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conference Proceedings - 2023 3rd international conference on artificial intelligence, automation and algorithms, ai2a 2023

Conference Proceedings - 2023 3rd International Conference o...

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3rd international conference on artificial intelligence, automation and algorithms, ai2a 2023

ISBN: (纸本)9798400707605

The proceedings contain 28 papers. The topics discussed include: RHC method based 2D-equal-step path generation for UAV swarm online cooperative path planning in dynamic mission environment;unseen codec spoof speech detection based on channel-robust feature;study on the fault diagnosis method of ship main engine unbalanced data based on improved DQN;a novel control scheme of stable electricity and high efficiency supply in SOFC-based DC micro-grid;a control method of SOFC-based DC micro-grid to avoid fuel starvation when external load power increases;an agent motion model construction method based on sequential attention neural network;research on control strategy of manipulator based on deep reinforcement learning;and identification of high-risk areas for geological disasters using classification methods under complex environmental conditions.

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3rd international conference on artificial intelligence and Knowledge Processing, aiKP 2023

3rd International Conference on Artificial Intelligence and ...

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3rd international conference on artificial intelligence and Knowledge Processing, aiKP 2023

ISBN: (纸本)9783031686160

The proceedings contain 28 papers. The special focus in this conference is on artificial intelligence and Knowledge Processing. The topics include: How Do Senior Secondary Level Students and Their Teachers Perceive artificial intelligence and Its Implementation? An Exploratory Study;anomalous Sound Pattern Detection for Machine Health Monitoring;performance Evaluation of Various Machine Learning algorithms for Lung Cancer Prediction Using Demographic Data;enhancing Stock Portfolio Optimization Based on a Hybrid Approach Using artificial Bee Colony Optimization and Firefly Optimization;Enhancing Yarn Quality in the Cotton Industry: ai- Based Nep Detection for Improved Manufacturing Processes;breast Cancer Diagnosis from Ultrasonic Image and Histopathology Image Using Deep Learning Approach;Advancing Time Series Forecasting: LSTM Networks with Multiple Attention Mechanisms;trajectory Tracking and Navigation Model for Autonomous Vehicles Using Reinforcement Learning;quantum Graph Neural Networks Based Protein-Ligand Classification;comparative Analysis on Speech Driven Gesture Generation;enhancing Deep Learning: Leveraging Skip Connections and Memory Efficiency;quality-Based Decision-Making Using Image Processing for Supply Chain Management;enhancing Endometrial Tumor Detection: Early Diagnosis with Advanced Vision Transformer Architecture;sweetSight: A Deep Convolutional Neural Network Approach for Automatic Categorization of Bengal Sweets;a Systematic Review: How Computer Vision is Transforming Agriculture in Economic Growth;automatic Conversion of Broadcasted Football Match Recordings to Its 2D Top View;measuring the Vehicle-in-Motion, Density and Allocation of Traffic Signal Using Transfer Learning;Ensemble Model of VGG16, ResNet50, and DenseNet121 for Human Identification Through Gait Features;Performance of Sentiment Analysis APIs on Political Opinion Polling;summarization of Telugu Text Discourses;crowd-Sourced Supervisors for the Automatic Invigilation of Online

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RHC Method Based 2D-equal-step Path Generation for UAV Swarm Online Cooperative Path Planning in Dynamic Mission Environment 23

RHC Method Based 2D-equal-step Path Generation for UAV Swarm...

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3rd international conference on artificial intelligence, automation and algorithms, ai2a 2023

作者： Shen, Yue Fan, Guoliang School of Artificial Intelligence University of Chinese Academy of Sciences China Institute of Automation Chinese Academy of Sciences China

ISBN: (纸本)9798400707605

This paper first mathematically models the UAV swarm online cooperative path planning problem based on the prerequisite assumptions of transparent posture and dynamic mission environment. Then the receding horizon control (RHC) and 2D-equal-step path generation method are briefly introduced and combined with the improved firefly optimization algorithm to solve the UAV swarm online cooperative path planning problem modeled in the previous. Simulations show that the improved firefly algorithm combining the RHC and 2D-equal-step path generation methods can be used to optimally solve the UAV swarm online cooperative path planning problem for moving mission targets in dynamic environments, and the improved firefly algorithm is more powerful and more efficient than the original algorithm in this process of application. © 2023 Owner/Author.

关键词： Unmanned aerial vehicles (UAV)

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A solution of TSP based on the improved ant colony optimization 23

A solution of TSP based on the improved ant colony optimizat...

