Tesis sobre el tema "Data storage into DNA molecules"

La quantité de données numériques produites dans le monde chaque année augmente exponentiellement et les supports actuels de stockage atteignent leurs limites. Dans ce contexte, le stockage de données sur molécules d'ADN est très prometteur. Stockant jusqu’à 10¹⁸ octets par gramme d'ADN pour une consommation d'énergie quasi nulle, il a une durée de vie 100 fois plus longue que les disques durs. Cette technologie de stockage étant en développement, il est opportun d’y intégrer nativement des mécanismes pour sécuriser les données. C’est l’objet de cette thèse. Notre première contribution est une analyse des risques de l’ensemble de la chaîne de stockage, qui nous a permis d’identifier des vulnérabilités des procédés numériques et biologiques, en termes de confidentialité, d’intégrité, de disponibilité et de traçabilité. Une seconde contribution est l’identification d’opérateurs élémentaires permettant des manipulations simples de l’ADN. Avec ceux-ci, nous avons développé notre troisième contribution, une solution de chiffrement DNACipher qui impose un déchiffrement biomoléculaire des molécules avant de pouvoir lire les données correctement. Cette solution, qui repose sur des enzymes, a nécessité le développement d’un codage des données numériques en séquences ADN appelée DSWE ; notre quatrième contribution. Cet algorithme respecte les contraintes liées aux procédés biologiques (e.g. homopolymères) et à notre DNACipher. Enfin, notre dernière contribution est une validation expérimentale de notre chaîne de stockage sécurisée. C’est la première preuve de concept montrant qu’il est possible de sécuriser ce nouveau support de stockage sur la base de manipulations biomoléculaires
The volume of digital data produced worldwide every year is increasing exponentially, and current storage solutions are reaching their limits. In this context, data storage on DNA molecules holds great promise. Storing up to 10¹⁸ bytes per gram of DNA for almost no energy consumption, it has a lifespan 100 times longer than hard disks. As this storage technology is still under development, the opportunity presents itself to natively integrate data security mechanisms. This is the aim of this thesis. Our first contribution is a risk analysis of the entire storage chain, which has enabled us to identify vulnerabilities in digital and biological processes, particularly in terms of confidentiality, integrity, availability and traceability. A second contribution is the identification of elementary biological operators for simple manipulations of DNA. Using these operators, we have developed a DNACipher encryption solution that requires biomolecular decryption (DNADecipher) of the molecules before the data can be read correctly. This third contribution, based on enzymes, required the development of a coding algorithm for digital data into DNA sequences, a contribution called DSWE. This algorithm respects the constraints of biological processes (e.g. homopolymers) and our encryption solution. Our final contribution is an experimental validation of our secure storage chain. This is the first proof of concept showing that it is possible to secure this new storage medium using biomolecular manipulations

During the digital revolution there has been an explosion in the amount of data produced by humanity and the capacity of conventional storage devices has been struggling to keep up with this aggressive growth. This has highlighted the need for new means to store digital information, especially cold data. In this dissertations we will build upon the work done by the I3S MediaCoding team on utilizing DNA as a novel storage medium,thanks to its incredibly high information density and effectively infinite shelf life. We will expand on their previous works and adapt them to operate on the Nanopore MinIONsequencer, by increasing the noise resistance during the decoding process, and adding a post-processing step to repair the damage caused by the sequencing noise.

