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A Systematic Literature Review on Blockchain Oracles: State of Research, Challenges, and Trends
(2023)
To enable data exchange between the Blockchain protocol (on-chain) and the real world (off-chain), e.g., non-Blockchain-based applications and systems, a software called Oracle is used [3]. Blockchain oracle is an important component in the use of off-chain data for on-chain smart contracts. However, there is limited scientific literature available on this important blockchain topic. Therefore, in this paper, a novel systematic literature review based on intelligent methods, e.g., information linking, topic clustering and focus identification through frequency calculations, is proposed. Thus, the current state of scientific research interest, content and challenges, and future research directions for blockchain oracles are identified. This paper shows that there is little unbiased literature that does not call oracles a problem. From the results of this new literature review framework, relevant areas of data handling and verification with blockchain oracles are identified for future research.
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.
Over recent years, Maximal Extractable Value (MEV) has gained significant importance within the decentralized finance (DeFi) ecosystem. Remarkably, within just two years of its emergence, MEV has seen an extraction of approximately 600 million USD - a phenomenon that has sparked concerns regarding potential threats to blockchain stability.
With growing interest in the Ethereum network and the growing DeFi sector, research surrounding MEV has substantially increased. This work aims to offer a comprehensive understanding of MEV. Additionally, this research quantifies the largest types of MEV (Arbitrage, Sandwich and Liquidations) from March 2022 to March 2023. The data are then compared to other sources, revealing a general upward trend, with a particularly noticeable increase in Sandwich Attacks.
The cryptocurrency ecosystem has seen significant growth with Ethereum and Bitcoin as foundational pillars. Ethereum introduced smart contracts revolutionizing decentralized applications (dApps) across various domains. Scalability challenges led to alternative ecosystems like Binance Smart Chain and Polygon, maintaining compatibility through the Ethereum Virtual Machine (EVM). Bitcoin also faces scalability issues, leading to the Lightning Network's development—an off-chain solution with payment channels for scalable instant transactions. Interoperability is increasingly crucial as the cryptocurrency ecosystem continues to grow, enabling seamless interactions between assets and data across multiple blockchain platforms. EVM-compatible blockchains and the Lightning Network offer unique advantages in their respective use cases. This paper utilizes atomic swaps to create a secure, fast, and user-friendly trustless bridge between the Lightning Network and EVM-compatible blockchains, fostering the growth of both ecosystems and unlocking novel opportunities.
Currently, the Internet of Things (IoT) is connected to the virtual world through the Web of Things (WoT), allowing efficient utilization of real-world objects with Internet technologies. The WoT facilitates abstract interaction between applications and connected IoT devices, allowing owners to switch between devices while using multiple ones. To achieve this, virtual assets in WoT devices can be tokenized through smart contracts and transferred using hashed proof as transactions within blockchain networks that support virtual currencies. The goal of Web of Things is to establish connectivity, interoperability, and integration among IoT devices using web standards and protocols, reducing reliance on device manufacturers. This enables easy integration of Web 3.0 cryptocurrency for device management. This study proposes a solution for WoT applications involving different cryptocurrency definitions. Finally, simulation results are presented to demonstrate the tokenization-based ownership transfer in the Web of Things.
This desk research will initiate an exploration of present and potential blockchain applications in the higher education sector of Europe. The aim of this research is to create a theoretical base for a further postgraduate research and analysis, so to create an effective model/framework to augment the integration of blockchain technology into existing organizational processes, initially in higher educational institutions, but which may be adaptable and generalizable to other specific uses. Due to the novelty of the topic, academic resources related to the research area are limited. Most studies seem to focus on blockchain-based applications in industries such as finance, healthcare, and supply chain management, and there is little evidence of the impact of blockchain technology on education. This paper discusses present and suggests some potential blockchain-based applications in education in Europe and beyond. This research provides a groundwork for education and academia stakeholders, policymakers and researchers to exploit the potential of blockchain in different functions of an education system.
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.
