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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.
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.
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.
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 this thesis, we implement, correct, and modify the compartmental model described in “Transmission Dynamics of Large Coronavirus Disease Outbreak in Homeless Shelter, Chicago, Illinois, USA, 2020”. Our objective is to engage in reading and understanding scientific literature, reproduce the results, and modify or generalize an existing mathematical model. We provide an overview of epidemiological models, focusing on simple compartmental SEIR models. We correct inaccuracies and misprints in the original implementation and use the limited-memory Broyden–Fletcher–Goldfarb–Shanno algorithm to fit the model’s parameters. Furthermore, we modify the model by introducing an additional compartment. The resulting model has a more intuitive interpretation and relies on fewer assumptions. We also perform the fitting process for this alternative model. Finally, we demonstrate the advantages of our modified implementations and discuss other possible approaches.
Tokenization projects are currently very present when it comes to new blockchain technologies. After explaining the fundamentals of cross-chain interaction, the bachelor thesis will focus on tokenizing technology for Bitcoin on Ethereum. To get a more practical context, implementing the currently most successful decentralized tokenization project is described.
This thesis proposes a solution to the practical problem of supervising relatively basic mechanic processes in robotics by means of computervision. Supervision happens by comparing the tracked movement with a known, ideal recording of the movement that acts as a model.
First, this thesis analyzes possible approaches to the problem regarding data structures and representation, ways of extracting the data from the recording and ways to compare the data sets of two recordings. Then, a specific solution is implemented in C++ and explained.
In dieser Arbeit wurden neuartige Proteasen aus psychrotoleranten Bakterienstämmen isoliert und auf ihre biochemischen Eigenschaften charakterisiert. Des Weiteren konnten S8 Familie Proteasen Gene amplifiziert werden und Unterschiede in der Aminosäuresequenz konnten in Zusammenhang mit den biochemischen Eigenschaften der Proteasen in Verbindung gebracht werden.
This Bachelor thesis investigates the learning rules of the Hebbian, Oja and BCM neuron models for their convergence to, and the stability of, the fixed points. Existing research is presented in a structured manner using consistent notation. Hebbian learning is neither convergent nor stable. Oja learning converges to a stable fixed point, which is the eigenvector corresponding to the largest eigenvalue of the covariance matrix of the input data. BCM learning converges to a fixed point which is stable, when assuming a discrete distribution of orthogonal inputs that occur with equal probability. Hebbian learning can therefore not be used in further applications, where convergence to a stable fixed point is required. Furthermore, this Bachelor thesis came to the conclusion that determining the fixed points of the BCM learning rule explicitly involves extensive calculation and other methods for verifying the stability of possible fixed points should be considered.