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Laser welding of hidden T-joints, connecting the web-sheet through the face-sheet of the joint can provide advantages like increased lightweight potential in manufacturing sandwich structures with thin-walled cores. However, maintaining the correct positioning of the beam relative to the joint is challenging. A method to reduce the effort of positioning is using optical coherence tomography (OCT), that interferometrically measures the reflection distance inside of the keyhole during laser deep penetration welding. In this study new approaches for targeted data processing of the OCT-signal to automatically detect misalignments are presented. It is shown that considering multiple components from the inference pattern and the respective signal intensities improve the detection accuracy of misalignments.
Bitcoin's energy consumption and social costs in relation to its capacity as a settlement layer
(2021)
Bitcoin runs on energy. The decentralized network’s amount of energy consumption has resulted in multifaceted discussions about its efficiency and environmental impact. To put Bitcoin’s energy consumption into perspective, we propose to relate (a) the energy consumption in TWh and (b) resulting social costs in the form of carbon emissions to the Dollar value settled on the Bitcoin network. Both metrics allow to relate and quantify the capacity of Bitcoin as a settlement layer to the network’s energy consumption and resulting carbon missions, or social costs. We find that in early 2021 Bitcoin (a) settles between $2,333 and $7,555 for each Dollar spent on energy and (b) that, on average, a Dollar settled on the Bitcoin blockchain causes in social costs between 0.007% and 0.01%, depending on the estimated energy consumption converted into the costs of carbon emissions. These results help to assess the efficiency, cost and sustainability of Bitcoin and may allow a comparison of Bitcoin with existing settlement base layers such as Fedwire or gold
We propose a method for edge detection in images with multiplicative noise based on Ant Colony System (ACS). To adapt the Ant Colony System algorithm to multiplicative noise, global pheromone matrix is computed by the Coefficient of Variation. We carried out a performance comparison of the edge detection Ant Colony System algorithm among several techniques, the best results were found in the gradient and the coefficient of variation.
Pulsed laser processing of vacuum component surfaces is a promising method for electron cloud mitigation in particle accelerators. By generating a hierarchically structured surface, the escape probability of secondary electrons is reduced. The choice of laser treatment parameters – such as laser power, scanning speed and line distance – has an influence on the resulting surface morphology as well as on its performance. The impact of processing parameters on the surface properties of copper is investigated by Secondary Electron Yield (SEY) measurements, Scanning Electron Microscopy (SEM), ablation depth measurements in an optical microscope and particle release analysis. Independent of the laser wavelength (532nm and 1064nm), it was found that the surface morphology changes when varying the processing parameters. The ablation depth increases and the SEY reduces with increasing laser fluence. The final application requires the capability to treat tens of meters of vacuum pipes. The limiting factors of this type of surface treatment for the applicability in particle accelerators are discussed.
Long-range tertiary interactions between RNA tetraloops and their receptors stabilize the folding of ribosomal RNA and support the maturation of the ribosome. Here, we use FRET-assisted structure prediction to develop a structural model of the GAAA tetraloop receptor (TLR) interaction and its dynamics. We build the docked TLR de novo, label the RNA in silico and compute FRET histograms based on MD simulations. The predicted mean FRET efficiency is remarkably consistent with single-molecule experiments of the docked tetraloop. This hybrid approach of experiment and simulation will promote the elucidation of dynamic RNA tertiary contacts and accelerate the discovery of novel RNA and RNA-protein interactions as potential future drug targets.
We report on our recent progress in creating a new type of compact laser that uses thulium-based fiber CPA technology to emit a central wavelength of 2 μm. This laser can produce pulse energies of >100 μJ and an average power of >15 W. It is designed to be long-lasting and is built for industrial use, making it a great fit for integration into laser machines used for materials processing. These laser parameters are ideal for working with semiconductors like silicon, allowing for tasks such as micro-welding, cutting of filaments, dicing, bonding and more.
We demonstrate a thulium-based fiber amplifier delivering pulses tunable between <120fs and 2ps duration at up to 228 μJ of pulse energy at a center wavelength of 1940 nm and 500-kHz repetition rate. Due to the excellent long-term stability, this system proves the ability of this technology to be integrated into ultra-fast material processing machines.
