The stock market (SM) is fundamentally nonlinear in nature and the people invest in SM on the basis of predictions. The SM prediction is a highly challenging and complex process. The classical techniques may not guara...
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As virtual reality (VR) continues to expand, particularly in social VR platforms and immersive gaming, understanding the factors that shape user experience is becoming increasingly important. Avatars and locomotion me...
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This work focuses on reengineering an HMI implemented in a third-party legacy tool to an IEC 61499 implementation. We propose a method to re-engineer the view for a process system and gather relevant information for t...
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In the certification problem, the algorithm is given a function f with certificate complexity k and an input x*, and the goal is to find a certificate of size ≤ poly(k) for f's value at x*. This problem is in NPN...
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Virtual experiences can significantly influence our perception and behavior in the real world, shaping how we interact with and navigate physical environments. In this paper, we examine the impact of learning navigati...
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In this paper, we propose an algorithm that automatically labels datasets for the development and testing of autonomous vehicles. Traditionally, it is commonly used hand-labeled datasets, which is costly and time-cons...
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Manual inspection of fruit diseases is a time-consuming and costly because it is based on naked-eye *** authors present computer vision techniques for detecting and classifying fruit leaf *** of computer vision techni...
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Manual inspection of fruit diseases is a time-consuming and costly because it is based on naked-eye *** authors present computer vision techniques for detecting and classifying fruit leaf *** of computer vision techniques are preprocessing original images for visualization of infected regions,feature extraction from raw or segmented images,feature fusion,feature selection,and *** following are the major challenges identified by researchers in the literature:(i)lowcontrast infected regions extract irrelevant and redundant information,which misleads classification accuracy;(ii)irrelevant and redundant information may increase computational time and reduce the designed model’s *** paper proposed a framework for fruit leaf disease classification based on deep hierarchical learning and best feature *** the proposed framework,contrast is first improved using a hybrid approach,and then data augmentation is used to solve the problem of an imbalanced *** next step is to use a pre-trained deep model named Darknet53 and fine-tune ***,deep transfer learning-based training is carried out,and features are extracted using an activation function on the average pooling ***,an improved butterfly optimization algorithm is proposed,which selects the best features for classification using machine learning *** experiment was carried out on augmented and original fruit datasets,yielding a maximum accuracy of 99.6%for apple diseases,99.6%for grapes,99.9%for peach diseases,and 100%for cherry *** overall average achieved accuracy is 99.7%,higher than previous techniques.
The mega-constellation network has gained significant attention recently due to its great potential in providing ubiquitous and high-capacity connectivity in sixth-generation(6G)wireless communication ***,the high dyn...
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The mega-constellation network has gained significant attention recently due to its great potential in providing ubiquitous and high-capacity connectivity in sixth-generation(6G)wireless communication ***,the high dynamics of network topology and large scale of mega-constellation pose new challenges to the constellation simulation and performance *** this paper,we introduce UltraStar,a lightweight network simulator,which aims to facilitate the complicated simulation for the emerging mega-constellation of unprecedented ***,a systematic and extensible architecture is proposed,where the joint requirement for network simulation,quantitative evaluation,data statistics and visualization is fully *** characterizing the network,we make lightweight abstractions of physical entities and models,which contain basic representatives of networking nodes,structures and protocol ***,to consider the high dynamics of Walker constellations,we give a two-stage topology maintenance method for constellation initialization and orbit ***,based on the discrete event simulation(DES)theory,a new set of discrete events is specifically designed for basic network processes,so as to maintain network state changes over ***,taking the first-generation Starlink of 11927 low earth orbit(LEO)satellites as an example,we use UltraStar to fully evaluate its network performance for different deployment stages,such as characteristics of constellation topology,performance of end-to-end service and effects of network-wide traffic *** simulation results not only demonstrate its superior performance,but also verify the effectiveness of UltraStar.
Recently, deep reinforcement learning (DRL) has been employed in flexible job-shop scheduling problems (FJSP) to minimize makespan within flexible manufacturing systems (FMS). In practice, numerous modern enterprises ...
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Literature on power quality compensators (PQC) was shown to increase the reliability of the power system. While finite control set model predictive control (MPC) achieves high fidelity tracking for multi-objective cos...
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