The fatigue assessment of structural components is a significant topic investigated both in the academia and industry. Despite the significant progress in comprehension over the past few decades, fatigue damage remain...
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The fatigue assessment of structural components is a significant topic investigated both in the academia and industry. Despite the significant progress in comprehension over the past few decades, fatigue damage remains a significant challenge, often leading to unexpected component failures. One commonly used approach for fatigue assessment is the critical plane analysis, which aids in identifying the critical location and early crack propagation direction in a component. However, the conventional method for calculating critical plane factors is computationally demanding and is typically utilized only when the critical regions of the component are already known. In situations where the critical areas are difficult to be identified due to complex geometry, loads, or constraints, a more efficient method is required for evaluating critical plane factors. This research paper introduces an analytical algorithm to efficiently evaluates the widely used Findley critical plane factor. The algorithm operates within the framework of linear-elastic material behavior and proportional loading conditions, relying on tensor invariants and coordinate transformation laws. The algorithm has been tested on different component geometries, including a box-welded joint and a tubular specimen, subjected to proportional loading conditions such as tension, torsion, and a combination of them. The analytical method allowed a significant reduction in computation time while providing the exact solution of critical plane factor and critical plane orientations.
To address the challenges associated with insufficient feature extraction and gradient degradation encountered when dealing with deepening network structures in image classification tasks, this paper presents a ResGME...
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To address the challenges associated with insufficient feature extraction and gradient degradation encountered when dealing with deepening network structures in image classification tasks, this paper presents a ResGMEANet(Residual Group Multi-scale Enhanced Attention Network). The model introduces a multi-scale attention enhancement module. This design draws inspiration from the original model's capability to independently capture feature correlations in channels and spaces. By implementing shuffle operations and feature transformations within the group, our method expands the receptive field through the utilization of multiple convolution kernels. Additionally, we incorporate an improved tensor synthesis attention, building upon the traditional convolution attention, to derive attention feature maps after feature enhancement. Evaluation on the CIFAR-10 and CIFAR-100 datasets shows that ResGMEANet outperforms both the original backbone model and several existing mainstream methods in classification accuracy. This work aims to provide a new perspective for the future by combining residual neural networks with different attention mechanisms.
With the continuous exploitation of offshore natural gas, the content of CO2 produced gradually increases. It is not economical to separate more CO2 from natural gas after transportation, and more CO2 will aggravate t...
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With the continuous exploitation of offshore natural gas, the content of CO2 produced gradually increases. It is not economical to separate more CO2 from natural gas after transportation, and more CO2 will aggravate the corrosion of pipelines. The commonly used decarburization process is not suitable for offshore platforms, and there are problems of high energy consumption and large space occupation. Therefore, dense phase separation of associated gas with high carbon dioxide content is a better separation method. In this paper, the equation of state is optimized by comparing the experimental and CO2 system phase characteristics simulation. Based on the selected equation of state (EOS), a three-level separation model of phase equilibrium characteristics is established. The separation efficiency is simulated to complete the separation of CO2 and methane. The separation process is optimized by a genetic algorithm, and the temperature and pressure under the best separation efficiency are determined. The PR-EOS was selected as the equation with the highest calculation accuracy. Through process simulation and algorithm optimization, the best separation efficiency was 72.23%.
Chemical explosives such as TNT are widely used in special scenarios, such as civil explosives, due to their simple preparation and high energy density. However, the temperature of the fireball produced by the explosi...
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Chemical explosives such as TNT are widely used in special scenarios, such as civil explosives, due to their simple preparation and high energy density. However, the temperature of the fireball produced by the explosion of these explosives is extremely high. Moreover, this approach may cause many casualties and economic losses if not prevented. To accurately measure the temperature of a transient explosion field and study its space-time distribution, a two-dimensional high-speed temperature measurement system was built based on blackbody radiation theory, high-speed photography, image Bayer array and improved interpolation algorithm. The explosive fireball produced in a static explosion test of 10 kg of TNT was measured within the shooting range. TNT was added with an auxiliary blackbody (tungsten). Compared to traditional explosion temperature measurement methods, the experimental results showed that the colorimetric temperature measurement method based on the improved interpolation algorithm and the addition of tungsten powder could more accurately measure the temporal and spatial distributions of the temperature field. This work can aid in the prevention in the accidents during the transportation, storage, and manufacturing of chemicals relevant to process industries.
This article presents the flow and techniques used to design a low-power digital signal processor chip used in a hearing aid system implementing multiband compression in 20 bands, pattern recognition, adaptive filteri...
