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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.