Safety, quality, and sustainability concerns have arisen from global supply chains. Stakeholders incur risk regarding these factors, given their significance and complexity. Thus, each business's supply chain risk management must prioritize product characteristics. Accordingly, an effective traceability solution that can monitor and regulate product and supply chain aspects is crucial, especially in a given scenario. This re-search paper elucidates the potential of smart contracts in blockchain to enhancing the efficacy of business transactions and ensuring comprehensive traceability within the supply chain of paper-based coffee cups The improved levels of transaction transparency and security in traditional supply chains have been achieved through the digitization of supply chain ecosystem interactions and transactions. This approach makes verifying sources, manufacturing procedures, and quality standards easier in complex supply chains. Accordingly, the integration helps stakeholders monitor and track the whole ecosystem, promoting transparency, predictability, and dependability.
In the swiftly changing world of academic publishing, the Sea of Wisdom platform seizes the opportunity to innovate. By combining the technologies of blockchain, decentralized finance (DeFi), and Non-Fungible Tokens (NFTs) with traditional scholarly communication, we present a groundbreaking, decentralized solution. Our design, although adaptable, primarily uses Ethereum's Virtual Machine, tapping into its robust scientific community.
In laser drilling, one challenge is to achieve a high drilling quality in high aspect ratio drilling. Ultra-short pulsed lasers use different concepts like thin disks, fibers and rods. The slab technology is implemented because of their flexibility and characteristics. They bring together both advantages and deliver high pulse energies at high repetition rates. Materials with a thickness > 1.5 mm demand specialized optics handling the high power and pulse energies with adapted processing strategies, integrated in a machine setup. In this contribution, we focus on all the necessary components and strategies for drilling high precision holes with aspect ratios up to 1:40.
Laser engraving requires a precise ablation per pulse through all layers of a depth map. To transform this process towards areas of a square meter and more within an acceptable time, needs high-power ultra-short pulsed lasers for the precision and a high scan speed for the beam distribution. Scan speeds in the range of several 100 m/s can be achieved with a polygon scanner. In this work, a polygon scanner has been utilized within a roll-engraving machine to treat an 800 x 220 mm² (L x Dia) roll with 0.55 m² in a laser engraving process. The machine setup, the processing strategy and the data handling has been investigated and result in an efficient large area process. Pre-tests were performed with a multi-MHz-frequency nanosecond-pulsed laser, to investigate the processing strategy. A method to overcome the duty cycle of the polygon scanner was found in the synchronization of two polygons, enabling the use on a single laser source in a time-sharing concept. The throughput and the utilization of the laser source can be increased by the factor of two
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.
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.
For monitoring laser beam welding processes and detecting or actively avoiding process defects, acoustic based measurements can be used in addition to optical measurement methods such as pyrometry. To reliably detect process events, it is essential to position the respective sensors in such a way that specific signal characteristics are reproducible and significant. However, there are only few investigations regarding the positioning for airborne sound sensors, especially for the detection of process emissions in the ultrasonic range. Therefore, in this research, the influence of the process distance as well as the angle and orientation of the microphone to a laser beam deep penetration welding process is investigated with respect to the detectability of process emissions in different frequency bands. It is shown that for a wide ultrasonic range a flat sensor angle with respect to the sample surface leads to an increased signal strength of the acoustic emissions compared to steep angles.
In this work, Direct Laser Interference Patterning (DLIP) is used in conjunction with the polygon scanner technique to fabricate textured polystyrene and nickel surfaces through ultra-fast beam deflection. For polystyrene, the impact of scanning speed and repetition rate on the structure formation is studied, obtaining periodic features with a spatial period of 21 μm and reaching structure heights up to 23 μm. By applying scanning speeds of up to 350 m/s, a structuring throughput of 1.1 m²/min has been reached. Additionally, the optical configuration was used to texture nickel electrode foils with line-like patterns with a spatial period of 25 μm and a maximum structure depth of 15 μm. Subsequently, the structured nickel electrodes were assessed in terms of their performance for the Hydrogen Evolution Reaction (HER). The findings revealed a significant improvement in HER efficiency, with a 22% increase compared to the untreated reference electrode.
Decentralization is one of the key attributes associated with blockchain technology. Among the different developments in recent years, decentralized autonomous organizations (DAOs) have been of growing interest. DAOs are currently a key part of another emerging use case, namely decentralized science (DeSci). Given the novelty of the field, an integrative definition of DeSci has not been established, but some inherent concepts and ideas can be traced back to the Open Science movement. Although the DeSci movement has the potential to benefit the public, for example through funding underrepresented research areas or more inclusive and transparent research in general, some negative aspects of decentralization should not be neglected. Due to the novelty of blockchain and emerging use cases, research can and should precede mass adoption, to which this paper aims to contribute.
