Pub Date : 2022-01-24DOI: 10.1186/s13362-022-00120-3
G. Nastasi, V. Romano
{"title":"Drift-diffusion models for the simulation of a graphene field effect transistor","authors":"G. Nastasi, V. Romano","doi":"10.1186/s13362-022-00120-3","DOIUrl":"https://doi.org/10.1186/s13362-022-00120-3","url":null,"abstract":"","PeriodicalId":44012,"journal":{"name":"Journal of Mathematics in Industry","volume":"12 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65846416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-13DOI: 10.1186/s13362-022-00119-w
Carpio, Ana, Simón, Alejandro, Torres, Alicia, Villa, Luis F.
Medical data often appear in the form of numerical matrices or sequences. We develop mathematical tools for automatic screening of such data in two medical contexts: diagnosis of systemic lupus erythematosus (SLE) patients and identification of cardiac abnormalities. The idea is first to implement adequate data normalizations and then identify suitable hyperparameters and distances to classify relevant patterns. To this purpose, we discuss the applicability of Plackett-Luce models for rankings to hyperparameter and distance selection. Our tests suggest that, while Hamming distances seem to be well adapted to the study of patterns in matrices representing data from laboratory tests, dynamic time warping distances provide robust tools for the study of cardiac signals. The techniques developed here may set a basis for automatic screening of medical information based on pattern comparison.
{"title":"Pattern recognition in data as a diagnosis tool","authors":"Carpio, Ana, Simón, Alejandro, Torres, Alicia, Villa, Luis F.","doi":"10.1186/s13362-022-00119-w","DOIUrl":"https://doi.org/10.1186/s13362-022-00119-w","url":null,"abstract":"Medical data often appear in the form of numerical matrices or sequences. We develop mathematical tools for automatic screening of such data in two medical contexts: diagnosis of systemic lupus erythematosus (SLE) patients and identification of cardiac abnormalities. The idea is first to implement adequate data normalizations and then identify suitable hyperparameters and distances to classify relevant patterns. To this purpose, we discuss the applicability of Plackett-Luce models for rankings to hyperparameter and distance selection. Our tests suggest that, while Hamming distances seem to be well adapted to the study of patterns in matrices representing data from laboratory tests, dynamic time warping distances provide robust tools for the study of cardiac signals. The techniques developed here may set a basis for automatic screening of medical information based on pattern comparison.","PeriodicalId":44012,"journal":{"name":"Journal of Mathematics in Industry","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138526251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-06DOI: 10.1186/s13362-022-00124-z
M. Godehardt, A. Moghiseh, Christopher Oetjen, J. Ohser, K. Schladitz
{"title":"An unambiguous cloudiness index for nonwovens","authors":"M. Godehardt, A. Moghiseh, Christopher Oetjen, J. Ohser, K. Schladitz","doi":"10.1186/s13362-022-00124-z","DOIUrl":"https://doi.org/10.1186/s13362-022-00124-z","url":null,"abstract":"","PeriodicalId":44012,"journal":{"name":"Journal of Mathematics in Industry","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44668692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-03DOI: 10.1186/s13362-021-00116-5
N. Nowaczyk, Jörg Kienitz, S. Acar, Qian Liang
{"title":"How deep is your model? Network topology selection from a model validation perspective","authors":"N. Nowaczyk, Jörg Kienitz, S. Acar, Qian Liang","doi":"10.1186/s13362-021-00116-5","DOIUrl":"https://doi.org/10.1186/s13362-021-00116-5","url":null,"abstract":"","PeriodicalId":44012,"journal":{"name":"Journal of Mathematics in Industry","volume":"12 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65846303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01Epub Date: 2022-01-03DOI: 10.1186/s13362-021-00117-4
Davide Pradovera, Fabio Nobile
In the field of model order reduction for frequency response problems, the minimal rational interpolation (MRI) method has been shown to be quite effective. However, in some cases, numerical instabilities may arise when applying MRI to build a surrogate model over a large frequency range, spanning several orders of magnitude. We propose a strategy to overcome these instabilities, replacing an unstable global MRI surrogate with a union of stable local rational models. The partitioning of the frequency range into local frequency sub-ranges is performed automatically and adaptively, and is complemented by a (greedy) adaptive selection of the sampled frequencies over each sub-range. We verify the effectiveness of our proposed method with two numerical examples.
