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6th International conference on Software Testing, Machine Learning and Complex Process Analysis, TMPA 2021

作者： Dubinin, D.V. Kochegurov, A.I. Kochegurova, E.A. Geringer, V.E. Tomsk State University of Control Systems and Radioelectronics Prospect Lenina 40 Tomsk634050 Russia National Research Tomsk Polytechnic University Lenin Avenue 30 Tomsk634050 Russia Ravensburg Fallenbrunnen 2 Friedrichshafen88045 Germany

ISBN: (纸本)9783031504228

The paper describes a mechanism for modeling an optical flow as a random vector field – closed areas on the image plane with certain brightness and dynamics of changes in the vector field. The optical flow is formed by a homogeneous, three-dimensional point renewal process. The characteristics of the vector field on the image plane of the resulting optical flow are interconnected by the Palm’s formulas. The type of the constituent elements of the vector field (the alphabet, which determines the morphology of the field on the image plane) is chosen randomly. The proposed approach will produce various types of interconnected digital sequences of images with horizontal, vertical and diagonal elements;create the prerequisites for efficient and flexible motion analysis on digital video sequences;make it possible to use the probabilistic factor in researching image processing algorithms and comparing the algorithms based on a detailed factor analysis. © 2024, Springer Nature Switzerland AG.

关键词： optical flows

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A Word Structure Similarity Framework for Wordle Game 15

A Word Structure Similarity Framework for Wordle Game

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15th International conference on Signal processing systems, ICSPS 2023

作者： Huang, Yi Rao, Wenjun Lao, Bin Lu, Wei Han, Ling Bo School of Information Science and Technology Guangdong University of Foreign Studies China School of Foreign Languages Sun Yat-sen University China School of Electronics and Information Engineering Guangdong Ocean University China

ISBN: (纸本)9781510675056

In 2022, lots of tweets consisting of emoji squares and a few words describing moods emerge on Twitter. In fact, it is the result of a word guessing game called Wordle. In order to figure out the relationship among words in Wordle, this paper tries to study the feedback data of its players and extract useful information to further improve the design of Wordle as well as other games of its kind. Specifically, from the perspective of word structure, strict and fuzzy matching algorithms were designed to simulate the data distribution of target word, while some common structure features of words were extracted and weighted by word frequency. On one hand, the data distribution of the target word is simulated with reference to the words with the most similar structures. On the other hand, the difficulty of a word in the Wordle game was quantified by analyzing the number of player’s tries, and then the difficulty coefficient of each word was calculated. Combined with the above numerical algorithms, the difficulty of the target word was evaluated objectively by the difficulty of its similar word sequences. Experiments showed that the proposed framework achieved good performance on the Wordle dataset. Our work was awarded Honorable Mention in 2023 Mathematical Contest in Modeling (MCM). © 2024 SPIE.

关键词： Data mining

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Network Asset Sensitive information Management System Based on Golang

Network Asset Sensitive Information Management System Based ...

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2023 International conference on algorithms, Computing and Data processing, ACDP 2023

作者： Fu, Shichen Zhang, Kunshan State Grid Zhangzhou Electric Fujian Fuzhou China

ISBN: (纸本)9798350326680

With the swift upsurge in the quantity of IoT devices in the power Internet of Things, as well as their intrinsic heterogeneity, limited computing power, and weak network load capacity, collecting IoT assets becomes challenging, and these devices are highly susceptible to external attacks. To address this issue, a network asset sensitive information management and control tool is designed specifically for organizations such as power grids that possess numerous IoT devices and other network assets. This tool automates the collection and pre-warning of vulnerabilities associated with assets like IoT devices and domain names in the power network. By doing so, it significantly reduces the need for human resources, material costs, and potential economic losses, while also minimizing the risk of network attacks on the power grid. However, many asset-sensitive information collection systems are initially designed without sufficient consideration of corresponding security protection mechanisms, making them highly vulnerable to attacks and exploits by hackers. Consequently, these systems often suffer from incomplete information collection, leakage of sensitive information, and other abnormalities. To address these shortcomings, this study focuses on the development of a fast and accurate Internet asset high concurrency scanning tool based on the Go programming language. Additionally, it investigates device fingerprint collection methods for ports and leverages YAML integration to achieve efficient and precise device fingerprint collection. Moreover, the study explores the use of Echarts for visualizing big data, enabling data analysis visualization, and facilitating the rapid identification of risk assets by relevant personnel. Furthermore, it examines the implementation of a precise risk warning and notification function based on containerized deployment, assisting relevant personnel in promptly responding to and defending against potential threats. © 2023 IEEE.

关键词： information management

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Nano mode converter using dynamic refractive index modulation 9

Nano mode converter using dynamic refractive index modulatio...

