This thesis describes new gene finding methods for eukaryotic gene prediction. The current methods for deriving model parameters for gene prediction algorithms are based on curated or experimentally validated set of genes or gene elements. These training sets often require time and additional expert efforts especially for the species that are in the initial stages of genome sequencing. Unsupervised training allows determination of model parameters from anonymous genomic sequence with. The importance and the practical applicability of the unsupervised training is critical for ever growing rate of eukaryotic genome sequencing. Three distinct training procedures are developed for diverse group of eukaryotic species. GeneMark-ES is developed for species with strong donor and acceptor site signals such as Arabidopsis thaliana, Caenorhabditis elegans and Drosophila melanogaster. The second version of the algorithm, GeneMark-ES-2, introduces enhanced intron model to better describe the gene structure of fungal species with posses with relatively weak donor and acceptor splice sites and well conserved branch point signal. GeneMark-LE, semi-supervised training approach is designed for eukaryotic species with small number of introns. The results indicate that the developed unsupervised training methods perform well as compared to other training methods and as estimated from the set of genes supported by EST-to-genome alignments. Analysis of novel genomes reveals interesting biological findings and show that several candidates of under-annotated and over-annotated fungal species are present in the current set of annotated of fungal genomes.

Made available in DSpace on 2016-03-15T19:37:36Z (GMT). No. of bitstreams: 1 Marcos Almeida do Amaral.pdf: 924821 bytes, checksum: 9688a401b13ea6bec24b0af1024abf72 (MD5) Previous issue date: 2011-02-01 / Communications have achieved great development on several fronts over the years. Among these, the communication using chaotic signals has been object of growing interest among researchers due to the characteristics of spread spectrum and hard detection. However these techniques still have inferior performance in comparison to conventional methods in non-ideal channels. To contribute do the solution of this problem, statistical estimation algorithms have been applied to the detection of the transmitted signal. The objective of this thesis is to study a communication system using chaotic carriers and reception with maximum likelihood (ML-CSK - Maximum Likelihood Chaos Shift Keying). For this, the application of Viterbi algorithm in chaotic modulation signals is investigated. As the previously proposed algorithms offer only good performance to signals generated by maps that present well-behaved probability density, a new technique was designed based on analysis of the map characteristics, obtained numerically through a training vector. The results of performed simulations assure the applicability and the good performance of the proposed innovations. / As comunicações têm alcançado grande desenvolvimento em várias frentes ao longo dos anos. Dentre estas, a comunicação utilizando sinais caóticos vêm sendo objeto de crescente interesse por parte dos pesquisadores devido às características de espalhamento espectral e difícil detecção. Entretanto estas técnicas ainda apresentam um desempenho inferior em comparação com os métodos convencionais em canais não ideais. Para contornar este problema, algoritmos estatísticos de estimação vêm sendo aplicados na detecção dos sinais transmitidos. O objetivo desta dissertação é estudar um sistema de comunicação utilizando portadoras caóticas e recepção com máxima verossimilhança (ML-CSK - Maximum Likelihood Chaos Shift Keying). Para isto, a aplicação do algoritmo de Viterbi em sistemas de modulação por sinais caóticos é investigada. A partir da constatação de que os algoritmos propostos anteriormente só apresentam bom desempenho para sinais gerados por mapas que apresentam densidade de probabilidade bem comportada, uma nova técnica foi concebida baseada no levantamento das características do mapa, obtidas numericamente através de um vetor de treinamento. Os resultados das simulações executadas atestam a aplicabilidade e o bom desempenho das inovações propostas.

Approved for public release; distribution is unlimited. / Trellis-Coded Modulation (TCM) is employed with quadrature amplitude modulation (QAM) to provide error correction coding with no expense in bandwidth. There are two common implementations of TCM, namely pragmatic TCM and Ungerboeck TCM. Both schemes employ Viterbi algorithms for decoding but have different code construction. This thesis investigates and compares the performance of pragmatic TCM and Ungerboeck TCM by implementing the Viterbi decoding algorithm for both schemes with 16-QAM and 64-QAM. Both pragmatic and Ungerboeck TCM with six memory elements are considered. Simulations were carried out for both pragmatic and Ungerboeck TCM to evaluate their respective performance. The simulations were done using Matlab software, and an additive white Gaussian noise channel was assumed. The objective was to ascertain that pragmatic TCM, with its reduced-complexity decoding, is more suitable to adaptive modulation than Ungerboeck TCM. / Civilian

