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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.
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.
This study presents an analysis of the coverage made by the journals El País (Spain), Folha de S. Paulo (Brazil) and Süddeutsche Zeitung (Germany) about the protests in Brazil against the 2013 Confederations Cup and the 2014 FIFA World Cup to establish a comparison between them and see which topics were emphasized by the newspapers and which tone they use in their reporting. Based on the research questions, four categories were developed for the analysis of the journals: article structure; topic of the article; actors/group of persons and tone of the reporting, all of them composed by several subcategories. It was concluded that the themes highlighted by the European newspapers were different from those stressed on the Brazilian diary. Nonetheless, all the reviewed newspapers made a neutral coverage of the protests.
This paper examines the communication channels used by innovation projects at the ProtoSpace Hamburg, when engaging with stakeholders, and tries to answer the thesis question whether new media channels improve the chances of success for innovation projects, when used for this communication. Expert interviews with eight experts in com-munication, innovation and stakeholder management were conducted and then analyzed through the application of Mayring´s qualitative content analysis, in order to answer the posed question.
Functions, which can be summarized to the keyword Internet Protocol Television (IPTV) describe the transmission of video services to users via Internet Protocol (IP). Accompanying to this new television transmission path Home Theatre PCs (HTPC) running a so called Media Center platform are more and more entering the living rooms as a companion for the popular LCD and Plasma displays. Perfect ease of use and the visual integration on the screen and also into the living room is raising their acceptance. These HTPCs are a central node for multimedia services such as TV, radio and email within the networked household. Thus, there are good preconditions for the use of a HTPC as end device for Telco operator driven IPTV and telecommunication services. In the context of this diploma thesis possibilities for the provisioning of IPTV and Next Generation Network (NGN) services on a converged multimedia home entertainment platform for the living room will be investigated, especially Vista Media Center platforms. For this reason, standardization activities will be investigated, which deal with the integration of IPTV and telecommunication services into NGN. The validation of the results will be achieved by the design and implementation of a Vista Media Center Add-In, which can be integrated as an IP Multimedia Subsystem (IMS) based User Agent (UA) in ETSI TISPAN Release 2 IPTV infrastructures. Additionally, a Cross Domain messaging service for IMS based UA is created, which enables a cross-network communication between users.
Drought is one of the most common and dangerous threats plants have to face, costing the global agricultural sector billions of dollars every year and leading to the loss of tons of harvest. Until people drastically reduce their consumption of animal products or cellular agriculture comes of age, more and more crops will need to be produced to sustain the ever growing human population. Even then, as more areas on earth are becoming prone to drought due to climate change, we may still have to find or breed plant varieties more suitable to grow and prosper in these changing environments.
Plants respond to drought stress with a complex interplay of hormones, transcription factors, and many other functional or regulatory proteins and mapping out this web of agents is no trivial task. In the last two to three decades or so, machine learning has become immensely popular and is increasingly used to find patterns in situations that are too complex for the human mind to overlook. Even though much of the hype is focused on the latest developments in deep learning, relatively simple methods often yield superior results, especially when data is limited and expensive to gather.
This Master Thesis, conducted at the IPK in Gatersleben, develops an approach for shedding light on the phenotypic and transcriptomic processes that occur when a plant is subjected to stress. It centers around a random forest feature selection algorithm and although it is used here to illuminate drought stress response in Arabidopsis thaliana, it can be applied to all kinds of stresses in all kinds of plants.
The voluntary international blog VaultingNews exists for two years now. Meanwhile the
team grew and the costs increased. This thesis is a collection of tools, which can help
to improve the communication of the team members who are spread all over the world
and introduces monetization ideas where the focus lies on establishing an online fan
shop based in Germany. This chapter results in a check list which laws have to be
observed.