Two-photon absorption (2PA) has been used for a number of scientific and technological applications, exploiting the fact that the 2PA probability is directly proportional to the square of the incident light intensity (while one-photon absorption bears a linear relation to the incident light intensity). This intrinsic property of 2PA leads to 3D spatial localization, important in fields such as optical data storage, fluorescence microscopy, and 3D microfabrication. The spatial confinement that 2PA enables has been used to induce photochemical and photophysical events in increasingly smaller volumes and allowed nonlinear, 2PA-based, technologies to reach sub-diffraction limit resolutions. The primary focus of this dissertation is the development of novel, efficient 2PA, fluorene-based molecules to be used either as photoacid generators (PAGs) or fluorophores. A second aim is to develop more effective methods of synthesizing these compounds. As a third and final objective, the new molecules were used to develop a write-once-read many (WORM) optical data storage system, and stimulated emission depletion probes for bioimaging. In Chapter I, the microwave-assisted synthesis of triarylsulfonium salt photoacid generators (PAGs) from their diphenyliodonium counterparts is reported. The microwave-assisted synthesis of these novel sulfonium salts afforded reaction times 90 to 420 times faster than conventional thermal conditions, with photoacid quantum yields of new sulfonium PAGs ranging from 0.01 to 0.4. These PAGs were used to develop a fluorescence readout-based, nonlinear three-dimensional (3D) optical data storage system (Chapter II). In this system, writing was achieved by acid generation upon two-photon absorption (2PA) of a PAG (at 710 or 730 nm). Readout was then performed by interrogating two-photon absorbing dyes, after protonation, at 860 nm. Two-photon recording and readout of voxels was demonstrated in five and eight consecutive, crosstalk-free layers within a polymer matrix, generating a data storage capacity of up to 1.8 x 1013 bits/cm3. The possibility of using these PAGs in microfabrication is described in Chapter III, where two-photon induced cationic ring-opening polymerization (CROP) crosslinking of an SU8 resin is employed to produce free-standing microstructures. Chapter IV describes the investigation of one- and two-photon stimulated emission transitions by the fluorescence quenching of a sulfonyl-containing fluorene compound in solution at room temperate using a picosecond pump-probe technique. The nature of stimulated transitions under various fluorescence excitation and quenching conditions were analyzed theoretically, and good agreement with experimental data was demonstrated. Two-photon stimulated transitions S1 to S0 were shown at 1064 nm. The two-photon stimulated emission cross section of the sulfonyl fluorophore was estimated as aproximately 240 - 280 GM, making this compound a good candidate for use in two-photon stimulated emission depletion (STED) microscopy.
Ph.D.
Department of Chemistry
Sciences
Chemistry PhD

