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2023 international conference on Control, Communication and Computing, ICCC 2023

2023 International Conference on Control, Communication and ...

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5th international conference on Control, Communication and Computing, ICCC 2023

ISBN: (纸本)9798350334128

the proceedings contain 139 papers. the topics discussed include: artificial level language: a library of computing engine for natural languages;fourth order sliding mode control of position for electro-hydraulic actuator;design of hexapod robot with adaptive gait transition on rough terrain;energy-efficient data aggregation schemes for low-power distributed wireless sensor networks using compressed sensing;adaptive neural attitude and altitude control of a quadrotor UAV with external disturbances via sliding mode control;an indigenous 32 bit pipelined processor for space applications;design of ins aided receiver integrity monitoring algorithm (ARIM) for GNSS integrated navigation systems;algebraic topology as an analytic tool to check lossless nature of geometric algorithms;implementing a land registration system using non-fungible tokens to represent land in the system and side-chain for data storage;a novel general purpose processing ASIC for inertial sensors;semi-autonomous non-singular terminal sliding mode control of a micro aerial robot for outdoor wall climbing operation;investigations on recent advancements in the fabrication of in-plane micro-supercapacitors as portable energy storage devices;Reswave-Net: a wavelet based residual U-Net for brain tumor segmentation and overall survival prediction;and bidirectional voltage level shifter with configurable voltage range.

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A Review of Spectral Estimation in Underwater Acoustic Signal Processing 5

A Review of Spectral Estimation in Underwater Acoustic Signa...

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5th IEEE Advanced Information Management, Communicates, Electronic and Automation Control conference, IMCEC 2022

作者： Peng, Chao International School of Microelectronics Dongguan University of Technology DongGuan China

ISBN: (纸本)9781665479677

this paper first introduces the direct method of classical power spectrum estimation, and then proposes two improved classical power spectrum estimation methods: Welch Method and MultiTaper (MTM) Method. then the Maximum Entropy Spectral Estimation (based on Burg) in parametric spectral estimation is introduced. then the power spectrum is extended in the spatial domain, and two kinds of spatial spectrum estimation methods, MUSIC Method and ESPRIT method, and their improved algorithms are introduced. All of the above methods have been simulated in Matlab environment. We have compared various spectrum estimation methods in detail, and analyzed and summarized their respective advantages and disadvantages. Finally, the paper points out the shortcomings of current power spectrum estimation and the future development direction. © 2022 IEEE.

关键词： Underwater acoustics

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Based on Navmesh to implement AI intelligent pathfinding in three-dimensional maps in UE4 5

Based on Navmesh to implement AI intelligent pathfinding in ...

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5th international conference on algorithms, Computing and Artificial Intelligence, ACAI 2022

作者： Zhang, Xinyuan Zhang, Xinyou International Design Art College Inner Mongolia Normal University Hohhot China

ISBN: (纸本)9781450398343

Abstract: the development of science and technology has led to the development of the game industry. As the mainstream development engine of the current three-dimensional game, UE4 is popular with game developers for its powerful rendering technology and model processing technology. there will be a large number of non-player characters (NPC, non-player character) in the game, and these AI-controlled characters are an important way for developers to interact with users. Among them, pathfinding is the most important part of the game's AI character, which gives the AI character vitality, so that the AI character can interact with the player, chase, and automatically complete the movement to the target point. Pathfinding is the core function of an AI character, and there are many current pathfinding methods, such as Dijstra algorithm, best-first search algorithm, A-star algorithm. Most of these pathfinding algorithms are used in 2D static maps, but there is no detailed description of 3D pathfinding by pathfinding algorithms in UE4. this paper first introduces and compares several map pathfinding models, then experimentally compares different pathfinding algorithms, and then uses blueprint programming to implement AI role pathfinding in the three-dimensional map in UE4 based on the optimal performance algorithm. Finally, the overall experimental results are summarized and sorted out, and the direction for future development is pointed out. © 2022 ACM.

关键词： Engines

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Hybrid Prediction Method Using Experts and Models

Hybrid Prediction Method Using Experts and Models

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international conference on Problems of Cybernetics and Informatics (PCI)

作者： Vugar Aliyev Merab Pkhovelishvili Natela Archvadze Zurab Gasitashvili Zaza Tsiramua CEO & Founder International Event Organizer Company AMIR Technical Services LLC Baku Azerbaijan Faculty of Informatics and Control Systems Georgian Technical University Tbilisi Georgia Faculty of Exact and Natural Sciences Ivane Javakhishvili Tbilisi State University Tbilisi Georgia Education Department Deputy Rector for Science Georgian Technical University Tbilisi Georgia

the article considers a hybrid forecasting model, which first considers "necessary" and "sufficient" forecasting models in the decision-making process, then selects the best pairs or triples of models, and finally attract experts. It discusses how to work with the hybrid model when to involve experts and according to what criteria. algorithms for choosing a new forecasting model, as well as algorithms for the need to change an expert, have been developed. the choice of experts is based on the predictions they make, not just their competence. the result of the forecast is the best pair of intersections of expert and model forecasts. A specific example illustrating the presented algorithms is considered.

