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For audio signals, we use the sign of the coefficients of the redundant discrete wavelet transform to generate primary hash vectors assigning bit 1 to positive or zero coefficients and bit 0 in the negative case. Discarding the highest frequency band and using a 6 step transform we get for each sample a 6 bit primary hash value which we may save as an integer. We then select a possible primary hash value (in our experiments we chose 0 or 63) and take the time indices where this primary hash value occurs as the secondary hash vector which is attributed to the whole audio signal. Comparing two audio signals, the number of elements in the intersection of the corresponding time indices are called "number of matches", a high number may indicate a similarity between the files. This secondary hash vector turns out to be robust against addition of noise, GSM-, G.726-, MP3 coding and packet loss. It may therefore be useful to detect spam telephone calls without analyzing the semantic content by the similarity of the corresponding signals. An algorithm is given to detect similar but shifted signals. Results of experiments are reported using a test corpus of 5 000 audio files of regular calls and 200 audio files of different versions of 20 original spam recordings augmented by a set of 45 files of different versions of 9 "special spam" signals.
The use of nematic liquid crystal (LC) mixtures for microwave frequency applicationspresents a fundamental drawback: many of these mixtures have not been properly characterizedat these frequencies, and researchers do not have an a priori clear idea of which behavior they canexpect. This work is focused on developing a new procedure for the extraction of the main parametersof a nematic liquid crystal: dielectric permittivity and loss tangent at 11 GHz under differentpolarization voltages; splay elastic constantK11, which allows calculation of the threshold voltage(Vth); and rotational viscosityγ11, which allows calculating the response time of any arbitrary device.These properties will be calculated by using a resonator-based method, which is implementedwith a new topology of substrate integrated transmission line. The LC molecules should be rotated(polarized) by applying an electric field in order to extract the characteristic parameters; thus,the transmission line needs to have two conductors and low electric losses in order to preserve theintegrity of the measurements. This method was applied to a well-known liquid crystal mixture(GT3-23002 from MERCK) obtaining the permittivity and loss tangent versus bias voltage curves,the splay elastic constant, and the rotational viscosity of the mixture. The results validate the viabilityof the proposed method.
For most classes of chains, it is known if these contain locks, but especially for fixed-angle equilateral equiangular obtuse open polygonal chains in 3D, which can be used to model protein backbones, this is unknown. Fixed-angle equilateral equiangular obtuse closed and open polygonal chains can be used to model polymers. For these, it is clear, that locks based on knots exist, but not which chains are generally locked. We therefore examine both open and closed fixed-angle equilateral equiangular obtuse chains. For this purpose, those chains are divided into various subgroups and, depending on the subgroup, other aspects are investigated to show locks. Techniques from knot theory, graph theory, and specifically robot arm reachability and motion planning are combined. Algorithms are developed to create chains in desired configurations and to study them. It is shown why all fixed-angle equilateral equiangular obtuse closed chains are expected to be locked or in rare cases rigid and non-locked, but never non-locked and non-rigid. For fixed-angle equilateral equiangular obtuse open chains it is shown why it is expected that there are open chains that are locked and that the smallest locked open chain has 𝑛=7.
A test tool for Langton's ant-based algorithms is created. Among other things, it can create test files for the NIST-Statistical-Test-Suite. The test tool is used to investigate the invertibility, ring formation and randomness of 7 created models which are extensions of Langton’s ant. The models are examined to possibly use them as pseudo-random generator (PRG) or block cipher. All models use memories which are based on tori. This property is central, because this is how rings are formed in the first place and in addition the behavior of all models at the physical boundaries of the memory is clearly defined in this way. The different models have special properties which are also investigated. These include variable color sets, discrete convolution, multidimensionality, and the use of multiple ants, which are arranged fractal hierarchically and influence each other. The extensions convolution, multidimensional scalable and multidimensional scalable fractal ant colony are presented here for the first time. It is shown that well-chosen color sets and high-dimensional tori are particularly well suited as a basis for Langton's ant based PRGs. In addition, it is shown that a block cipher can be generated on this basis.
The publish or perish culture of scholarly communication results in quality and relevance to be are subordinate to quantity. Scientific events such as conferences play an important role in scholarly communication and knowledge exchange. Researchers in many fields, such as computer science, often need to search for events to publish their research results, establish connections for collaborations with other researchers and stay up to date with recent works. Researchers need to have a meta-research understanding of the quality of scientific events to publish in high-quality venues. However, there are many diverse and complex criteria to be explored for the evaluation of events. Thus, finding events with quality-related criteria becomes a time-consuming task for researchers and often results in an experience-based subjective evaluation. OpenResearch.org is a crowd-sourcing platform that provides features to explore previous and upcoming events of computer science, based on a knowledge graph. In this paper, we devise an ontology representing scientific events metadata. Furthermore, we introduce an analytical study of the evolution of Computer Science events leveraging the OpenResearch.org knowledge graph. We identify common characteristics of these events, formalize them, and combine them as a group of metrics. These metrics can be used by potential authors to identify high-quality events. On top of the improved ontology, we analyzed the metadata of renowned conferences in various computer science communities, such as VLDB, ISWC, ESWC, WIMS, and SEMANTiCS, in order to inspect their potential as event metrics.
