During vapour phase soldering, the lateral size of the specimen tray determines the number of assemblies that can be soldered at once. Increased productivity, thus less power consumption can be achieved by increasing ...
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The discovery of effective and efficient deception detection techniques in video data has significant implications in various fields such as psychology and law enforcement. With the advancement of computer technology,...
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Complex proteins are needed for many biological *** amino acid chains reveals their properties and *** support healthy tissue structure,physiology,and *** medicine and treatments require quantitative protein identific...
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Complex proteins are needed for many biological *** amino acid chains reveals their properties and *** support healthy tissue structure,physiology,and *** medicine and treatments require quantitative protein identification and *** technical advances and protein sequence data exploration,bioinformatics’“basic structure”problem—the automatic deduction of a protein’s properties from its amino acid sequence—remains *** function inference from amino acid sequences is the main biological data *** study analyzes whether raw sequencing can characterize biological facts.A massive corpus of protein sequences and the Globin-like superfamily’s related protein families generate a solid vector representation.A coding technique for each sequence in each family was devised using two representations to identify each amino acid precisely.A bispectral analysis converts encoded protein numerical sequences into images for better protein sequence and family *** and validation employed 70%of the dataset,while 30%was used for *** paper examined the performance of multistage deep learning models for differentiating between sixteen protein families after encoding and representing each encoded sequence by a higher spectral representation image(Bispectrum).Cascading minimized false positive and negative cases in all *** initial stage focused on two classes(six groups and ten groups).The subsequent stages focused on the few classes almost accurately separated in the first stage and decreased the overlapping cases between families that appeared in single-stage deep learning *** single-stage technique had 64.2%+/-22.8%accuracy,63.3%+/-17.1%precision,and a 63.2%+/19.4%*** two-stage technique yielded 92.2%+/-4.9%accuracy,92.7%+/-7.0%precision,and a 92.3%+/-5.0%*** work provides balanced,reliable,and precise forecasts for all families in all measures.
A novel multi-cost function model-based finite-set predictive control method is presented for grid-side converters equipped with LCL filters. This approach aims to overcome the tedious tuning of weighting factors. In ...
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In this study, we assess the efficacy of convolutional neural networks (CNNs) for classifying chest X-ray images into COVID-19, Lung Opacity, Viral Pneumonia, and Normal categories using a dataset of 21,165 images fro...
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The opportunities for writing mathematical optimization programs have become much wider in recent years through competitive programming contests. Despite this, frequently-used algorithmic frameworks, i.e., metaheurist...
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Fulfilling increasing performance demands of space and automotive applications can be problematic as high dependability is required. Memory is one of the most radiationsensitive parts, so it is often protected with in...
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This study presents an innovative method to improve the accuracy of indoor mapping by deploying and integrating a sensor that transmits two-dimensional data with a three-dimensional mesh created by another device. The...
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This study presents results from a vegetation-induced flow experimental study which investigates 3-D turbulence structure profiles,including Reynolds stress,turbulence intensity and bursting analysis of open channel *...
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This study presents results from a vegetation-induced flow experimental study which investigates 3-D turbulence structure profiles,including Reynolds stress,turbulence intensity and bursting analysis of open channel *** vegetation densities have been built between the adjacent vegetations,and the flow measurements are taken using acoustic Doppler velocimeter(ADV)at the locations within and downstream of the vegetation *** different tests are conducted,where the first test has compact vegetations,while the second and the third tests have open spaces created by one and two empty vegetation slots within the vegetated *** reveals that over 10%of eddies size is generated within the vegetated zone of compact vegetations as compared with the fewer *** turbulence structures variation is also observed at the points in the non-vegetated *** findings from burst-cycle analysis show that the sweep and outward interaction events are dominant,where they further increase away from the *** effect of vegetation on the turbulent burst cycle is mostly obvious up to approximately two-third of vegetation height where this phenomenon is also observed for most other turbulent structure.
A relationship between lung transplant success and many features of recipients’/donors has long been ***,modeling a robust model of a potential impact on organ transplant success has proved *** this study,a hybrid fe...
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A relationship between lung transplant success and many features of recipients’/donors has long been ***,modeling a robust model of a potential impact on organ transplant success has proved *** this study,a hybrid feature selection model was developed based on ant colony opti-mization(ACO)and k-nearest neighbor(kNN)classifier to investigate the rela-tionship between the most defining features of recipients/donors and lung transplant success using data from the United Network of Organ Sharing(UNOS).The proposed ACO-kNN approach explores the features space to identify the representative attributes and classify patients’functional status(i.e.,quality of life)after lung *** efficacy of the proposed model was verified using 3,684 records and 118 input features from the *** developed approach examined the reliability and validity of the lung allocation *** results are promising regarding accuracy prediction to be 91.3%and low computational time,along with better decision capabilities,emphasizing the potential for automatic classification of the lung and other organs allocation *** addition,the proposed model recommends a new perspective on how medical experts and clinicians respond to uncertain and challenging lung alloca-tion *** such ACO-kNN model,a medical professional can sum-marize information through the proposed method and make decisions for the upcoming transplants to allocate the donor organ.
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