Over the last two decades, the rapid advances in digitization methods put us on the fourth industrial era’s cusp. It is an era of connectivity and interactivity between various industrial processes that need a new, trusted environment to exchange and share information and data without relying on third parties. Blockchain technologies can provide such a trusted environment. This paper focuses on utilizing the blockchain with its characteristics to build machine-to-machine (M2M) communication and digital twin solutions. We propose a conceptual design for a system that uses smart contracts to construct digital twins for machines and products and executes manufacturing processes inside the blockchain. Our solution also employs the decentralized identifiers standard (DIDs) to provide self-sovereign digital identities for machines and products. To validate the approach and demonstrate its applicability, the paper presents an actual implementation of the proposed design to a simulated case study done with the help of Fischertechnik factory model.
As part of the research project Trusted Blockchains for the Open, Smart Energy Grid of the Future (tbiEnergy), one of the objectives is to investigate how a holistic blockchain approach for the realization of a local energy market could be accomplished and how corresponding hardware security mechanisms can be integrated. This paper provides an overview of the implemented prototype and describes the system and its processes.
Procurement processes are deemed to lack supporting digital technologies that raise efficiency and automation.
Blockchain solutions are piloted in procurement in order to offer a decentralized IT infrastructure covering these needs. This paper aims at identifying current blockchain approaches in the field of procurement and presenting affected business processes. In order to get an overview of the current state of the art, a systematic literature mapping is conducted.
Moreover, the out-comes are gathered and categorized in a classification scheme. Based on the analysis, systematic maps are presented to showcase relevant findings. Within the findings, several blockchain use cases in the field of procurement are identified and information about addressed challenges, utilized blockchain frameworks and affected business processes are extracted.
Blockchain and other distributed ledger technologies are evolving into enabling infrastructures for innovative ICT-solutions. Numerous features, such as decentralization, programmability, and immutability of data, have led to a multitude of use cases that range from cryptocurrencies, tracking and tracing to automated business protocols or decentralized autonomous systems. For organizations that seek blockchain adoption, the overwhelming spectrum of potential application areas requires guidance reducing complexity and support the development of blockchain-based concepts. This paper introduces a classification approach to provide design and implementation guidance that goes beyond current textbook classifications. As an outcome, a typology for management and business architects is developed, before the paper concludes with an instantiation of existing use cases and a discussion of their classes.
Reputation is indispensable for online business since it supports customers in their buying decisions and allows sellers to justify premium prices. While IS research has investigated reputation systems mainly as review systems on online platforms for business-to-consumer (B2C) transactions, no proper solutions have been developed for business-to-business (B2B) transactions yet. We use blockchain technology to propose a new class of reputation systems that apply ratings as voluntary bonus payments: Before a transaction is performed, customers commit to pay a bonus that is granted if a service provider has performed a service properly. As opposed to rival reputation systems that build on cumulated ratings or reviews, our system enables monetized reputation mechanisms that are inextricably linked with online transactions. We expect this system class to provide more trustworthy ratings, which might reduce agency costs and serve quality providers to establish a reputation towards new customers.
Mapping identities, digital assets, and people’s profiles on the internet is getting much traction in the blockchain cosmos lately. The new technology is currently forming architectures that will further pave new ways to reach fundamental mechanisms to interact in a decentralized, user-centered manner. These schemes are often declared as the next generation of the web. Within the article will be shown, how the internet has evolved in managing identities, what problems arose, and how new data architectures help build applications on top of privacy rights. Both technological and ethical perspectives are viewed to answer which guidelines should be considered to fulfill the upcoming branch of decentralized services and what we can learn from historical schemes regarding their privacy, accounting, and user data.
The financial world of blockchains is mostly covered by Bitcoin, taking up about 210 billion dollars in market cap. Despite the huge security and independence which the technology offers to the users, it's not quite easy to adapt with upcoming applications due to the regulated infrastructure behind. For small-scale transactions, everyday use applications or the access to a variety of crypto technologies and projects, Bitcoin is relatively limited in future development. The compatibility for most of those applications is covering currencies from more development-driven blockchains like Ethereum. Those want to reach out for the user base that's already in hold of Bitcoins and offer them a seamless transition to new applications without the risk of losing their funds. Within the article, atomic swaps and tokenization are covered up and current approaches compared. Both mechanisms are used to fulfill this symbiosis between Bitcoin and Ethereum.
To get a more practical view, an example on how to implement such a tokenization within an app is shown. This will give deeper insights and offers inspiration for digital identity-based app development.