Le génome humain est principalement constitué d'ADN, une macromolécule constituée d'une longue séquence linéaire de bases, étroitement serrée pour s'insérer dans le noyau relativement petit. L'empaquetage donne lieu à de multiples niveaux hiérarchiques d'organisation. Des recherches récentes ont montré que, parallèlement à la séquence linéaire, l'agencement spatial du génome joue un rôle important dans la fonction et l'activité du génome. La visualisation des aspects li-né-aires et spatiaux des données du génome est donc nécessaire. Dans cette thèse, nous nous concentrons sur le concept d'abstraction visuelle continue pour les données multi-échelles, appliqué à la visualisation du génome humain. L'abstraction visuelle est un concept inspiré par des illustrations qui simplifie le travail de traitement visuel, en guidant l'attention du spectateur vers les aspects importants.Nous commençons par extraire les caractéristiques des données multi-échelles et faisons une comparaison parallèle entre le génome et les données astronomiques. Les différences existantes créent le besoin d'approches différentes. Un point commun cependant est la nécessité de transitions continues qui aident les spectateurs à saisir les relations et les différences de taille relative entre les échelles. Pour satisfaire aux conditions posées par les deux aspects des données génomiques multi-échelles, nous présentons deux cadres conceptuels, basés sur les mêmes données. Le premier cadre, ScaleTrotter, représente la structure spatiale du génome, à tous les niveaux disponibles. Il donne à l'utilisateur la liberté de voyager du noyau d'une cellule aux atomes des bases, en passant par les différents niveaux d'organisation du génome. Pour rendre possible l'exploration de la structure de tous les niveaux, des transitions temporelles fluides sont utilisées. Même si toutes les échelles ne sont pas visibles simultanément, la transition temporelle utilisée superpose deux représentations d'un même élément à des échelles consécutives, ce qui met en évidence leur relation. Pour garantir la compréhensibilité et l'interactivité des données, les parties inutiles des données sont extraites à l'aide d'une caméra dépendante de l'échelle. Le deuxième cadre, Multiscale Unfolding, se concentre sur des aspects qui ne sont pas visibles dans ScaleTrotter : la séquence linéaire et une vue d'ensemble simultanée de tous les niveaux organisationnels. Les données sont redressées pour déplier l’empaquetage qui se produit à plusieurs niveaux de manière à conserver la connectivité entre les éléments. Pour représenter tous les niveaux disponibles, nous utilisons des transitions spatiales douces entre les niveaux. Ces transitions spatiales sont basées sur le même concept que les transitions temporelles du cadre précédent, en superposant les échelles et en mettant l'accent sur leur relation et leur différence de taille. Nous introduisons une technique d'interaction appelée Multiscale Zliding qui permet l'exploration des données et met davantage l'accent sur les différences de taille entre les niveaux. Dans chaque cadre conceptuel, l'un des deux aspects linéaire ou spatial des données sur le génome est sacrifié pour mettre l'accent sur l'autre. La thèse se termine par une discussion sur la possibilité de combiner les deux cadres, en minimisant les sacrifices pour explorer les deux aspects du génome qui sont d'égale importance. Dans cette thèse, nous faisons un pas de plus vers la compréhension complète de l'activité du génome
The human genome consists mainly of DNA, a macromolecule consisting of a long linear sequence of bases, tightly packed to fit in the relatively small nucleus. The packing gives rise to multiple hierarchical organizational levels. Recent research has shown that, along with the linear sequence, the spatial arrangement of the genome plays an important role in the genome’s function and activity. The visualization of both linear and spatial aspects of genome data is therefore necessary. In this thesis, we focus on the concept of continuous visual abstraction for multiscale data, applied to the visualization of the human genome. Visual abstraction is a concept inspired by illustrations that makes the job of visual processing simpler, by guiding the attention of the viewer to important aspects. We first extract characteristics of multiscale data and makes a parallel comparison between genome and astronomical data. The existing differences create the need for different approaches. A common point however is the need for continuous transitions that helps viewers grasp the relationships and relative size differences between scales. To satisfy the conditions posed by the two aspects of the multiscale genome data, we present two conceptual frameworks, based on the same data. The first framework, ScaleTrotter, represents the spatial structure of the genome, on all available levels. It gives users the freedom to travel from the nucleus of a cell to the atoms of the bases, passing through the different organizational levels of the genome. To make the exploration of the structure of all levels possible, smooth temporal transitions are used. Even though all the scales are not simultaneously visible, the temporal transition used superimposes two representations of the same element at consecutive scales emphasizing their relationship. To ensure the understandability and interactivity of the data, unnecessary parts of the data are abstracted away with the use of a scale-dependent camera. The second framework, Multiscale Unfolding, focuses on aspects that are not visible in ScaleTrotter: the linear sequence and a simultaneous overview of all the organizational levels. The data is straightened to unfold the packing that occurs on several levels in a way that conserves the connectivity between the elements. To represent all the available levels, we use smooth spatial transitions between the levels. These spatial transitions are based on the same concept of the temporal transitions of the previous framework, superimposing scales and emphasizing on their relationship and size difference. We introduce an interaction technique called Multiscale Zliding that allows the exploration of the data and further emphasizes the size differences between the levels. In each framework, one of either linear of spatial aspect of genome data is sacrificed to emphasize the other. The thesis concludes with a discussion about the possibility of combining the two frameworks, minimizing the sacrifices to explore the two equally important aspects of the genome. In this thesis, we take a step closer to fully understanding the activity of the genome

The aim of this study is focused on two main areas of NGS analysis data: RNA-seq(with a specific interest in meta-transcriptomics) and DNA somatic mutations detection. We developed a simple and efficient pipeline for the analysis of NGS data derived from gene panels to identify DNA somatic point mutations. In particular we optimized a somatic variant calling procedure that was tested on simulated datasets and on real data. The performance of our system has been compared with currently available tools for variant calling reviewed in literature. For RNA-seq analysis, in this work we tested and optimized STAble, an algorithm developed originally in our laboratory for the de novo reconstruction of transcripts from non reference based RNA-seq data. At the beginning of this study, the first module of STAble was already been written. The first module is the one which reconstructs a list of transcripts starting from RNA-seq data. The aim of this study, particularly, consisted in adding a new module to STAble, developed in collaboration with Cambridge University, based on the flux-balance analysis in order to link the metatranscriptomic analysis to a metabolic approach. This goal has been achieved in order to study the metabolic fluxes of microbiota starting from metatranscriptomic data.

