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IEEE International Conference on Communications (ICC)

作者： Zhiyu Zhu Yang Yang Mingzhe Chen Caili Guo Yipeng Bai Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral Gables FL USA Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

Visible light positioning (VLP) is a promising positioning technique, which, however, typically requires multiple luminaires to achieve accurate positioning. This paper proposes a novel visual odometry (VO) assisted visible light positioning algorithm (VO-VLP) in achieving positioning with only a single luminaire. In the considered model, a user equipped with a camera jointly uses geometric features in the captured images and coordinates information obtained via visible light communication (VLC) for positioning. The proposed VLP algorithm does not rely on any extra inertial measurement unit and relaxes the tilted angle limitation at the user. In particular, VO-VLP first uses the circle feature of a luminaire to obtain dual normal vectors of the luminaire. Then, the basic principle of VO is used to eliminate the wrong normal vector by exploiting the geometric features in two consecutive images captured when the user moves. Finally, the pose and location of the user are obtained by using an artificially marked point on the luminaire's contour. VO-VLP can achieve accurate positioning with only a single luminaire and a camera. Simulation results show that the proposed indoor positioning algorithm can achieve a 97th-percentile positioning accuracy of around 10 cm.

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Fusing Bluetooth with Pedestrian Dead Reckoning: A Floor Plan-Assisted Positioning Approach

arXiv

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arXiv 2025年

作者： Pan, Wenxuan Yang, Yang Chen, Mingzhe Wei, Dong Guo, Caili Mao, Shiwen Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Department of Electrical and Computer Engineering the Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Wireless Engineering Research and Education Center Auburn University AuburnAL36849 United States

Floor plans can provide valuable prior information that helps enhance the accuracy of indoor positioning systems. However, existing research typically faces challenges in efficiently leveraging floor plan information and applying it to complex indoor layouts. To fully exploit information from floor plans for positioning, we propose a floor plan-assisted fusion positioning algorithm (FP-BP) using Bluetooth low energy (BLE) and pedestrian dead reckoning (PDR). In the considered system, a user holding a smartphone walks through a positioning area with BLE beacons installed on the ceiling, and can locate himself in real time. In particular, FP-BP consists of two phases. In the offline phase, FP-BP programmatically extracts map features from a stylized floor plan based on their binary masks, and constructs a mapping function to identify the corresponding map feature of any given position on the map. In the online phase, FP-BP continuously computes BLE positions and PDR results from BLE signals and smartphone sensors, where a novel grid-based maximum likelihood estimation (GML) algorithm is introduced to enhance BLE positioning. Then, a particle filter is used to fuse them and obtain an initial estimate. Finally, FP-BP performs post-position correction to obtain the final position based on its specific map feature. Experimental results show that FP-BP can achieve a real-time mean positioning accuracy of 1.19 m, representing an improvement of over 28% compared to existing floor plan-fused baseline algorithms. Copyright © 2025, The Authors. All rights reserved.

关键词： Photomapping

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Early Detection of Cercospora and Powdery Mildew Diseases in Sugar Beet Using UAV-Based Remote Sensing and Machine Learning

SSRN

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SSRN 2024年

作者： Tuğrul, Koç Mehmet Kaya, Rıza Özkan, Kemal Ceyhan, Merve Gürel, Uğur Fidantemiz, Yavuz Fatih Aydoğdu, Muharrem Eskişehir Osmangazi University Faculty of Agriculture Turkey Turkish Sugar Factories Corp. Sugar Institute Plant Protection Department Turkey Eskişehir Osmangazi University Faculty of Engineering and Architecture Department of Computer Engineering Turkey Republic of Türkiye Ministry of Agriculture and Forestry Transitional Zone Agricultural Research Institute Directorate Agricultural Irrigation and Land Reclamation Unit Turkey Republic of Türkiye Ministry of Agriculture and Forestry General Directorate of Agricultural Reform Agricultural Production Enterprise Directorate of Agricultural Extension In-Service Training Center Turkey Turkish Academic Network and Information Centre Turkey