There are multiple ways to gain information about an individual and its health status, but an increasingly popular field in medicine has become the analysis of human breath, which carries a lot of information about metabolic processes within the individuals body. The information in exhaled breath consists of volatile (organic) compounds (VOCs). These VOCs are products of metabolic processes within the individuals body, thus might be an indicator for diseases disturbing those processes. The compounds are to be detected by mass-spectrometric (MS) or ion-mobility spectrometric (IMS) techniques, making the analysis of these compounds not only bounded to exhaled breath. The resulting data is spectral data, capturing concentrations of the VOCs indirectly through intensities. However, a number of about 3000 VOCs [1] could already be determined in human exhaled breath. The number of research paper about VOC-analysis and detection had risen nearly constantly over the last decade 1. Furthermore, the technique to identify VOCs could also be used to capture biomarker from alien species within the individuals body. Extracting VOCs from an individual can be done by non- or minimal invasive techniques. However, the manual identification of VOCs and biomarkers related to a certain disease or infection is not feasible due to the complexity of the sample and often unknown metabolic products, thus automized techniques are needed. [1–4] To establish breath analysis as a diagnosis tool, machine learning methodes could be used. Machine learning has become a popular and common technique when dealing with medical data, due to the rapid analysis. Taking this advantage, breath analysis using machine learning could become the model of choice for diagnosis, keeping in mind that conventional methodes are laboratory based and thus when trying detect bacterial infection need sometimes several days to identify the organism. [5]
The main purpose of this thesis is to investigate factors influencing the buying decision of cigarette smokers. To achieve this, different theories concerning consumer buying behavior and factors influencing have been discussed to achieve a deeper understand of consumer behaviour. To enable me comprehend the influence factors that influence the buying decision of a smoker as a consumer, a survey with questionnaires was performed. The results of the survey indicates that brand awareness, quality of the tobacco, price, packaging, advertisement, influence by others and availability are the major factors influencing the buying decision of a smoker, with availability, quality, price and brand awareness having the most effective influence on a smoker.
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.
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.
Derived from the Ancient Greek word τραῦμα (engl. wound,
damage), the word trauma refers to either physical or emotional wounds. Nowadays, it is mostly used in the context of psychological wounds, inflicted by an identity-shattering event – an event that causes the traumatised to not be able to reconcile their lived reality with the expectation of a human universal experience anymore. The last decade, the last two years in particular, and the last two weeks ad absurdum, have scarred the global landscape of human existence beyond recognition. From Putin’s unexpected reimposition of mutually assured destruction doctrines via the global SARS-Cov-2 pandemic to the lingering threat of climate doom, people all over the globe have been faced with persistent threats to their most basic perceptions of ontological safety. This article seeks to examine the impact of the SARS-Cov-2 pandemic and to which degree it is justified to speak of a pandemic trauma. In addition, it engages with the liminality of pandemic trauma as a shared, collective and an isolated, individual experience, and potential mitigation strategies for building community resilience.
The objective of this diploma thesis is to analyse the results of functional tests carried out on hydraulic valve blocks at Wujin Plant of Bosch Rexroth (Chang-zhou) Co., Ltd., (China). Based on this analysis, tests could be checked for systematic errors and root causes of failures be identified. Finally, this helped i n-crease the first pass yield of testing to release resources so far bound in inefficient testing processes. Furthermore, a tracking mechanism was established to monitor the function of crucial sensors at test benches.
In the past few years, social media has become the most popular communication software, replacing phone calls, text messages, television and even advertisements. Social media has become the most important channel for spreading opinions. As a result of this trend, many politicians have also started to operate social media (Wang, Tsai, & Chen 2019). This study was conducted in order to understand whether there was an intercandidate agenda-setting effect between the Facebook posts of legislative candidates and presidential candidates during the election period, and whether the legislative candidates' Facebook posts were influenced by the presidential candidates' Facebook posts. The target population of this study was the three presidential candidates in Taiwan's 2020 presidential election — Dr. Tsai Ing-Wen, Mr. Han Kuo-Yu, and Mr. James Soong — as well as the 36 legislative candidates in Taipei, Taichung, and Kaohsiung.
The study focused on Facebook posts from 1thNovember 2019 to 10th January 2020, 10 weeks before the voting day. Text-mining and cosine similarity were used to organize the posts and compare the similarity between posts. Finally, the similarity between posts was presented as a line graph.
The study revealed that there was an inter-candidate agenda-setting effect between legislative candidate posts and presidential candidate posts, and that Dr. Tsai Ing-Wen, who was also the incumbent president during the campaign, was the most influential Facebook poster during the entire election.
Future research is proposed on the inter-candidate agenda-setting effect only analyzing the similarity of posts among the candidates to discuss the influence of the candidates' Facebook agenda-setting during a specific election period.
