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Artificial intelligence Indulgence in Protection of Cybercrime 3

Artificial Intelligence Indulgence in Protection of Cybercri...

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3rd international conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Nautiyal, Radhika Jha, Radhey Shyam Kathuria, Samta Singh, Rajesh Kathuria, Abhinav Pandey, Vaibhav Uttaranchal University Law College Dehradun Dehradun India Uttaranchal University Lcd Division of Research & Innovation Dehradun India Uttaranchal University Uit Division of Research & Innovation Dehradun India

ISBN: (纸本)9798350322842

It is difficult to picture life in the twenty-first century without the internet. Everything and anything can be reached quickly and easily with just one click adding to its disadvantages alongside to all of its benefits. Any illegal behaviour that is carried out online or using a computer is considered a cybercrime. The risk of cybercrime has expanded dramatically along with technology and the internet. Cybercrime can have serious repercussions;include monetary losses, theft of identity, and even dangers to national security. The use of AI is used extensively to prevent cybercrime in order to address this growing menace. Artificial intelligence (AI) based IDS serve to quickly identify and stop cyber-attacks, eliminating the potential harm that it may cause. The study examines the application of AI in preventing cybercrime, as well as the algorithms it employs and its potential applications in the future are all covered in this study. It also focuses at how to use AI to strengthen and improve cybercrime detection and tracking. Finally, the findings of proposed research is discussed and draw the conclusion that AI has a substantial impact on cybercrime detection and prevention. © 2023 IEEE.

关键词： Intrusion detection

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A Path Planning Algorithm for Mobile robot Based on MR-QL in the Unknown Scene 3

A Path Planning Algorithm for Mobile Robot Based on MR-QL in...

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3rd international conference on Computer, Big Data and Artificial intelligence, ICCBDAI 2022

作者： Fu, Zongli Liu, Zhandong Hu, Chuangye Ding, Nan College of Computer Science and Technology Xinjiang Normal University Urumqi China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Dalian University of Technology Dalian China

The Q-Learning (QL) algorithm is widely used for path planning. As the scene in which the mobile robot is located becomes complex, the algorithm suffers from the limitations of low convergence speed and long exploration paths. Therefore, a Max Reward-Q-learning (MR-QL) path planning algorithm based on maximum reward is proposed for complex unknown scenarios. The original algorithm's discrete reward function and action selection strategy are improved, and a new reward function is designed to dynamically adjust the reward mechanism to heuristically guide the robot motion. The action selection strategy is also optimized to avoid invalid exploration and improve the algorithm's convergence. Finally, three experimental environments with different complexity are constructed to demonstrate the feasibility of the proposed algorithm. The simulation results show that the MR-QL algorithm is about 50% of the original algorithm in terms of exploration step length and training time, and the convergence speed of the algorithm is better than the original algorithm. © Published under licence by IOP Publishing Ltd.

关键词： Mobile robots

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Design of a bionic snake-like robot 3

Design of a bionic snake-like robot

引用

3rd international conference on Mechanical, Electronics, and Electrical and Automation Control, METMS 2023

作者： Meng, Xianyu Zhao, Songrui Yu, Xiquan Liu, Hongsheng Wang, Shuo Department of Changchun University of Science and Technology Jilin Province Changchun China

ISBN: (纸本)9781510666689

Bionics is a subject that studies various excellent characteristics such as the structure, function and information control of organisms. These characteristics will give us a lot of inspiration in terms of mechanical design and will also provide new construction ideas for practical engineering applications. In this paper, based on the structural characteristics of the natural biological snake, a bionic snake-like robot with a meandering posture is designed. Bionic snake-like robot uses STM32F103ZET6 MCU and 16-way servo control board as the main control unit. The servo provides the driving force. Through the use of pulleys and various sensors, functions such as various attitude movements and real-Time detection are realized. Using Solidworks software to carry out 3D modeling of the bionic snake-like robot and make a bionic snake-like robot model for experimental testing. The physical model size is 120mm*120mm*850mm. The results show that: on a relatively flat ground, the time for the bionic snake-like robot to move through a horizontal distance of 1m is about 5.50s. The bionic snake-like robot runs stably during the test and has no stuttering phenomenon. © 2023 SPIE. All rights reserved.