As economies are getting more and more interconnected, the importance of the global logistics sector grew accordingly. However, both structural challenges and current events lead to recent supply chain disruptions, exposing the vulnerabilities of the sector. Simultaneously, blockchain has emerged as a key innovative technology with use cases going far beyond the exchange of virtual currencies. This paper aims to analyze how the technology is transforming global logistics and its challenges. Therefore, six use cases, are presented to give an overview of the technological possibilities of blockchain and smart contracts. The analysis combines theoretical approaches from scientific journals and combines them with findings from real-world implementations. The paper finds that the technology can change supply chain design fundamentally, with processes and decisions being automated and power within supply chain structures changing. However, implementations also face technological, environmental, and organizational challenges that need to be solved for wide-spread adoption.
More than 10 years after the invention of Bitcoin, the underlying blockchain technology is having an increasing effect on today’s society. Although one of the most popular application areas of blockchain is still the field of cryptocurrencies, the technological concepts are crossing into further application domains such as international supply chains. Fast-changing markets, high costs of time and risk management as well as biased relationships between the actors pose big challenges to an appropriate supply chain management. Based on a case study about sensor tracking, this paper explores the potential impact of blockchain on small and medium enterprises within an international supply chain. We will show that blockchain technologies offers a high potential to reduce inequalities of power relations between involved actors within supply chains. To achieve this, the requirements for the use of blockchain in supply chain management will be analyzed by means of a conducted case study and an expert survey of the companies concerned.
Current research in identity management is focusing on decentralized trust establishment for distributed identities. One of these decentralized trust models is Self-Sovereign Identities (SSI). With SSI each entity should be able to independently present and manage provable information about itself as well as request and review evidence from other entities. Using a distributed blockchain, information for verifying the authenticity of this evidence can be obtained from any other entity. This concept can be used not only for people, but also for authentication and authorization during the life cycle of devices in the Internet of Things (IoT). This paper presents an SSI-based concept for authentication and authorization of IoT devices among each other, intended to contribute to the change in trust on the internet. The SSI methodology employing a blockchain offers the possibility to establish mutual trust and proof of ownership without relying on any third party. The paper describes the concept, offers a reference implementation, and gives a discussion of the approach.
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.
Digital Power of Attorney catalyzed by Software Requirements for Blockchain-based Applications
(2022)
Blockchain Technology (BT) with so-called web3 is at an inflection point between new sub-theme hypes and world-wide industrialization over last three years thanks to large companies like MicroStrategy [1], Facebook [2] and several Venture-Capital formations [3] who are already fighting over market share and community growth. Our work represents insights from Literature-based Software Requirement (SR) elicitation for a specific Blockchain-based Application, which is creation, managing and control of digital Power of Attorney (POA). The context of POA is not only a financial driven use-case it is by far a heavy weight universal legal transaction. We use a morphological box and reduced PRIMS-P to synthesis a generic specification for further Blockchain-based Application development. Formulated SRs in POA context are reflected on our core actors which are Grantor and authorized, trusted, external Entities. Proposed characteristics for relationship and effects are visualized in a reference model originally used in digital platform ecosystems [4]. This design and modelling approach facilitated closing discussion of BT and its future eCommerce perspective.
Dynamic object roles and corresponding contexts can model complex applications with higher-level abstraction. These abstracted applications can be used in wider areas such as financial institutions, health care, and supply chain network. Role management which consists of the creation of role objects, and binding role object between core objects still suffers from non-intrusive logging-monitoring, auditing, and resilient data source for role-based applications. Moreover, immutable smart contracts cause problems concerning bug fixing and maintenance without dynamic binding to new smart contract objects. An object that is created from a smart contract (contract class) can be transparently attached to a role object utilizing the Role Object Pattern (ROP). However, ROP itself does not contain a context definition and context-specific role assignment grouping the definition of smart contract relationships in abstracted data types. In this study, we would like to implement an extended version of the role object pattern called Context-based Role Object Pattern (ContextROP) with an onchain smart contract language called Solidity to solve fundamental problems. To evaluate the proposal, we will implement a use case with the design pattern proceeding with qualitative and quantitative analysis.
