Daniyal Kazempour

k-Local Graphs

Christian Beth, Pamela Fleischmann, Annika Huch, Daniyal Kazempour et autres

Code accompanying the paper "k-local Graphs", which extends the notion of k-locality to coloured graphs and proposes a priority search algorithm to compute the k-locality of a graph, orders of magnitude faster than exhaustive search.

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k-Local Graphs

Christian Beth, Pamela Fleischmann, Annika Huch, Daniyal Kazempour et autres

Code accompanying the paper "k-local Graphs", which extends the notion of k-locality to coloured graphs and proposes a priority search algorithm to compute the k-locality of a graph, orders of magnitude faster than exhaustive search.

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On the Selection of AI Algorithms for Industrial Automation: Batch vs. Streaming Algorithms

Marius Krüger, Daniyal Kazempour, Kathrin Land, Peer Kröger et autres

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Concept-based force-signature analysis of tool-parameter effects in fine blanking

Martin Unterberg, Daria Gelbich, Frank Schweinshaupt, Antonia Holzapfel et autres

Abstract Fine blanking part quality is highly sensitive to tool parameterization, yet cause–effect relationships are obscured by substantial process noise. This limits the utility of both simulation and scalar process metrics for tool optimization and mechanistic understanding. At the same time, high-resolution …

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Concept-based force-signature analysis of tool-parameter effects in fine blanking

Martin Unterberg, Daria Gelbich, Frank Schweinshaupt, Antonia Holzapfel et autres

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Reconstructing surface ocean carbon flux from physical parameters using deep learning methods

Sweety Mohanty, Lavinia Patara, Willi Rath, Daniyal Kazempour et autres

The global ocean carbon sink is a critical component of the Earth’s climate but current models are limited in their predictive capability because of the high computational cost that a biogeochemical model, required to simulate air-sea CO₂ fluxes, entails. In this study, …

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Concept-Based Force-Signature Analysis of Tool-Parameter Effects in Fine Blanking

Martin Unterberg, Daria Gelbich, Frank Schweinshaupt, Antonia Holzapfel et autres

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Correcting Wave-Induced Reflectance Anomalies in Pan-Sharpened Very High-Resolution Satellite Data

Eike M. Sch¨utt, Daniyal Kazempour, Peer Kr¨oger, Natascha Oppelt

The increasing spatial resolution of satellite sensors– now reaching sub-meter scale– enables advanced applications in aquatic remote sensing, including highly detailed bathymetry or habitat mapping. However, this fine resolution also increases pixel-level susceptibility to wave glint and whitecap contami nation. These wave-induced …

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Concept-based force-signature analysis of tool-parameter effects in fine blanking

Martin Unterberg, Daria Gelbich, Frank Schweinshaupt, Antonia Holzapfel et autres

Fine blanking part quality is highly sensitive to tool parameterization, yet cause–effect relationships are obscured by substantial process noise. This limits the utility of both simulation and scalar process metrics for tool optimization and mechanistic understanding. At the same time, high-resolution force-signature …

Provenance Analysis Based on Cluster In‐Betweenness and Support Vector Machines: Identifying Migrant Candidates Using Multi‐Isotope Fingerprints

Andrea Göhring, Daniyal Kazempour, Jan Robert Bensien, Sweety Mohanty et autres

ABSTRACT Provenance reconstruction using strontium and lead stable isotopes can produce complex multidimensional fingerprints, challenging traditional methods. Identifying nonlocals, who migrated between sites, is a major task. Migrants are identifiable by divergent multi‐isotope fingerprints due to isotopic mixing between origin and destination …

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Supplementary data to Mohanty et al. (2024): Detection and Tracking of Carbon Biomes via Integrated Machine Learning Methods

Sweety Mohanty, Lavinia Patara, Daniyal Kazempour, Peer Kröger

Detection and tracking of carbon biomes via integrated machine learning

Sweety Mohanty, Lavinia Patara, Daniyal Kazempour, Peer Kröger

In the framework of a changing climate, it is useful to devise methods capable of effectively assessing and monitoring the changing landscape of air–sea CO 2 fluxes. In this study, we developed an integrated machine learning tool to objectively classify and track …

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