Agricultural production, vital for nutrition, hurts its yield, quality, and overall production due to the negative effects of diseases and pests. Remote sensing technologies have become an important tool for diagnosing and monitoring diseases, compared to traditional methods, which are time-consuming and have limited sampling. High-resolution drone and satellite images provide fast and accurate solutions to detect and diagnose product development, health, pests, and *** research was carried out to investigate whether it is possible to detect Cercospora leaf spot (Cercospora beticola Sacc.) disease and Powdery Mildew (Erysiphe betae (Vaňha) Weltzien) disease, which cause significant economic losses in sugar beet, in the early period before the disease is physically seen, with images taken with UAV under field conditions. To reveal the difference in the methods applied in producer fields, topics were created such as control in the Cercospora field (without pesticide), Metos climate station early warning system and processing of UAV-based images, control in the Powdery mildew field, visual detection of the disease and spraying according to the processing of UAV-based images, and three topics were created. Trial plots were created for the subject with six replications. According to the research results, it was determined that there was a decrease in the NDVI index values in the leaves before the disease occurred in the images obtained with UAV-based images and that this change was an important warning about the onset of the disease. Accordingly, it has been demonstrated that it is possible to detect diseases early with KNN and LR algorithms, which provide high discrimination and prediction success. © 2024, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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A Survey on Indoor Visible Light Positioning Systems: Fundamentals, Applications, and Challenges

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IEEE Communications Surveys and Tutorials 2024年

作者： Zhu, Zhiyu Yang, Yang Chen, Mingzhe Guo, Caili Cheng, Julian Cui, Shuguang Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China University of Miami Department of Electrical and Computer Engineering and Institute for Data Science and Computing Coral GablesFL33146 United States Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing100876 China The University of British Columbia Faculty of Applied Science School of Engineering KelownaBCV1V 1V7 Canada 518172 Hong Kong

The growing demand for location-based services in areas like virtual reality, robot control, and navigation has intensified the focus on indoor localization. Visible light positioning (VLP), leveraging visible light communications (VLC), becomes a promising indoor positioning technology due to its high accuracy and low cost. This paper provides a comprehensive survey of VLP systems. In particular, since VLC lays the foundation for VLP, we first present a detailed overview of the principles of VLC. Then, we provide an in-depth overview of VLP algorithms. The performance of each positioning algorithm is also compared in terms of various metrics such as accuracy, coverage, and orientation limitation. Beyond the physical layer studies, the network design for a VLP system is also investigated, including multi-access technologies, resource allocation, and light-emitting diode (LED) placements. Next, the applications of the VLP systems are overviewed. Finally, this paper outlines open issues, challenges, and opportunities for the research field. In a nutshell, this paper constitutes the first holistic survey on VLP from state-of-the-art studies to practical uses. © 1998-2012 IEEE.

关键词： Resource allocation

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DFGC-VRA: DeepFake Game Competition on Visual Realism Assessment

DFGC-VRA: DeepFake Game Competition on Visual Realism Assess...

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IEEE International Joint Conference on Biometrics (IJCB)

作者： Bo Peng Xianyun Sun Caiyong Wang Wei Wang Jing Dong Zhenan Sun Rongyu Zhang Heng Cong Lingzhi Fu Hao Wang Yusheng Zhang Hanyuan Zhang Xin Zhang Boyuan Liu Hefei Ling Luka Dragar Borut Batagelj Peter Peer Vitomir Štruc Xinghui Zhou Kunlin Liu Weitao Feng Weiming Zhang Haitao Wang Wenxiu Diao Center for Research on Intelligent Perception and Computing (CRIPAC) Institute of Automation Chinese Academy of Sciences (CASIA) Beijing China Beijing University of Civil Engineering and Architecture (BUCEA) China Interactive Entertainment Group of Netease Inc Guangzhou China Huazhong University of Science and Technology (HUST) China Faculty of Computer and Information Science University of Ljubljana (UNILJ) Slovenia Faculty of Electrical Engineering University of Ljubljana (UNILJ) Slovenia University of Science and Technology of China (USTC) China Institute of Network Technology (INT) Yantai China Nanjing University of Science and Technology (NUST) China