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This article presents the flow and techniques used to design a low-power digital signal processor chip used in a hearing aid system implementing multiband compression in 20 bands, pattern recognition, adaptive filtering, and finescale noise cancellation. The pad limited 20 mm(2) chip contains 1.3 M transistors and operates at 2.5 MHz under 1.05-V supply voltage, Under these conditions, the DSP consumes 660 muW and performs 50 million 22-bit operations per second, therefore achieving 0.013 mW/Mops (milliwatts per million operations), which is a factor of seven better than prior results achieved in this field. The chip has been manufactured using a 0.25-mum 5-metal 1-poly process with normal threshold voltages. This low-power application-specific integrated circuit (ASIC) relies on an automated algorithm to silicon flow, low-voltage operation, massive clock gating, LP/LV libraries, and low-power-oriented architectural choices.
This letter introduces the implementation of H.263 video codec based on multimedia DSP TM1300, and discuses several key problems related to video coding.
This letter introduces the implementation of H.263 video codec based on multimedia DSP TM1300, and discuses several key problems related to video coding.
The process of parameter estimation in order to characterize a population using algorithms is in constant development and perfection. Recent years show that data-based decision-making is complex when there is uncertai...
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The process of parameter estimation in order to characterize a population using algorithms is in constant development and perfection. Recent years show that data-based decision-making is complex when there is uncertainty generated by statistical censoring. The purpose of this article is to evaluate the effect of statistical censoring on the normal distribution, which is common in many processes. Parameter estimation properties will be characterized with the conditional expected value algorithm, using different censoring percentages and sample sizes. The estimation properties chosen for the study will focus on the monitoring and decision-making related to industrial processes with the presence of censoring.
In recent years,artificial intelligence has been extensively applied in the diagnosis of gastric cancer based on medical *** particular,using deep learning as one of the mainstream approaches in image processing has m...
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In recent years,artificial intelligence has been extensively applied in the diagnosis of gastric cancer based on medical *** particular,using deep learning as one of the mainstream approaches in image processing has made remarkable *** this paper,we also provide a comprehensive literature survey using four electronic databases,PubMed,EMBASE,Web of Science,and *** literature search is performed until November *** article provides a summary of the existing algorithm of image recognition,reviews the available datasets used in gastric cancer diagnosis and the current trends in applications of deep learning theory in image recognition of gastric *** the theory of deep learning on endoscopic image *** further evaluate the advantages and disadvantages of the current algorithms and summarize the characteristics of the existing image datasets,then combined with the latest progress in deep learning theory,and propose suggestions on the applications of optimization *** on the existing research and application,the label,quantity,size,resolutions,and other aspects of the image dataset are also *** future developments of this field are analyzed from two perspectives including algorithm optimization and data support,aiming to improve the diagnosis accuracy and reduce the risk of misdiagnosis.
Nowadays anyone possesses at least one personal document, whether it is an identity card or a driving license. In many of our daily activities, working with documents or the necessity to present them in different cont...
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Nowadays anyone possesses at least one personal document, whether it is an identity card or a driving license. In many of our daily activities, working with documents or the necessity to present them in different contexts became something normal. Given the current situation, we are all going through, having to deal with the current pandemic situation, we have adapted to some extent to new ways of communicating, working, and resolving things, in general, using Internet tools and platforms. In this context, a small part of the fight we have with the bureaucracy has been won, many of the documents that once could only be brought only in physical locations can now be scanned and sent by email or attached to a form on the website. Hoping that the pandemic has also taught us good things, we want to believe that these ways of communication will be kept in place even after this issue is over, to avoid unnecessary waste of time and congestion. The focus of this project is developing an application that can create textual information data from a simple image provided by the user that will enable the possibility of sharing digital versions of documents, making our lives so much better.
This paper proposes a cochlear prosthetic system with an implanted digital signal processor （DSP）. This system transmits voice-band signals with a low data rate through the wireless link, free of the data-rate limit...
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This paper proposes a cochlear prosthetic system with an implanted digital signal processor （DSP）. This system transmits voice-band signals with a low data rate through the wireless link, free of the data-rate limitation and suitable for future development. By optimizing the speech processing algorithm and the DSP hardware design, the implanted DSP manages to execute the continuous interleaved sampling （CIS） algorithm at a clock frequency of 3MHz and a power consumption of only 1.91mW. With an analytic power-transmission efficiency of the wireless inductive link （40%）, the power overhead caused by the implanted DSP is derived as 2.87roW,which is trivial when compared with the power consumption of existing cochlear prosthetic systems （tens of milliwatts）. With the DSP implanted,this new system *** easily developed into a fully implanted cochlear prosthesis.
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