Refine
Document Type
- Master's Thesis (119)
- Bachelor Thesis (90)
- Conference Proceeding (66)
- Diploma Thesis (14)
- Final Report (6)
Year of publication
Language
- English (295) (remove)
Keywords
- Blockchain (40)
- Maschinelles Lernen (27)
- Vektorquantisierung (9)
- Algorithmus (7)
- Bioinformatik (6)
- Bitcoin (6)
- Graphentheorie (6)
- Internet der Dinge (6)
- Neuronales Netz (6)
- Unternehmen (6)
Institute
- Angewandte Computer‐ und Biowissenschaften (114)
- 06 Medien (35)
- 03 Mathematik / Naturwissenschaften / Informatik (28)
- Wirtschaftsingenieurwesen (21)
- 01 Elektro- und Informationstechnik (7)
- 04 Wirtschaftswissenschaften (7)
- Ingenieurwissenschaften (4)
- Sonstige (4)
- 02 Maschinenbau (2)
- 05 Soziale Arbeit (1)
Thіs bachеlоr thеsіs was еxеcutеd fоr Іntеrpіpе cоmpany and іt cоncеntratеs оn іts busіnеss stratеgy оn іntеrnatіоnal markеts, еspеcіally оn Mіddlе Еastеrn pіpеs markеt. Chооsіng an іnapprоprіatе еntry busіnеss stratеgy can lеad tо sіgnіfіcant nеgatіvе cоnsеquеncеs, busіnеss stratеgy sеlеctіоn оn іntеrnatіоnal markеts іs оnе оf thе mоst crіtіcal dеcіsіоns іn іntеrnatіоnal tradе systеm. Thе thеоrеtіcal framеwоrk оf thе bachеlоr thеsіs іs prоvіdеd іn thе sеcоnd chaptеr, whіch was maіnly cоllеctеd by dеsktоp studyіng. Thе thеоry rеvіеw cоntaіns dеscrіptіоn оf varіоus fоrеіgn markеt stratеgіеs, mеthоds and mеchanіsms оf dеcіsіоn-makіng, lеvеls and typеs оf busіnеss еnvіrоnmеnt. A cоmbіnatіоn оf thеоrіеs іs adоptеd tо facіlіtatе thе prоcеss оf gathеrіng thе rеquеstеd іnfоrmatіоn. Thе thіrd chaptеr cоntaіns іnfоrmatіоn abоut Іntеrpіpе Cоmpany und іt´s еcоnоmіc actіvіty іn thе hоst cоuntry and abrоad. Gеnеral іnfоrmatіоn abоut Іntеrpіpе Cоmpany, іts currеnt pоsіtіоn, busіnеss dеvеlоpmеnt stratеgy fоr 2015-2016 yеars arе prеsеntеd. Thе sіtuatіоn оn thе pіpеs and whееls markеt іn Ukraіnе durіng thе pеrіоd 2014-2015 was analyzеd and оn accоunt оf thіs thе rеasоns оf dеclіnе іn prоfіts and salеs wеrе еducеd. Cоіncіdеntly thе pеnеtratіоn fоrms оf Іntеrpіpе Cоmpany tо fоrеіgn cоuntrіеs wеrе cоnsіdеrеd. Іn thіs rеgard thе mоst succеssful еntry fоrms arе suggеstеd tо bе accеptеd as thе maіn kеy stratеgy оf pеnеtratіоn tо thе іntеrnatіоnal markеt. Thе fоrth chaptеr prоvіdеs thе іnfоrmatіоn abоut thе cеrtaіn apprоach оf pеnеtratіоn оf Іntеrpіpе Cоmpany tо thе Mіddlе Еastеrn pіpе markеt. Thе purpоsе іs tо іncrеasе thе numbеr оf dеlіvеrіеs tо оіl and gas cоmpanіеs іn thіs rеgіоn and cоntіnuе еstablіshіng оf іts rеlatіоns wіth kеy agеnts and dіstrіbutоrs. Thе prоjеct aіms tо еlеvatе currеnt pоsіtіоn оf thе еntеrprіsе оn Mіddlе Еastеrn pіpеs markеt and adjust advantagеоus іntеrnatіоnal rеlatіоns fоr bоth cоuntеrparts. Data іs cоllеctеd frоm varіоus sоurcеs, іncludіng: bооks and jоurnals іn thе thеоrеtіcal framеwоrk, nеwspapеrs, cоmpany’s publіshеd rеpоrts, prеss rеlеasеs, catalоguеs, bullеtіns, brоchurеs, prеsеntatіоn, Іntеrnеt rеsоurcеs еtc. іn thе еmpіrіcal study.