Bottom-up self-assembly can be used to create structures with sub-20 nm feature sizes or materials with advanced electrical properties. Here I demonstrate processes to enable such self-assembling systems including block copolymers and DNA origami, to be integrated into nanoelectronic devices. Additionally, I present a method which utilizes the high stability and electrical conductivity of graphene, which is a material formed using a bottom-up growth process, to create archival data storage devices. Specifically, I show a technique using block copolymer micelle lithography to fabricate arrays of 5 nm gold nanoparticles, which are chemically modified with a single-stranded DNA molecule and used to chemically attach DNA origami to a surface. Next, I demonstrate a method using electron beam lithography to control location of nanoparticles templated by block copolymer micelles, which can be used to enable precise position of DNA origami on a surface. To allow fabrication of conductive structures from a DNA origami template, I show a method using site-specific attachment of gold nanoparticles to and a subsequent metallization step to form continuous nanowires. Next, I demonstrate a long-term data storage method using nanoscale graphene fuses. Top-down electron beam lithography was used to pattern atomically thin sheets of graphene into nanofuses. To program the fuses, graphene is oxidized as the temperature of the fuse is raised via joule heating under a sufficiently high applied voltage. Finally, I investigate the effect of the fuse geometry and the electrical and thermal properties of the fuse material on the programming requirements of nanoscale fuses. Programming voltages and expected fuse temperatures obtained from finite element analysis simulations and a simple analytical model were compared with fuses fabricated from tellurium, a tellurium alloy, and tungsten.

L’explosion de la quantité de données est l’un des plus grands défis de l'évolution numérique, entraînant une croissance de la demande de stockage à un rythme tel qu'elle ne peut pas rivaliser avec les capacités réelles des périphériques. L'univers numérique devrait atteindre plus de 175 zettaoctets d'ici 2025, tandis que le 80% de ces données est rarement consultée (données froides), mais archivée sur des bandes magnétiques pour des raisons de sécurité et de conformité réglementaire. Les dispositifs de stockage conventionnels ont une durée de vie limitée de 10 à 20 ans et doivent donc être fréquemment remplacés pour garantir la fiabilité des données, un processus qui est coûteux en termes d'argent et d'énergie. L'ADN est un candidat très prometteur pour l'archivage à long terme de données « froides » pendant des siècles voire plus à condition que l'information soit encodée dans un flux quaternaire constitué des symboles A, T, C, G, pour représenter les 4 composants de la molécule d'ADN, tout en respectant certaines contraintes d'encodage importantes. Dans cette thèse, nous présentons de nouvelles techniques de codage pour le stockage efficace d'images numériques dans l'ADN. Nous avons implémenté un nouvel algorithme de longueur fixe pour la construction d'un code quaternaire robuste qui respecte les contraintes biologiques et proposé deux fonctions de "mapping" différentes pour permettre une flexibilité par rapport aux besoins d'encodage. De plus, l'un des principaux défis du stockage des données dans l’ADN étant le coût élevé de la synthèse, nous faisons une toute première tentative pour introduire une compression contrôlée dans la solution de codage proposée. Le codec proposé est compétitif par rapport à l'état de l'art. En outre, notre solution de codage / décodage de bout en bout a été expérimentée dans une expérience de laboratoire humide pour prouver la faisabilité de l'étude théorique dans la pratique
Data explosion is one of the greatest challenges of digital evolution, causing the storage demand to grow at such a rate that it cannot compete with the actual capabilities of devices. The digital universe is forecast to grow to over 175 zettabytes by 2025 while 80% is infrequently accessed (“cold” data), yet safely archived in off-line tape drives due to security and regulatory compliance reasons. At the same time, conventional storage devices have a limited lifespan of 10 to 20 years and therefore should be frequently replaced to ensure data reliability, a process which is expensive both in terms of money and energy. Recent studies have shown that due to its biological properties, DNA is a very promising candidate for the long-term archiving of “cold” digital data for centuries or even longer under the condition that the information is encoded in a quaternary stream made up of the symbols A, T, C and G, to represent the 4 components of the DNA molecule, while also respecting some important encoding constraints. Pioneering works have proposed different algorithms for DNA coding leaving room for further improvement. In this thesis we present some novel image coding techniques for the efficient storage of digital images into DNA. We implemented a novel fixed length algorithm for the construction of a robust quaternary code that respects the biological constraints and proposed two different mapping functions to allow flexibility according to the encoding needs. Furthermore, one of the main challenges of DNA data storage being the expensive cost of DNA synthesis, we make a very first attempt to introduce controlled compression in the proposed encoding workflow. The, proposed codec is competitive compared to the state of the art. Furthermore, our end-to-end coding/decoding solution has been experimented in a wet lab experiment to prove feasibility of the theoretical study in practice

