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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Li, Ke Lyu, Gengyu Chen, Hao Xie, Bochen Yang, Zhen Li, Youfu Deng, Yongjian College of Computer Science Beijing University of Technology China School of Computer Science and Engineering Southeast University China Department of Mechanical Engineering City University of Hong Kong Hong Kong

ISBN: (纸本)157735897X

Event cameras have gained attention in segmentation due to their higher temporal resolution and dynamic range compared to traditional cameras. However, they struggle with issues like lack of color perception and triggering only at motion edges, making it hard to distinguish objects with similar contours or segment spatially continuous objects. Our work aims to address these often overlooked issues. Based on the assumption that various objects exhibit different motion patterns, we believe that embedding the historical motion states of objects into segmented scenes can effectively address these challenges. Inspired by this, we propose the ESS framework "Know Where You Are From" (KWYAF), which incorporates past motion cues through spatio-temporal propagation embedding. This framework features two core components: the Sequential Motion Encoding Module (SME) and the Event-Based Reliable Region Selection Mechanism (ER2SM). SMEs construct prior motion features through spatio-temporal correlation modeling for boosting final segmentation, while ER2SM adapts to identify high-confidence regions, embedding motion more precisely through local window masks and reliable region selection. A large number of experiments have demonstrated the effectiveness of our proposed framework in terms of both quantity and quality. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Image segmentation

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Enhancing Website Authenticity Verification with Random Forest Algorithm 7th

Enhancing Website Authenticity Verification with Random Fore...

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7th International Conference on Soft Computing and Signal Processing, ICSCSP 2024

作者： Sesha Talpa Sai, P.H.V. Jayashankar, M.V. TatiChandanBhargav Ribin, N. ShyamSasi Tiwari, Kishan Bhaumik, Amiya Department of Mechanical Engineering Malla Reddy College of Engineering and Technology Hyderabad India School of Mechanical Engineering Lincoln University College Petaling Jaya Malaysia Department of Computer Science and Engineering Malla Reddy University Hyderabad India Lincoln University College Petaling Jaya Malaysia

ISBN: (纸本)9789819609239

The emergence of fraudulent websites is a serious concern since it can defraud gullible Internet users of large amount of money. The intricate layout of these phony websites makes it difficult to identify them manually. Automated detection systems have become an essential defense mechanism. Nevertheless, many of these systems rely on crude fraud indicators, which are sometimes unable to keep up with the speed at which fraudulent websites are created and vanish. Different strategies are needed to handle this issue and identify fake websites more successfully. Out of all of these, the random forest classifier performs better than other techniques. Real-time detection is facilitated by integrating our classifier into a browser plugin, which promises an impressive true positive rate of 98.8%. This study presents website authenticity enhancement using cybersecurity features by examining the effectiveness of random forest algorithm to identify phony websites. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Random forests

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Advances in 3D bioprinting for environmental remediation and hazardous materials treatment

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Environmental science and Pollution Research 2024年第44期31卷 55984-55995页

作者： Vellalapalayam Manoharan, Gobinath Munuswamy, Naresh Babu Johnpeter, Jasmine Hephzipah Veeramani, Sathya Balasubramanian, Hemalatha Department of Mechanical Engineering Rajalakshmi Institute of Technology Chennai600 124 India Department of Mechanical Engineering Easwari Engineering College Chennai600 089 India Department of Electronics and Communication Engineering R.M.K. Engineering College Chennai601 206 India Department of Computer Science Engineering Vel Tech Rangarajan Dr. Sagunthala R & ampD Institute of Science and Technology Chennai600 062 India Department of Civil Engineering St. Peter’s Institute of Higher Education and Research Chennai600 054 India

The high-throughput method based on the micron-level structure that 3D bioprinting technology offers for various environmental microbiological engineering applications is made possible by its several printing paths and precision programming control. This versatility makes it an on-demand manufacturing technology. A novel 3D manufacturing technique called 3D bioprinting may be used to precisely uptake and disperse bacteria to create microbial active substances with a variety of intricate functionalities for environmental applications. The technological challenges that the current 3D bioprinting technology must face include the mechanical properties of materials, the creation of specific bioinks to adapt to different strains, and the exploration of 4D bioprinting for intelligent applications. Therefore, this analysis delves deeply into the core technological ideas of 3D bioprinting, bioink materials, and their environmental applications. It also offers recommendations about the challenges and opportunities associated with 3D bioprinting. Combined with the present advancements in microbe enhancement technology, 3D bioprinting will provide an enabling platform for multifunctional microorganisms and facilitate the management of in situ directional responses in the environmental domain. This review highlights the applications of 3D bioprinting in the environmental monitoring and bioremediation. 3D printing in solid waste management is also discussed in detail. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： 3D bioprinting Bioink Biomaterial Integrated biomaterials

