229 hasil untuk "Max"
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Buku
Gesammelte Aufsätze 0 zur Religionssoziologie
Geboren 1864 in Erfurt; Studium der Jurisprudenz, Geschichte, Nationalökonomie und Philosophie in Heidelberg, Berlin und Göttingen; 1889 Promotion über die Geschichte der Handelsgesellschaften im Mittelalter; 1891 Habilitationsschrift über Römische Agrargeschichte; Ordinarius für Nationalökonomie…
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Deep Learning for Change Detection in Remote Sensing Images: Comprehensive Review and Meta-Analysis
Deep learning (DL) algorithms are considered as a methodology of choice for remote-sensing image analysis over the past few years. Due to its effective applications, deep learning has also been introduced for automatic change detection and achieved great success. The present study attempts to…
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Current Trends and Applications of Machine Learning in Tribology—A Review
Machine learning (ML) and artificial intelligence (AI) are rising stars in many scientific disciplines and industries, and high hopes are being pinned upon them. Likewise, ML and AI approaches have also found their way into tribology, where they can support sorting through the complexity of…
Dari koleksi institusi
- Basic concepts in sociologyMax Weber · 1962 · Universitas Riau (UNRI)
- Etika proterestan & spirit klapitalismeWeber, Max · 2006 · Universitas Riau (UNRI)
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Arsenic: A Global Environmental Challenge
Arsenic is a naturally occurring metalloid and one of the few metals that can be metabolized inside the human body. The pervasive presence of arsenic in nature and anthropogenic sources from agricultural and medical use have perpetuated human exposure to this toxic and carcinogenic element. Highly…
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AI Feynman: A physics-inspired method for symbolic regression
, and it discovers all of them, while previous publicly available software cracks only 71; for a more difficult physics-based test set, we improve the state-of-the-art success rate from 15 to 90%.
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Strengthening supply chain resilience during COVID ‐19: A case study of JD .com
Abstract The coronavirus/SARS‐CoV‐2 (COVID‐19) outbreak has caused severe supply chain disruptions in practically all industries worldwide. Online e‐commerce platforms, which interact directly with various industries and service numerous consumers, have become remarkable interfaces to observe the…
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Deep Neural Networks for Estimation and Inference
We study deep neural networks and their use in semiparametric inference. We establish novel nonasymptotic high probability bounds for deep feedforward neural nets. These deliver rates of convergence that are sufficiently fast (in some cases minimax optimal) to allow us to establish valid…
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Data sovereignty: A review
New data-driven technologies yield benefits and potentials, but also confront different agents and stakeholders with challenges in retaining control over their data. Our goal in this study is to arrive at a clear picture of what is meant by data sovereignty in such problem settings. To this end, we…
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Review on model predictive control: an engineering perspective
Abstract Model-based predictive control (MPC) describes a set of advanced control methods, which make use of a process model to predict the future behavior of the controlled system. By solving a—potentially constrained—optimization problem, MPC determines the control law implicitly. This shifts the…
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CADD-Splice—improving genome-wide variant effect prediction using deep learning-derived splice scores
BACKGROUND: Splicing of genomic exons into mRNAs is a critical prerequisite for the accurate synthesis of human proteins. Genetic variants impacting splicing underlie a substantial proportion of genetic disease, but are challenging to identify beyond those occurring at donor and acceptor…
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On-Time Last-Mile Delivery: Order Assignment with Travel-Time Predictors
We study how delivery data can be applied to improve the on-time performance of last-mile delivery services. Motivated by the delivery operations and data of a food delivery service provider, we discuss a framework that integrates travel-time predictors with order-assignment optimization. Such…
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Emerging models of data governance in the age of datafication
The article examines four models of data governance emerging in the current platform society. While major attention is currently given to the dominant model of corporate platforms collecting and economically exploiting massive amounts of personal data, other actors, such as small businesses, public…
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Plant mitochondria – past, present and future
The study of plant mitochondria started in earnest around 1950 with the first isolations of mitochondria from animal and plant tissues. The first 35 years were spent establishing the basic properties of plant mitochondria and plant respiration using biochemical and physiological approaches. A…
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Mitochondria and Parkinson’s Disease: Clinical, Molecular, and Translational Aspects
Mitochondrial dysfunction represents a well-established player in the pathogenesis of both monogenic and idiopathic Parkinson's disease (PD). Initially originating from the observation that mitochondrial toxins cause PD, findings from genetic PD supported a contribution of mitochondrial dysfunction…
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2D materials for future heterogeneous electronics
Graphene and related two-dimensional (2D) materials have remained an active field of research in science and engineering for over fifteen years. Here, the authors investigate why the transition from laboratories to fabrication plants appears to lag behind expectations, and summarize the main…
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Gut Microbiota in Hypertension and Atherosclerosis: A Review
Gut microbiota and its metabolites such as short chain fatty acids (SCFA), lipopolysaccharides (LPS), and trimethylamine-N-oxide (TMAO) impact cardiovascular health. In this review, we discuss how gut microbiota and gut metabolites can affect hypertension and atherosclerosis. Hypertensive patients…
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CADD v1.7: using protein language models, regulatory CNNs and other nucleotide-level scores to improve genome-wide variant predictions
Machine Learning-based scoring and classification of genetic variants aids the assessment of clinical findings and is employed to prioritize variants in diverse genetic studies and analyses. Combined Annotation-Dependent Depletion (CADD) is one of the first methods for the genome-wide…