An implementation framework has been developed in this thesis for a well-known APX-hard combinatorial optimization problem known as Block Sorting. The motivation for the study of this problem comes from applications such as computational biology and optical character recognition. While existing Block Sorting research has been theoretically focused on the development and analysis of several approximation algorithms for Block Sorting, little or no work has been carried out thus far on the implementation of the proposed approximation algorithms. The conceptualization of an implementation framework and illustrating its use by experimenting with the existing approximation algorithms will provide means for discovering newer approaches to handling this important problem. As the main contribution, the research in this thesis provides a new greedy algorithm for Block Sorting in which each block move either reduces the number of blocks by two or three blocks, or reduces by one the number of reversals or inversions in the orig- inal permutation. Experimental results for all algorithms are also provided along with a comparison of their performance using the number of block moves and approximation ratios as performance metrics when sorting permutations of a given order, and as the order of permutations is varied. Preliminary results from the experimentation were shared at the 2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) [1]. To the best of our knowledge, this is the first work that has been focused on the implementation and experimental performance analysis of any algorithm for Block Sorting. We believe the results presented in this thesis will be useful for researchers and practitioners working in this area.

The progess in NMRQIP can be outlined in to four parts.1) Implementation of theoretical protocols on small number of qubits. 2) Demonstration of QIP on various NMR systems. 3) Designing and implementing the algorithms for mixed initial states. 4) Developing the techniques for coherent and decoherent control on higher number(up to 15) of qubits. This thesis contains some efforts in the direction of first three points. Quantum-state discrimination has important applications in the context of quantum communication and quantum cryptography. One of the characteristic features of quantum mechanics is that it is impossible to devise a measurement that can distinguish nonorthogonal states perfectly. However, one can distinguish them with a finite probability by an appropriate measurement strategy. In Chapter 2, we describe the implementation of a theoretical protocol of programmable quantum-state discriminator, on a two-qubit NMR System. The projective measurement is simulated by adding two experiments. This device does the unambiguous discrimination of a pair of states of the data qubit that are symmetrically located about a fixed state. The device is used to discriminate both linearly polarized states and eillipitically polarized states. The maximum probability of successful discrimination is achieved by suitably preparing the ancilla quubit. The last step of any QIP protocol is the readout. In NMR-QIP the readout is done by using density matrix tomography. It was first proposed by Ernst and co-workers that a two-dimensional method can be used to correlate input and output states. This method uses an extra (aniclla) qubit, whose transitions indicate the quantum states of the remaining qubits. The 2D spectrum of ancilla qubit represent the input and output states along F1 and F2 dimensions respectively. However the 2D method requires several t1 increments to achieve the required spectral width and resolution in the indirect dimension, hence leads to large experimental time. In chapter 3, the conventional 2D NMRQIP method is speeded-up by using Hadamard spectroscopy. The Hadamard method is used to implement various two-, three-qubit gates and qutrit gates. We also use Hadamard spectroscopy for information storage under spatial encoding and to implement a parallel search algorithm. Various slices of water sample can be spatially encoded by using a multi-frequency pulse under the field gradient. Thus the information of each slice is projected to the frequency space. Each slice represents a classical bit, where excitation and no excitation corresponds to the binary values 0 and 1 respectively. However one has to do the experiment for each binary information, by synthesizing a suitable multi-frequency pulse. In this work we show that by recording the data obtained by various Hadamard encoded multi-frequency pulses, one can suitably decode it to obtain any birnary information, without doing further experiments. Geometric phases depend only on the geometry of the path executed in the projective Hilbert space, and are therefore resilient to certain types of errors. This leads to the possibility of an intrinsically fault-tolerant quantum computation. In liquid state NMRQIP. Controlled phase shift gates are achieved by using qubit selective pulses and J evolutions, and also by using geometir phases. In order to achieve higher number of qubits in NMR, one explores dipolar couplings which are larger in magnitude, yielding strongly coupled spectra. In such systems since the Hamiltonian consists of terms, it is difficult to apply qubit selective pulses. However such systems have been used for NMRQIP by considering 2n eigen states as basis states of an n-qubit system. In chapter 4, it is shown that non-adiabatic geometric phases can be used to implement controlled phase shift gates in strongly dipolar coupled systems. A detailed theoretical explanation of non-adiabatic geometric phases in NMR is given, by using single transition operators. Using such controlled phase shift gates, the implementation of Deutsch-Jozsa and parity algorithms are demonstrated. Search algorithms play an important role in the filed of information processing. Grovers quantum search algorithm achieves polynomial speed-up over the classical search algorithm. Bruschweiler proposed a Liouville space search algorithm which achieve polymonial speed-up. This algorithm requires a weakly coupled system with a mixed initial state. In chapter 5 we modified the Bruschweiler’s algorithm, so that it can be implemented on a weakly as well as strongly coupled system. The experiments are performed on a strongly dipolar coupled four-qubit system. The experiments from four spin-1/2 nuclei of a molecule oriented in a liquid crystal matrix. Chapter 6 describes the implementation of controlled phase shift gates on a quadrupolar spin-7/2 nucleus, using non-adiabatic geometric phases. The eight energy levels of spin-7/2 nucleus, form a three qubit system. A general procedure is given, for implementing a controlled phase shift gate on a system consisting of any number of energy levels. Finally Collin’s version of three-qubit DJ algorithm using multi-frequency pulses, is implemented in the spin-7/2 system.