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Nanophotonics and Micro/Nano Optics IX 2023

作者： Lv, Linji Wang, Qianqian Zhao, Kuo Liu, Ziyang Liu, Haida Yang, Chenyi Li, Dandan Chen, Ke School of Optics and Photonics Beijing Institute of Technology Beijing100081 China Key Laboratory of Photonic Information Technology Ministry of Industry and Information Technology Beijing100081 China

ISBN: (纸本)9781510667952

Active nanophotonic devices play an important role in optical communication systems. Improving modulation efficiency and reducing the footprint of these devices are crucial for low energy information processing and on chip communication. The Multi Frequency-Domain Finite Difference (MF-FDFD) algorithm was invented to address the inherent the large difference in scale between the modulation frequency and the frequency of optical waves of active nanophotonic devices. However, due to the fact that the MF-FDFD algorithm itself requires solving a large number of unknowns compared to traditional FDFD algorithms, the current MF-FDFD algorithm still stays in two-dimensional and is difficult to calculate in three-dimensional. To solve this problem, we introduced Newton and Born methods to accelerate and complete the the solution of algorithm, and developed a three-dimensional MF-FDFD algorithm. We validated our algorithm by simulating a mode converter. Our algorithm can effectively perform first principles simulations for active nanophotonic devices, laying the foundation for future intelligent inverse design. © 2023 SPIE. All rights reserved.

关键词： Newton-Raphson method

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Strengthen Aircraft Real-Time Multiple Object Tracking with optical Flow and Histogram of Oriented Gradient Provided HSMA Implemented in Low-Cost Energy VPU for UAV 3

Strengthen Aircraft Real-Time Multiple Object Tracking with ...

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3rd International conference on Innovative Research in Applied Science, Engineering and Technology, IRASET 2023

作者： Mohamed, Benaly Hajar, El Karch Noura, Jariri Rachid, El Gouri Lamaari, Hlou Abdelkader, Mezouari Ibn Tofail University Laboratory of Electronic Systems Information Processing Mechanics and Energetics Faculty of Sciences Kenitra Morocco National School of Applied Sciences Ibn Tofail University Laboratory of Advanced Systems Engineering Kenitra Morocco

ISBN: (纸本)9798350398366

Researchers and algorithm developers have always strived to make tracking more accurate than before, by developing deferents algorithms that prove their efficiency and effectiveness in international competitions (VOT, MOT challenge,...), but taking care of one side without others may be the reason why limiting the fields of application of that software, which makes them confined only to these competitions or confined to applications domains without others and this is not the end object in itself. For example, the use of complex tracking algorithms in the drone makes the processing unit very slow and unsuitable for real-time tracking, instead that the use of highly efficient processing systems for acceleration consumes a lot of energy, which reduces the time the drone stays in flight. In this paper, we suggest our approach;HashSet Matching Algorithm (HSMA) provided by optical Flow appearance features and HOG for developing an object-tracking algorithm to address the issue of a complex MOT algorithm for real-time tracking. The MOT challenge data-set experiment results show that the suggested technique can handle object occlusion difficulties successfully while reducing processing time. This algorithm is implemented in the Vision processing Unit (VPU) to enhance the time flying of UAVs and to ensure low energy consumption. Our approach performs very well in real application scenarios, demonstrating that it is more practical. © 2023 IEEE.

关键词： optical flows

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Research on traffic sign recognition algorithms for autonomous vehicles in smart city traffic systems 4

Research on traffic sign recognition algorithms for autonomo...

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4th International conference on Computer Vision and Pattern Analysis, ICCPA 2024

作者： Wang, Chuanfei School of Government Beijing Normal University Beijing100875 China

ISBN: (纸本)9781510682528

With the continuous advancement of smart city construction, autonomous driving technology is playing an increasingly important role in urban traffic systems. This study aims to explore the development and optimization of traffic sign recognition algorithms for autonomous vehicles in smart city traffic environments. By comprehensively analyzing current traffic sign recognition technologies, this paper proposes a traffic sign recognition system based on the YOLOv5 algorithm and utilizes the open-source COCO dataset for model training and testing. The images were preprocessed and annotated, employing CSPDarknet53 as the backbone network, which effectively extracts image features through multiple convolutional layers and residual blocks. A deep learning model was trained, capable of recognizing and classifying various traffic signs such as stop, speed limit, and turn signs. The research results indicate that the model demonstrates high average precision (AP) on the COCO dataset, effectively identifying traffic signs of different sizes and angles, even in complex backgrounds, with high robustness. Compared to traditional methods, the recognition accuracy has improved by 15%, and it has a significant advantage in real-time processing. © 2024 SPIE.