This dissertation investigates four methods for attacking stream ciphers that are based on nonlinear combining generators: -- Two exhaustive-search correlation attacks, based on the binary derivative and the Lempel-Ziv complexity measure. -- A fast-correlation attack utilizing the Viterbi algorithm -- A decimation attack, that can be combined with any of the above three attacks. These are ciphertext-only attacks that exploit the correlation that occurs between the ciphertext and an internal linear feedback shift-register (LFSR) of a stream cipher. This leads to a so-called divide and conquer attack that is able to reconstruct the secret initial states of all the internal LFSRs within the stream cipher. The binary derivative attack and the Lempel-Ziv attack apply an exhaustive search to find the secret key that is used to initialize the LFSRs. The binary derivative and the Lempel-Ziv complexity measures are used to discriminate between correct and incorrect solutions, in order to identify the secret key. Both attacks are ideal for implementation on parallel processors. Experimental results show that the Lempel-Ziv correlation attack gives successful results for correlation levels of p = 0.482, requiring approximately 62000 ciphertext bits. And the binary derivative attack is successful for correlation levels of p = 0.47, using approximately 24500 ciphertext bits. The fast-correlation attack, utilizing the Viterbi algorithm, applies principles from convolutional coding theory, to identify an embedded low-rate convolutional code in the pn-sequence that is generated by an internal LFSR. The embedded convolutional code can then be decoded with a low complexity Viterbi algorithm. The algorithm operates in two phases: In the first phase a set of suitable parity check equations is found, based on the feedback taps of the LFSR, which has to be done once only once for a targeted system. In the second phase these parity check equations are utilized in a Viterbi decoding algorithm to recover the transmitted pn-sequence, thereby obtaining the secret initial state of the LFSR. Simulation results for a 19-bit LFSR show that this attack can recover the secret key for correlation levels of p = 0.485, requiring an average of only 153,448 ciphertext bits. All three attacks investigated in this dissertation are capable of attacking LFSRs with a length of approximately 40 bits. However, these attacks can be extended to attack much longer LFSRs by making use of a decimation attack. The decimation attack is able to reduce (decimate) the size of a targeted LFSR, and can be combined with any of the three above correlation attacks, to attack LFSRs with a length much longer than 40 bits. / Dissertation (MEng (Electronic Engineering))--University of Pretoria, 2007. / Electrical, Electronic and Computer Engineering / unrestricted

Η παρούσα διατριβή εισάγει μεθόδους για τον αυτόματο τεμαχισμό σημάτων ομιλίας. Συγκεκριμένα παρουσιάζονται τέσσερις νέες μέθοδοι για τον αυτόματο τεμαχισμό σημάτων ομιλίας, τόσο για γλωσσολογικά περιορισμένα όσο και μη προβλήματα. Η πρώτη μέθοδος κάνει χρήση των σημείων του σήματος που αντιστοιχούν στα ανοίγματα των φωνητικών χορδών κατά την διάρκεια της ομιλίας για να εξάγει όρια ψευδό-φωνημάτων με χρήση του αλγορίθμου δυναμικής παραμόρφωσης χρόνου. Η δεύτερη τεχνική εισάγει μια καινοτόμα υβριδική μέθοδο εκπαίδευσης κρυμμένων μοντέλων Μαρκώφ, η οποία τα καθιστά πιο αποτελεσματικά στον τεμαχισμό της ομιλίας. Η τρίτη μέθοδος χρησιμοποιεί αλγορίθμους μαθηματικής παλινδρόμησης για τον συνδυασμό ανεξαρτήτων μηχανών τεμαχισμού ομιλίας. Η τέταρτη μέθοδος εισάγει μια επέκταση του αλγορίθμου Βιτέρμπι με χρήση πολλαπλών παραμετρικών τεχνικών για τον τεμαχισμό της ομιλίας. Τέλος, οι προτεινόμενες μέθοδοι τεμαχισμού χρησιμοποιούνται για την βελτίωση συστημάτων στο πρόβλημα της σύνθεσης ομιλίας, αναγνώρισης ομιλίας και αναγνώρισης γλώσσας. / The present dissertation introduces methods for the automatic segmentation of speech signals. In detail, four new segmentation methods are presented both in for the cases of linguistically constrained or not segmentation. The first method uses pitchmark points to extract pseudo-phonetic boundaries using dynamic time warping algorithm. The second technique introduces a new hybrid method for the training of hidden Markov models, which makes them more effective in the speech segmentation task. The third method uses regression algorithms for the fusion of independent segmentation engines. The fourth method is an extension of the Viterbi algorithm using multiple speech parameterization techniques for segmentation. Finally, the proposed methods are used to improve systems in the task of speech synthesis, speech recognition and language recognition.