Η ραγδαία ανάπτυξη και διείσδυση των νέων τεχνολογιών πληροφορίας και επικοινωνίας έχει επιφέρει ριζικές αλλαγές σε όλους τους τομείς της ανθρώπινης δράσης (Castells, 1998). Ιδιαίτερο ενδιαφέρον παρουσιάζει η επιρροή των τεχνολογιών αυτών στον τομέα της εκπαίδευσης. Οι εξελίξεις στον χώρο της τεχνολογίας και επικοινωνίας καθώς και η διάδοση του Internet μετεξέλιξαν αναπόφευκτα την εκπαιδευτική διαδικασία, από το κλασσικό συγκεντρωτικό μοντέλο σε ένα πιο άμεσο και ευέλικτο: η «εξ’ Αποστάσεως Εκπαίδευση» (e-learning) είναι μια εναλλακτική μορφή εκπαίδευσης, που επιδιώκει να καλύψει τους περιορισμούς της παραδοσιακής εκπαίδευσης. Στην παρούσα μεταπτυχιακή διπλωματική εργασία σχεδιάστηκε και υλοποιήθηκε ένα ολοκληρωμένο σύστημα Δυναμικής Ανάλυσης και Πρόβλεψης της επίδοσης των εκπαιδευομένων, για ένα σύστημα εξ΄ αποστάσεως εκπαίδευσης. Η βασική ιδέα εμφορείται από την ανάγκη των ιδρυμάτων εξ΄ αποστάσεως εκπαίδευσης, για την κάλυψη των εκπαιδευτικών αναγκών και την παροχή υψηλής ποιότητας σπουδών. Η εξόρυξη γνώσης για την πρόβλεψη της επίδοσης των εκπαιδευομένων συμβάλλει καθοριστικά στην επίτευξη υψηλής ποιότητας σπουδών. Η ικανότητα και η δυνατότητα πρόβλεψης της απόδοσης των εκπαιδευομένων μπορεί να φανεί χρήσιμη με αρκετούς τρόπους για την διαμόρφωση ενός συστήματος, που θα μπορεί να αποτρέψει την αποτυχία καθώς και την παραίτηση των εκπαιδευομένων. Αξίζει να σημειωθεί ότι στα συστήματα εξ’ αποστάσεως εκπαίδευσης η συχνότητα «εγκατάλειψης» είναι αρκετά υψηλότερη από αυτή στα συμβατικά πανεπιστήμια. Για την πρόβλεψη της επίδοσης των εκπαιδευομένων, η απαιτούμενη πληροφορία βρίσκεται «κρυμμένη» στο εκπαιδευτικό σύνολο δεδομένων (δλδ. βαθμοί γραπτών εργασιών, βαθμοί τελικής εξέτασης, παρουσίες φοιτητών) και είναι εξαγώγιμη με τεχνικές εξόρυξης. Η χρήση μεθόδων εξόρυξης δεδομένων (data mining) στον τομέα της εκπαίδευσης παρουσιάζει αυξανόμενο ερευνητικό ενδιαφέρον. Ο νέος αυτός «αναπτυσσόμενος» τομέας έρευνας, που ονομάζεται «Εκπαιδευτική Εξόρυξη Δεδομένων», ασχολείται με την ανάπτυξη μεθόδων εξόρυξης «γνώσης» από τα εκπαιδευτικά σύνολα δεδομένων. Πράγμα που επιτυγχάνεται με τη χρήση τεχνικών όπως τα δέντρα απόφασης, τα Νευρωνικά Δίκτυα, Naïve Bayes, k-means, κλπ. Η παρούσα εργασία έχει σχεδιαστεί να προσφέρει ένα μοντέλο εξόρυξης δεδομένων χρησιμοποιώντας τη μέθοδο των δέντρων απόφασης, για το σύστημα τριτοβάθμιας εκπαίδευσης στο ανοιχτό πανεπιστήμιο. Η «γνώση» που προκύπτει από τα δεδομένα εξόρυξης θα χρησιμοποιηθεί με στόχο την διευκόλυνση και την ενίσχυση της μάθησης, καθώς επίσης και στη λήψη αποφάσεων. Στην παρούσα εργασία, εξάγουμε «γνώση» που σχετίζεται με τις επιδόσεις των μαθητών στην τελική εξέταση. Επίσης, γίνεται εντοπισμός των ατόμων που εγκαταλείπουν το μάθημα και των μαθητών που χρειάζονται ιδιαίτερη προσοχή και εντέλει δίνει τη δυνατότητα στους καθηγητές να παράσχουν την κατάλληλη παροχή συμβουλών. / The rapid development and intrusion of information technology and communications have caused radical changes in all sectors of human’s activity. (Castells, 1998). Of particular interest is the great technology’s influence on education. Due to the adoption of the new technologies, e-learning has been emerged and developed. As a result, distance learning has transformed and new possibilities have appeared. It is remarkable that distance learning became and considered as a scout of the new era in education and contributed to the quality of education: e-learning is trying to cover the limitations of conventional teaching environment. In the present thesis, an integrated system of dynamic analysis and prediction of the performance of students in distance education has been designed and implemented. The initial idea for designing this system came from the higher distance education institutes’ need to provide quality education to its students and to improve the quality of managerial decisions. One way to achieve highest level of quality in higher distance education e-learning system is by discovering knowledge from educational data to study the main attributes that may affect the students’ performance. The discovered knowledge can be used to offer a helpful and constructive recommendations to the academic planners in higher distance education institutes to enhance their decision making process, to improve students’ academic performance, trim down failure rate and dropout rate, to assist instructors, to improve teaching and many other benefits. Dropout rates in university level distance learning are definitely higher than those inconventional universities, thus limiting dropout is essential in university-level distance learning.

