In a social networked industry, the focus is on collaboration between humans and technology. Communication is the basic prerequisite for synergetic collaboration between all players. It includes non-verbal as well as verbal interactions. To enable non-verbal interaction, machines must be able to detect and understand human movements. This article presents the ongoing fundamental research on the analysis of human movements using sensor-based activity recognition and identifies potential for a transfer to industrial applications. The focus is on the practical feasibility of activity recognition by adding further data streams such as the position data of logistical objects and tools, meaning the context in which a certain activity is carried out. -- In der Social Networked Industry steht die Zusammenarbeit von Mensch und Technik im Vordergrund. Grundvoraussetzung für eine synergetische Zusammenarbeit aller Akteure ist die Kommunikation, welche neben verbalen auch nonverbale Interaktionen umfasst. Um eine nonverbale Interaktion zu ermöglichen, müssen Maschinen in der Lage sein, menschliche Bewegungen zu erfassen und zu verstehen. Dieser Beitrag stellt die laufende Grundlagenforschung z
Nichtverbale Signale sind ein elementarer Bestandteil der menschlichen Kommunikation. Sie erfüllen eine Vielzahl von Funktionen bei der Klärung von Mehrdeutigkeiten, der subtilen Aushandlung von Rollen oder dem Ausdruck dessen, was im Inneren der Gesprächspartner vorgeht. Viele Studien mit sozial-interaktiven Robotern zeigen, dass vom Menschen inspirierte Bewegungsmuster ähnlich interpretiert werden wie die von realen Personen. Dieses Kapitel erläutert daher die wichtigsten Funktionen, welche die jeweiligen Bewegungsmuster in der Kommunikation erfüllen, und gibt einen Überblick darüber, wie sie auf Roboter übertragen werden können. -- Non-verbal signals are a fundamental part of human communication. They serve a variety of functions in clarifying ambiguities, subtly negotiating roles, or expressing what is going on inside the interlocutors. Many studies with socially-interactive robots show that human-inspired movement patterns are interpreted similarly to those of real people. This chapter therefore explains the most important functions that the respective movement patterns fulfill in communication and gives an overview of how they can be transferred to robots.
This paper proposes an unsupervised workflow to pseudo-label extracellular spikes from human brain slice MEA recordings into two putative cell types: pyramidal cells and interneurons. Here, the raw data from the data acquisition system is used and processed. The pipeline for pre-processing includes bandpass filtering, threshold--based spike detection, frame alignment and normalization. In the ML workflow, dimensionality reduction (PCA, t-SNE, UMAP), clustering (GMM, k-means). To achieve an online system, template matching and OSort under varying curation strictness is also considered. All pipelines are evaluated by different cluster quality with within-cluster Pearson correlation, Silhouette score, and Calinski-Harabasz index. Applying stricter curation improves separation at some cost to inclusivity.
Model-based process design and operation involves here-and-now and wait-and-see decisions. Here-and-now decisions include design variables like the size of heat exchangers or the height of distillation columns, whereas wait-and-see decisions are directed towards operational variables like reflux and split ratios. In this contribution, we describe how to deal with these different types of decisions in a multicriteria framework, offering an adjustability for the wait-and-see variables while at the same time respecting optimality guarantees on process KPIs.
Autonomous driving needs good roads, but 85% of Brazilian roads have damages that deep learning models may not regard as most semantic segmentation datasets for autonomous driving are high-resolution images of well-maintained urban roads. A representative dataset for emerging countries consists of low-resolution images of poorly maintained roads and includes labels of damage classes; in this scenario, three challenges arise: objects with few pixels, objects with undefined shapes, and highly underrepresented classes. To tackle these challenges, this work proposes the Performance Increment Strategy for Semantic Segmentation (PISSS) as a methodology of 14 training experiments to boost performance. With PISSS, we reached state-of-the-art results of 79.8 and 68.8 mIoU on the Road Traversing Knowledge (RTK) and Technik Autonomer Systeme 500 (TAS500) test sets, respectively. Furthermore, we also offer an analysis of DeepLabV3+ pitfalls for small object segmentation.
We consider the shape optimization of flow fields for electrochemical cells. Our goal is to improve the cell by modifying the shape of its flow field. To do so, we introduce simulation models of the flow field with and without the porous transport layer. The latter is less detailed and used for shape optimization, whereas the former is used to validate our obtained results. We propose three objective functions based on the uniformity of the flow and residence time as well as the wall shear stress. After considering the respective optimization problems separately, we use techniques from multi-criteria optimization to treat the conflicting objective functions systematically. Our results highlight the potential of our approach for generating novel flow field designs for electrochemical cells.
Diazo compounds are gathering interest for their potential in promoting greener synthesis routes. We investigate, at a lab-scale, the continuous synthesis of diazo acetonitrile (DAN) using a micro-structured flow reactor and a flow reaction calorimeter. Data concerning DAN formation in the former, and relative to reaction heat and gas flow rate in the latter, are collected. We present both a physical and a grey-box simulation model, both of which are calibrated to our measurements. Both models provide valuable insights into the DAN synthesis. The grey-box approach is useful to incorporate the complex chemical reaction pathways for DAN synthesis and decomposition that are currently hard to address with the physical model.
Celebrating the United States' 250th anniversary, NASA released a stunning Hubble portrait of Messier 3, an ancient globular cluster with more than 500,000 stars。 The remarkable cluster is helping scientists unravel the Milky Way's past thanks to its rare stars and possible origins in a long ago cosmic merger
Researchers have proposed that black holes stop evaporating at the last moment, leaving behind tiny remnants that preserve all the information they contain。 The same seven-dimensional geometry behind this idea could also help explain why elementary particles have mass
US military drone losses in Iran war spur Pentagon call for cheap replacements
Astronomers have finally cracked the mystery of the famous “Pink Planet,” a strange world 57 light-years away that has puzzled scientists for more than a decade。 Using the James Webb Space Telescope, researchers discovered that its atmosphere contains water vapor, methane, carbon dioxide, ammonia, and something never directly confirmed before in su
Scientists have uncovered new evidence that fireworks can pollute both the air and water in ways that extend beyond the visible smoke。 The findings show that leftover debris, fine particles, and airborne chemicals may affect ecosystems and increase people's exposure to air pollution during major celebrations
A new sunlight-powered material can convert visible light into higher-energy UV light, overcoming a challenge that has frustrated scientists for years。 The breakthrough could enable cleaner air purification, solar-driven chemistry, and advanced manufacturing technologies using nothing more than natural sunlight
A new quantum theory bridges two rival models of how impurities behave inside many-particle systems, resolving a problem that has challenged physicists for decades。 The findings could reshape experiments on ultracold atoms, semiconductors, and other exotic forms of quantum matter
Ancient asteroid impacts may have done more than reshape Earth's surface—they could have helped spark life itself。 New computer models show the collisions created enormous underground hydrothermal systems by cracking the planet's crust and allowing hot water to flow through it。 These long-lasting, life-friendly environments may have covered much of
Scientists have created a silicon chip that can write dozens of DNA sequences simultaneously using electricity and water-based enzymes, offering a cleaner alternative to conventional DNA manufacturing。 The breakthrough could eventually support portable DNA-writing devices and even massive DNA data storage, although new chemistry will be needed to s
Researchers have created quantum control techniques that can make a system appear to run backward in time。 By precisely managing quantum measurements, they can reshape the system's arrow of time and even harvest energy from the measurement process itself。 The breakthrough could lead to more powerful quantum computers, quantum batteries, and other a