To address the problem of inaccurate prediction of slab quality in continuous casting, an algorithm based on particle swarm optimisation and differential evolution is proposed. The algorithm combines BP neural network...
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Classification of quantum phases is one of the most important areas of research in condensed matter *** this work,we obtain the phase diagram of one-dimensional quasiperiodic models via unsupervised ***,we choose two ...
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Classification of quantum phases is one of the most important areas of research in condensed matter *** this work,we obtain the phase diagram of one-dimensional quasiperiodic models via unsupervised ***,we choose two advanced unsupervised learning algorithms,namely,density-based spatial clustering of applications with noise(DBSCAN)and ordering points to identify the clustering structure(OPTICS),to explore the distinct phases of the Aubry–André–Harper model and the quasiperiodic p-wave *** unsupervised learning results match well with those obtained through traditional numerical ***,we assess similarity across different algorithms and find that the highest degree of similarity between the results of unsupervised learning algorithms and those of traditional algorithms exceeds 98%.Our work sheds light on applications of unsupervised learning for phase classification.
In recent years,Mobile Edge Computing(MEC)has received extensive research attention due to its characteristics,such as real-time data processing and flexible application ***,traditional MEC server deployment relies on...
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In recent years,Mobile Edge Computing(MEC)has received extensive research attention due to its characteristics,such as real-time data processing and flexible application ***,traditional MEC server deployment relies on the terrestrial Base Stations(BSs),resulting in high deployment costs and limited coverage *** response to these challenges,air-ground coordination has emerged,which effectively combines the advantages of edge computing and Unmanned Aerial Vehicles(UAVs),providing an effective architecture for edge *** utilizing the flexibility of UAVs and empowering them into edge nodes with computing resources,the coverage range of MEC can be expanded,thereby reducing the reliance of edge devices on terrestrial ***,leveraging terrestrial BSs as supplements to the computing power compensates for relatively limited computational capabilities of *** extensive studies have been conducted on air-ground coordination,there are few related summaries of application technologies and ***,the key technologies of air-ground coordination and applications are comprehensively reviewed in this ***,to provide guidance for interested researchers,the development trends and potential applications of air-ground coordination are explored.
To address the matching problem caused by the significant differences in spatial features, spectrum and contrast between heterologous images, a heterologous image matching method based on salience region is proposed i...
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Rock burst is a kind of severe engineering disaster resulted from dynamic fracture process of *** macrofailure behaviors of rocks are primarily formed after experiencing the initiation,propagation,and coalescenceof **...
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Rock burst is a kind of severe engineering disaster resulted from dynamic fracture process of *** macrofailure behaviors of rocks are primarily formed after experiencing the initiation,propagation,and coalescenceof *** this paper,the grain-based discretized virtual internal bond model is employed to investigatethe fracturing process of unloaded rock under high in-situ stresses from the micro-fracture *** micro-fracturing process reveals that the longitudinal stress waves induced by unloading lead to thevisible unloading *** influences of in-situ stresses,mineral grain sizes,and grain heterogeneity on rockmacro and micro fracture are ***-crack areas of tensile and shear cracks and micro-crack anglesare statistically analyzed to reveal the rock micro-fracture *** simulated results indicate thatthe combined effect of the stress state transition and the unloading effect dominates the rock unloading *** vertical and horizontal in-situ stresses determine the stress state of surrounding rock after unloading andthe unloading effect,*** the vertical stress increases,the stress level after unloading is higher,andthe shear failure characteristics become more *** the horizontal stress increases,the unloading effectincreases,leading to the intensification of tensile *** mineral grain size and grain heterogeneity alsohave nonnegligible influences on rock unloading *** micro-fracture perspective provides further insightinto the unloading failure mechanism of deep rock excavation.
In recent years,various adversarial defense methods have been proposed to improve the robustness of deep neural *** training is one of the most potent methods to defend against adversarial ***,the difference in the fe...
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In recent years,various adversarial defense methods have been proposed to improve the robustness of deep neural *** training is one of the most potent methods to defend against adversarial ***,the difference in the feature space between natural and adversarial examples hinders the accuracy and robustness of the model in adversarial *** paper proposes a learnable distribution adversarial training method,aiming to construct the same distribution for training data utilizing the Gaussian mixture *** distribution centroid is built to classify samples and constrain the distribution of the sample *** natural and adversarial examples are pushed to the same distribution centroid to improve the accuracy and robustness of the *** proposed method generates adversarial examples to close the distribution gap between the natural and adversarial examples through an attack algorithm explicitly designed for adversarial *** algorithm gradually increases the accuracy and robustness of the model by scaling ***,the proposed method outputs the predicted labels and the distance between the sample and the distribution *** distribution characteristics of the samples can be utilized to detect adversarial cases that can potentially evade the model *** effectiveness of the proposed method is demonstrated through comprehensive experiments.
The successful implementation of bioelectronic devices attached to living organism hinges on a number of material and device characteristics,including not only electrical and mechanical performances to gather physiolo...
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The successful implementation of bioelectronic devices attached to living organism hinges on a number of material and device characteristics,including not only electrical and mechanical performances to gather physiological signals from living organism thus enabling status monitoring,but also permeability or breathability for gas/nutrient exchange between living organisms and surroundings to ensure minimum perturbation of the intrinsic biological ***,most bioelectronic devices built on planar polymeric substrates,such as polydimethylsiloxane(PDMS),polyurethane(PU),and polyimide(PI),lack efficient gas permeability,which may hinder the emission of volatile compounds from the surface of living organism,affecting the natural metabolism and reducing the comfort of ***,achieving permeability or breathability in bioelectronic devices is a significant ***,the devices made of gas-permeable materials with porous structures,that combine electronic components with daily garments,such as fibric and textile,offer exciting opportunities for breathable *** this review,several types of gas-permeable materials with their synthesis and processing routes are ***,two methods for measuring water vapor transmission rate of materials are discussed in ***,recent progress in the use of gaspermeable materials for the applications of plant-and skin-attached electronics is summarized systematically.
Based on the security of distributed machine learning data and model based on remote proof, a cross-domain dynamic remote proof scheme based on ring signature improves the efficiency of computer cluster proof, the app...
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Since OpenAI opened access to ChatGPT,large language models(LLMs)become an increasingly popular topic attracting researchers’attention from abundant ***,public researchers meet some problems when developing LLMs give...
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Since OpenAI opened access to ChatGPT,large language models(LLMs)become an increasingly popular topic attracting researchers’attention from abundant ***,public researchers meet some problems when developing LLMs given that most of the LLMs are produced by industries and the training details are typically *** datasets are an important setup of LLMs,this paper does a holistic survey on the training datasets used in both the pre-train and fine-tune *** paper first summarizes 16 pre-train datasets and 16 fine-tune datasets used in the state-of-the-art ***,based on the properties of the pre-train and fine-tune processes,it comments on pre-train datasets from quality,quantity,and relation with models,and comments on fine-tune datasets from quality,quantity,and *** study then critically figures out the problems and research trends that exist in current LLM *** study helps public researchers train and investigate LLMs by visual cases and provides useful comments to the research community regarding data *** the best of our knowledge,this paper is the first to summarize and discuss datasets used in both autoregressive and chat *** survey offers insights and suggestions to researchers and LLM developers as they build their models,and contributes to the LLM study by pointing out the existing problems of LLM studies from the perspective of data.
In this paper we describe the selection of a modern build automation tool for an industry research partner of ours, namely an insurance company. Build automation has become increasingly important over the years. Today...
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