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Optimization technique for optimal location selection based on medical image watermarking on healthcare system

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Journal of Intelligent and Fuzzy systems 2023年第4期45卷 6549-6559页

作者： Umaamaheshvari, A. Sivasankari, K. Suguna, N. Kshirsagar, Pravin R. Tirth, Vineet Rajaram, A. Akshaya College of Engineering and Technology Anna University Tamilnadu Coimbatore India Department of Computer Science and Engineering Akshaya College of Engineering and Technology India Department of Artificial Intelligence G.H. Raisoni College of Engineering Nagpur India Mechanical Engineering Department College of Engineering King Khalid University Asir Abha Saudi Arabia E.G.S Pillay Engineering College India

The optimization algorithms mimic the process of natural evolution. In watermarking, appropriate positions to insert the watermark is identified by the image that covers. These positions represent the populations of genetic algorithms. The major drawback in genetic algorithm are that it may get stuck-up at a local optimum while moving towards the best global solution and hence the result is poor when compared to other local optimization techniques. The proposed work based on Bandelet based biogeography firefly hybrid algorithms. The Number of pixels, Intensity of the pixel and contrast are considered for watermarking. The redundancy is reduced by Bandelet and used to determine the best location to embed the information into an image both locally and globally. Results of these techniques are compared based on coefficient correlation, index structural similarity, and noise ratio from peak signal. © 2023 - IOS Press. All rights reserved.

关键词： Genetic algorithms

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Crop Disease and Pest Management in Agriculture via UAV Remote Sensing and Advanced Machine Learning Models 3

Crop Disease and Pest Management in Agriculture via UAV Remo...

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3rd International Conference on Integrated Circuits and Communication systems, ICICACS 2025

作者： Punitha, A. Jayamangala, S. Joel Josephson, P. Bharathi, K. Sindhu, V. Singh, Kamlesh Chettinad College of Engineering and Technology Department of Computer Science and Engineering Karur India Santhiram Engineering College Nandyal Department of Electronics and Communication Engineering Nandyal India Malla Reddy Engineering College Department of Electronics and Communication Engineering Dhulapally Medchal India Erode Sengunthar Engineering College Department of Agricultural Engineering Erode India Christ University Department of Computer Science Bangalore India School of Management Sciences Department of Mechanical Engineering Uttar Pradesh India

ISBN: (纸本)9798331508456

Pests and diseases greatly reduce crop quality and yield;therefore, IA relies on effective pest and disease control. UAVs have become a crucial remote sensing (RS) tool for agricultural process monitoring and management. This study will examine major advances in this field using bibliometric methodologies including author co-occurrence and keyword co-contribution studies. The suggested technique involves preprocessing, feature extraction, and model training. Data quality improves with preprocessing. UAV images are used for feature extraction, focusing on canopy structure and height. PPO is trained the prediction model. Compared to ultramodern GANs and LSTM networks, the recommended model wins. The model consistently outperforms competitors with 91.17 percent accuracy. The study suggests employing UAVs in smart farming to reduce pests and diseases. The suggested model's accuracy and reliability improve crop quality and production by solving agricultural monitoring and management problems. © 2025 IEEE.