The topic of soulbound, non-transferable tokens is getting lots of interest within the blockchain space lately as decentralized societies become more tangible with Web3 social media applications and DAOs. In this article, I want to outline how such tokens function, their problems for adoption and standardization, and how they differ from verifiable credentials in the SSI field. As such soulbound assets will likely rely on extended recovery and asset management schemes to become viable identities that safely gain reputation and trust, features like social recovery and contract-based accounting are incorporated. By combining those new technologies and the theoretical crypto-native identity construct, the paper will give an impression of the future user-centric data economy.
The wind energy sector is undergoing digitalization processes that span multi-tier supply chains of turbine components and wind farm maintenance, amongst others. In an industrial use case that includes Siemens Gamesa Renewable Energy, Vestas and APQP4Wind, the processes of producing, fastening, and servicing bolts in turbines are mapped to a digital model. The model follows the lifetime of turbine bolts from the manufacturing phase, to fastening in turbines and maintenance, until their replacement and recycling. The development of the digital model is iteratively addressed in a design science research approach, as the authors actively contribute to the project. Distributed ledgers (DLs) support the notary documentation of the bolts and turbines, from their registration phase to the assembly-, technical service verification- and recycling phases. The immutable and decentralized nature of DLs secures the data against tampering and prevents any changes taken unilaterally by engaging the service stakeholders and component providers in a blockchain consortium.
In this paper, we designed, implemented, and tested a special surveillance camera system based on a combination of classical image processing algorithms. The system’s sub-objective consists of tracking experimental vehicles driving on a defined trajectories (Rail) in real time. Furthermore, it analyzes the scene to collect additional vehicles & rail-related information. The system then uses the gathered data to reach its main objective which confines oneself in independently predicting vehicles collision. Consequently, we propose a hybrid method of detecting and tracking ATLAS-vehicles efficiently. To detect the vehicle at the beginning of the video, periodically every n-frame, and in the case where the tracked vehicle has been lost, we used Histogram Back-Projection. By contrast, Kernelized correlation filter is used to track the detected vehicles. Combining these two methods provides one of the best trade-offs between accuracy and speed even on a single processing core. The proposed method achieves the best performance compared with three different approaches on a custom dataset.
Reducing costs is an important part in todays business. Therefore manufacturers try to reduce unnecessary work processes and storage costs. Machine maintenance is a big, complex, regular process. In addition, the spare parts required for this must be kept in stock until a machine fails. In order to avoid a production breakdown in the event of an unexpected failure, more and more manufacturers rely on predictive maintenance for their machines. This enables more precise planning of necessary maintenance and repair work, as well as a precise ordering of the spare parts required for this. A large amount of past as well as current information is required to create such a predictive forecast about machines. With the classification of motors based on vibration, this paper deals with the implementation of predictive maintenance for thermal systems. There is an overview of suitable sensors and data processing methods, as well as various classification algorithms. In the end, the best sensor-algorithm combinations are shown.
In the field of Blockchain Technology applications and research, non-fungible tokens (NFTs) have gained significant attention in recent years. Whilst current research is focused on NFT use cases or the purchase of NFTs from an investor’s perspective, the NFT launch (i.e. primary market) from a creator’s perspective remains uncovered. However, the launch strategy is considered to be an important factor for the success of a product. Therefore, our research paper aims to explore launch strategies of NFTs. Thereby, we discuss the marketing mix instruments price (i.e. pricing strategy), place (i.e. mint mechanism), and promotion. Through an empirical approach of conducting eight expert interviews, we examine parameters that are used to define an NFT launch strategy and assess their preference of different stakeholders.
Global challenges like climate change, food security, and infectious diseases such as the COVID-19 pandemic are nearly impossible to tackle when established experts and upstart innovators work in silos. If research organizations, governments, universities, NGOs, and the private sector could collaborate on these challenges more easily, lasting solutions would certainly come more quickly. Aligned with the United Nations’ Sustainable Development Goals, SAIRA connects key players in different arenas: scientists and engineers at research and technology organizations (RTOs) looking to collaborate on sustainable development projects, companies seeking R&D support to tackle their most challenging problems, and startups with innovative ideas and a desire to scale. The platform is a blockchain-secured open innovation platform, anchored on Max Plank Digital Library's blockchain network bloxberg, that assures the authenticity and integrity of all user-generated content and collaboration processes.