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.
Humans started using the principles of insurance thousands of years ago when they lived in tribes in smaller villages. If one of the tribe members were injured, the others would take care of him and his family. The basic principle of insurance is several people covering each other against a particular risk. Today, most people in regions like Europe have access to insurance, while many people worldwide still have no access at all. The cost and accessibility may be improved with a blockchain-based parametric approach. The insurance process in a parametric approach is exclusively based on data, and decisions are made objectively. Blockchain is a necessary and integral part of the approach to create transparency and connect the customer’s and investor’s risk capital. The paper offers an overview of the opportunities and challenges of blockchain-based parametric insurance, a catalog of criteria for such insurance, a description of all components and their interaction for implementation on Ethereum, and a reference implementation of a train delay insurance in Germany.
Cryptocurrencies are characterized by high volatility, both in the short and long term. Experienced traders exploit this to make profits from price fluctuations by swing trading. However, this requires closely observing and analyzing the prices and trading positions at the right time. Only a few specialists, who spend time focusing on this, or optimized trading bots are able to actually make continuously profits. The autradix protocol is a selfoptimizing and self-learning parametric trading algorithm that analyzes price actions in real-time and adaptively optimizes the algorithm’s parameters to realize the user’s investment objective. Embedded in an adaptive genetic algorithm, possible parameterizations are simulated and the optimal for the investigated trading pairs are calculated. The generic trading protocol API enables coupling with various crypto exchanges and decentralized protocols. A smart contract based decentralized, trustless, and tokenized fund, controlled by a DAO, enables users to invest, operate trading agents, and to participate in the profits generated according to their share.
With the advancement in cryptography and emerging internet technology, electronic voting is gaining popularity since it ensures ballot secrecy, voter security, and integrity. Many commercial startups and e-Voting systems have been proposed, but due to lack of trust, privacy, transparency, and hacking issues, many solutions have been suspended. Blockchain, along with cryptographic primitives, has emerged as a promising solution due to its transparent, immutable, and decentralized nature. In this paper, we summarized the properties that existing solutions should satisfy and explained some cryptographic primitives like ZKP, Ring signatures along with their security limitations. We gave a comprehensive review of some blockchain-based e-Voting systems and discussed their strengths and weaknesses based on the given properties with table of comparison.
Abstract: Blockchain Technology has become an innovative, mature tool for digital transformation, disrupting more and more application areas in their business processes, values, or even economic models. This paper leverages more than 30 academic publications on prototypes and their Blockchain-based use cases to transact certificates in the context of public education. The conceptual design and guiding ideas are reflected in the practical application development for the Federal Ministry of Education and Research ECHT! project within the showcase region WIR! in Mittweida and are used for the research design. During this approach we applied agile methods and the current certificate process to propose a comprehensive disclosure of a new software prototype including a three-layered architecture with multi-stakeholder components. The artefact instantiation contributes to the practical knowledge base within Information System Research and specifically in digital certificate processes starting from creation, searching, and proofing up to revoking by consideration of an existing IT landscape as well as organizational hierarchy.
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.
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
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.
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.
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.
While blockchain technology is still in an early stage of its development, it is already of surging economic importance.
In the literature, blockchain is referred to as either being a disruptive, institutional, foundational, or general purpose technology. There is still no consensus about the economic theory that should apply for analyzing its economic effects. This article draws on use cases from the coffee supply chain to explore, which theories could potentially apply to an emerging blockchain economy.
Smart ultrafast laser processing with rotating beam – Laser micro drilling, cutting and turning
(2021)
Current micro drilling, cutting and turning processes are mainly based on EDM, milling, stamping, honing or grinding. All these technologies are using a tool with a predefined geometry that is transferred to the working piece. In contrast the laser is a highly flexible tool, which can adapt its size very fast by changing only a software setting. Thanks to the efforts in laser development during the last years, stable ultrafast lasers with sufficient average power and high repetition rates became industrially available. For using as many pulses as possible, a cost-efficient production demands for innovative processes and machining setups with fast axes movement and special optics for beam manipulation. GFH has developed a helical drilling optics, which rotates the beam up to 30.000 rpm in a very precise circle and allows furthermore to adjust the diameter and the incidence angle. This enables the laser to be used for high precision drilling and cutting and also for micro turning processes.