Made available in DSpace on 2016-08-17T14:52:41Z (GMT). No. of bitstreams: 1 Dissertacao-WilanderTestonePereiraSilva.pdf: 3903191 bytes, checksum: b91ff906a27937df64d75b330c6ea137 (MD5) Previous issue date: 2016-03-11 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / In this dissertation we present a research in aspects of stochastic modeling, convergence and applications of least mean square (LMS) algorithm, normalized least mean square (NLMS) algorithm and proportionate normalized least mean square (PNLMS) algorithm. Specifically, the aim is to address the LMS algorithm in your extension, defining his concepts, demonstrations of properties, algorithms and analysis of convergence, Learning Curve and Misadjustment of the algorithm in question. Within of the context of sensor networks and spatial filtering is evaluated the performance of the algorithms by the learning curve of the referred algorithms for arrangements of adaptive antennas. In the intrinsic context of the application in electrical engineering, in area of telecommunications that seek the best alternative and aims to optimize the process of transmission/reception to eliminate interference, and the least amount of elements in adaptive antenna arrays, which they are known as smart antenna, which aims to reach a signal noise ratio for small value, with appropriate number of elements. The performance of the LMS algorithm is evaluated in sensor networks that is characterized by an antenna array. Results of computer simulations for different scenarios of operation show that the algorithms have good numerical results of convergence to a suitable choice of the parameters related with the rate of learning that are associated with their average curves and the beamforming of the smart antenna array. / Nesta dissertação de mestrado apresenta-se uma investigação em aspectos de modelagem estocástica, convergência e aplicações dos algoritmos de mínimos quadrados médio (LMS), mínimos quadrados médio normalizado (NLMS) e mínimos quadrados médio normalizado proporcional (PNLMS). Particularmente, aborda-se o Algoritmo LMS em sua extensão, definindo conceitos, demonstrações de propriedades, algoritmos e análise de convergência, Curva de Aprendizagem e Desajuste do referido algoritmo. Dentro do contexto de redes de sensores e filtragem espacial avalia-se o desempenho dos algoritmos por meio da curva de aprendizagem dos referidos algoritmos para os arranjos de antenas adaptativas. No contexto intrínseco da aplicação em engenharia elétrica, isto é, na área de telecomunicações procura-se a melhor alternativa e almeja-se a otimização do processo de transmissão/recepção para eliminar interferências e a menor quantidade de elementos em arranjos de antenas adaptativas, que são conhecidas como antenas inteligentes, e que tem como objetivo atingir uma relação Sinal Ruído para valor pequeno, com número adequado de elementos. O desempenho do algoritmo LMS é avaliado em redes de sensores que é caracterizada por um arranjo de antenas. Resultados de simulações computacionais para diferentes cenários de operação mostram que os algoritmos apresentam bons resultados numéricos de convergência para uma escolha adequada dos parâmetros relacionados com a taxa de aprendizagem que são associadas com suas curvas médias e com a conformação de feixes do arranjo em antenas inteligentes.