{"title":"A technique for non-intrusive greedy piecewise-rational model reduction of frequency response problems over wide frequency bands.","authors":"Davide Pradovera, Fabio Nobile","doi":"10.1186/s13362-021-00117-4","DOIUrl":"https://doi.org/10.1186/s13362-021-00117-4","url":null,"abstract":"<p><p>In the field of model order reduction for frequency response problems, the minimal rational interpolation (MRI) method has been shown to be quite effective. However, in some cases, numerical instabilities may arise when applying MRI to build a surrogate model over a large frequency range, spanning several orders of magnitude. We propose a strategy to overcome these instabilities, replacing an unstable global MRI surrogate with a union of stable local rational models. The partitioning of the frequency range into local frequency sub-ranges is performed automatically and adaptively, and is complemented by a (greedy) adaptive selection of the sampled frequencies over each sub-range. We verify the effectiveness of our proposed method with two numerical examples.</p>","PeriodicalId":44012,"journal":{"name":"Journal of Mathematics in Industry","volume":"12 1","pages":"2"},"PeriodicalIF":2.6,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8724177/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39827391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1007/978-981-16-6046-7
Jong-Chul Ye
{"title":"Geometry of Deep Learning","authors":"Jong-Chul Ye","doi":"10.1007/978-981-16-6046-7","DOIUrl":"https://doi.org/10.1007/978-981-16-6046-7","url":null,"abstract":"","PeriodicalId":44012,"journal":{"name":"Journal of Mathematics in Industry","volume":"54 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88452807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1007/978-3-319-63082-3
Franziska Abend
{"title":"Progress in Industrial Mathematics at ECMI 2021","authors":"Franziska Abend","doi":"10.1007/978-3-319-63082-3","DOIUrl":"https://doi.org/10.1007/978-3-319-63082-3","url":null,"abstract":"","PeriodicalId":44012,"journal":{"name":"Journal of Mathematics in Industry","volume":"10 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79085356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1007/978-3-030-96173-2
{"title":"Novel Mathematics Inspired by Industrial Challenges","authors":"","doi":"10.1007/978-3-030-96173-2","DOIUrl":"https://doi.org/10.1007/978-3-030-96173-2","url":null,"abstract":"","PeriodicalId":44012,"journal":{"name":"Journal of Mathematics in Industry","volume":"83 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73912807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-07DOI: 10.1186/s13362-021-00115-6
Moritz Ebeling-Rump, D. Hömberg, Robert Lasarzik, Thomas Petzold
{"title":"Topology optimization subject to additive manufacturing constraints","authors":"Moritz Ebeling-Rump, D. Hömberg, Robert Lasarzik, Thomas Petzold","doi":"10.1186/s13362-021-00115-6","DOIUrl":"https://doi.org/10.1186/s13362-021-00115-6","url":null,"abstract":"","PeriodicalId":44012,"journal":{"name":"Journal of Mathematics in Industry","volume":"2022 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2021-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65846743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-30DOI: 10.1186/s13362-021-00114-7
Launay, Hugo, Willot, François, Ryckelynck, David, Besson, Jacques
We develop a methodology for classifying defects based on their morphology and induced mechanical response. The proposed approach is fairly general and relies on morphological operators (Angulo and Meyer in 9th international symposium on mathematical morphology and its applications to signal and image processing, pp. 226-237, 2009) and spherical harmonic decomposition as a way to characterize the geometry of the pores, and on the Grassman distance evaluated on FFT-based computations (Willot in C. R., Méc. 343(3):232–245, 2015), for the predicted elastic response. We implement and detail our approach on a set of trapped gas pores observed in X-ray tomography of welded joints, that significantly alter the mechanical reliability of these materials (Lacourt et al. in Int. J. Numer. Methods Eng. 121(11):2581–2599, 2020). The space of morphological and mechanical responses is first partitioned into clusters using the “k-medoids” criterion and associated distance functions. Second, we use multiple-layer perceptron neural networks to associate a defect and corresponding morphological representation to its mechanical response. It is found that the method provides accurate mechanical predictions if the training data contains a sufficient number of defects representing each mechanical class. To do so, we supplement the original set of defects by data augmentation techniques. Artificially-generated pore shapes are obtained using the spherical harmonic decomposition and a singular value decomposition performed on the pores signed distance transform. We discuss possible applications of the present method, and how medoids and their associated mechanical response may be used to provide a natural basis for reduced-order models and hyper-reduction techniques, in which the mechanical effects of defects and structures are decorrelated (Ryckelynck et al. in C. R., Méc. 348(10–11):911–935, 2020).