In this effort, we consider the performance of a dedicated short range communication (DSRC) system for inter-vehicle communications (IVC). The DSRC standard employs convolutional codes for forward error correction (FEC). The performance of the DSRC system is evaluated in three different channels with convolutional codes, regular low density parity check (LDPC) codes and quasi-cyclic (QC) LDPC codes. In addition, we compare the complexity of these codes. It is shown that LDPC and QC-LDPC codes provide a significant improvement in performance compared to convolutional codes. / Graduate

Dans le premier chapitre, la notion d'évaluation des risques sismiques est définie et les caractéristiques sismotectoniques de la région d'étude sont brièvement présentés. Un examen rigoureux des modèles stochastiques, appliqués au domaine de la sismologie est fourni. Dans le chapitre 2, différents modèles semi-Markoviens sont développés pour étudier la sismicité des îles Ioniennes centrales ainsi que le Nord de la mer Egée (Grèce). Les quantités telles que le noyau semi-Markovien et les probabilités de destination sont évaluées, en considérant que les temps de séjour suivent les distributions géométrique, discrète Weibull et Pareto. Des résultats utiles sont obtenus pour l'estimation de la sismicité. Dans le troisième chapitre un nouvel algorithme de Viterbi pour les modèles semi-Markoviens cachés est construit, dont la complexité est une fonction linéaire du nombre d'observations et une fonction quadratique du nombre d'états cachés, la plus basse existante dans la littérature. Une extension de ce nouvel algorithme est développée pour le cas où une observation dépend de l'état caché correspondant, mais aussi de l'observation précédente (cas SM1-M1). Dans le chapitre 4 les modèles semi-Markoviens cachés sont appliquées pour étudier la sismicité du Nord et du Sud de la mer Égée. La séquence d'observation est constituée des magnitudes et des positions d’un tremblement de terre et le nouvel algorithme de Viterbi est mis en œuvre afin de décoder les niveaux des tensions cachés qui sont responsables pour la sismogenèse. Les phases précurseurs (variations des tensions cachées) ont été détectées en avertissant qu’un tremblement de terre pourrait se produire. Ce résultat est vérifié pour 70 sur 88 cas (le score optimal). Les temps de séjour du processus caché étaient supposés suivre les distributions Poisson, logarithmique ou binomiale négative, tandis que les niveaux de tensions cachés ont été classés en 2, 3 ou 4 états. Les modèles de Markov caché ont également été adaptés sans présenter des résultats intéressants concernant les phases précurseurs. Dans le chapitre 5 un algorithme de Viterbi généralisé pour les modèles semi-Markoviens cachés, est construit dans le sens que les transitions au même état caché sont autorisées et peuvent également être décodées. De plus, une extension de cet algorithme généralisé dans le contexte SM1-M1 est présentée. Dans le chapitre 6 nous modifions de manière convenable le modèle Cramér-Lundberg y compris des sinistres négatifs et positifs, afin de décrire l'évolution avec le temps des changements de contraintes de Coulomb (valeurs ΔCFF) calculées pour sept épicentres (M ≥ 6) du Nord de la mer Egée. Formules pour les probabilités de ruine sont définies sous une forme générale. Corollaires sont également formulés pour la distribution exponentielle et Pareto. L'objectif est de mettre en lumière la question suivante qui pose la problématique dans la Sismologie: Au cours d'une année pourquoi un tremblement de terre s’est produit dans une position précise et pas dans une autre position, aux régions sismotectoniquement homogènes ayant valeurs ΔCFF positives. Les résultats montrent que les nouvelles formules de probabilité peuvent contribuer à répondre au problème susmentionné. / In the first chapter the definition of the seismic hazard assessment is provided, the seismotectonic features of the study areas are briefly presented and the already existing mathematical models applied in the field of Seismology are thoroughly reviewed. In chapter 2, different semi-Markov models are developed for studying the seismicity of the areas of the central Ionian Islands and the North Aegean Sea (Greece). Quantities such as the kernel and the destination probabilities are evaluated, considering geometric, discrete-Weibull and Pareto distributed sojourn times. Useful results are obtained for forecasting purposes. In the third chapter a new Viterbi algorithm for hidden semi-Markov models is developed, whose complexity is a linear function of the number of observations and a quadratic function of the number of hidden states, the lowest existing in the literature. Furthermore, an extension of this new algorithm is introduced for the case that an observation depends on the corresponding hidden state but also on the previous observation (SM1-M1 case). In chapter 4, different hidden semi-Markov models (HSMMs) are applied for the study of the North and South Aegean Sea. The earthquake magnitudes and locations comprise the observation sequence and the new Viterbi algorithm is implemented in order to decode the hidden stress field associated with seismogenesis. Precursory phases (variations of the hidden stress field) were detected warning for an anticipated earthquake occurrence for 70 out of 88 cases (the optimal model’s score). The sojourn times of the hidden process were assumed to follow Poisson, logarithmic or negative binomial distributions, whereas the hidden stress levels were classified into 2, 3 or 4 states. HMMs were also adapted without presenting significant results as for the precursory phases. In chapter 5 a generalized Viterbi algorithm for HSMMs is constructed in the sense that now transitions to the same hidden state are allowed and can also be decoded. Furthermore, an extension of this generalized algorithm in the SM1-M1 context is given. In chapter 6 we modify adequately the Cramér-Lundberg model considering negative and positive claims, in order to describe the evolution in time of the Coulomb failure function changes (ΔCFF values) computed at the locations of seven strong (M ≥ 6) earthquakes of the North Aegean Sea. Ruin probability formulas are derived and proved in a general form. Corollaries are also formulated for the exponential and the Pareto distribution. The aim is to shed light to the following problem posed by the seismologists: During a specific year why did an earthquake occur at a specific location and not at another location in seismotectonically homogeneous areas with positive ΔCFF values (stress enhanced areas). The results demonstrate that the new probability formulas can contribute in answering the aforementioned question.

