Certain estimates place skin cancer as the most lethal form of the disease worldwide. Spreading to other parts of the body and requiring invasive procedures like chemotherapy and radiation therapy are the results of d...
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This paper is aimed to provide a new design modeling of the gripper via using the intelligent computing model. The gripper is designed to get benefit of a symmetric structure and compliant mechanism that can manipulat...
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This paper is aimed to provide a new design modeling of the gripper via using the intelligent computing model. The gripper is designed to get benefit of a symmetric structure and compliant mechanism that can manipulate the objects with a stable force. The numerically experimental samples for the gripper are built and the finite element simulations are implemented. The displacement of left hand is collected. An intelligent computing model is formulated via a hybridization of the teachinglearning optimization and feed forward neural network. The teachinglearning optimization algorithm is embedded into neural network to enhance the training process. The results determined that the mean square error values of the entire model, the training, the testing, and validating are about 6.04e-07, 6.11e-07, 6.50e-08, and 1.10e-06, respectively. Furthermore, the coefficient of determination value of the entire model, the training, the testing, and validating are 0.9975, 0.9970, 0.9998, and 0.9677, accordingly. In addition, the proposed intelligent predictor is outperformed other regression methods such as linear regression, full 2nd order polynomial regression, and traditional artificial neural network. Moreover, the errors among the estimated from the proposed intelligent method and the prediction errors are less than 3%. It revealed that the proposed intelligent methodology is a well-suitable predictor for modeling the behaviors of gripper. The gripper is capable of providing a displacement amplification ratio of 2.85 and a max grasping force of 145.96 N. The gripper is potential for many practical applications such as robotics and manipulators in agricultural and electrics engineering.
This paper discusses the feasibility of using an automated pipeline that is text-to-speech and speech-to-text, which will be powered with the usage of Optical Character Recognition (OCR) that may be used for extractin...
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The proceedings contain 192 papers. The topics discussed include: application of artificial intelligence and big data in smart buildings;engine detection and online monitoring technology based on image recognition;mec...
ISBN:
(纸本)9798350395631
The proceedings contain 192 papers. The topics discussed include: application of artificial intelligence and big data in smart buildings;engine detection and online monitoring technology based on image recognition;mechanical parts life prediction and health monitoring system based on deep learning;research on optimal zoning of energy Internet source load matching power grid based on improved K-means algorithm;design of power load forecasting algorithm for distribution network based on machine learning;analysis of sea ice area fluctuation in the arctic circle based on big data and SARIMA model;a redesign method for embroidery pattern graphics based on multiscale image processing technology;and research on data mining of university management decision support archives based on cloud computing.
The utilization of artificial intelligence (AI) and other cutting-edge techniques in the field of medical image analysis has exhibited significant potential. Nevertheless, a significant obstacle that impedes the exten...
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The mouse has been a vital tool for human-computer interaction, with wired, wireless, and Bluetooth variations requiring power to connect a dongle to a PC. The proposed work uses the latest technology in computer visi...
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Predicting oceanic phenomena plays a very important role in ensuring maritime safety, managing coastal areas and preparing them for any disasters like cyclone or tsunami. There are several factors that contribute to t...
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This study presents a comparative analysis of the Deep Q-Network (DQN) and Deep Deterministic Policy Gradient (DDPG) reinforcement learning algorithms in the context of stock trading, focusing on historical stock pric...
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In order to solve the problem of dangerous accidents caused by unsafe behaviors in university laboratories, We propose an improved method based on the RTFM model. This method combines Dilated convolution and multi-hea...
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This article designs a classification method for long educational news texts based on labeled educational news reports. Firstly, CNN is used to extract local features of text information. Then, a bidirectional long sh...
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