In batch production systems, detecting low-yield machines is essential for minimizing the production of defective pieces, which is a complex problem that currently requires multiple experts, considerable capital, or a...
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Identifying cyberattacks that attempt to compromise digital systems is a critical function of intrusion detection systems(IDS).Data labeling difficulties,incorrect conclusions,and vulnerability to malicious data injec...
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Identifying cyberattacks that attempt to compromise digital systems is a critical function of intrusion detection systems(IDS).Data labeling difficulties,incorrect conclusions,and vulnerability to malicious data injections are only a few drawbacks of using machine learning algorithms for *** overcome these obstacles,researchers have created several network IDS models,such as the Hidden Naive Bayes Multiclass Classifier and supervised/unsupervised machine learning *** study provides an updated learning strategy for artificial neural network(ANN)to address data categorization problems caused by unbalanced *** to traditional approaches,the augmented ANN’s 92%accuracy is a significant improvement owing to the network’s increased resilience to disturbances and computational complexity,brought about by the addition of a random weight and standard *** the ever-evolving nature of cybersecurity threats,this study introduces a revolutionary intrusion detection method.
Polypropylene fibers are extensively incorporated into reinforced concrete to enhance performance aspects such as crack resistance, flexural and tensile strength, fire resistance, and overall durability. However, curr...
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Polypropylene fibers are extensively incorporated into reinforced concrete to enhance performance aspects such as crack resistance, flexural and tensile strength, fire resistance, and overall durability. However, current methods for evaluating factors like fiber inclusion percentage, distribution, and orientation within the concrete matrix are often limited, destructive, and time-consuming. This study explores developing and applying a non-contact microwave non-destructive method (NMNDT) for assessing polypropylene fiber-reinforced concrete. The NMNDT system measures the reflection and transmission characteristics of microwave signals through the concrete, correlating these properties with the physical and mechanical characteristics of the material. Key findings indicate a strong correlation between microwaves’ reflection and transmission properties, the quality of fiber distribution, and the fiber content within the concrete. For instance, the study found that the reflection coefficient (S11) increased from 0.36 to 0.39, with fiber content varying from 0.5 to 1.5 kg/m³, while the transmission coefficient (S21) decreased from 0.46 to 0.38 over the same range. The compressive strength of fiber-reinforced concrete was predicted with a correlation coefficient (R) of 0.98 using artificial neural networks (ANN). These microwave properties can predict mechanical properties such as tensile and compressive strength, with the ANN model achieving more than 97% accuracy. The study highlights the innovative potential of microwave technology as a non-invasive evaluation technique for polypropylene fiber-reinforced concrete, offering a promising avenue for rapid and non-destructive quality control and performance assessment. The integration of ANN further enhances the predictability of the strength properties of polypropylene fiber-reinforced concrete, significantly contributing to advancements in the field of fiber-reinforced concrete evaluation and quality
Delay tolerant wireless sensor networks(DTWSN)is a class of wireless network that finds its deployment in those application scenarios which demand for high packet delivery ratio while maintaining minimal overhead in o...
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Delay tolerant wireless sensor networks(DTWSN)is a class of wireless network that finds its deployment in those application scenarios which demand for high packet delivery ratio while maintaining minimal overhead in order to prolong network lifetime;owing to resource-constrained nature of *** fundamental requirement of any network is routing a packet from its source to *** of a routing algorithm depends on the number of network parameters utilized by that routing *** the recent years,various routing protocol has been developed for the delay tolerant networks(DTN).A routing protocol known as spray and wait(SnW)is one of the most widely used routing algorithms for *** this paper,we study the SnW routing protocol and propose a modified version of it referred to as Pentago SnW which is based on pentagonal number *** to binary SnW shows promising results through simulation using real-life scenarios of cars and pedestrians randomly moving on a map.
This study employs similar simulation testing and discrete element simulation coupling to analyze the failure and deformation processes of a model coal seam's *** caving area of the overburden rock is divided into...
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This study employs similar simulation testing and discrete element simulation coupling to analyze the failure and deformation processes of a model coal seam's *** caving area of the overburden rock is divided into three zones:the delamination fracture zone,broken fracture zone,and compaction *** caving and fracture zones'heights are approximately 110 m above the coal seam,with a maximum subsidence of 11 *** delamination fracture zone's porosity range is between 0.2 and 0.3,while the remainder of the roof predominantly exhibits a porosity of less than *** addition,the numerical model's stress analysis revealed that the overburden rock's displacement zone forms an'arch-beam'structure starting from 160 m,with the maximum and minimum stress values decreasing as the distance of advancement *** the stress beam interval of the overburden rock,the maximum value changes periodically as the advancement distance *** on a comparative analysis between observable data from on-site work and numerical simulation results,the stress data from the numerical simulation are essentially consistent with the actual results detected on-site,indicating the validity of the numerical simulation results.
Predicting crimes before they occur can save lives and losses of property. With the help of machine learning, many researchers have studied predicting crimes extensively. In this paper, we evaluate state-of-the-art cr...
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In this paper, the computation of graph Fourier transform centrality (GFTC) of complex network using graph filter is presented. For conventional computation method, it needs to use the non-sparse transform matrix of g...
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Vertical drains are used to accelerate consolidation of clays in ground improvement *** zones exist around these drains,where permeability is reduced due to soil disturbance caused by the installation *** solution is ...
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Vertical drains are used to accelerate consolidation of clays in ground improvement *** zones exist around these drains,where permeability is reduced due to soil disturbance caused by the installation *** solution is widely used in practice to consider the effects of drain discharge capacity and smear on the consolidation *** this study,a computationally efficient diameter reduction method(DRM)obtained from the Hansbo solution is proposed to consider the smear effect without the need to model the smear zone *** by analytical and numerical results,a diameter reduction factor is analytically derived to reduce the diameter of the drain,while achieving similar solutions of pore pressure dissipation profile as the classical full model of the smear zone and *** the DRM,the excess pore pressure u obtained from the reduced drain in the original un-disturbed soil zone is accurate enough for practical applications in numerical *** performance of DRM is independent of soil material *** also show equally accurate performance of DRM under conditions of multi-layered soils and coupled radial-vertical groundwater flow.
This research introduces a unique approach to segmenting breast cancer images using a U-Net-based ***,the computational demand for image processing is very ***,we have conducted this research to build a system that en...
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This research introduces a unique approach to segmenting breast cancer images using a U-Net-based ***,the computational demand for image processing is very ***,we have conducted this research to build a system that enables image segmentation training with low-power *** accomplish this,all data are divided into several segments,each being trained *** the case of prediction,the initial output is predicted from each trained model for an input,where the ultimate output is selected based on the pixel-wise majority voting of the expected outputs,which also ensures data *** addition,this kind of distributed training system allows different computers to be used *** is how the training process takes comparatively less time than typical training *** after completing the training,the proposed prediction system allows a newly trained model to be included in the ***,the prediction is consistently more *** evaluated the effectiveness of the ultimate output based on four performance matrices:average pixel accuracy,mean absolute error,average specificity,and average balanced *** experimental results show that the scores of average pixel accuracy,mean absolute error,average specificity,and average balanced accuracy are 0.9216,0.0687,0.9477,and 0.8674,*** addition,the proposed method was compared with four other state-of-the-art models in terms of total training time and usage of computational *** it outperformed all of them in these aspects.
Growing demands for customized, sustainable, and high-performance infrastructure urgently require innovative construction methodologies. Conventional methods for fiber-reinforced polymer concrete are not efficient in ...
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