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Fortifying Cyber Defenses: A Deep Dive into the Development of an AI-Powered Network Intrusion Detection System 5th

Fortifying Cyber Defenses: A Deep Dive into the Development ...

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5th international conference on Computing, Communications, and Cyber Security, IC4S 2023

作者： Rai, Hari Mohan Galymzada, Alin Almas, Konsbayev Nurzhan, Duzbayev Alibek, Makhayev Department of Cybersecurity International Information Technology University Almaty Kazakhstan

ISBN: (纸本)9789819725496

In the ever-evolving world of cybersecurity, it is essential to strengthen defenses against complex threats. this article provides a comprehensive overview of the development and deployment of an AI-powered network intrusion detection system (NIDS) as a fundamental element in improving organizational cyber resilience. Starting with an examination of the challenges posed by traditional intrusion detection systems (IDS), the article highlights the limitations of rule-based approaches in the face of rapidly evolving cyber threats. Emphasizing the need for real-time threat detection, the article introduces AI-powered NIDS as an adaptive solution. A focus on machine-learning algorithms, including supervised and unsupervised techniques, sheds light on the system's ability to automatically distinguish normal network behavior from potential intrusions. Deep learning models, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), are explored for their transformative impact on accuracy and adaptability in real-time data analysis. the article contextualizes these advancements by tracing the evolution of intrusion detection mechanisms, from rule-based systems to sophisticated AI-driven solutions. It delves into related work, covering machine-learning applications, anomaly detection, and the emergence of ensemble methods and hybrid approaches. Recognizing challenges such as adversarial attacks and interpretability concerns, the article concludes by emphasizing the broader importance of AI-powered NIDS in strengthening digital infrastructures. Serving as a valuable resource for cybersecurity professionals and organizations, this article combines technical depth with practical insights, offering strategic considerations for navigating the complexities of the modern cyber threat landscape. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Network security

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Fast, High-precision Subregion Stereo Matching Method 5

Fast, High-precision Subregion Stereo Matching Method

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5th IEEE Eurasia conference on IOT, Communication and Engineering, ECICE 2023

作者： Li, Jiangtao Chen, Fan Ma, Youqing Liu, Qinju Song, Wenge Xu, Xinchao Shenhua Shendong Coal Group Corporation Ltd Shanxi China International Research Center of Big Data for Sustainable Development Goals Beijing China Aerospace Information Research Institute Chinese Academy of Sciences Key Laboratory of Digital Earth Science Beijing China Liaoning Technical University School of Geomatics Fuxin China

ISBN: (纸本)9798350314694

A fast, high-precision subregion stereo-matching method was proposed to mitigate the conflict between the precision and matching speed of the existing methods. First, initial matching was carried out using grids with fixed spacing, and a Delaunay triangulation network was constructed. the network was refined based on the weighted center of gravity of the triangles, and the matching grid points and refinement points were included in the support point set. the accurate disparities of the support points were determined via quadratic approximation. then, the grids were divided into two parts, i.e., edge regions and non-edge regions, according to the disparity of their vertices. For the edge regions, the edge disparities were generated to create the initial disparity planes, and disparity propagation and normal vector optimization of each pixel in the propagation region of edge expansion were carried out. the matching cost was calculated according to the hue and grayscale gradient difference using the hue, saturation, and value (HSV) as the weighting factors. For the non-edge regions, the disparities were determined by quadratic approximation of the initial values obtained by linear interpolation of the grid vertices. Last, the disparities of the edge and non-edge regions were fused to obtain the optimal disparity of the whole image. Four pairs of stereo images in the Middlebury dataset were used for testing, the results of which were compared to those of the PatchMatch stereo (PMS), stereo gait feature (SGF), consistent stereo matching (CSM), and global edge constraint (GEC) algorithms with satisfactory matching performance. the results showed that the proposed method had a promising matching performance on both the smooth disparity regions and the edge disparity regions, and the matching accuracies in terms of non-occ and disc were better than those of the other methods. In particular, the disc index was 1.22% lower than that of the suboptimal method, and the matching

关键词： disparity propagation edge disparity quadratic approximation stereo matching triangulation network

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GNSS Time Synchronization Attack Detection Algorithm Based on Clock Bias Change Covariance

GNSS Time Synchronization Attack Detection Algorithm Based o...

引用

Power Electronics, Computer Applications (ICPECA), IEEE international conference on

作者： Peng Jia Qingmin Liao Shenzhen International Graduate School Tsinghua University Shenzhen China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

this paper proposes a GNSS Time Synchronization Attack (TSA) detection algorithm based on clock bias change covariance. By leveraging the synchronization characteristics in the variation patterns of TSA signals, the algorithm effectively detects TSA by calculating the covariance of clock bias changes. Experimental results demonstrate that, compared to the clock drift correlation algorithm, this algorithm not only achieves higher detection sensitivity and accuracy, enabling a clear distinction between normal and TSA signals, but also operates faster, detecting TSA 17.86% earlier on average. Additionally, it reduces computational complexity, saving 17.86% of processing time. this practical detection algorithm is particularly suitable for resource-constrained hardware devices, enhancing the GNSS system's resistance to TSA, ensuring timing accuracy and system stability, and providing reliable security for critical infrastructure.

