the safety management of a water conservancy construction site faces difficulties. To effectively supervise all workers' operational activity, this study develops a human activity recognition model using a modifie...
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the proceedings contain 24 papers. the topics discussed include: are large language models good at fuzzy reasoning?;machine learning-based predictive model for fabric wastage in the apparel industry due to defective f...
ISBN:
(纸本)9798400717437
the proceedings contain 24 papers. the topics discussed include: are large language models good at fuzzy reasoning?;machine learning-based predictive model for fabric wastage in the apparel industry due to defective fabric raw materials;optimizing neural network training efficiency through spectral parameter-based multiple adaptive learning rates;machine learning-based patent transferability forecasting for emerging technology: a case study of graphene-based supercapacitors;automated pest control: computer vision for wildlife surveillance;anomaly detection in retinal imagery using variational autoencoders;evaluating the suitability of inception score and frechet inception distance as metrics for quality and diversity in image generation;and continuous estimation of distribution algorithms for the parametric optimization of geothermal power plants.
Objective: Both simulation and experimental studies show that human walking is a passive biped walking mode adapting to the gravity environment of the earth, and its energy consumption rate is much lower than that of ...
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the proceedings contain 66 papers. the topics discussed include: development of UAV image processing algorithms for early detection of fires in natural ecosystems;modeling satellite repeater for UAV;methods for matchi...
ISBN:
(纸本)9798331534141
the proceedings contain 66 papers. the topics discussed include: development of UAV image processing algorithms for early detection of fires in natural ecosystems;modeling satellite repeater for UAV;methods for matching the current UAV frame with satellite images to improve the accuracy of the visual navigation system;combining pathfinding and weapon-target assignment for air defense;the use of neural networks and quantum algorithms for the classification images from UAV;deep learning-based UAV detection;implementation of an adaptive multi-channel filter system on FPGA;synthesis and modelling of control system for quadrotor motion;algorithm for calculating optimal parameters contributing to UAV operation efficiency;UAV flight control under the presence of dynamic geofencing;and using stacked ensemble classifiers to speed up object recognition in images for mine detection drones.
this paper addresses the challenge of achieving resilient quantized consensus in multiagent systems operating within adversarial environments. Existing algorithms often rely on an assumption of the maximum adversarial...
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Accurate gait phase recognition is crucial for real-time analysis and intervention in rehabilitation, biomechanics, and prosthetics. However, achieving this is challenging due to the diverse machine learning (ML) trai...
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ISBN:
(纸本)9798350351491;9798350351484
Accurate gait phase recognition is crucial for real-time analysis and intervention in rehabilitation, biomechanics, and prosthetics. However, achieving this is challenging due to the diverse machine learning (ML) training methods. this study employs ML algorithms to classify gait phases, focusing on stance and swing phases, utilizing open-source data from 100 participants (41.91 +/- 5.3 yrs). the classification algorithms considered are k-Nearest Neighbor (k-NN), Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and Naive Bayesian (NB) algorithms. the study evaluates these algorithm performances using two training methods with five and ten lower body movements: one randomly selects 80% of stance and swing phase data for training, while the other divides data by participants, allocating 80% for training and 20% for testing. When assessing accuracy with five movements, RF achieved 99.8% for both training methods. With ten movements, RF achieved a high accuracy of 99.9% using the second method. Notably, the performance of all ML algorithms exhibited improvement when considering data from ten movements versus five. Additionally, it was observed that the second training method proved more effective with five-movement data compared to data involving ten movements. this comprehensive evaluation highlights the potential of machine learning algorithms for accurate gait phase recognition in diverse applications with varied training methods.
In the dynamic landscape of VLSI technology, Quantum-dot Cellular Automata (QCA) has emerged as a promising contender to traditional CMOS technology, owing to its potential for smaller feature sizes, higher operationa...
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ISBN:
(数字)9798350350470
ISBN:
(纸本)9798350350470;9798350350487
In the dynamic landscape of VLSI technology, Quantum-dot Cellular Automata (QCA) has emerged as a promising contender to traditional CMOS technology, owing to its potential for smaller feature sizes, higher operational frequencies, and reduced power requirements. Early investigations in the QCA realm have predominantly emphasized the deployment of varied sequential and combinational circuit models, acting as fundamental elements for numerous applications. However, recent trends have seen a shift towards the development of application-specific designs using QCA. Motivated by this trend, this paper endeavors to explore the utilization of reversible logic gates in the design of an Arithmetic Unit within the QCA framework. the objective is to implement key arithmetic components, including a Full Adder, Full Subtractor, Multiplier, Divider, and then integrate them using a 4:1 MUX to form a comprehensive Arithmetic Unit. the performance evaluation of these components is conducted across multiple metrics, including area utilization, quantum cost, delay, energy consumption, and QCA cell utilization. To confirm the functionality of the proposed designs, comprehensive simulations are performed, generating waveform outputs that undergo thorough functional verification.
Withthe recent emergence of generative AI (Artificial intelligence), Large Language Model (LLM) based tools such as ChatGPT have become popular assistants to humans in diverse tasks. ChatGPT has also been widely adop...
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ISBN:
(纸本)9798350386608;9798350386592
Withthe recent emergence of generative AI (Artificial intelligence), Large Language Model (LLM) based tools such as ChatGPT have become popular assistants to humans in diverse tasks. ChatGPT has also been widely adopted for solving programming problems and for generating source code in software development. this research investigates boththe code quality and the consistency of code quality over iterative prompts in 625 ChatGPT-generated Python code samples in the DevGPT dataset and the corresponding code snippets regenerated by manually prompting ChatGPT. Code samples are measured in terms of seven Halstead complexity metrics. We also assess how consistent they are across code snippets generated by different versions of ChatGPT. It was found that while ChatGPT generates good quality code across iterative prompts, it does generate semi-frequent bugs, similar to how humans do, necessitating code review before integration. these traits also remain consistent across code snippets generated by subsequent releases of ChatGPT. these results suggest using AI-generated source code in software development will not hinder the process.
Withthe development of computer vision technology and the development of navigation and obstacle avoidance algorithms, coupled withthe serious shortage of guide dogs in today's society, this paper realizes the i...
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ISBN:
(纸本)9798400708305
Withthe development of computer vision technology and the development of navigation and obstacle avoidance algorithms, coupled withthe serious shortage of guide dogs in today's society, this paper realizes the identification and obstacle avoidance of quadruped robot dogs in some terrains by combining quadruped robot dogs, computer vision detection and radar.
the proceedings contain 45 papers. the topics discussed include: enhancing dental service efficiency: development and evaluation of a smart dental appointment system;advancing proactive producer mobility management in...
ISBN:
(纸本)9798331519513
the proceedings contain 45 papers. the topics discussed include: enhancing dental service efficiency: development and evaluation of a smart dental appointment system;advancing proactive producer mobility management in named data networking: a conceptual model;proposing a blockchain-based assessment management upon education of Malaysia;performance evaluation and proposed enhancement of latest image watermarking schemes against specific forgery attacks;automating web data collection: challenges, solutions, and python-based strategies for effective web scraping;comparative analysis of data compression and communication algorithms;majority voting-based heterogeneous ensemble method for intrusion detection system;and optimized campus navigation using mobile app: network analysis for effective route planning.
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