of serum creatinine, urea nitrogen, TNF-α, IL-6 and LPS were measured by ELISA. Renal and colon tissue were examined by HE staining and microscopy. The protein expressions of LC3, beclin-1, ZO-1 and claudin-1 were detected by Western blot. Results Compared with the sham operation group, the model group rats gradually showed a slow response to external stimuli, slow action, withered and yellow hair color, dull luster, pale conjunctiva and slow weight gain. The levels of serum creatinine, urea nitrogen and inflammatory factors in the model group were all higher than those in the sham operation group, and increased at 8 weeks compared with 4 weeks (P＜0.05). Renal pathology in the model group showed renal tubular dilatation, lymphatic and monocyte infiltration, glomerulosclerosis and interstitial fibrosis. Histopathology of colon in model group showed atrophy and collapse of intestinal villi, infiltration of inflammatory cells in mucosal layer and aggravation of pathological changes, which was more serious at 8 weeks than at 4 weeks. The expression of LC3Ⅱ/Ⅰ, Beclin-1, ZO-1 and Claudin-1 in the model group decreased as compared to those of sham operation group(P＜0.05), and much decreased at 8 weeks as compared with 4 weeks (P＜0.05). Conclusions Autophagy disorder may be a potential mechanism causing intestinal mucosal barrier injury in rats with chronic renal failure.

Published
2022
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