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7 results on '"Anguo Zhao"'

1. Biomarker profiling to determine clinical impact of microRNAs in cognitive disorders

Author

Weijie Zhai, Meng Zhao, Chunxiao Wei, Guimei Zhang, Yiming Qi, Anguo Zhao, and Li Sun

Subjects
Alzheimer’s disease, Bioinformatics, Cognitive impairment, Dementia, Post-stroke cognitive impairment, MicroRNA, Medicine, Science
Abstract

Abstract Alzheimer’s disease (AD) and post-stroke cognitive impairment (PSCI) are the leading causes of progressive dementia related to neurodegenerative and cerebrovascular injuries in elderly populations. Despite decades of research, patients with these conditions still lack minimally invasive, low-cost, and effective diagnostic and treatment methods. MicroRNAs (miRNAs) play a vital role in AD and PSCI pathology. As they are easily obtained from patients, miRNAs are promising candidates for the diagnosis and treatment of these two disorders. In this study, we performed complete sequencing analysis of miRNAs from 24 participants, split evenly into the PSCI, post-stroke non-cognitive impairment (PSNCI), AD, and normal control (NC) groups. To screen for differentially expressed miRNAs (DE-miRNAs) in patients, we predicted their target genes using bioinformatics analysis. Our analyses identified miRNAs that can distinguish between the investigated disorders; several of them were novel and never previously reported. Their target genes play key roles in multiple signaling pathways that have potential to be modified as a clinical treatment. In conclusion, our study demonstrates the potential of miRNAs and their key target genes in disease management. Further in-depth investigations with larger sample sizes will contribute to the development of precise treatments for AD and PSCI.

Published
2024
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5. Activity Recognition and Localization based on UWB Indoor Positioning System and Machine Learning

Author

Ruofei Chang, Long Cheng, Anguo Zhao, Kexin Wang, Yifan Wang, and Hengguang Li

Subjects
Artificial neural network, Computer science, business.industry, Ultra-wideband, 020206 networking & telecommunications, Robotics, 02 engineering and technology, Kalman filter, Machine learning, computer.software_genre, Support vector machine, Activity recognition, Indoor positioning system, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Artificial intelligence, Hidden Markov model, business, computer
Abstract

Joint activity recognition and localization plays an important role in many fields such as smart healthcare system, smart home, human-computer interaction, and robotics. Ultrawideband (UWB) is considered as a promising technology for high-precision indoor positioning system. But few studies have been done to simultaneously recognize and localize human activities based on the UWB indoor positioning system. In this paper, the possibility of simultaneously recognizing and localizing human activities with a self-developed UWB indoor positioning system is investigated. First, a few signal processing and machine learning techniques are applied to improve the positioning accuracy of the UWB indoor positioning system. Three machine learning methods based on support vector machine, artificial neural network, and hidden Markov model are then used to recognize five types of human activities based on the range measurements from the UWB indoor positioning system. Experimental results show that our approach achieves satisfactory performances in the joint activity recognition and localization task.

Published
2020

6. Ultra Wideband Indoor Positioning System based on Artificial Intelligence Techniques

Author

Zhaoqi Wu, Anguo Zhao, Bo Lai, Yuanting Wang, Qiang Yang, and Long Cheng

Subjects
Signal processing, Multipath interference, Computer science, business.industry, Ultra-wideband, 020206 networking & telecommunications, Ranging, 02 engineering and technology, Kalman filter, Radio navigation, Field (computer science), Indoor positioning system, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Artificial intelligence, business
Abstract

High-precision indoor positioning has nowadays emerged as a critical function for many applications. However, many existing indoor positioning systems either fail to achieve a high positioning accuracy or are very easily affected by indoor environments composed of many obstacles, preventing them from satisfying many application requirements. Ultra wideband (UWB) has recently drawn extensive attention in the field of indoor positioning due to its great ability to achieve high ranging and localization accuracy while minimizing the effect of multipath interference. Meanwhile, advanced artificial intelligence and signal processing techniques have been explored to improve the precision and performance of indoor positioning system. In this paper, a high-precision UWB indoor positioning system integrating artificial intelligence and signal processing techniques is designed. And field tests are also conducted to validate the design of the system.

Published
2020

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