This paper presents the summary report on the DeepFake Game Competition on Visual Realism Assessment (DFGC-VRA). Deep-learning based face-swap videos, also known as deepfakes, are becoming more and more realistic and deceiving. The malicious usage of these face-swap videos has caused wide concerns. There is a ongoing deepfake game between its creators and detectors, with the human in the loop. The research community has been focusing on the automatic detection of these fake videos, but the assessment of their visual realism, as perceived by human eyes, is still an unexplored dimension. Visual realism assessment, or VRA, is essential for assessing the potential impact that may be brought by a specific face-swap video, and it is also useful as a quality metric to compare different face-swap methods. This is the third edition of DFGC competitions, which focuses on the new visual realism assessment topic, different from previous ones that compete creators versus detectors. With this competition, we conduct a comprehensive study of the SOTA performance on the new task. We also release our MindSpore codes to further facilitate research in this field (https://***/bomb2peng/DFGC-VRA-benckmark).

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SCENIC: An Area and Energy-Efficient CNN-based Hardware Accelerator for Discernable Classification of Brain Pathologies using MRI

SCENIC: An Area and Energy-Efficient CNN-based Hardware Acce...

引用

International Conference on VLSI Design

作者： Bodepu Sai Tirumala Naidu Shreya Biswas Rounak Chatterjee Sayak Mandal Srijan Pratihar Ayan Chatterjee Arnab Raha Amitava Mukherjee Janet Paluh SandLogic Technologies Bangalore India Department of Electronics and Telecommunication Engineering Jadavpur University Kolkata India Network Science Institute Northeastern University Boston USA Advanced Architecture Research Intel Edge.AI Intel Corporation Santa Clara USA Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Amritapuri India College of Nanoscale Science and Engineering Nanobioscience SUNY Polytechnic Institute Albany New York USA

ISBN: (数字)9781665485050

ISBN: (纸本)9781665496612

Biomedical brain imaging lies at the interface of visual, and spatial neuropathology and neurosurgical intervention. Future treatments are expected to require greater feature detail in imaging as well as underlying mechanisms that will be synergistically advanced. This will be made more accessible via low power embedded devices and cloud platforms through applied deep learning software and hardware analysis. Towards that end, we develop a hardware-software co-design technique referred to as SCENIC (or, Separable Convolution Enabled Non-Invasive Classification) for the identification and classification of glioma brain tumors, using physical tissue features reflected in parameter weighted MRI scan types such as-T1-w, T1-ce, T2-w and FLAIR. The high performance hardware exceeds current accuracy, resource efficiency and time consumption parameters. The proposed SCENIC-CNN Accelerator is synthesized on 45 nm process technology andit can operate at a minimum frequency of 1GHz while maintaining low-power consumption of only 0.36 W and a low chip-area size of 0.431mm 2 . Our classification accuracy achieves 98.3% in detection of the presence of a tumor pathology and 99.62% within classification of imaging modalities that relate to tissue parameters such as fat content, blood or CSF flow and tissue density. Compared to prominent state-of the-art Convolutional Neural network (CN) models being designed for biomedical imaging, SCENIC is competitive versus XceptionNet, InceptionV3, ResNet-50, and VGG-16. With model compression techniques, SCENIC requires a memory space of less than 0.265MB. We discuss design methodology as applied to future goals to meet challenging needs to distinguish tumor origins, such as glioma and metastasized tumors, along with other neuropathologies that may be TBI, vascular or developmental. SCENIC will aid impactful, cost-effective, rapid and accurate neurosurgical intervention and treatments.

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Long Text Classification Based on BERT 5

Long Text Classification Based on BERT

引用

5th IEEE Information Technology, networking, Electronic and Automation Control Conference, ITNEC 2021

作者： Weijie, DIng Yunyi, Li Jing, Zhang Xuchen, Shen Big-data and Network Security Research Institute Zhejiang Police College Hangzhou310053 China College of Information Engineering Zhejiang University of Technology Hangzhou310023 China Key Laboratory of Public Security Information Application Based on Big-data Architecture Ministry of Public Security Hangzhou310053 China Zhejiang Police College Department of Investigation Hangzhou310053 China Zhejiang Police College Department of Computer and Information Security Hangzhou310053 China Science and Technology Management Section Hangzhou311203 China

ISBN: (纸本)9781665415989

Existing text classification algorithms generally have limitations in terms of text length and yield poor classification results for long texts. To address this problem, we propose a BERT-based long text classification method. First, we slice the long text and use BERT to encode the sliced clauses to obtain the local semantic information. Second, we use BiLSTM to fuse the local semantic information and adopt the attention mechanism to increase the weight of important clauses in the long text, so as to obtain the global semantic information. Finally, the global semantic information is input to the softmax layer for classification. Experimental results show that the proposed method achieves higher accuracy than commonly used models. © 2021 IEEE.