我们开发了一种基于其形态和诱导机械响应的缺陷分类方法。所提出的方法是相当通用的，依赖于形态学算子(Angulo和Meyer在第9届国际数学形态学及其在信号和图像处理中的应用研讨会上，pp. 226-237, 2009)和球面谐波分解作为表征孔隙几何形状的方法，以及基于fft计算评估的Grassman距离(Willot in C. R.， msamac .)。(3):232 - 245,2015)，用于预测弹性响应。我们在焊接接头的x射线断层扫描中观察到一组被困的气孔，并对其进行了实施和详细说明，这些气孔显著改变了这些材料的机械可靠性(Lacourt et al. in Int)。j .号码。方法工程学报，121(11):2581-2599,2020)。首先利用“k-介质”准则和相关的距离函数将形态和力学响应空间划分为簇。其次，我们使用多层感知器神经网络将缺陷和相应的形态表征与其机械响应联系起来。如果训练数据包含足够数量的代表每个机械类的缺陷，则该方法可以提供准确的机械预测。为此，我们通过数据增强技术来补充原始的缺陷集。对孔隙符号距离变换进行球谐分解和奇异值分解，得到人工生成的孔隙形状。我们讨论了本方法的可能应用，以及如何使用介质及其相关的机械响应来为降阶模型和超约化技术提供自然基础，其中缺陷和结构的机械效应是去相关的(Ryckelynck et al. in C. R.， m。348(年级):911 - 935,2020)。
{"title":"Mechanical assessment of defects in welded joints: morphological classification and data augmentation","authors":"Launay, Hugo, Willot, François, Ryckelynck, David, Besson, Jacques","doi":"10.1186/s13362-021-00114-7","DOIUrl":"https://doi.org/10.1186/s13362-021-00114-7","url":null,"abstract":"We develop a methodology for classifying defects based on their morphology and induced mechanical response. The proposed approach is fairly general and relies on morphological operators (Angulo and Meyer in 9th international symposium on mathematical morphology and its applications to signal and image processing, pp. 226-237, 2009) and spherical harmonic decomposition as a way to characterize the geometry of the pores, and on the Grassman distance evaluated on FFT-based computations (Willot in C. R., Méc. 343(3):232–245, 2015), for the predicted elastic response. We implement and detail our approach on a set of trapped gas pores observed in X-ray tomography of welded joints, that significantly alter the mechanical reliability of these materials (Lacourt et al. in Int. J. Numer. Methods Eng. 121(11):2581–2599, 2020). The space of morphological and mechanical responses is first partitioned into clusters using the “k-medoids” criterion and associated distance functions. Second, we use multiple-layer perceptron neural networks to associate a defect and corresponding morphological representation to its mechanical response. It is found that the method provides accurate mechanical predictions if the training data contains a sufficient number of defects representing each mechanical class. To do so, we supplement the original set of defects by data augmentation techniques. Artificially-generated pore shapes are obtained using the spherical harmonic decomposition and a singular value decomposition performed on the pores signed distance transform. We discuss possible applications of the present method, and how medoids and their associated mechanical response may be used to provide a natural basis for reduced-order models and hyper-reduction techniques, in which the mechanical effects of defects and structures are decorrelated (Ryckelynck et al. in C. R., Méc. 348(10–11):911–935, 2020).","PeriodicalId":44012,"journal":{"name":"Journal of Mathematics in Industry","volume":"33 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2021-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138526225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：