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3rd international conference on artificial intelligence, automation and algorithms, ai2a 2023

作者： Nie, Hengyu Li, Meijuan Chen, Xuebo Cui, Zaihui School of Electronic Information and Engineering University of Science and Technology Liaoning Anshan China School of Artificial Intelligence Anshan Normal University Anshan China

ISBN: (纸本)9798400707605

In recent years, self-driving delivery vehicles have been used more and more widely. The route planning of courier vehicles can be abstracted as the traveling salesman problem (TSP). For the courier vehicle path optimization problem, an improved population-based ant colony optimization algorithm (IPACO) is proposed. The ant colony optimization algorithm (ACO) is a swarm intelligent bionic algorithm with the advantages of positive feedback, robustness, and easy combination with other algorithms, but it also has the problems of low solution accuracy and easy to fall into local optimality. In order to avoid these problems, the 2-opt local optimization operator is combined in the algorithm search process to improve the diversity of the population. In addition, the property that the simulated annealing algorithm probabilistically accepts relatively poor solutions is used to optimize the optimal ants during the iterative process. Finally, some TSPLIB examples are selected to verify the performance of the algorithm, and the fast adaptation capability of the algorithm under the change of path node weights is verified by simulation. © 2023 ACM.

关键词： Traveling salesman problem

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Word-Constrained Response Generation for international Chinese Language Education based on Decoder Backward Attention 23

Word-Constrained Response Generation for International Chine...

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3rd international conference on artificial intelligence, automation and algorithms, ai2a 2023

作者： Sun, Jingbo Song, Tianbao Liu, Haitao Peng, Weiming Song, Jihua School of Artificial Intelligence Beijing Normal University Beijing China School of Computer Science and Engineering Beijing Technology and Business University Beijing China Chinese Character Research and Application Laboratory Beijing Normal University Beijing China Linguistic Data Consortium University of Pennsylvania PhiladelphiaPA United States

ISBN: (纸本)9798400707605

Dialogue systems are a valuable technology in the field of natural language processing to improve work, learning, and daily life. Currently, dialogue systems are employed as an educational technology for mentoring, evaluation, and personalized learning. To make dialogue teaching achieve the purpose of training vocabulary at the primary level of international Chinese learning education, we first collect the entire dialogue corpus from textbooks to create the dataset, and then we propose a dialogue response generation model, Seq2BF-Attention, containing a specific word based on the sequence to backward and forward sequences framework by adding an attention to enhance the modeling of dialogue posts. We also provide two decoder connection strategies, backward hidden connection and backward attention, to handle the problems of not sharing parameters and incoherent generation separately. It has been experimentally proven that our suggested models perform well in both the ICLE and Weibo datasets across all metrics. © 2023 ACM.

关键词： Decoding

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An Evidential Classifier with Multiple Pre-trained Language Models for Nested Named Entity Recognition 23

An Evidential Classifier with Multiple Pre-trained Language ...

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3rd international conference on artificial intelligence, automation and algorithms, ai2a 2023

作者： Liu, Haitao Song, Jihua Peng, Weiming School of Artificial Intelligence Beijing Normal University Beijing China Chinese Character Research and Application Laboratory Beijing Normal University Beijing China

ISBN: (纸本)9798400707605

Nested named entity recognition (NER) is an important and challenging task in information extraction. One effective approach is to detect regions in sentences that are later classified by neural networks. Since pre-trained language models (PLMs) were proposed, nested NER models have benefited a lot from them. However, it is common that only one PLM is utilized for a given model, and the performance varies with different PLMs. We note that there exist some conflicting predictions which lead to the final variation. Thus, there is still room for investigation as to whether a model could achieve even better performance by conducting a comprehensive analysis of results from various PLMs. In this paper, we propose an evidential classifier with multiple PLMs for nested NER. First, the well-known deep exhaustive model is trained separately with different PLMs, whose predictions are then treated as pieces of evidence that can be represented in the framework of Dempster-Shafer theory. Finally, the pooled evidence is obtained using a combination rule, based on which the inference is performed. Experiments are conducted on the GENIA dataset, and detailed analysis demonstrates the merits of our model. © 2023 ACM.

关键词： Computational linguistics

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Research on the Application of artificial intelligence Technology in UAV Trajectory Prediction Algorithm 3

Research on the Application of Artificial Intelligence Techn...

