Affinity Propagation Method it is necessary to modify the algorithm by using Principal Component Analysis (PCA). PCA method is used to reduce the attributes or characteristics that are less influential on the data so ...
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Soilborne diseases like Fusarium oxysporum and Rhizoctonia solani significantly impact sugar beet production, causing major yield losses. Accurate disease rating and characterization enhance disease management and bre...
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Soilborne diseases like Fusarium oxysporum and Rhizoctonia solani significantly impact sugar beet production, causing major yield losses. Accurate disease rating and characterization enhance disease management and breeding by tracking progression, assessing resistance, and guiding control strategies. Existing diagnostic approaches often focus on limited aspects of disease assessment, addressing only one or two ICQP objectives—identification, classification, quantification, and prediction—leaving gaps in comprehensive disease management. This study proposes an all-in-one framework that integrates hyperspectral imaging and machine learning to address all ICQP objectives. Hyperspectral data were collected from 122 plants inoculated with F. oxysporum and R. solani over 30 days using a Specim IQ hyperspectral sensor (400–1000 nm, 204 bands). To ensure accurate spectral data extraction, image segmentation was performed using a trained Deeplabv3+ model. Optimal wavelengths for each ICQP task were identified using the ANOVA algorithm and fed into three machine learning classifiers, including random forest (RF), multilayer perceptron (MLP), and support vector machine (SVM). The study revealed that no single spectral region or machine learning model was universally optimal across all ICQP objectives. Chlorophyll-sensitive wavelengths (670–700 nm) were optimal for both F. oxysporum and R. solani disease identification, while the near-infrared range (830–1000 nm) provided critical insights for disease type classification. RF achieved the highest accuracy (96%) in identifying healthy and infected plants and demonstrated strong performance in disease type classification. For disease quantification, MLP achieved superior results with 94% accuracy and an IoU of 88%, enabling detailed pixel-level mapping of disease severity with high confidence. This study demonstrates the importance of task-specific optimization in spectral analysis and machine learning, linking spectral features t
This paper describes an intelligent approach based on agents that are able to drive and coordinate trains on stretches of railway line containing a crossing loop. Halts close to or even in crossing loops lead to incre...
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Multi-Processors Systems-on-Chip (MPSoCs) are demanding for high performance, low power and high density, and therefore, three-dimensional integrated circuits (3DIC) emerge as a solution to integrate these systems. In...
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This paper reports on a simulation conducted to determine the number of semiautonomous robots that one operator can handle. Robots can be teleoperated, meaning a human controls the robot and tells it what to do;autono...
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This paper reports on a simulation conducted to determine the number of semiautonomous robots that one operator can handle. Robots can be teleoperated, meaning a human controls the robot and tells it what to do;autonomous, where the robot makes its own decisions;or teleautonomous, a combination of the two. The use of autonomous robots may reduce operator errors due to fatigue. However, at times, these robots may require human intervention, e.g., if they get stuck or in Urban Search and Rescue if a victim is found. A simulation of multiple autonomous robots and one human operator was conducted. The results indicate that while 7-10 robots give the operator barely any idle time, 1-4 robots allow too much. Based on these results, a single human operator handling somewhere between 5-6 robots might be ideal.
In recent times, there has been considerable attention directed towards Facial Expression Recognition (FER) due to its extensive utility across diverse domains. However, the universality of facial expressions has been...
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Nowadays, many people are starting to care about early investment. One of the most popular investments lately, especially for millennials, is a stock investment. In investing, there are advantages and risks of loss. O...
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The dynamic environment of Business Coalition (BC) requires a flexible access control approach to deal with user management and policy writing. However, the traditional approach applied to BC assigns to access control...
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Internet of Things (IoT) is a technology that is currently on a trend. Interconnecting networks on IoT are useful in the automation process, but it has vulnerabilities to network-based disruptions and attacks;such as ...
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This study reviews factors affecting AR-based chemistry learning with the BIM model. Although there have been many kinds of research explaining the application of augmented reality (AR) and building information modeli...
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