The work proposes the improvement of queue management priority-based Traffic engineering method. It is based on the interaction prediction principle to coordinate decisions at various levels. The lower level of calcul...
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This paper proposes a Complex-Valued Neural Network (CVNN) for glucose sensing in milli-meter wave (mmWave). Based on the propagation characteristics of millimeter wave in glucose medium, we obtain the S21 parameter o...
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Searching reads from unknown origins in a reference database and finding evolutionarily similar genomes is central to many applications. Quantifying the similarity by estimating the distance between each read and matc...
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This paper presents a solution for counting fruit in agricultural greenhouses using Unmanned Aerial Vehicles (UAV s). Initially, a heuristic based on Simulated Annealing was used to optimize the UAV's trajectory, ...
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ISBN:
(数字)9798350357882
ISBN:
(纸本)9798350357899
This paper presents a solution for counting fruit in agricultural greenhouses using Unmanned Aerial Vehicles (UAV s). Initially, a heuristic based on Simulated Annealing was used to optimize the UAV's trajectory, ensuring efficient coverage of the beds. Next, digital image processing (DIP) techniques were implemented to count the fruit, including depth segmentation, application of bounding boxes, color filtering, and element counting. The DIP accuracy was evaluated in multiple scenarios and the results indicate high reliability in fruit counting, with the potential to optimize agricultural operations and provide valuable information to producers. Possible future improvements could include further refinements in image processing to increase the accuracy of counting other fruits. Ultimately, this work contributes to the advancement of automation in agriculture by offering a viable and efficient solution for counting fruit in greenhouses using UAV s.
Data communications within the smart power grid components are susceptible to cyberattacks due to the inter-connected nature of the grid and reliance on communication networks. Such cyberattacks can exploit the integr...
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ISBN:
(数字)9789464593617
ISBN:
(纸本)9798331519773
Data communications within the smart power grid components are susceptible to cyberattacks due to the inter-connected nature of the grid and reliance on communication networks. Such cyberattacks can exploit the integrity of the exchanged data and result in operational instability. Existing data-driven cyberattack detection systems (CDSs) are proposed in the literature but their effectiveness is only verified against one type of cyberattacks. In reality, a smart grid system could encounter more than one attack type at once. Thus, in this paper, we investigate the resilience of state-of-the-art data-driven CDSs against replay false data injection, adversarial evasion, and adversarial data poisoning attacks on a realistic IEEE 118-bus system model. It turns out that a convolutional recurrent graph autoencoder-based CDS offers an attack detection rate of 96 – 97.5%, which outperforms other machine learning and deep learning-based data-driven CDSs by 16 – 54% since it captures the recurrent and spatial aspects of the data without being trained on attack data.
Stunting in toddlers is a chronic nutritional issue that affects the physical and cognitive development of children, with serious long-term consequences such as reduced cognitive function and an increased risk of chro...
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ISBN:
(数字)9798350379839
ISBN:
(纸本)9798350379846
Stunting in toddlers is a chronic nutritional issue that affects the physical and cognitive development of children, with serious long-term consequences such as reduced cognitive function and an increased risk of chronic diseases in adulthood. Therefore, early identification and prevention efforts for stunting are crucial. Classifying toddlers into categories of at-risk for stunting or not is essential to provide timely and appropriate interventions. This study employs data mining techniques using the decision tree algorithm to expedite the stunting detection process and improve the accuracy of nutritional status classification in children. The results indicate that the constructed decision tree model can classify children's nutritional status with an accuracy of 83.26%. The decision tree achieves high accuracy in classifying stunting in toddlers due to its ability to handle complex data and identify significant patterns within the data.
While deep learning-based Alzheimer's disease (AD) diagnosis has recently made significant advancements, particularly in predicting the conversion of mild cognitive impairment (MCI) to AD based on MRI images, ther...
Rocket launch centers are crucial in technological development across various fields, including meteorology, long-distance real-time communications, geoprocessing, and satellite operations. However, one of the challen...
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ISBN:
(数字)9798350350869
ISBN:
(纸本)9798350350876
Rocket launch centers are crucial in technological development across various fields, including meteorology, long-distance real-time communications, geoprocessing, and satellite operations. However, one of the challenges in tracking probing rockets is accurately identifying their position from the moment of launch until the initial seconds, due to ground noise that interferes with traditional radar location systems. In this study is proposed an innovative method to precisely determine the distance between the rocket and the ground telemetry station. We utilize onboard telemetry signals processed by the Acquisition and Processing Data Trajectory (APDtraj) system, developed by Delsis Aerospace for the Launch Center. This system enables the identification of the rocket's position both on the ground and during the early stages of flight, using telemetry data processed by APDtraj. This monitoring equipment alone calculated the distance between the Telemetry Station and the rocket just moments before launch lift-off with an error of only 16.844 meters from the actual position of origin. Based on our studies, we were able to measure the radial distance and location between the rocket and the telemetry station just four seconds after launch, even without reliable radar information, which is often disrupted by ground noise. This technological advancement not only enhances the efficiency of rocket launch operations but also expands overall tracking capabilities.
This paper discusses the design of observer-based fault estimation (FE) and fault-tolerant control (FTC) for a linear time-invariant (LTI) system subject to uncertainties, external disturbances, actuator faults, and s...
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ISBN:
(数字)9798350349740
ISBN:
(纸本)9798350349757
This paper discusses the design of observer-based fault estimation (FE) and fault-tolerant control (FTC) for a linear time-invariant (LTI) system subject to uncertainties, external disturbances, actuator faults, and sensor faults. Initially, an unknown input observer for an augmented system is designed to simultaneously estimate system states, actuator faults, and sensor faults. This augmented system was created by introducing an augmented state vector composed of system states and various faults. Subsequently, the fault-tolerant controller is designed to stabilize the system outputs. To reduce the effect of disturbances on the fault estimation, and make the controller robust, the UIO and the FTC gain matrices are obtained by minimizing a multi-objective function formed from a set of performance indices defined in the frequency domain. The effectiveness of the proposed method is demonstrated through its application to a DC motor system.
This study aims to increase the number of access users by limiting the sample size to 30 users while ensuring that every Optical Network Unit (ONU) receives data from the Optical Line Terminal (OLT). The proposed solu...
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