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3rd international conference on Networking Systems of ai, INSai 2023

作者： Liu, Shaogang Zhang, Lingyan Qin, Chaowu West Yunnan University School of Artificial Intelligence & Information Engineering Lincang China

ISBN: (纸本)9798350344660

This study is based on artificial intelligence technologies such as machine learning algorithms and data visualization analysis, and is committed to designing and implementing a UAV trajectory prediction model. This model uses the random forest algorithm to perform UAV trajectory regression and prediction, and uses data visualization technology to extract features and reduce dimensionality of the data. First, the existing relevant literature is reviewed, and the research status and development trends of UAV trajectory prediction are sorted out. Subsequently, a large amount of UAV transaction data from 2023 was collected and cleaned, and analyzed, preprocessed and feature extracted for this data. On this basis, the random forest algorithm was used to perform regression and prediction of UAV trajectorys. This study conducted an in-depth analysis of the accuracy and error of the model, and summarized the advantages, disadvantages and future development directions of the model. © 2023 IEEE.

关键词： Prediction models

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Movement Pattern Recognition in Boxing Using Raw Inertial Measurements 3rd

Movement Pattern Recognition in Boxing Using Raw Inertial Me...

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3rd international conference on Optimization, Learning algorithms and Applications (OL2A)

作者： Puchalski, Radoslaw Giernacki, Wojciech Poznan Univ Tech Poznan Poland

ISBN: (纸本)9783031530357;9783031530364

In the paper, a new machine-learning technique is proposed to recognize movement patterns. The efficient system designed for this purpose uses an artificial neural network (ANN) model implemented on a microcontroller to classify boxing punches. artificial intelligence (ai) enables the processing of sophisticated and complex patterns, and the X-CUBE-ai package allows the use of these possibilities in portable microprocessor systems. The input data to the network are linear accelerations and angular velocities read from the sensor mounted on the boxer's wrist. By using simple time-domain measurements without extracting signal features, the classification is performed in real-time. An extensive experiment was carried out for two groups with different levels of boxing skills. The developed model demonstrated high efficiency in the identification of individual types of blows.

关键词： activity recognition artificial intelligence artificial neural networks edge computing microcontrollers

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BREAST ai: Low Cost, Explainable artificial intelligence Based App for Efficient Diagnosis of Breast Cancer in Developing Areas 3

BREAST AI: Low Cost, Explainable Artificial Intelligence Bas...

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3rd IEEE international conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2023

作者： Addala, Vibha Liberal Arts and Science Academy Computer Science Austin United States

ISBN: (纸本)9798350333862

Breast cancer is the most common cancer among women. Accurate diagnosis of breast cancer is crucial for successful treatment. However, many women in developing areas do not have access to similar medical resources as those in more developed areas, resulting in poor outcomes. Disparities range from a lack of mammograms in rural settings, as they are solely applicable to the breast, to a lack of trained radiologists to diagnose breast cancer. The goal of this research was to develop an artificial intelligence-based app for the accurate diagnosis of breast cancer via ultrasound scans without the need for an internet connection. The artificial intelligence model developed was a fine-tuned MobileNet-V2 convolutional neural network, trained on 624 ultrasound scans and tested on 156 scans from the Baheya Hospital in Egypt. The testing accuracy was 87.50%. To understand how the algorithm was making predictions (Explainable ai), code was created to generate heat maps to highlight parts of the breast ultrasound that were most significant in helping the algorithm make its decision. The ai model was downloaded as a TensorFlow Lite file, which allows for on-device machine learning, eliminating the need for an internet connection to operate, and developed into a user-friendly app. Further work, such as using a more diverse dataset, trying different convolutional neural network architectures, building a multimodal model, and implementing denoising algorithms can be done to improve this research. © 2023 IEEE.

关键词： Diagnosis

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An Example of Ontology in Medical Diagnosis: A Case Study 3rd

An Example of Ontology in Medical Diagnosis: A Case Study

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3rd international conference on Optimization, Learning algorithms and Applications (OL2A)

作者： Prnjak, Antonela Rosic, Marko Zaharija, Goran Krpan, Divna Mladenovic, Monika Univ Split Fac Sci Split Croatia

ISBN: (纸本)9783031530241;9783031530258

The widespread use of ai tools in recent years has put even more emphasis on the interaction between humans and computers in terms of information exchange and knowledge representation. Appropriate knowledge representation is important in the context of human-computer interaction because the knowledge has to be represented in a manner that is understandable to humans while still being useful for computers. This paper describes the approach of knowledge representation using ontologies and provides a use case example of using this approach in medical diagnosis.

关键词： Ontologies Knowledge Representation artificial intelligence

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