The shape-memory Nitinol as a nickel-titanium alloy is widely used in actuator and medical applications. However, the connection of a flange to the rod is a critical point. Therefore, laser rod end melting enables material accumulations to generate a preform at the end of a rod, followed by die forming, so that the flange can be generated. This process has been successfully applied on 1.4301 steel. This study is aimed to investigate laser rod end melting of shape-memory Nitinol regarding the resultant surface quality of the preforms. The results showed that spherical preforms could be generated without visible surface discoloration due to oxidation. By using different scan rates, different solidification conditions occurred which led to significantly different surface structures. These findings show that laser rod end melting can principally be applied on Nitinol to generate preforms for flanges whereby the surface quality depends on the solidification conditions.
Beam shaping and splitting with diffractive optics for high performance laser scanning systems
(2021)
Diffractive optical elements (DOEs) enable novel high performance and process-tailored scanning strategies for galvanometer-based scan heads. Here we present several such concepts integrating DOEs with laser scanners and the respective application use cases. Beam shaping DOEs providing a homogeneous fluence over a custom defined profile, such as a rectangular Top-Hat, enable increased process quality in Laser-Induced Forward Transfer (LIFT) compared to the Gaussian beam of the laser source. We show that aberrations which occur over the necessary large wafer-sized image field can be eliminated through the use of a synchronous XY-stage motion. Another application that benefits from the use of DOEs is laser drilling. Drilling in display and electronics manufacturing demands high throughput that can only be achieved through the use of beam splitting DOEs for parallel processing. To this end, the joint MULTISCAN project is developing a variable multi-beam tool capable of scanning and switching each individual beamlet for increased control.
Increasing speed in laser processing is driven by the development of high-power lasers into ranges of more than 1 kW. Additionally, a proper distribution of these laser power is required to achieve high quality processing results. In the case of high pulse repletion rates, a proper distribution of the pulses can be obtained from ultrafast beam deflection in the range of several 100 m/s. A two-dimensional polygon mirror scanner has been used to distribute a nanosecond pulsed laser with up to 1 kW average power at a wavelength of 1064 nm for multi pass laser engraving. The pulse duration of this laser can be varied between 30 ns and 240 ns and the pulse repetition rate is set between 1 and 4 MHz. The depth information is included in greyscale bitmaps, which were used to modulate the laser during the scanning accordingly to the lateral position and the depth. The process allows high processing rates and thus high throughput.
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.
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.
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.
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.
At a global level, different studies disclose that transport systems are responsible for 25% of CO2 emissions. In the context of sustainable mobility, one of the challenges in the short term is associated with the research and improvement of alternative fuels, which should allow a fast decrease in the generation of greenhouse gases due to sustainable transport means. In this sense, green hydrogen can play a fundamental role. Green hydrogen is the basis for producing synthetic fuels, which can replace oil and its derivatives. Synthetic fuels or e-fuel are hydrocarbons produced from carbon dioxide (CO2) and green hydrogen (H2) as the only raw materials. H2 or efuel could be used in many sectors (manufacturing, residential, transportation, mining and other industries). In this study, different applications of hydrogen are evaluated by techno-economic analysis. The main variable that affects the production of hydrogen and its derivatives is the cost of electricity. Considering the renewable energy potential of Chile, it is feasible to develop in Chile the green hydrogen production as an energy vector, which would be technically and economically viable, together with the environmental benefits
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.
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.
Cyanobacteria, prokaryotic microorganisms with basically the same oxygenic photosynthesis as higher plants, are becoming excellent green cell factories for sustainable generation of renewable chemicals and fuels from solar energy and carbon dioxide. In the presentation I will visualize the concept green cell factories by introducing and discussing two examples: (i) engineering cyanobacteria to produce the important bulk chemical and potential blend-in biofuel butanol from sunlight and carbon dioxide, so called photosynthetic butanol, and (ii) generation of a functional semisynthetic [FeFe]-hydrogenase linking to the native metabolism in living cells of the unicellular cyanobacterium Synechocystis PCC 6803.
