Autonomous Vehicle (AV) usage has become predominant in the rapidly evolving landscape of urban transportation. Integrating AVs and non-AVs in the existing traffic infrastructure has significantly increased the comple...
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This paper presents the application of Kolmogorov-Arnold Networks (KAN) in classifying metal surface defects. Specifically, steel surfaces are analyzed to detect defects such as cracks, inclusions, patches, pitted sur...
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In response to the growing environmental complexities, the agricultural sector is actively integrating advanced technologies to fortify its adaptability and operational efficiency. A pivotal avenue of exploration cent...
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In response to the growing environmental complexities, the agricultural sector is actively integrating advanced technologies to fortify its adaptability and operational efficiency. A pivotal avenue of exploration centers on exploiting machine learning models for the prediction of greenhouse parameters. This study explores the prediction of greenhouse energy demand and production. For that, the study employs a new hybrid approaches (series and parallel), combining artificial neural networks and boosting trees, to predict air-conditioning electrical consumption and photovoltaic modules' electrical production. Model performance is evaluated based on statistical indicators, including the coefficient of correlation (R) and the normalized root mean square error (nRMSE). Results reveal that series and parallel hybrid models demonstrate acceptable to good performance (10%
One of the industry’s most common applications of lasers is engraving, which is generally performed on flat surfaces. However, there are many situations where the object to be engraved has an unevenly curved geometry...
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We discuss recent progress in the understanding of the formation of patterns of snow crystals. In particular, we concentrate on the transition from hexagonal to dendritic patterns that occurs with an increase in the d...
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We discuss recent progress in the understanding of the formation of patterns of snow crystals. In particular, we concentrate on the transition from hexagonal to dendritic patterns that occurs with an increase in the degree of supersaturation. Our numerical results demonstrate that the anisotropy of surface kinetics plays a very important role in the formation of faceted shapes of snow crystals in the form of hexagonal prisms and of facets seen at the tips of dendrites. Furthermore, it is shown that the conditions for the transition from a hexagonal to a dendritic pattern are given by the supersaturation and the dimensionless crystal size relative to the mean free path of a water molecule in air.
An efficient novel approach is introduced to predict the effectiveness of chemotherapy treatment in lung cancer by monitoring the serum N-glycome of patients combined with artificial intelligence-based data analysis. ...
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This paper compares the performance of an indoor cellular system in terms of capacity and channel assignment delay for different Dynamic Channel Assignment (DCA) and Fixed Channel Assignment (FCA) schemes. We refer to...
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This paper compares the performance of an indoor cellular system in terms of capacity and channel assignment delay for different Dynamic Channel Assignment (DCA) and Fixed Channel Assignment (FCA) schemes. We refer to specific group of DCAs, namely Channel Segregation and Reuse Partitioning (RP). Our main concern is to show that these DCA schemes offer better performance than FCA. Since the structure and floor layout of a building will have a major influence on the propagation and hence on the cell shape, a path loss simulator is developed for predicting the path loss which is used in evolving base station layouts. computer simulation, based on Monte Carlo method, is carried out using the path loss values and the base station layouts. The results indicate that increased traffic capacity can be achieved with ail DCAs in comparison with FCA. The highest capacity and a shorter channel assignment delay are delivered by Self-Organized Reuse Partitioning DCA scheme.
Loss functions are at the heart of deep learning, shaping how models learn and perform across diverse tasks. They are used to quantify the difference between predicted outputs and ground truth labels, guiding the opti...
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In [2] Ibarra introduced a restricted Version of one-way muItihead pushdown automaton (PDA), called a simple one-way multihead PDA, and showed that such machines recognize only languages with semilinear property. The ...
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In [2] Ibarra introduced a restricted Version of one-way muItihead pushdown automaton (PDA), called a simple one-way multihead PDA, and showed that such machines recognize only languages with semilinear property. The main result of this paper is that for each k greater than or equal to 1, simple (sensing) one-way (k+1)-head PDA's are more powerful than simple (sensing) one-way k-head PDA's. This paper also investigates closure properties for simple (sensing) one-way muItihead PDA's.
This paper investigates the (Formula presented.) control problem for discrete-time uncertain slow sampling Markov jump systems under the event-triggered scheme. Discrete-time Markov jumps are controlled using an event...
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