Statistical pattern recognition for audio-forensics : empirical investigations on the application scenarios audio steganalysis and microphone forensics

Magdeburg, Univ., Fak. für Informatik, Diss., 2013

Multimodal automatic user disposition recognition in human-machine interaction

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2013

Neural correlates of context-dependent memory : the role of the insula in episodic encoding and recognition memory ; an fMRI experiment

Magdeburg, Univ., Med. Fak., Diss., 2014

Efficiency Comparison of DFT/IDFT Algorithms by Evaluating Diverse Hardware Implementations

In this paper we investigate various algorithms for performing Fast Fourier Transformation (FFT)/Inverse Fast Fourier Transformation (IFFT), and proper techniques for maximizing the FFT/IFFT execution speed, such as pipelining or parallel processing, and use of memory structures with pre-computed values (look up tables -LUT) or other dedicated hardware components (usually multipliers). Furthermore, we discuss the optimal hardware architectures that best apply to various FFT/IFFT algorithms, along with their abilities to exploit parallel processing with minimal data dependences of the FFT/IFFT calculations. An interesting approach that is also considered in this paper is the application of the integrated processing-in-memory Intelligent RAM (IRAM) chip to high speed FFT/IFFT computing. The results of the assessment study emphasize that the execution speed of the FFT/IFFT algorithms is tightly connected to the capabilities of the FFT/IFFT hardware to support the provided parallelism of the given algorithm. Therefore, we suggest that the basic Discrete Fourier Transform (DFT)/Inverse Discrete Fourier Transform (IDFT) can also provide high performances, by utilizing a specialized FFT/IFFT hardware architecture that can exploit the provided parallelism of the DFT/IDF operations. The proposed improvements include simplified multiplications over symbols given in polar coordinate system, using sinе and cosine look up tables, and an approach for performing parallel addition of N input symbols.

Efficiency Comparison of DFT/IDFT Algorithms by Evaluating Diverse Hardware : Implementations,Parallelization Prospectsand Possible Improvements

In this paper we investigate various algorithms for performing Fast Fourier Transformation (FFT)/Inverse Fast Fourier Transformation (IFFT), and proper techniquesfor maximizing the FFT/IFFT execution speed, such as pipelining or parallel processing, and use of memory structures with pre-computed values (look up tables -LUT) or other dedicated hardware components (usually multipliers). Furthermore, we discuss the optimal hardware architectures that best apply to various FFT/IFFT algorithms, along with their abilities to exploit parallel processing with minimal data dependences of the FFT/IFFT calculations. An interesting approach that is also considered in this paper is the application of the integrated processing-in-memory Intelligent RAM (IRAM) chip to high speed FFT/IFFT computing. The results of the assessment study emphasize that the execution speed of the FFT/IFFT algorithms is tightly connected to the capabilities of the FFT/IFFT hardware to support the provided parallelism of the given algorithm. Therefore, we suggest that the basic Discrete Fourier Transform (DFT)/Inverse Discrete Fourier Transform (IDFT) can also provide high performances, by utilizing a specialized FFT/IFFT hardware architecture that can exploit the provided parallelism of the DFT/IDF operations. The proposed improvements include simplified multiplications over symbols given in polar coordinate system, using sinе and cosine look up tables,and an approach for performing parallel addition of N input symbols.

Visual recognition systems in a car passenger compartment with the focus on facial driver identification

Magdeburg, Univ., Fak. für Informatik, Diss., 2014

Practical Aspects of Genetic Algorithms’ Implementation in Life Cycle Management of Electrotechnical Equipment

Some practical aspects of Genetic algorithms’ implementation regarding to life cycle management of electrotechnical equipment are considered.

Value creation : the recognition and use of scientific potential in entrepreneurship

Otto-von-Guericke-Universität Magdeburg, Fakultät für Wirtschaftswissenschaft, Univ., Dissertation, 2015

Recognition characters and new records of two species of Phylloscyrtini (Orthoptera, Gryllidae, Trigonidiinae) from southern Brazil

The Phylloscyrtini occurs from eastern United States to Argentina and includes 21 valid species. It is a highly neglected group of crickets and little is known about its biology and distribution. Cranistus colliurides Stål, 1861 and Phylloscyrtus amoenus (Burmeister, 1880) were recorded for the state of Rio Grande do Sul, southern Brazil, and information on calling song, stridulatory file and recognition characters were provided.

Can genetic algorithms explain experimental anomalies? An application to common property resources

It is common to find in experimental data persistent oscillations in the aggregate outcomes and high levels of heterogeneity in individual behavior. Furthermore, it is not unusual to find significant deviations from aggregate Nash equilibrium predictions. In this paper, we employ an evolutionary model with boundedly rational agents to explain these findings. We use data from common property resource experiments (Casari and Plott, 2003). Instead of positing individual-specific utility functions, we model decision makers as selfish and identical. Agent interaction is simulated using an individual learning genetic algorithm, where agents have constraints in their working memory, a limited ability to maximize, and experiment with new strategies. We show that the model replicates most of the patterns that can be found in common property resource experiments.

Two algorithms to find a power integral basis

"Vegeu el resum a l'inici del fitxer adjunt."

Dance movement patterns recognition

"Es tracta d'un projecte dividit en dues parts independents però complementàries, realitzades per autors diferents. Aquest document conté originàriament altre material i/o programari només consultable a la Biblioteca de Ciència i Tecnologia"

Inbreeding avoidance through kin recognition: choosy females boost male dispersal.

Inbreeding avoidance is predicted to induce sex biases in dispersal. But which sex should disperse? In polygynous species, females pay higher costs to inbreeding and thus might be expected to disperse more, but empirical evidence consistently reveals male biases. Here, we show that theoretical expectations change drastically if females are allowed to avoid inbreeding via kin recognition. At high inbreeding loads, females should prefer immigrants over residents, thereby boosting male dispersal. At lower inbreeding loads, by contrast, inclusive fitness benefits should induce females to prefer relatives, thereby promoting male philopatry. This result points to disruptive effects of sexual selection. The inbreeding load that females are ready to accept is surprisingly high. In absence of search costs, females should prefer related partners as long as delta<r/(1+r) where r is relatedness and delta is the fecundity loss relative to an outbred mating. This amounts to fitness losses up to one-fifth for a half-sib mating and one-third for a full-sib mating, which lie in the upper range of inbreeding depression values currently reported in natural populations. The observation of active inbreeding avoidance in a polygynous species thus suggests that inbreeding depression exceeds this threshold in the species under scrutiny or that inbred matings at least partly forfeit other mating opportunities for males. Our model also shows that female choosiness should decline rapidly with search costs, stemming from, for example, reproductive delays. Species under strong time constraints on reproduction should thus be tolerant of inbreeding.

Modeling sequencing errors by combining Hidden Markov models.

Among the largest resources for biological sequence data is the large amount of expressed sequence tags (ESTs) available in public and proprietary databases. ESTs provide information on transcripts but for technical reasons they often contain sequencing errors. Therefore, when analyzing EST sequences computationally, such errors must be taken into account. Earlier attempts to model error prone coding regions have shown good performance in detecting and predicting these while correcting sequencing errors using codon usage frequencies. In the research presented here, we improve the detection of translation start and stop sites by integrating a more complex mRNA model with codon usage bias based error correction into one hidden Markov model (HMM), thus generalizing this error correction approach to more complex HMMs. We show that our method maintains the performance in detecting coding sequences.