Level sets are extensively used for the visualization of scalar fields. The Reeb graph of a scalar function tracks the evolution of the topology of its level sets. It is obtained by mapping each connected component of a level set to a point. The Reeb graph and its loop-free version called the contour tree serve as an effective user interface for selecting meaningful level sets and for designing transfer functions for volume rendering. It also finds several other applications in the field of scientific visualization. In this thesis, we focus on designing algorithms for efficiently computing the Reeb graph of scalar functions and using the Reeb graph for effective visualization of scientific data. We have developed three algorithms to compute the Reeb graph of PL functions defined over manifolds and non-manifolds in any dimension. The first algorithm efficiently tracks the connected components of the level set and has the best known theoretical bound on the running time. The second algorithm, utilizes an alternate definition of Reeb graphs using cylinder maps, is simple to implement and efficient in practice. The third algorithm aggressively employs the efficient contour tree algorithm and is efficient both theoretically, in terms of the worst case running time, and practically, in terms of performance on real-world data. This algorithm has the best performance among existing methods and computes the Reeb graph at least an order of magnitude faster than other generic algorithms. We describe a scheme for controlled simplification of the Reeb graph and two different graph layout schemes that help in the effective presentation of Reeb graphs for visual analysis of scalar fields. We also employ the Reeb graph in four different applications – surface segmentation, spatially-aware transfer function design, visualization of interval volumes, and interactive exploration of time-varying data. Finally, we introduce the notion of topological saliency that captures the relative importance of a topological feature with respect to other features in its local neighborhood. We integrate topological saliency with Reeb graph based methods and demonstrate its application to visual analysis of features.