This thesis aims to research the platform YouTube and whether “being a YouTuber” qualifies as a profession or not and what leads to this. The author combines existing scientific data and information provided by YouTubers doing this as a job and uses the compilation method. The author merges that material and uses it to create a bachelor thesis that covers both the theoretical and practical approach. The aim was to find out if there is a success recipe that can be followed that leads to views and clicks which are essential for the profession as a YouTuber. To do this, the author created two channels to see how the factors mentioned in this thesis are applied and if the approach leads to success. The findings of this thesis showed, that although the profession of a YouTuber can be classified as a job, it needs to be viewed differently from commonly known and in society accepted careers. Becoming a YouTuber and making money from this business, therefore, cannot be guaranteed.
Workload Optimization Techniques for Password
Guessing Algorithms on Distributed Computing Platforms
(2019)
The following thesis covers several ways to optimize distributed computing platforms for cryptanalytic purposes. After an introduction on password storage, password guessing attacks and distributed computing in general, a set of inital benchmark results for a variety of different devices will be analyzed. The shown results are mainly based on utilization of the open source password recovery tool Hashcat. The second part of this work shows an algorithmic implementation for information retrieval and workload generation. This thesis can be used for the conception of a distributed computing system, inventory analysis of available hardware devices, runtime and cost estimations for specific jobs and finally strategic workload distribution.
In this thesis, the changes in economy and society and the resulting effects on the labor market are being outlined. Current studies show that the shrinking labor market and the increasing digitalization result in a lack of skilled tech talent and a transition from an employer market to a clear employee market. Derived from the findings of the scientific research on this topic and conducted expert interviews, practical recommendations for recruitment actions within the scope of employer branding will be defined in order to help corporations to gain the needed tech skill set and drive innovation.
This work concentrates on the frequently used marketing instrument brand personality. Its effect on the consumer and how it drives consumer behaviour through TV advertis-ing are the focus. Scientific material, utilising research results of the last 20 years, has been analysed to investigate this subject. Furthermore, the example of Southern Comfort provides an insight of brand personality being applied to the real world of marketing business.
This paper explores the origins of Maori images in New Zealand film history. Discussing the history of Maori and their society brings us closer to a, once almost extinct, race and its struggle for self-representation and self-governance. By taking an in-depth look at New Zealands film history we get to understand how Maori were the subject of the earliest films and at what time they started making their own films. Combining those elements gives us the opportunity to understand how early images of Maori were created by Pakeha directors. By looking at different films throughout film history shows how Maori images evolved in time, especially when Maori started depicting themselves. This paper not only answers questions about Maori images in film but also tries to make people realise what odds Maori had to overcome in their daily struggle for selfdetermination.
The following is a description and outline of the work done at the Cornell Lab of Ornithology developing Nation Feathers VR, a virtual reality game for learning about bird calls and songs. The goal was to develop a game which is intuitive, educational and entertaining. Furthermore, the software needed to be structured in a way that allows for feasible future expansion. This required careful data saving and retrieval. The game gives the player an opportunity to learn and apply that knowledge, all while maintaining a shorter runtime in order to reduce the total time spent in the virtual world. This is meant to prevent any discomfort to the player that may result from extended use of the VR headset.
VQ-VAE is a successful generative model which can perform lossy compression. It combines deep learning with vector quantization to achieve a discrete compressed representation of the data. We explore using different vector quantization techniques with VQ-VAE, mainly neural gas and fuzzy c-means. Moreover, VQ-VAE consists of a non-differentiable discrete mapping which we will explore and propose changes to the original VQ-VAE loss to fit the alternative vector quantization techniques.
Protein structures are essential elements in every biological system evolved on earth, where they function as stabilizing elements, signaltransducers or replication machin eries. They are consisting of linear-bonded amino acids, which determine the three-dimensional structure of the protein, whereas the structure in turn determines the function. The native and biological active structure ofa protein can be understood as the folding state of a polypeptide chain at the global minimum of free energy.
By means of protein energy profiling, which is an approach derived from statistical physics it is possible to assign a so called energy profile to a protein structure. Such an energy profile describes the local energetic interaction features of every amino acid within the structure and introduces an energetic point of view, instead of a structural or sequential onto proteins.
This work aims to give a perspective to the question of how we may gain pattern information out of energy profiles. The concrete subjects are energy-mapped Pfam family alignments and investigations on finding motifs or patterns indiscretizised energy profile segments.
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.
The number of Internet of Things (IoT) devices is increasing rapidly. The Trustless Incentivized Remote Node Network, in short IN3 (Incubed), enables trustworthy and fast access to a blockchain for a large number of low-performance IoT devices. Although currently IN3 only supports the verification of Ethereum data, it is not limited to one blockchain due to modularity. This thesis describes the fundamentals, the concept and the implementation of the Bitcoin verification in IN3.
nicht vorhanden
This study explores the opportunities and risks associated with user-generated content (UGC) in the communication strategies of marketing departments from a business perspective. With the rise of social media and online platforms, UGC has become a powerful tool for brands to engage with their audience, build trust, and enhance brand awareness. However, implementing UGC also comes with inherent risks, including the loss of control over brand messaging, potential negative user-generated content, and legal implications.