This work aims at a task of speaker diarization. The goal is to implement a system which is able to decide "who spoke when". Particular components of implementation are described. The main parts are feature extraction, voice activity detection, speaker segmentation and clustering and finally also postprocessing. This work also contains results of implemented system on test data including a description of evaluation. The test data comes from the NIST RT Evaluation 2005 - 2007 and the lowest error rate for this dataset is 18.52% DER. Results are compared with diarization system implemented by Marijn Huijbregts from The Netherlands, who worked on the same data in 2009 and reached 12.91% DER.

Master thesis is related to the problematics of automatic speech recognition on systems with restricted hardware resources - embedded systems. The object of this work was to design and implement speech recognition system on embedded systems, that do not contain floating-point processing units. First objective was to choose proper hardware architecture. Based on the knowledge of available HW resources, the recognition system design was made. During the system development, optimalization was made on constituent elements so they could be mounted on chosen HW. The result of the the project is successful recognition of Czech numerals on embedded system.

Approved for public release; distribution is unlimited / OFDM systems have experienced increased attention in recent years and have found applications in a number of diverse areas including telephone-line based ADSL links, digital audio and video broadcasting systems, and wireless local area networks (WLAN). Orthogonal frequency-division multiplexing (OFDM) is a powerful technique for high data-rate transmission over fading channels. However, to deploy OFDM in a WLAN environment, precise frequency synchronization must be maintained and tricky frequency offsets must be handled. In this thesis, various techniques to improve the data throughput of OFDM WLAN are investigated. A simulation tool was developed in Matlab to evaluate the performance of the IEEE 802.11a physical layer. We proposed a rapid time and frequency synchronization algorithm using only the short training sequence of the IEEE 802.11a standard, thus reducing the training overhead to 50%. Particular attention was paid to channel coding, block interleaving and antenna diversity. Computer simulation showed that drastic improvement in error rate performance is achievable when these techniques are deployed. / Lieutenant, Hellenic Navy