This work deals with the construction of a microscope for combined total internal reflection fluorescence (TIRF) and confocal microscopy. It is especially designed for single-molecule fluorescence spectroscopy. The design of the microscope body is based on the miCube (Hohlbein lab, Wageningen University, NL). The excitation and detection pathways were adapted to allow both TIRF and confocal illumination as well as camera and pointdetection for two color-channels to allow single-molecule Förster resonance transfer measurements
Development of a genetic biomonitoring test for the investigation of pollinator-plant-interactions
(2021)
There is a world-wide decline in biodiversity recorded. Especially insects and accompanying pollinators are threatened. When the foraging behaviour of pollinators is understood in detail, future crop and floral pollination services can be sustained and it is possible to establish projects for the conservation of pollinators and plant biodiversity. With the use of nanopore sequencing methods it is possible to detect pollen species that were collected by pollinators by their genetic information. In this study, a protocol for portable nanopore sequencing of DNA from pollen that was collected by honey bees, bumble bees and wild bees is being designed. DNAmetabarcoding is used to identify species within the mixed DNA sample. The ITS2-region will be used as a barcode. We will investigate pollen preferences of three pollinator species by placing their hives or nests at the same. Based on the results, landscape management schemes are developed that target pollen preferences and nutritional requirements of managed and wild social bee species as well as solitary wild bees.
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.
Standard assembly time is an important piece of data in product development that is used to compare different product variants or manufacturing variants. In the presented approach, standard time is created with the use of a decision tree regarding standard manual and machine-manual operations, taking into consideration product characteristics and typical tools, equipment and layout. The analysed features include, among others: information determined during product development, such as product structure, parts characteristics (e.g. weight, size), connection type, as well as the information determined during assembly planning: tools (e.g. hand screw driver, power screw driver, pliers), equipment (e.g. press, heater), workstation layout (e.g. distance, way of feeding). The object-attribute-value (OAV) framework was applied for the assembly characteristic. An example of the decision tree application to predict standard assembly time was presented for a mechanical subassembly. The case study was dedicated to standard time prediction for a bearing assembly. The presented approach is particularly important for the enterprises which offer customized products.
We use machine learning for the selection and classification of single–molecule trajectories to replace commonly used user–dependent sorting algorithms. Measured fluorescence time series of labelled single molecules need to be sorted into ’good molecules’ and ’bad’ molecules before further kinetic and thermodynamic analysis.
Currently, processing, sorting and analysis of the data is mainly done with the help of laboratory specific programs.
Although there are freely available programs for processing smFRET data, they do not offer ’molecular sorting’ or it is purely empirical. Only recently, new approaches came up to solve this problem by means of machine learning. Here, we describe a sound terminology for molecular sorting of smFRET data and present an efficient workflow for manual annotation followed by the training of the ML algorithm. Descriptive statistics of our generated dataset are provided and will serve as the basis for supervised ML-based molecular sorting algorithms yet to be developed.
This article aims to explain mathematically, why the so called double descent observed by Belkin et al., Reconciling modern machine-learning practice and the classical bias-variance trade-off, PNAS 116(32) (2019), p. 15849-15854, occurs on the way from the classical approximation regime of machine learning to the modern interpolation regime. We argue that this phenomenon may be explained by a decomposition of mean squared error plus complexity into bias, variance and an unavoidable irreducible error inherent to the problem. Further, in case of normally distributed output errors, we apply this decomposition to explain, why LASSO provides reliable predictors avoiding overfitting.
Marker-based systems can digitally record human movements in detail. Using the digital biomechanical human model Dynamicus, which was developed by the Institut für Mechatronik, it is possible to model joint angles and their velocities such accurately that it can be used to improve motion analysis in competitive sports or for ergonomic evaluation of motion sequences. In this paper, we use interpretable machine learning techniques to analyze the gait. Here, the focus is on the classification between foot touchdown and drop-off during normal walking. The motion data for training the model is labeled using force plates. We analyze how we could apply our machine learning models directly on new motion data recorded in a different scenario compared to the initial training, more precise on a treadmill. We use the properties of the interpretable model
to detect drift and to transfer our model if necessary.
Prototype-based Vector Quantization is one of the key methods in data processing like data compression or interpretable classification learning. Prototype vectors serve as references for data and data classes. The data are given as vectors representing objects by numerical features. Famous approaches are the Neural Gas Vector Quantizer (NGVQ) for data compression and Learning Vector Quantizers (LVQ) for classification tasks. Frequently, training of those models is time consuming. In the contribution we discuss modifications of these algorithms adopting ideas from quantum computing. The aim for this is a least twofold: First quantum computing provides ideas for enormous speedup making use of quantum mechanical systems and inherent parallelization.