关键词： Object detection Detection and tracking algorithms Unmanned vehicles Performance modeling Feature extraction Image processing Data modeling Image segmentation Mathematical optimization

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Recent advances in lensless imaging

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OPTICA 2022年第1期9卷 1-16页

作者： Boominathan, Vivek Robinson, Jacob T. Waller, Laura Veeraraghavan, Ashok Rice Univ Houston TX 77005 USA Univ Calif Berkeley Berkeley CA 94720 USA

Lensless imaging provides opportunities to design imaging systems free from the constraints imposed by traditional camera architectures. Due to advances in imaging hardware, fabrication techniques, and new algorithms, researchers have recently developed lensless imaging systems that are extremely compact and lightweight or able to image higher-dimensional quantities. Here we review these recent advances and describe the design principles and their effects that one should consider when developing and using lensless imaging systems. (C) 2021 optical Society of America under the terms of the OSA Open Access Publishing Agreement

关键词： Charge coupled devices Image processing Imaging systems Three dimensional imaging Vertical cavity surface emitting lasers X ray imaging

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Algorithm for Enhancing the Resolution of Workshop Part Images

Algorithm for Enhancing the Resolution of Workshop Part Imag...

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2023 International conference on Engineering of optical System and Precision Instruments, ICEOP 2023

作者： Hua, Jiyong Yin, Hongmei Li, Zhijun Wang, Shaojun Chen, Chen College of Information Engineer Yangzhou University Yangzhou China Yangzhou Customs Yangzhou China Jiangsu Baoer Electronic Comp. Yangzhou China Jiangsu College of Tourism Yangzhou China

The resolution of the input image will affect the restoration effect of the image. In a fixed environment, obtaining high-quality images requires expensive acquisition devices, such as cameras. There are many ways to improve image quality. Instead of increasing hardware investment, it is better to find methods in image post-processing. Deep learning algorithms have obvious advantages in image processing. Based on deep learning, we propose an algorithm to convert camera captured images into high-resolution images. VDSR (Very Accurate Super Resolution) is a typical algorithm. Use residual image learning to predict accurate residual images from input images. Residual corresponds to the high-frequency information in an image, representing pixels that undergo drastic changes in the image, and can highlight the edges and contours of the target. Our proposed algorithm is more accurate than existing algorithms and improves visual effects. © Published under licence by IOP Publishing Ltd.

关键词： Learning algorithms

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A Graph Based Approach for Cyberbullying Classification Using Machine Learning algorithms 14

A Graph Based Approach for Cyberbullying Classification Usin...

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14th International conference on Intelligent systems: Theories and Applications, SITA 2023

作者： Khedraoui, Khadija Zine-Dine, Khalid Madani, Abdellah Chouaib Doukkali University Laroseri Laboratory El Jadida Morocco Mohammed v University in Rabat Faculty of Sciences Rabat Morocco

ISBN: (纸本)9798350308211

Using Social Network Services becomes a huge necessary, especially for teenagers. They can get closer in the real time. With more than 237 million daily active users [1], Twitter allows sharing short messages named « tweets ». Some users can employ offensive words, pictures or videos against another person via electronic devices. This phenomenon is calling cyberbullying. Because of timid, fear or weak cyberbullying attacks teens in darkness. Victims suffer in silence and can be driven to lower self-esteem, depression or suicide. In that aims many researches in computer science, sociology and psychiatry take the challenge and many initiatives are developed in order to detect offensive, abusive and negative *** of the huge number of users, the tweets make a raw dataset containing a lot of information that must be purified. Some information are misspelled, missing, duplicated or inuseless. Our work is based on Natural Language processing;we will discuss the importance of the data pre-processing and feature engineering before proceeding to the text classification using Machine Learning algorithms. © 2023 IEEE.

关键词： Text processing

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Research on Carrier Phase Recovery in Coherent optical Communication systems 24

Research on Carrier Phase Recovery in Coherent Optical Commu...

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2024 International conference on Image processing, Intelligent Control and Computer Engineering, IPICE 2024

作者： Liu, Hao Zheng, Jiangpeng He, Qiuting Key&Core Technology Innovation Institute of the Greater Bay Area China

ISBN: (纸本)9798400710285

Coherent optical communication system (COCS) can achieve high-speed and long-distance transmission, but their structure is complex and costly. In coherent optical communication, problems such as link damage caused by the transmission medium and noise in transmission affect the transmission of data information. At the same time, the recovery of original data is also the key to optical communication. In response to these problems, this paper studies the carrier phase recovery in COCS. The article analyzes the advantages and disadvantages of existing phase recovery algorithms (PRA) and proposes a PRA based on the minimum first-order distance (MFOD). The algorithm first uses a blind phase search algorithm to find a rough estimate interval of the phase noise, and then uses MFOD to quickly find the phase noise and reduce the complexity of the algorithm. The simulation results show that the line width tolerance of the PRA based on the MFOD and the blind phase search algorithm are basically the same, but the complexity is reduced by 68% compared with the blind phase search algorithm. © 2024 Copyright held by the owner/author(s).

关键词： optical fiber communication

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