关键词： Classification (of information)

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A Survey on Indoor Visible Light Positioning Systems: Fundamentals, Applications, and Challenges

arXiv

引用

arXiv 2024年

作者： Zhu, Zhiyu Yang, Yang Chen, Mingzhe Guo, Caili Cheng, Julian Cui, Shuguang The Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States The Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The Faculty of Applied Science School of Engineering The University of British Columbia KelownaBCV1V 1V7 Canada The Chinese University of Hong Kong Shenzhen518172 China

关键词： Resource allocation

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Adaptive Information Bottleneck Guided Joint Source and Channel Coding for Image Transmission

arXiv

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arXiv 2022年

作者： Sun, Lunan Yang, Yang Chen, Mingzhe Guo, Caili Saad, Walid Poor, H. Vincent The Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States The Beijing Laboratory of Advanced Information Net works School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The Wireless@VT Group Bradley Department of Electrical and Computer Engineering Virginia Tech ArlingtonVA United States The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

Joint source and channel coding (JSCC) for image transmission has attracted increasing attention due to its robustness and high efficiency. However, the existing deep JSCC research mainly focuses on minimizing the distortion between the transmitted and received information under a fixed number of available channels. Therefore, the transmitted rate may be far more than its required minimum value. In this paper, an adaptive information bottleneck (IB) guided joint source and channel coding (AIB-JSCC) method is proposed for image transmission. The goal of AIB-JSCC is to reduce the transmission rate while improving the image reconstruction quality. In particular, a new IB objective for image transmission is proposed so as to minimize the distortion and the transmission rate. A mathematically tractable lower bound on the proposed objective is derived, and then, adopted as the loss function of AIB-JSCC. To trade off compression and reconstruction quality, an adaptive algorithm is proposed to adjust the hyperparameter of the proposed loss function dynamically according to the distortion during the training. Experimental results show that AIB-JSCC can significantly reduce the required amount of transmitted data and improve the reconstruction quality and downstream task accuracy. Copyright © 2022, The Authors. All rights reserved.

关键词： Economic and social effects

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A Review on Current and Old SCADA networks Applied to Water Distribution Systems 1

A Review on Current and Old SCADA Networks Applied to Water ...

引用

1st International Conference of Intelligent Computing and Engineering, ICOICE 2019

作者： Franco, Daniel Jose Muhammed, Abdullah Bin Subramaniam, Shamala K. Abdullah, Azizol Silva, Rui Miguel Akram, Omar Khasro University Putra Malaysia Department of Communication Technology and Network Serdang Malaysia Lab Ubinet Computer Security and Cybercrime Polytechnic Institute of Beja Department of Engineering Beja Portugal University Putra Malaysia Department of Architecture Serdang Malaysia

ISBN: (纸本)9781728144870

Water is probably the oldest factor receiving attention from the population, since the beginning of the human race. The evolution of water supply systems is directly related to the urban growth of the cities and their geographical location. This study focuses on SCADA (Supervisory Control And Data Acquisition) systems used to control and managing water distribution systems all around the world, highlighting their components and deeply approaching SCADA networks and communication protocols. Based on the need of protection and security on SCADA networks, this study aims to provide a review of the existing literature, through the case study of water distribution systems, identifying the different components of a SCADA system, as well as its communication architectures and protocols and some known attacks, to design a framework on current and old SCADA networks. Results show that SCADA systems are not just applied to water distribution and water waste systems, but also to many other industrial automated systems that control on crucial systems. The security of such systems is yet weak and faces many vulnerabilities and threats, where security mechanisms must be applied. For this purpose, the study of SCADA networks and communications is considered a crucial point for the correct development of security tools. © 2019 IEEE.

关键词： SCADA systems

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