To investigate these dynamics, an empirical mixed-methods approach was employed, including expert interviews and a comprehensive literature review. The findings indicate that UGC offers significant opportunities for marketing departments, such as increased customer loyalty, enhanced authenticity, brand awareness, as well as a diverse set of possible content. However, the study also reveals the potential risks associated with UGC, highlighting the importance of managing these risks effectively.
In the following study the properties of the superabsorbent polymer Broadleaf P4 were investigated according to the aim to apply that polymer within constructed wetlands. The application of the polymer in constructed wetlands shall result in an improvement of the removal of pesticides. For that the polymer was given into lab-scale wetlands together with pumice and were compared to a control wetland, which was filled with gravel. The wetlands were running for several weeks in which the nutrient removal was recorded. The polymer was also tested according to its property to adsorb the pesticides before adding the pesticides to the wetland beds.
In Machine Learning, Learning Vector Quantization(LVQ) is well known as supervised learning method. LVQ has been studied to generate optimal reference vectors because of its simple and fast learning algorithm [12]. In many tasks of classification, different variants of LVQ are considered while training a model. In this thesis, the two variants of LVQ, Generalized Matrix Learning Vector Quantization(GMLVQ) and Generalized Tangent Learning Vector Quantization(GTLVQ) have been discussed. And later, transfer learning technique for different variants of LVQ has been implemented, visualized and we have compared the results using different datasets.
Community acquired pneumonia (CAP) is a very common, yet infectious and sometimes lethal disease. Therefor, this disease is connected to high costs of diagnosis and treatment. To actually reduce the costs for health care in this matter, diagnosis and treatment must get cheaper to conduct with no loss in predictive accuracy. One effective way in doing so would be the identification of easy detectable and highly specific transcriptomic markers, which would reduce the amount of work required for laboratory tests by possibly enhanced diagnosis capability.
Transcriptomic whole blood data, derived from the PROGRESS study was combined with several documented features like age, smoking status or the SOFA score. The analysis pipeline included processing by self organizing maps for dimensionality and noise reduction, as well as diffusion pseudotime (DPT). Pseudotime enabled modelling a disease run of CAP, where each sample represented a state/time in the modelled run. Both methods combined resulted in a proposed disease run of CAP, described by 1476 marker genes. The additional conduction of a geneset analysis also provided information about the immune related functions of these marker genes.
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.
Influenza A viruses are responsible for the outbreak of epidemics as well as pandemics worldwide. The surface protein neuraminidase of this virus is responsible, among other things, for the release of virions from the cell and is thus of interest in pharmacological research. The aim of this work is to gain knowledge about evolutionary changes in sequences of influenza A neuraminidase through different methods. First, EVcouplings is used with the goal of identifying evolutionary couplings within the protein sequences, but this analysis was unsuccessful. This is probably due to the great sequence length of neuraminidase. Second, the natural vector method will be used for sequence embedding purposes, in hopes to visualize sequential progression of the virus protein over time. Last, interpretable machine learning methods will be applied to examine if the data is classifiable by the different years and to gain information if the extracted information conform to the results from the EVcouplings analysis. Additionally to using the class label year, other labels such as groups or subtypes are used in classification with varying results. For balanced classes the machine learning models performed adequately, but this was not the case for imbalanced data. Groups and subtypes can be classified with a high accuracy, which was not the case for the years, continents or hosts. To identify the minimal number of features necessary for linear separation of neuraminidase group 1 subtypes, a logistic regression was performed at last, resulting in the identification of 15 combinations of nine amino acid frequencies. Since the sequence embedding as well as the machine learning methods did not show neuraminidase evolution over time, further research is necessary, for example with focus on one subtype with balanced data.
Proteins are involved in almost every aspect of life, mediating a wide range of cellular tasks. The protein sequence dictates the spatial arrangement of the residues and thus ultimately the function of a rotein. Huge effort is put into cumbersome structure eludication experiments which obtain models describing the observed spatial conformation of a protein, enabling users to predict their function, to understand their mode of action or to design tailored drugs to cure disease caused by misfolded or misregulated proteins.
However, the result of structure determination experiments are merely models of reality, made under simplifying assumptions - sometimes containing major undetected errors. On the other hand, such experiments are resource demanding and they cannot supply the actual demand.
Thus, scientists are predicting the structure of proteins in silico, resulting in models that are even
more prone to error.
In consequence, the structure biologists search after a practicable definition of structure quality and over the last two decades several model quality assessment programs emerged, measuring the local and global quality of peculiar structures. Seven representatives were studied, regarding the paradigms they follow and the features they use to describe the quality of residues. Their predications were compared, showing that there is almost no common ground among the tools.
Is there a way to combine their statements anyway?
Finally, the accumulated knowledge was used to design a novel evaluation tool, addressing problems previously spotted. Thereby, high quality of its predication as well as superior usability was
key. The strategy was compared to existing approaches and evaluated on suitable datasets.
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.