This is the first study in which the Facebook posts of Taiwanese politicians are analyzed and the relationships were analyzed and the relationships were systematically compared, across multiple degrees, which opens up a whole new subject for future elections in Taiwan.
The games industry has significantly grown over the last 30 years. Projects are getting bigger and more expensive, making it essential to plan, structure and track them more efficiently.
The growth of projects has increased the administrative workload for producers, project managers and leads, as they have to monitor and control the progress of the project in order to keep a permanent overview of the project. This is often accompanied by a lack of insight into the project and basic communication within the team. Therefore, the goal of this thesis is to enhance conventional project management methods with process structures that occur frequently in game development.
This thesis initially elaborates on what project management in the game industry actually is: Here, methods are considered, especially agile methods and progress tracking prac-tices, which were created for software development and have become a standard in game development. Subsequently, an example is used to demonstrate how process management can function within the development of video games. Based on this, the ideal is depicted, which is implemented and used in a tool at the German games studio KING Art GmbH. This ideal is compared with expert interviews in order to verify its gen-eral validity in the industry.
By integrating process structures, the administrative effort can be reduced, communica-tion within game development can be simplified, while the current project status can be permanently presented. This benefits both project management and leads, as well as the entire team. Further application tests of this theory would have to be organized to check scalability and to draw comparisons to other applications.
Due to the intractability of the Discrete Logarithm Problem (DLP), it has been widely used in the field of cryptography and the security of several cryptosystems is based on the hardness of computation of DLP. In this paper, we start with the topics on Number Theory and Abstract Algebra as it will enable one to study the nature of discrete logarithms in a comprehensive way, and then, we concentrate on the application and computation of discrete logarithms. Application of discrete logarithms such as Diffie Hellman key exchange, ElGamal signature scheme, and several attacks over the DLP such as Baby-step Giant-step method, Silver Pohlig Hellman algorithm, etc have been analyzed. We also focus on the elliptic curve along with the discrete logarithm over the elliptic curve. Attacks for the elliptic curve discrete logarithm problem, ECDLP have been discussed. Moreover, the extension of several discrete logarithms-based protocols over the elliptic curve such as the elliptic curve digital signature algorithm, ECDSA have been discussed also.
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.
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.
This Bachelor thesis deals with connected systems consisting of a multitude of similar electronic devices
(often referred to as agents) endowed with information processing abilities. It is required that these socalled multi-agent systems solve a certain task with a high reliability, while the individual components
are not able to solve the problem on their own in a satisfying manner. A central control unit can not or
shall not be used in such systems for a variety of different reasons: For example, a significant drawback of
a central control unit is the vulnerability of the system. If the central control unit fails, the whole system breaks down. Therefore, multi-agent systems require special algorithms enabling the agents to solve a
common, global problem in a suitable manner by local interaction only.
In this thesis distributed algorithms are investigated which can be used for distributed information pro-cessing and control of such multi-agent systems. In the first part of this work, it is assumed that each
agent posses a private information state about a common parameter of interest. The described consensus algorithm enables all agents to reach a system-wide identical information state by local information
exchanges only. Subsequently, it is considered the case that every agent has access to streaming data containing information about an a priori unknown parameter. The diffusion strategy described in the second
part enables the agents to estimate this parameter and to minimize a global cost function which depends
on it. Both algorithms are described in a general framework and can therefore be applied to a variety of
different problems. One application of these strategies, which is described in the third part of this work,
is the simulation of swarming behavior.
Cancer is one of the main causes of death in developed countries, and cancer treatment heavily depends on successful early detection and diagnosis. Tumor biomarkers are helpful for early diagnose. The goal of this discovery method is to identify genetic variations as well as changes in gene expression or activity that can be linked to a typical cancer state.
First, several cancer gene signaling pathways were introduced and then combined. 27 candidate genes were selected, through the analysis of several data sets in the GEO database, a few expression difference matrices were established. Those candidate genes were tested in the matrices and found five genes PLA1A, MMP14, CCND1, BIRC5 and MYC that have the potential to be tumor biomarkers. Two of these genes have been further discussed, PLA1A is a potential biomarker for prostate cancer, and MMP14 can be considered as a biomarker for NSC lung cancer.
Finally, the significance of this study and the potential value of the two genes are discussed, and the future research in this direction is a prospect.