关键词： Insect control

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Optimal Deep Convolutional Neural Network for Vehicle Detection in Remote Sensing Images

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computers, Materials & Continua 2023年第2期74卷 3117-3131页

作者： Saeed Masoud Alshahrani Saud S.Alotaibi Shaha Al-Otaibi Mohamed Mousa Anwer Mustafa Hilal Amgad Atta Abdelmageed Abdelwahed Motwakel Mohamed I.Eldesouki Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Electrical Engineering Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Information System College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia

Object detection(OD)in remote sensing images(RSI)acts as a vital part in numerous civilian and military application areas,like urban planning,geographic information system(GIS),and search and rescue *** recognition from RSIs remained a challenging process because of the difficulty of background data and the redundancy of recognition *** latest advancements in deep learning(DL)approaches permit the design of effectual OD *** study develops an Artificial Ecosystem Optimizer with Deep Convolutional Neural Network for Vehicle Detection(AEODCNN-VD)model on Remote Sensing *** proposed AEODCNN-VD model focuses on the identification of vehicles accurately and *** detect vehicles,the presented AEODCNN-VD model employs single shot detector(SSD)with Inception network as a baseline *** addition,Multiway Feature Pyramid Network(MFPN)is used for handling objects of varying sizes in *** features from the Inception model are passed into theMFPNformultiway andmultiscale feature ***,the fused features are passed into bounding box and class prediction *** enhancing the detection efficiency of the AEODCNN-VD approach,AEO based hyperparameter optimizer is used,which is stimulated by the energy transfer strategies such as production,consumption,and decomposition in an *** performance validation of the presentedmethod on benchmark datasets showed promising performance over recent DL models.

关键词： Object detection remote sensing vehicle detection artificial ecosystem optimizer convolutional neural network

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Design of Mobile Robot Automatic Navigation system Based on ROS 5

Design of Mobile Robot Automatic Navigation System Based on ...

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5th Asia-Pacific Conference on Image Processing, Electronics and computers, IPEC 2024

作者： Duan, Chenxu Xue, Ling Kumar, Sachin School of Mechanical Engineering Sichuan University Jinjiang College Meishan620680 China Department of Computer Science and Engineering Galgotias College of Engineering and Technology Greater Noida India

ISBN: (纸本)9781643685243

Mobile robot is the key equipment of flexible production system, flexible handling system and automatic storage system. As an important bridge connecting logistics and production, mobile robot can effectively improve the production efficiency of manufacturing enterprises and reduce production costs. Under the background of the close combination of information technology and manufacturing industry, higher requirements are put forward for its automation and intelligence. Aiming at the problem of large error accumulation caused by the existing navigation methods using odometer navigation and GPS navigation technology, this paper takes Turtlebot3-waffle mobile robot as the research object and carries out the research of automatic navigation system. Firstly, the basic motion and attitude are analyzed, and the forward and inverse kinematics models and dead reckoning formulas are established. Then, the core algorithms of map building, autonomous positioning and autonomous navigation are studied, and several simulation environments are established on the ROS simulation platform to verify the algorithms. Finally, an autonomous navigation simulation system is built on the ROS platform, and the laser radar SLAM map based on gmapping algorithm is constructed for the established simulation environment model, and the automatic navigation function is simulated by using the map. In the experiment, the robot successfully planned the corresponding local path and global path and successfully reached the navigation target point, which verified the feasibility and effectiveness of the automatic navigation system. It provides a reference for the research of mobile robot automatic navigation system. © 2024 The Authors.

关键词： Motion planning

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Interoperability and Standardization in the Internet of Things 9

Interoperability and Standardization in the Internet of Thin...

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9th International Conference on science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Saidala, Ravi Kumar Haseeb, V.V. Padmapriya, G. Jayabalan, S. Priya, V. Kalai Shaikh, Anwar Ahamed Alliance University Department of Computer Science Engineering Karnataka Bangalore560076 India Nam College Department of Computer Science Kerala Tamil Nadu Kallikkandy 670693 India School of Computing Srm Institute of Science And Technology Department of Computing Technologies Chennai Tamil Nadu Kattankulathur603203 India Panimalar Engineering College Department of Computer Science And Business System Tamil Nadu Chennai600123 India Rmk College of Engineering And Technology Department of Computer Science And Engineering Puduvoyal601206 India KoneruLakshmaiah Education Foundation Department of Computer Science And Engineering Andhra Pradesh Vaddeswaram522502 India

ISBN: (纸本)9798350365092

This research highlights the importance of standards and interoperability in the IoT. An essential component of IoT ecosystems is interoperability, which refers to the ability for various systems and devices to converse and share data. Formats for data, methods of communication, and safeguards are all outlined by standards. Widespread adoption and scalability are made possible through interoperability and standards, which allow devices from many manufacturers to communicate with one another. This research investigates the alliances, regulatory authorities, and commercial associations that cooperate in the creation and advancement of open standards that can be embraced by other entities. The main objective of the research is to showcase the construction of an Internet of Things device capable of communicating with various embedded peripheral protocols utilizing Plug and Play (PnP) technology. Moreover, the research examines the impact of regulatory frameworks on the IoT ecosystem and their role in fostering interoperability. An IoT ecosystem necessitates a standardized and open environment to provide optimal performance in terms of connectivity, data exchange, and innovation. This research contributes to the progress of harmonizing and achieving interoperability among World Wide Web Things. © 2024 IEEE.