Second, considering data and prototype vectors in terms of quantum systems, implicit data processing is performed, which frequently results in better data separation. We will highlight respective ideas and difficulties when equipping vector quantizers with quantum computing features.
Learning Vector Quantization (LVQ) methods have been popular choices of classification models ever since its introduction by T. Kohonen in the 90s. These days, LVQ is combined with Deep Learning methods to provide powerful yet interpretable machine-learning solutions to some of the most challenging computational problems.
However, techniques to model recurrent relationships in the data using prototype methods still remain quite unsophisticated. In particular, we are not aware of any modification of LVQ that allows the input data to have different lengths. Needless to say, such data is abundant in today's digital world and demands new processing techniques to extract useful information. In this paper, we propose the use of the Siamese architecture to not only model recurrent relationships within the prototypes but also the ability to handle prototypes of various dimensions simultaneously.
Sensor fusion is an important and crucial topic in many industrial applications. One of the challenging problems is to find an appropriate sensor combination for the dedicated application or to weight their information adequately. In our contribution, we focus on the application of the sensor fusion concept together with the reference to the distance-based learning for object classification purposes. The developed machine learning model has a bi-functional architecture, which learns on the one side the discrimination of the data regarding their classes and, on the other side, the importance of the single signals, i.e., the contribution of each sensor to the decision. We show that the resulting bi-functional model is interpretative, sparse, and simple to integrate in many standard artificial neural networks.
This paper looks at current projects in the field of Blockchain in education, their specific areas of application, possible advantages and weaknesses. Three examples developed by the team of authors are introduced in detail. First: Gallery-Defender a Serious Game, which was adapted to serve as a demonstrator in a stand-alone version to show the possibility to carry out exams directly from within the game and store the grades and meta-data on Blockchain. Second: Art-Quiz, an e-learning tool, which can be integrated into existing LMS systems and map exam results and further data using Blockchain technologies. Both were developed following an iterative design process. And third: The results of a focus group, which simulated the assignment of grades after an oral online exam. The three examples presented here are based on the Blockchain system Ardor/Childchain Ignis, but each demonstrator has a different set of features and approaches.
In addition, the integration of various Blockchain solutions was conceptually designed to make a Multi-Chain model possible.
With the increasing usage of blockchain technology, legal challenges such as GDPR compliance arise. Especially the right of erasure is considered challenging as blockchains are tamperproof by design. Several approaches investigated
possibilities to weaken the tamperproof aspect of blockchains in favor of GDPR compliance. This paper presents several approaches, then focuses on chameleon hash functions by evaluating the possibility to use these specific functions in a private blockchain. The goal of the built system is to take a step towards the digitization of the bill of lading used in international trade. This paper describes the developed software as well as the core considerations around the system such as network design or block structure.
Both cryptocurrency researchers and early adopters of cryptocurrencies agree that they possess a special kind of materiality, based on the laborious productive process of digital ‘mining’ [1]. This idea first appears in the Bitcoin White Paper [2] that encourages Bitcoin adopters to construct and justify its value in metaphoric comparison to gold mining. In
this paper, I explore three material aspects of blockchain: physical infrastructure, human language and computer code. I apply the concept of 'continuous materiality' [3] to show how these three aspects interact in practical implementations of blockchain such as Bitcoin and Ethereum. I start from the concept of ‘digital metallism’ that stands for ‘fundamental value’ of cryptocurrencies, and end with the move of Ethereum to ‘proof-of-stake’, partially as a countermeasure against ‘evil miners’. I conclude that ignoring material aspects of blockchain technology can only further problematize complicated relations between their technical, semiotic and social materiality.
After creating a new blockchain transaction, the next step usually is to make miners aware of it by having it propagated through the blockchain’s peer-to-peer network. We study an unintended alternative to peer-to-peer propagation: Exclusive mining. Exclusive mining is a type of collusion between a transaction initiator and a single miner (or mining pool). The initiator sends transactions through a private channel directly to the miner instead of propagating them through the peerto-peer network. Other blockchain users only become aware of these transactions once they have been included in a block by the miner. We identify three possible motivations for engaging in exclusive mining: (i) reducing transaction cost volatility (“confirmation as a service”), (ii) hiding unconfirmed transactions from the network to prevent frontrunning and (iii) camouflaging wealth transfers as transaction costs to evade taxes or launder money. We further outline why exclusive mining is difficult to prevent and introduce metrics which can be used to identify mining pools engaging in exclusive mining activity.
