A newly designed small, almost square shaped Ultra Wideband antenna is presented in this paper. Free space simulations provided promising results with a wider bandwidth and high efficiency up to 97.68% within the UWB ...
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A 2-element microstrip multiple-input multiple-output (MIMO) antenna with circular polarization (CP) diversity is reported for 5G wireless applications in the sub-6 GHz band. The MIMO configuration in a single layer c...
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This paper investigates the effect of an adaptive Penalty Factor (PF) approach in compromising the weights for the combined economic emission dispatch problem. The proposed method aims to enhance the existing penalty ...
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5G mmWave offers a high-precision positioning solution, functioning effectively in both line-of-sight (LoS) and operable non-line-of-sight (NLoS) conditions. However, in scenarios with complete signal blockage, integr...
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Photonic crystal ring resonators (PCRR) as momentous candidates for future photonic crystal integrated circuits (PCICs) draw worldwide attention. In this paper, different configurations are proposed based on single, p...
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Under the advancements of science and technology at present, artificial intelligence has become widely applied in daily life. Hence, deep learning has attracted much attention in recent years and has been widely used ...
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Electricity supply and planning play a vital role in supporting economic development and improving the quality of life for communities. Effective decision-making in this domain requires a thorough understanding of ele...
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ISBN:
(纸本)9798350358155
Electricity supply and planning play a vital role in supporting economic development and improving the quality of life for communities. Effective decision-making in this domain requires a thorough understanding of electricity load patterns and consumption trends. Exploratory Data Analysis offers valuable opportunities to gain insights from electricity load data, as a use case of data science. In this study, 33KV feeders' peak load electricity measurements are acquired from Ota transmission stations, spanning four years (2019 to 2022). This data provides a rich source of information on seasonal variations in electricity consumption toward understanding demand patterns for optimizing resource allocation and infrastructure planning. Data analytics was therefore implemented on the historical peak load measurements to gather actionable insights for industry practitioners. Experimental results returns mean load value as a range from 4.24 to 20.16, indicating variations in electricity demand across the areas. The median values, ranging from 4.00 to 18.00, shows load measurements tend to center around a relatively stable level. Standard deviations value, between 1.27 and 2.61, illustrate the degree of variability in load measurements. The maximum load value discovered as 23.5 signifies the highest demand observed during the four-year study period, while the minimum load value of 1.0 signifies periods of low electricity consumption. The results also highlight variations in total load, emphasizing the importance of location-specific policies and infrastructure planning. For instance, AMJE exhibits the highest total load of 967.5, followed by Sango with 850.5 and IDI-IROKO with 689.5. Positive correlations are observed between SANGO and SUMO, indicating a tendency for these locations to experience similar load patterns. Whereas, negative correlations observed between IDI-IROKO and SUMO indicate contrasting load patterns between these locations. These correlations provide valua
Data’s role is pivotal in the era of internet technologies, but unstructured data poses comprehension challenges. Data visualizations like charts have emerged as crucial tools for condensing complex information. Clas...
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Direction of arrival (DOA) estimation of acoustic signals has been studied extensively by many researchers. Improving the performance of the DOA estimation methods is a hot topic in array signal processing. In this st...
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In the automated packaging production line of industrial systems, various stitching defects of packaging bags are inevitable hence the automated detection technology for stitching defects based on digital image proces...
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In the automated packaging production line of industrial systems, various stitching defects of packaging bags are inevitable hence the automated detection technology for stitching defects based on digital image processing plays a crucial role in improving the quality and reliability of the packaging production line. This paper proposes a novel stitching defect detection method based on Vision Transformers. image preprocessing procedures such as image correction and cropping recognition are performed to construct the raw stitching defect dataset. The pre-trained ViT_Base_Patch16_224_In21k and MobileViT-XXS networks are proposed by transfer learning methods to improve the recognition of stitching defects. Six sets of experiments are performed on image data taken on a packaging production line, and on the test set, the defect detection models' accuracy rates achieve 0.95 and 0.989, respectively. The experimental results reveal that the proposed method can be effectively applied for online automatic detection of stitching defects in packaging production lines and has industrial application significance.
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