关键词： Interoperability

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Improved Bat Algorithm with Deep Learning-Based Biomedical ECG Signal Classification Model

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computers, Materials & Continua 2023年第2期74卷 3151-3166页

作者： Marwa Obayya Nadhem NEMRI Lubna A.Alharbi Mohamed K.Nour Mrim M.Alnfiai Mohammed Abdullah Al-Hagery Nermin M.Salem Mesfer Al Duhayyim Department of Biomedical Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Science and Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer Science College of Computers and Information TechnologyTabuk UniversitySaudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Computer Science College of ComputerQassim UniversitySaudi Arabia Department of Electrical Engineering Faculty of Engineering and TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam Bin Abdulaziz UniversitySaudi Arabia

With new developments experienced in Internet of Things(IoT),wearable,and sensing technology,the value of healthcare services has *** evolution has brought significant changes from conventional medicine-based healthcare to real-time observation-based *** Electrocardiogram(ECG)signals are generally utilized in examination and diagnosis of Cardiovascular Diseases(CVDs)since it is quick and non-invasive in *** to increasing number of patients in recent years,the classifier efficiency gets reduced due to high variances observed in ECG signal patterns obtained from *** such scenario computer-assisted automated diagnostic tools are important for classification of ECG *** current study devises an Improved Bat Algorithm with Deep Learning Based Biomedical ECGSignal Classification(IBADL-BECGC)*** accomplish this,the proposed IBADL-BECGC model initially pre-processes the input ***,IBADL-BECGC model applies NasNet model to derive the features from test ECG *** addition,Improved Bat Algorithm(IBA)is employed to optimally fine-tune the hyperparameters related to NasNet ***,Extreme Learning Machine(ELM)classification algorithm is executed to perform ECG classification *** presented IBADL-BECGC model was experimentally validated utilizing benchmark *** comparison study outcomes established the improved performance of IBADL-BECGC model over other existing methodologies since the former achieved a maximum accuracy of 97.49%.

关键词： Data science ECG signals improved bat algorithm deep learning biomedical data data classification machine learning

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Love Waves in a Piezoelectric Semiconductor Thin Film on an Elastic Dielectric Half-Space

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固体力学学报（英文版） 2023年第1期36卷 45-54页

作者： Ru Tian Guoquan Nie Jinxi Liu Ernian Pan Yuesheng Wang State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao UniversityShijiazhuang 050043China Department of Mathematics and Physics Shijiazhuang Tiedao UniversityShijiazhuang 050043China State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao UniversityShijiazhuang 050043China School of Mechanical Engineering Shijiazhuang Tiedao UniversityShijiazhuang 050043China State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao UniversityShijiazhuang 050043China College of Engineering and Institute of Pioneer Semiconductor Innovation National Yang Ming Chiao Tung UniversityTaiwanChina Department of Mechanics Beijing Jiaotong UniversityBeijing 100044China

In this paper,Love waves propagating in a piezoelectric semiconductor(PSC)layered structure are investigated,where a PSC thin film is perfectly bonded on an elastic dielectric *** dispersion equations are derived *** influence of semiconducting properties on the propagation characteristics is examined in *** results show that the semiconducting effect reduces the propagation speed,and that the Love waves can propagate with a speed slightly higher than the shear wave speed of the elastic dielectric *** wave speed and attenuation significantly depend on the steady-state carrier density and the thickness of the PSC thin *** is also found that when the horizontal biasing electric field is larger than the critical value(corresponding to the zero attenuation),the wave amplitude is *** findings are useful for the analysis and design of various surface wave devices made of PSC.

关键词： Love wave Piezoelectric semiconductor Layered structure Dispersion Attenuation

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