关键词： Global navigation satellite system Machine learning algorithms Accuracy Sensitivity Heuristic algorithms Hardware Critical infrastructure Synchronization Detection algorithms Clocks

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2022 international conference on Intelligent Systems and Computer Vision, ISCV 2022

2022 International Conference on Intelligent Systems and Com...

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5th international conference on Intelligent Systems and Computer Vision, ISCV 2022

ISBN: (纸本)9781665495585

the proceedings contain 71 papers. the topics discussed include: a new sampling strategy to improve the performance of mobile robot path planning algorithms;machine learning based methods for Arabic duplicate question detection;robust traffic signs classification using deep convolutional neural network;image-based visual servoing techniques for robot control;SASHA: a shift-add segmented hybrid approximated multiplier for image processing;graph based method for Arabic text summarization;face information forensics analysis based on facial aging: a survey;advanced financial data processing and labeling methods for machine learning;and recognition system of human activities based on time-frequency features of accelerometer data.

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Artificial Intelligence Application for Security Issues and Challenges in IoT 5

Artificial Intelligence Application for Security Issues and ...

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5th international conference on Contemporary Computing and Informatics, IC3I 2022

作者： Kwatra, Chetna Vaid Jain, Anupam Royappa, Angelina Bagchi, Susama Babu, S B G Tilak Chowdhary, Harish Lovely Professional University Punjab Pakhwara India Commerce and Management Poddar International College India Velammal Engineering College India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Aditya Engineering College India National Forensic Sciences University School of Doctoral Studies and Research India

ISBN: (纸本)9798350398267

More and more gadgets are getting internet access as a result of advances in technology, collectively known as the 'Internet of things' (IoT). In common parlance, the network of physical and digital components that make up commonplace objects is referred to as the 'Internet of things' (IoT). the Internet of things is a new and exciting area of research thanks to the worldwide proliferation of advanced technologies. One example is the Internet of things (IoT), which lets almost any object, user, service, network, location, or set of circumstances connect with each other. Since IoT's popularity has skyrocketed in the last several years, so have security concerns. AI is at the top of the list because it makes it possible to create complex algorithms, which are needed to protect critical infrastructure like networks, systems, and the Internet of things (IoT). Even so, hackers have learned to use AI to their advantage, and some of them even use AI to do bad things. this article aims to do just that by presenting and summarising the relevant literature in these areas. In order to do this, it gathers information about Internet of things devices, AI systems, AI attacks, and AI defenses. © 2022 IEEE.

关键词： Internet of things

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Machine Learning-Based Prediction of COVID-19: A Robust Approach for Early Diagnosis and Treatment 5th

Machine Learning-Based Prediction of COVID-19: A Robust Appr...

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5th international conference on Trends in Computational and Cognitive Engineering, TCCE 2023

作者： Johora, Fatema Tuj Mahfuja, Israt Binte Masuqur Rahman, A.N.M. Rahman, Md Mosfikur Rahman, Md Sadekur Department of Computer Science and Engineering Jahangirnagar University Dhaka Bangladesh Department of Computer Science and Engineering Daffodil International University Daffodil Bangladesh Department of Information Systems Kobe Institute of Computing Kobe Japan

ISBN: (纸本)9789819719228

the worldwide health catastrophe sparked by the COVID-19 epidemic continues, emphasizing the need for novel solutions in prediction, early diagnosis, and treatment. While vaccine development has progressed, the virus’s eradication remains questionable. this research presents a strong machine learning-driven approach to addressing this complicated problem. Rapid viral transmission and the lack of a single cure hamper illness diagnosis and treatment, particularly in highly populated developing countries like Bangladesh. Against this context, machine learning and artificial intelligence have emerged as critical instruments for the improvement of health care and medical research. this research investigates several machine learning algorithms and approaches that show potential for COVID-19 prediction. Among these is an algorithm that assesses individual vulnerability and environmental variables, allowing for self-diagnosis and early intervention, reducing the strain on healthcare institutions and government resources. this study demonstrates how machine learning may improve forecast accuracy and provide proactive treatment in pandemic management. Advanced techniques, such as K-nearest neighbor, Decision Tree, Random Forest, AdaBoost, XGBoost, Stochastic Gradient Descent, Linear SVC, Perceptron, Naive Bayes, Support Vector Machines, Logistic Regression, and Discriminant Analysis, are essential for achieving the best results. Finally, this research emphasizes the need for novel responses to global health challenges. Healthcare systems may improve their forecasting capacities and early intervention techniques by leveraging machine learning. this paper highlights technology’s revolutionary impact in redefining healthcare paradigms and encouraging resilience in the face of enormous difficulties. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： COVID-19

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