关键词： Bionics

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Dense reconstruction of substation room with LSD SLAM 3

Dense reconstruction of substation room with LSD SLAM

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3rd international conference on Artificial intelligence, Virtual Reality, and Visualization, AIVRV 2023

作者： Li, Zhaoqing Zhao, Xiaoxuan Li, Yihui College of Intelligence Science and Technology National University of Defense Technology Changsha China Faculty of Electrical and Control Engineering Liaoning Technical University Hu Ludao China

ISBN: (纸本)9781510671485

With the development of digital transmission and transformation systems, digital substations have become a prevalent trend in the electric power industry. However, the presence of many electrical components in substation environments with varying textures poses challenges for the reconstruction of a digital three-dimensional model and robot operation. To deal with that problem, this paper introduces the rich line features present in substation environments into the front-end feature tracking of 3D reconstruction in order to improve the accuracy of the 3D reconstruction. The optimized LSD algorithm is utilized for extracting line features in weak texture scenes. Additionally, a line segment merging algorithm is proposed to reduce the rate of mismatched line features and avoid redundancy through the combination of similar or repeated line segments. Finally, the paper presents a novel line feature matching method based on geometric constraints during the stage of online feature matching, which has the ability to improve matching accuracy while decreasing matching time. The experimental results demonstrate that the front-end visual odometer's optimization method proposed in this paper can offer better feature extraction and matching initial values compared to traditional methods for nonlinear optimization of the back-end of 3D reconstruction and loopback detection. © 2023 SPIE.

关键词： Textures

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Image Acquisition and Storage System of Binocular Camera Based on FPGA 3

Image Acquisition and Storage System of Binocular Camera Bas...

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3rd international conference on Artificial intelligence, Big Data and Algorithms, CAIBDA 2023

作者： Liu, Bingkun Wang, Dashuai Liu, Jianhua Changchun University of Science and Technology China

ISBN: (纸本)9781643684444

In order to better solve the problem that image processing technology is strict in real-time and stability, a binocular camera image acquisition and storage system based on FPGA is designed with the advantage of FPGA parallel processing. The system uses Xilinx ARTIX-7 XC7A35T as the master chip to control the CMOS camera as the image sensor for image acquisition, stores the acquired images in DDR3 SDRAM, and displays the images in the host computer by reading the memory data. The results show that the system has good real-time performance and stability, and meets the requirements of image transmission and processing. © 2023 The Authors.

关键词： Field programmable gate arrays (FPGA)

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Precision Agriculture Using IOT technology with a Case Study of Coffee Beans Production 3rd

Precision Agriculture Using IOT Technology with a Case Study...

引用

3rd international conference on Machine Vision and Augmented intelligence, MAI 2023

作者： Pawar, Sumathi Samaga, B. L. RajaLakshmi Pandith, Karuna Nayak, Vasanth Geetha, V. Thinakaran, Rajermani NMAM Institute of Technology Karnataka Nitte Karkala574110 India ISE Department Canara Engineering College Karnataka Benjanapadavu Bantwal575219 India Department of Information Technology NITK Karnataka Suratkal India Data Science and Information Technology INTI International University Negeri Sembilan Nilai Malaysia

ISBN: (纸本)9789819743582

World population is rapidly increasing which requires similar increase in food production. Agriculture is playing an important role in the world economy. Nowadays precision agriculture is the best method to be practiced by the farmers. Sensors, communication technology, and data analysis are building blocks of smart farming in precision agriculture process. This paper is focused on a survey of precision agriculture using IOT and details about various sensors used with a case study of Coffee beans production in Coffee estate. Various sensors used in pre-production, production, and post-production of coffee beans are discussed. This paper also addresses the need of communication technology and its ranges for suitability of smart farming, besides a review is conducted on applications of IOT in various tasks of precision agriculture. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Smart agriculture

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Application of Natural Language in Intelligent Media AI Writing 3

Application of Natural Language in Intelligent Media AI Writ...

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3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Mingxuan, Zhang Zichang, Dou Zhengyu, Tian Jingren, Jin Jiahao, Chen School of Software Shenyang University of Technology Liaoning Province Shenyang City110870 China School of Artificial Intelligence Shenyang University of Technology Liaoning Province Shenyang City110870 China

ISBN: (纸本)9798350319125

The application of natural language in intelligent media and artificial intelligence writing is a significant development in the field of artificial intelligence. Natural language processing (NLP) enables machines to understand and interpret human language, enabling them to generate content that is indistinguishable from what humans write. Intelligent media AI writing has many applications, including content creation for websites, social media posts, and news articles. With the help of NLP algorithm, machines can analyze a large amount of data and generate relevant content that meets user needs. One of the most significant advantages of using intelligent media for AI writing is its ability to produce high-quality content faster than humans. Machines can analyze data and generate content in real-time, enabling enterprises to keep up with the fast pace of online marketing. In short, the application of natural language in intelligent media and artificial intelligence writing has completely changed the way we create and consume content online. With the continuous progress of technology, we can look forward to further development in this field, which will continue to affect the way we interact with digital media. This article is based on the media equivalence theory and adopts a research method that combines questionnaire survey and experimental methods to explore the mechanism of the impact of AI writing on news credibility. This article proposes that users perceive the credibility of news written by AI as higher than that written by human journalists. Perceived news bias plays a mediating role, while news types play a moderating role. © 2023 IEEE.