The set of transactions that occurs on the public ledger of an Ethereum network in a specific time frame can be represented as a directed graph, with vertices representing addresses and an edge indicating the interaction between two addresses.
While there exists preliminary research on analyzing an Ethereum network by the means of graph analysis, most existing work is focused on either the public Ethereum Mainnet or on analyzing the different semantic transaction layers using
static graph analysis in order to carve out the different network properties (such as interconnectivity, degrees of centrality, etc.) needed to characterize a blockchain network. By analyzing the consortium-run bloxberg Proof-of-Authority (PoA) Ethereum network, we show that we can identify suspicious and potentially malicious behaviour of network participants by employing statistical graph analysis. We thereby show that it is possible to identify the potentially malicious
exploitation of an unmetered and weakly secured blockchain network resource. In addition, we show that Temporal Network Analysis is a promising technique to identify the occurrence of anomalies in a PoA Ethereum network.
Decentralizing Smart Energy Markets - tamper-proof-documentation of flexibility market processes
(2020)
The evolving granularity and structural decentralization of the energy system leads to a need for new tools for the efficient operation of electricity grids. Local Flexibility Markets (or "Smart Markets") provide platform concepts for market based congestion management. In this context there is a distinct need for a secure, reliable and tamper-resistant market design which requires transparent and independent monitoring of platform operation. Within the following paper different concepts for blockchain-based documentation of relevant processes on the proposed market platform are described. On this basis potential technical realizations are discussed. Finally, the implementation of one setup using Merkle tree operations is presented by using open source libraries.
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.
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.
To enable smart devices of the internet of things to be connected to a blockchain, a blockchain client needs to run on this hardware. With the Trustless Incentivized Remote Node Network, in short Incubed, it will be possible to establish a decentralized and secure network of remote nodes, which enables trustworthy and fast access to a blockchain for a large number of low-performance IoT devices. Currently, Incubed supports the verification of Ethereum data. To serve a wider audience and more applications this paper proposes the verification of Bitcoin data as well, which can be achieved due to the modularity of Incubed. This paper describes the proof data that is necessary for a client to prove the correctness of a node’s response and the process to verify the response by using this proof data as well. A proof-object which contains the proof data will be part of every response in addition to the actual result. We design, implement and evaluate Bitcoin verification for Incubed. Creation of the proof data for supported methods (on the server-side) and the verification process using this proof data (on the client-side) has been demonstrated. This enables the verification of Bitcoin in Incubed.
Mathematics behind the Zcash
(2020)
Among all the new developed cryptocurrencies, Zcash comes out to be the strongest cryptocurrency providing both transparency and anonymity to the transactions and its users by deploying the strong mathematics of zk-SNARKs. We discussed the zero knowledge proofs as a building block for providing the functionality to zk-SNARKs. It offers schnorr protocol which is further used in Zcash transactions where the validation of sent transaction is proved by cryptographic proof. Further, we deploy zk-SNARKs following common reference string that allows sender to prove that she knows a secret such that the proof is succinct, can be verified and does not leak the secret. Non-malleability, small proofs and effective verification make zk-SNARKs a classic tool in Zcash. We deal with NP problems therefore we have considered the elliptic curve cryptography to provide the security. Lastly, we explain Zcash transaction, the corresponding transaction completely hides the sender, receiver and amount of transaction using zero knowledge proof.
This paper analyses the status quo of large-scale decision making combined with the possibility of blockchain as an underlying decentralized architecture to govern common pool resources in a collective manner and evaluates them according to their requirements and features (technical and non-technical). Due to an increasing trend in the distribution of knowledge and an increasing amount of information, the combination of these decentralized technologies and approaches, can not only be beneficial for consortial governance using blockchain but can also help communities to govern common goods and resources. Blockchain and its trust-enhancing properties can potenitally be a catalysator for more collaborative behavior among participants and may lead to new insights about collective action and CPRs.