Hao Xiang(向浩)

Hao Xiang(向浩)

A doctoral student

Posts by Collection

portfolio

Edge computing Network Platform for Tactile Internet

The platform is divided into three modules: master domain, network domain, and controlled domain. In the controlled domain, the ROS platform is used to simulate the robot experimental environment, and instantiate the virtual manipulator and virtual objects (such as tables and bricks). Secondly, the master domain is the geographic touch terminal operated by humans, and the network domain is the traditional Ethernet USB, which represents network transmission. edge computing devices are used for resource allocation, including bandwidth, storage and other benefits. When users operate a robotic arm, they can provide virtual tactile feedback. What’s even more exciting is that when users touch a table or brick, the geomatic touch terminal is similar to touching a table in front of them. Therefore, the tactile internet provides a practical platform for tactile senses, which can be widely used in applications such as treatment, disaster relief, shopping, and provides a new network paradigm for human-mechine interaction.

Edge Computing Empowered Tactile Internet for Human Digital Twin in Physical Theraphy

This platform is mainly aimed at physical therapy applications and is divided into three modules: main domain, network domain, and controlled domain. The main control domain provides physical therapists with two operational behaviors (massage and hitting), where tapping is provided through geomatic touch and massage is provided through tactile gloves, and transmitted through the network domain to the controlled domain. Within the controlled domain, virtual high-fidelity scene modeling is provided, including virtual environments and physical therapy patients. Different operating systems in the main control domain provide different tactile feedback, which is exciting, The next step is to feed back the obtained tactile data to the human digital twin system, providing dynamic monitoring of patient data and ensuring safe data for patients.

Tactile Internet empowers medical servicest

The platform is divided into three modules for human organ therapy (such as vascular dredging): main domain, network domain, and controlled domain. In the control domain, Unity technology is used to virtualize human blood vessels and other internal organs. The left image shows capillaries and the right image shows the interior of blood vessels. This model is used for real-time detection of human blood vessel changes in digital twins. Secondly, the main domain is a geographic touch terminal operated by humans, while the network domain represents traditional Ethernet USB for network transmission. Edge computing devices are used for resource allocation, including bandwidth, storage, and other benefits. When doctors operate the geomatic touch, they can receive real-time virtual tactile feedback from blood vessels, providing navigation for surgery and vascular dredging (collision detection will be performed when touching the inside of the blood vessels, providing hardness feedback). The tactile feedback of this collision detection is exciting. When users navigate in real-time, it can detect whether the inner wall of blood vessels is blocked, and it can be unblocked, providing navigation effects for blood vessel routes, and can be promoted to other topics related to human health.

publications

Big data cloud platform server load balancing algorithm based on improved chaotic partition algorithm

Published in Journal 1, 2021

Due to the heterogeneity of big data cloud platform and the uneven distribution of data between cloud servers, when cloud server cluster processes a large number of tasks, the node load is often uneven. To solve this problem, a load balancing algorithm based on improved chaotic partition algorithm for big data cloud platform server is proposed. According to the statistics of the average resource consumption of various services provided by the cluster, combined with the running time and resource occupation of tasks on the server, the total remaining task load of the server at a certain time point is predicted, so as to obtain the actual task load status of the node, and correct the task load in time. Experiments show that the load balancing algorithm of big data cloud platform server based on improved chaotic partition algorithm can effectively balance the load of multi task heterogeneous cloud servers, and has high feasibility, Then, based on this improved load balancing algorithm, we can also extend it to the application of multi-objective algorithm, such as robot path planning, target allocation scheduling algorithm and so on. There will be similar and reasonable performance compared with the same period last year.

Recommended citation: Xiang H , Zhang T , Li Z .Big data cloud platform server load balancing algorithm based on improved chaotic partition algorithm[J].Journal of Physics: Conference Series, 2021, 1982(1):012116-.DOI:10.1088/1742-6596/1982/1/012116. https://iopscience.iop.org/article/10.1088/1742-6596/1982/1/012116/pdf

Yak Object Detection Based on Data Augmentation of Style Transfer Method

Published in Conference 1, 2022

To address the issue of complex yak data collection in the plateau area, as well as a lack of data, which leads to the limitation of the object detection model, a data enhancement method based on style transfer is used to increase the number of Tibetan plateau yak samples and improve object detection accuracy. In this study, we examine the results of several generative adversarial networks using the cycle generative adversarial network technique of alternate insertion residual network. Extend the original 450 yak data set by two times, manually generate four different data sets, compare the accuracy of different data sets using the YOLOv3 [1] object detection model, and verify that the alternating insertion residual network recurrent generation counter network improves the data effect. The test results suggest that this strategy may significantly enhance item detection accuracy in small samples.

Recommended citation: P. Gu, Z. Dong, Y. Xiao and H. Xiang, "Yak Object Detection Based on Data Augmentation of Style Transfer Method," 2021 International Conference on Information Technology and Biomedical Engineering (ICITBE), Nanchang, China, 2021, pp. 243-247, doi: 10.1109/ICITBE54178.2021.00060. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9694361

Research on State Modeling of Multiple Parsers Based on Attention Mechanism

Published in Conference 1, 2022

Transition-based dependency parsing is a fast and effective approach for dependency parsing. When the sentence is input to the transition-based dependency parser, the parser predicts a series of parsing actions from left to right. Stack information, which plays an essential role in the parsing process. In this paper, we propose a dependency parser that is based on bidirectional-LSTMs and an approach that uses the attention mechanism for learning representations of parser states. This model simulates the global state of the parser by capturing more relevant information, we dig into the stack information, buffer information, the word information that has been parsed out of the stack, the complete historical information of the actions taken by the parser, and semantic information during the parsing process. The words popped from the stack at each time step and the predicted action are then applied to the parsing task at the next time step, which is helpful to the parsing performance of the parser.

