Research on Reliability Testing Technology of Rail Transit Software by Ying YANG, Zhifei ZHOU, Buqi LIU, Weiqi JIAO

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Redshift Distributions of Fast Radio Bursts Inferred Using Clustering in Dispersion Measure Space by Hui Peng, Yu Yu

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Methodology to identify robots given the type of control designation by S. A. Arkhipenka, L. U. Shilin, A. A. Naurotsky, A. P. Kuznetsov

Subjects: “…data structure…”
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Smart Cities and Resident Well-Being: Using the BTOPSIS Method to Assess Citizen Life Satisfaction in European Cities by Ewa Roszkowska, Tomasz Wachowicz

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$$\textsc {McDag}$$ M C D A G : indexing maximal common subsequences for k strings by Giovanni Buzzega, Alessio Conte, Roberto Grossi, Giulia Punzi

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The nexus between structural transformation and poverty reduction in Maghreb region. A sectoral value-added analysis by FREEMAN MUNISI MATEKO

“…ABSTRACT The study examined the relationship between structural transformation and poverty reduction in the Maghreb region. …”
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Aboveground Biomass in West African Semi‐Arid Ecosystems: Structural Diversity, Taxonomic Contributions and Environmental Drivers by Kangbéni Dimobe, Shem Kuyah, Korotimi Ouédraogo, Ebagnerin Jérôme Tondoh, Adjima Thiombiano

“…ABSTRACT The role of plant diversity and biomass in ecosystem functioning and management is well recognized. However, the structural drivers of aboveground biomass (AGB) and their influence across savanna ecosystems remain understudied, particularly in semi‐arid regions. …”
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Mechanism that links perceived racism and discrimination and youth cannabis use, a structural equation modeling approach by Hongying Daisy Dai, Brian Young, Cheryl Beseler

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Utilizing RNA-seq data in monotone iterative generalized linear model to elevate prior knowledge quality of the circRNA-miRNA-mRNA regulatory axis by Alikhan Anuarbekov, Jiří Kléma

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Data-driven modeling and identification of a bistable soft-robot element based on dielectric elastomer by Abd Elkarim Masoud, Jürgen Maas

“…The bistable DE system consists of a buckled beam structure and symmetric DE membranes to achieve rapid switching between two stable states. …”
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The Performance of an ML-Based Weigh-in-Motion System in the Context of a Network Arch Bridge Structural Specificity by Dawid Piotrowski, Marcin Jasiński, Artur Nowoświat, Piotr Łaziński, Stefan Pradelok

“…In civil and bridge engineering, they can facilitate the identification of specific patterns through the analysis of data acquired from structural health monitoring (SHM) systems. …”
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Artificial Intelligence-Based Approach for Damage Localization in Ultrasonic Guided Wave-Based Structural Health Monitoring by Anastasiia Volovikova, Steffen Freitag, Oliver Schackmann, Vittorio Memmolo, Ahmed Bayoumi, Inka Mueller, Jochen Moll

“…Existing localization approaches are limited through them being applied on defined simple structures and requiring a large amount of data, which is usually unavailable in practical applications. …”
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Damage detection in structural health monitoring using hybrid convolution neural network and recurrent neural network by Dung Bui-Ngoc, Hieu Nguyen-Tran, Lan Nguyen-Ngoc, Hoa Tran-Ngoc, Thanh Bui-Tien, Hung Tran-Viet

“…Different machine learning techniques have been applied to attempt to extract features or knowledge from vibration data, however, they need to learn prior knowledge about the factors affecting the structure. …”
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Identifications of False Positives Amongst Sodium(I) Cations in Protein Three-Dimensional Structures—A Validation Approach Extendible to Any Alkali or Alkaline Earth Cation and to... by Oliviero Carugo

“…Validation of the data deposited in the Protein Data Bank is of the upmost importance, since many other databases, data mining processes, and artificial intelligence tools are strictly grounded on them. …”
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Damage Detection in Structural Health Monitoring using Hybrid Convolution Neural Network and Recurrent Neural Network by Thanh Bui-Tien, Dung Bui-Ngoc, Hieu Nguyen-Tran, Lan Nguyen-Ngoc, Hoa Tran-Ngoc, Hung Tran-Viet

“…Different machine learning techniques have been applied to attempt to extract features or knowledge from vibration data, however, they need to learn prior knowledge about the factors affecting the structure. …”
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Factors Influencing the Human Development Index in Indonesia Using Structural Equation Modeling-Partial Least Square by Rifki Saefullah, Besse Arnawisuda Ningsi

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Structural modeling of the effect of school culture on psychological well-being with the mediating role of narcissism and achievement emotions by maryam fallahi, samaneh salimi

“…The aim of the present study was to investigate the structural modeling of the effect of school culture on psychological well-being with the mediating role of narcissism and students' progress emotions. …”
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Gender-specific perception of job stressors and resources: a structural equation model-based secondary analysis by Angelina Heub, Andrea Schaller, Martin Lange

“…The national representative cross-sectional sample included 4,118 employees. The data were analyzed using structural equation modeling.ResultsCorrelations between quantitative demands, working time, co-worker support, quality of leadership, job control, and subjective perceived stress were first confirmed for a total sample of employees. …”
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Digital transformation of care for keratoconus patients: ML modeling structural outcomes of corneal collagen cross-linking by Yauhen Statsenko, Yauhen Statsenko, Yauhen Statsenko, Darya Smetanina, Roman Voitetskii, Gillian Lylian Simiyu, Mikalai Pazniak, Elena Likhorad, Aleh Pazniak, Pavel Beliakouski, Dmitri Abelski, Fatima Ismail, Klaus Neidl-Van Gorkom, Milos Ljubisavljevic, Milos Ljubisavljevic

“…BackgroundStructural outcomes of corneal collagen cross-linking (CXL) have not been thoroughly investigated. …”
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Structural knowledge-driven meta-learning for task offloading in vehicular networks with integrated communications, sensing and computing by Ruijin Sun, Yao Wen, Nan Cheng, Wei Wang, Rong Chai, Yilong Hui

“…Specifically, borrowing the iterative structure of the AM algorithm, also referred to as structural knowledge, the proposed SKDML adopts long short-term memory (LSTM) network-based meta-learning to learn an adaptive optimizer for updating variables in each sub-problem, instead of the handcrafted counterpart in the AM algorithm. …”
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