关键词： AI writing Journalism Natural language Smart media

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Artificial intelligence-Based Analysis of Biological Signals and Attention Assessment Methods 24

Artificial Intelligence-Based Analysis of Biological Signals...

引用

3rd international Symposium on robotics, Artificial intelligence and Information Engineering, RAIIE 2024

作者： Li, Zhijing Li, Hong Jiang, Yiping Guangdong University of Science and Technology Dongguan China

ISBN: (纸本)9798400718311

Biological information processing plays a pivotal role in modern life, with applications ranging from health monitoring to personalized medicine. This study endeavors to delve into a method employing artificial neural networks for the analysis of biological signals, specifically focusing on assessing individual attention levels. By harnessing physiological data such as heart rate variability and skin conductance, coupled with the utilization of artificial neural networks for data analysis and modeling, a more comprehensive understanding of individual attention states can be attained. In the experimental phase, a diverse pool of individuals was tested, and the experimental results were validated using recorded videos. The findings underscore the efficacy of the artificial neural network-based method in assessing individual attention levels, achieving an accuracy rate of 76.9%. This research not only introduces novel methodologies but also opens avenues for leveraging artificial intelligence technology in biological signal analysis and attention assessment. Future research endeavors could delve deeper into exploring additional features of biological signals and enhancing model performance to bolster assessment accuracy and practical applicability. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Artificial neural networks Attention assessment Biological signal analysis Wearable technology

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LiDAR-based human pose estimation with MotionBERT 21

LiDAR-based human pose estimation with MotionBERT

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21st IEEE international conference on Mechatronics and Automation (IEEE ICMA)

作者： Zhao, Zichen Zhuang, Chao Li, Jian Sun, Hao Hebei Univ Technol Coll Artificial Intelligence Tianjin Peoples R China Natl Rehabil Aids Res Ctr Beijing Peoples R China

ISBN: (纸本)9798350388084;9798350388077

Human body pose estimation has a wide range of applications in the field of artificial intelligence and is gradually applied in daily life. However, for some specific scenes and people, privacy and security need to be ensured, and devices such as cameras are no longer the optimal choice, so this paper proposes the idea of using LiDAR technology to acquire human body point cloud images, and preprocessing and segmentation to extract a pure human body point cloud model. First, the useful parts around the human body are extracted by preprocessing the point cloud image obtained from LiDAR scanning. Then, a segmentation technique is utilized to separate the human body from the surrounding objects, keeping only the human body part. Next, the excess noise is removed by filtering process to get the pure human body point cloud model. Finally, the motionBert3d model is used to estimate the pose of the preprocessed point cloud image, and the pose estimation points and the 3D pose estimation model of the human body are obtained, which lays the foundation for the subsequent human motion recognition.

关键词： LiDAR point cloud maps image preprocessing human pose estimation motionBert3d modeling

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Preface to Joint Workshop of the 4th Extraction and Evaluation of Knowledge Entities from Scientific Documents (EEKE2023) and the 3rd AI + Informetrics (AII2023) at JCDL 2023 4

Preface to Joint Workshop of the 4th Extraction and Evaluati...

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Joint Workshop of the 4th Extraction and Evaluation of Knowledge Entities from Scientific Documents and the 3rd AI + Informetrics, EEKE-AII 2023

作者： Zhang, Chengzhi Zhang, Yi Mayr, Philipp Lu, Wei Suominen, Arho Chen, Haihua Ding, Ying Nanjing University of Science and Technology No. 200 Xiaolinvgwei Nanjing210094 China Australian Artificial Intelligence Institute University of Technology Sydney 15 Broadway UltimoNSW Australia GESIS - Leibniz-Institute for the Social Sciences Unter Sachsenhausen 6-8 Cologne50667 Germany Wuhan University Luojiashan Wuhan430072 China VTT Technical Research Centre of Finland EspooFI-02044 Finland University of North Texas Texas DentonTX76201 United States University of Texas at Austin. AustinTX78712 United States

The Joint Workshop of the 4th Extraction and Evaluation of Knowledge Entities from Scientific Documents (EEKE2023;https://***/) and the 3rd AI + Informetrics (AII2023;https://***/) was held at Santa Fe, New Mexico, USA and online, co-located with the ACM/IEEE Joint conference on Digital Libraries (JCDL) 2023. The two workshop series aim to engage the communities in open problems in the extraction and evaluation of knowledge entities from scientific documents and the modeling and applications of AI + Informetrics for broad interests in science of science, science, technology, & innovation, etc. This joint workshop comprises keynote speeches, oral presentations, and poster sessions. The main topics of the proceedings include entity extraction and its applications, along with the integration of Artificial intelligence + Informetrics. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 international (CC BY 4.0). CEUR Workshop Proceedings (***)

关键词： Extraction

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