Recommended citation: B. Li, H. Xiang, C. Xiangxiu and N. Qun, "Research on State Modeling of Multiple Parsers Based on Attention Mechanism," 2021 2nd International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI), Shenyang, China, 2021, pp. 198-203. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9708445

PRSNet: A Masked Self-Supervised Learning Pedestrian Re-Identification Method

Published in Conference 1, 2022

In recent years, self-supervised learning has attracted widespread academic debate and addressed many of the key issues of computer vision. The present research focus is on how to construct a good agent task that allows for improved network learning of advanced semantic information on images so that model reasoning is accelerated during pre-training of the current task. In order to solve the problem that existing feature extraction networks are pre-trained on the ImageNet dataset and cannot extract the fine-grained information in pedestrian images well, and the existing pre-task of contrast self-supervised learning may destroy the original properties of pedestrian images, this paper designs a pre-task of mask reconstruction to obtain a pre-training model with strong robustness and uses it for the pedestrian re-identification task. The training optimization of the network is performed by improving the triplet loss based on the centroid, and the mask image is added as an additional sample to the loss calculation, so that the network can better cope with the pedestrian matching in practical applications after the training is completed. This method achieves about 5% higher mAP on Marker1501 and CUHK03 data than existing self-supervised learning pedestrian re-identification methods, and about 1% higher for Rank1, and ablation experiments are conducted to demonstrate the feasibility of this method. Our model code is located at this https URL.

Recommended citation: Xiao, Zhijie et al. “PRSNet: A Masked Self-Supervised Learning Pedestrian Re-Identification Method.” ArXiv abs/2303.06330 (2023): n. pag. https://arxiv.org/pdf/2303.06330.pdf

Research on Recommender System Based on Curiosity Guided Identity Modification

Published in Conference 1, 2022

Faced with the problem of information overload of big data, multi-factor fusion is the key technology of recommendation systems. How to provide personalized products for users accurately is the demand of recommendation system. Therefore, a new nearest neighbor algorithm is proposed to fuse the two kinds of identity and use curiosity as guidance to mining hidden information more efficiently, although the algorithm of curiosity modified identification degree swings in a small range, other evaluation indexes are improved. The improvement of the Receiver Operating Characteristic (ROC) curve shows that the robustness and improvement degree of the sub-algorithm is more significant.

Recommended citation: Xiang H, Dong Z, Gu P, et al. Research on Recommender System Based on Curiosity Guided Identity Modification[C]//2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture. 2021: 333-340. https://dl.acm.org/doi/pdf/10.1145/3495018.3495075

Edge Computing Empowered Tactile Internet for Human Digital Twin: Visions and Case Study

Published in magazine 1, 2023

Tactile Internet (TI), with the capability of providing multisensory haptic human-machine interactions, is envisioned as a key enabling technology for an emerging application, called human digital twin (HDT). HDT is expected to revolutionize the human lifestyle and prompts the development of Metaverse. However, the realization of HDT poses stringent demands on pervasive connectivity, real-time feedback, high-fidelity modeling and ultra-high reliability (between physical and virtual spaces), which can hardly be met by TI only. In this article, we thus shed light on the design of edge computing empowered TI (ECoTI) for HDT. Aiming at offering strong interactions and extremely immersive quality of experience, we introduce the system architecture of ECoTI for HDT, and analyze its major design requirements and challenges. Moreover, we present core guidelines and detailed steps for system implementations. In addition, we conduct an experimental study based on our recently built testbed, which shows a particular use case of ECoTI for HDT in physical therapy, and the results indicate that the proposed framework, i.e., ECoTI, can significantly improve the effectiveness of the system. Finally, we conclude this article with a brief discussion of open issues and future directions.

Recommended citation: *Hao Xiang*, Kun Wu, Jiayuan Chen, Changyan Yi, Jun Cai, Dusit Niyato, Xuemin, Shen. (2023). "Edge Computing Empowered Tactile Internet for Human Digital Twin: Visions and Case Study." Magazine 1. 1(1). http://xianghao.github.io/files/paper1.pdf](https://arxiv.org/pdf/2304.07454.pdf

talks

Talk 1 on Relevant Topic in Your Field

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teaching

Data Analysis and Application Based on Python

Undergraduate Course Training, Xinjiang University, School of Software，Southwest Jiaotong University, Panzhihua College, 2022

In response to the weak environment of undergraduate students, cultivate and cultivate the ability to analyze data, master the core and essence of Python programming language, explain the enterprise data analysis process, require undergraduate students to independently develop projects from an enterprise perspective, conduct project selection, requirement analysis, detailed design, testing, writing process documents, testing, and submitting reports to complete the process, and enhance the ability to develop processes for enterprises, And able to possess certain machine learning algorithms.

Development of Aircraft Battle Project Based on Qt

Undergraduate course, School of Software, Xinjiang University, 2022

Targeting the weak environment of undergraduate students, cultivating programming design thinking (C++direction), mastering the core and essence of C++and Qt programming languages, explaining the aircraft war project, requiring undergraduate students to independently develop a project from the perspective of the enterprise, conducting project selection, requirement analysis, detailed design, testing, writing process documents, defense, and submitting reports to complete the process, Enhance the mindset and ability of enterprise oriented development processes.