Image De-noising forms an integral part of image processing. It is used as a standalone algorithm for improving the quality of the image obtained through camera as well as a starting stage for image processing applications like face recognition, super resolution etc. Non Local Means (NL-Means) and Bilateral Filter are two computationally complex de-noising algorithms which could provide good de-noising results. Due to its computational complexity, the real time applications associated with these letters are limited. In this thesis, we propose the use of hardware accelerators such as GPU (Graphics Processing Units) and FPGA (Field Programmable Gate Arrays) to speed up the filter execution and efficiently implement using them. GPU based implementation of these letters is carried out using Open Computing Language (Open CL). The basic objective of this research is to perform high speed de-noising without compromising on the quality. Here we implement a basic NL-Means filter, a Fast NL-Means filter, and Bilateral filter using Gauss Polynomial decomposition on GPU. We also propose a modification to the existing NL-Means algorithm and Gauss Polynomial Bilateral filter. Instead of Gaussian Spatial Kernel used in standard algorithm, Box Spatial kernel is introduced to improve the speed of execution of the algorithm. This research work is a step forward towards making the real time implementation of these algorithms possible. It has been found from results that the NL-Means implementation on GPU using Open CL is about 25x faster than regular CPU based implementation for larger images (1024x1024). For Fast NL-Means, GPU based implementation is about 90x faster than CPU implementation. Even with the improved execution time, the embedded system application of the NL-Means is limited due to the power and thermal restrictions of the GPU device. In order to create a low power and faster implementation, we have implemented the algorithm on FPGA. FPGAs are reconfigurable devices and enable us to create a custom architecture for the parallel execution of the algorithm. It was found that the execution time for smaller images (256x256) is about 200x faster than CPU implementation and about 25x faster than GPU execution. Moreover the power requirements of the FPGA design of the algorithm (0.53W) is much less compared to CPU(30W) and GPU(200W).

This thesis deals with methods for optimization in image processing. There is described some of optimization techniques and some applications in image processing. There is also described detailed procedure and realization of bee algorithm, genetic algorithm, PSO algorithm and their realization in image registration, matched filtering, image segmentation and image reconstruction. Algorithms and their efficiencies are compared in the particular application for image processing.

The aim of this work is to automatically design a program that is able to detect dyskinetic movement features in the measured patient's movement data. The program will be developed using Cartesian genetic programming equipped with coevolution of fitness predictors. This type of coevolution allows to speed up a design performed by Cartesian genetic programming by evaluating a quality of candidate solutions using only a part of training data. Evolved classifier achieves a performance (in terms of AUC) that is comparable with the existing solution while achieving threefold acceleration of the learning process compared to the variant without the fitness predictors, in average. Experiments with crossover methods for fitness predictors haven't shown a significant difference between investigated methods. However, interesting results were obtained while investigating integer data types that are more suitable for implementation in hardware. Using an unsigned eight-bit data type (uint8_t) we've achieved not only comparable classification performance (for significant dyskinesia AUC = 0.93 the same as for the existing solutions), with improved AUC for walking patient's data (AUC = 0.80, while existing solutions AUC = 0.73), but also nine times speedup of the design process compared to the approach without fitness predictors employing the float data type, in average.

This thesis presents description of Genetic algorithm. The description begins with theory of complexity and following basic theory of genetic algorithm. Next part explains the principle of all three tasks – travelling salesman problem, knapsack problem and evolution of algorithm for five-in-a-row. The main focus was on developing the algorithm for five-in-a-row. The results were tested with other similar algorithms from internet. In case of travelling salesman problem and knapsack problem, the results were compared with gradient optimization methods.

The work deals with data security using BCH codes. In the work are described BCH codes in binary and non-binary form, and their most important subclass RS codes. Furthermore, this work describes the method of decoding Peterson-Gorenstein-Zierl, Berlekamp- Massey and Euclidean algorithm. For the presentation of encoding and decoding process, the application was created in Matlab, which has two parts – Learning BCH codes and Simulation of BCH codes. Using the generated application performance of BCH codes was compared at the last part of the work.