We study p-adic L-functions Lp(s, 휒) for Dirichlet characters 휒. We show that Lp(s, 휒) has a Dirichlet series expansion for each regularization parameter c that is prime to p and the conductor of 휒. The expansion is proved by transforming a known formula for p-adic L-functions and by controlling the limiting behavior. A fnite number of Euler factors can be factored of in a natural manner from the p-adic Dirichlet series. We also provide an alternative proof of the expansion using p-adic measures and give an explicit formula for the values of the regularized Bernoulli distribution. The result is particularly simple for c = 2, where we obtain a Dirichlet series expansion that is similar to the complex case.
A level graph G = (V,E,λ) is a graph with a mapping λ : V → {1,...,k}, k ≥ 1, that partitions the vertex set V as V = V1 ∪...∪ Vk, Vj = λ-1(j), Vi ∩ Vj = ∅ for i ≠ j, such that λ(v) = λ(u) + 1 for each edge (u, v) ∈ E. Thus a level planar graph can be drawn with the vertices of every Vj, 1 ≤ j ≤ k, placed on a horizontal line, representing the level lj , and without crossings of edges, which can be drawn as straight line segments between the levels. Healy, Kuusik and Leipert gave a complete characterization of minimal forbidden subgraphs for level planar graphs (MLNP patterns) for hierarchies [4]. Minimal in terms of deleting an ar- bitrary edge leads to level planarity. A radial graph partitions the vertex set on radii, which can be pictured as concentric circles, instead of levels, lj = (j cos(α), j sin(α)), α ∈ [0,2π), mapped around a shared center, where j, 1 ≤ j ≤ k indicates the concentric circles’ radius. Comparing embeddings of radial graphs with that of level graphs we gain a further possibility to place an edge and eventually avoid edge crossings which we wish to prevent for planarity reasons. This offers a new set of minimal radial non planar subgraphs (MRNP patterns). Some of the MLNP pat- terns can be adopted as MRNP patterns while some turn out to be radial planar. But based on the radial planar MLNP patterns and the use of augmentation we can build additional MRNP patterns that did not occur in the level case. Furthermore we point out a new upper bound for the number of edges of radial planar graphs. It depends on the subgraphs in- duced between two radii. Because of the MRNP patterns these subgraphs can either consist of a forest or a cycle with several branches. Applying the bound we are able to characterize extremal radial planar graphs. Keywords: radial graphs, minimal non-planarity, extremal radial planar
In this paper we describe traffic sign recognition with neural networks in the frequency domain. Traffic signs exist in all countries to regulate the traffic of vehicles and pedestrians. Each country has its own set of traffic signs that are more or less similar. They consist of a set of abstract forms, symbols, numbers and letters, which are combined into different signs. Automatic traffic sign recognition is important for driver assistance systems and for autonomous driving. Traffic sign recognition is a subtype of image recognition. The traffic signs are usually recorded by a camera and must be recognized in real time, i.e. assigned to a class. We use neural networks for traffic sign recognition. The special feature of our method is that the traffic sign recognition does not take place in the spatial domain but in the frequency domain. This has advantages because it is possible to significantly reduce the number of neurons and thus the computing effort of the neural network compared to a conventional neural network.
This project was done in collaboration with CERN and is part of the detector control system of the ATLAS experiment. The primary goal foresaw the development and testing of the FPGA card for the MOPS-HUB crate with the focus on radiation tolerance. This was accomplished with the approach of designing two different PCBs. The first PCB was created as a fast prototype with the use of a commercial SOM-board. This was also beneficial for confirming that the chosen FPGA is suitable for the MOPS-HUB application. After the successful assembly and test, a second, more complex and foremost radiation tolerant PCB was designed. This was achieved by solely using components of the CERN radiation database.
The second part of this thesis focuses on increasing the distance of TMR registers with a Python script. A method was created for extracting and later parsing a design’s placement
information from Vivado. Furthermore, were system designed and implemented to recognize TMR cells, to find and validate free cells and to finally create a new placement for import into Vivado. These algorithms were tested with a multitude of configurations and the quality, based on the maximum possible frequency of a design, determined.