In DNA-based data storage, the desired information is encoded into the quaternary sequence of synthetic DNA molecules, called oligos. We look at secure communication via information-containing oligos in the usual three-party setting, where Alice and Bob are legitimate communicators and Eve is an eavesdropper. Our scheme for secure DNAbased communication is two-fold: First, we store secret data in synthetic DNA molecules in a properly designed oligo pool of suitably high dilution. The oligo pool comprises information-containing oligos mixed with background genomic DNA cleaved into strands of the same length as the useful oligos. Designing oligos for storing the secret data involves the design of a library of primer pairs and a code book specific to this set of primers, that satisfy constraints on homopolymer run length, GC content, primerprimer dissimilarity, and primer-sequence dissimilarity. The differential knowledge of the designed primer pairs allows Bob to retrieve most of the information-containing DNA molecules after carrying out sufficient rounds of PCR amplification on the diluted oligo pool. In contrast, Eve is not able to access the stored information owing to her lack of any prior knowledge of the primer pairs. In order to improve upon the security of this scheme, we next develop an index-based secrecy coding scheme for the resulting wiretap system, where Bob observes a substantially lower number of erasures in the main channel, as compared to Eve’s channel, which suffers a large number of erasures (loss of DNA molecules). We show that under the conditions of a noise-free setting, proper library preparation, and proper measurement of oligos represented in smaller fractions, this coding scheme achieves the secrecy capacity of a DNA storage wiretap channel model with strong secrecy. An error-correcting code for reliable storage of DNA-based data must adhere to the constraints of GC content and homopolymer run length. In this thesis, we also explore the constraint of GC balance in the context of insertion and deletion error-correcting codes for DNA storage systems. We derive an upper bound on the cardinality of single indel-correcting GC-balanced quaternary codes. This allows us to deduce the minimal number of redundancy bits required for GC-balancing in such codes. We also develop a GC-balanced coding scheme for the correction of a single burst of 2 insertion or 2 deletion errors.

In this dissertation, we carry out an exploration of the fundamental limits of information-theoretic security in two different settings: multiterminal key agreement and DNA-based data storage. Most of the dissertation focuses on the problem of secret key agreement within the multiterminal source model introduced by Csiszár and Narayan (2004). In the last part of the dissertation, we formulate and characterize a notion of secure storage capacity in the context of DNA-based data storage. In the multiterminal source model, there is an underlying source that generates independent and identically distributed (i.i.d.) realizations of a random vector. The components of the random vector are finitely-supported random variables distributed according to a joint probability distribution that is specified in the model. Additionally, there is a finite set of users and a wiretapper, each of whom observes the realizations from some subset of the components of the source. The aim of the users is to interactively communicate over a noiseless public channel so that each user finally outputs a common random variable called a secret key, which is required to be secure from the wiretapper. The main object of interest is the wiretap secret key capacity, which is the maximum possible rate of a secret key that can be generated by the users. A substantial part of this dissertation attempts to gain insight into the single-letter characterization of wiretap secret key capacity, which is a problem that has remained largely unsolved. In the initial part of this dissertation, we explore the connection between secret key agreement and secure omniscience. The problem of secure omniscience is concerned with communication protocols for omniscience that minimize the rate of information leakage to the wiretapper. Our interest is in identifying broad classes of source models for which the wiretap secret key capacity can be achieved through an omniscience protocol that leaks the least possible amount of information to the wiretapper. In such cases, we say that there is a duality between secure omniscience and secret key agreement. In this dissertation, we show that this duality holds in the case of certain finite linear source (FLS) models, such as two-terminal FLS models and pairwise independent network models on trees with a linear wiretapper. On the other hand, we also give an example of a (non-FLS) source model for which the duality does not hold if we limit ourselves to communication-for-omniscience protocols with at most two (interactive) communications. Next, we give a characterization of the wiretap secret key capacity under two special situations: one is when the users are not allowed to communicate, and the other is when the communication rate goes to zero asymptotically. We show that both these characterizations have the same single-letter expression, which can be expressed in terms of the maximal common function. Our focus then shifts to the following question: When can the users generate a positive rate secret key? We give necessary and sufficient conditions for the secret key capacity to be positive, which extend known results on two-terminal sources to the multiterminal setting. For the special case of hypergraphical sources with a linear wiretapper, we derive a simpler equivalent condition for the positivity of secret key capacity in terms of the maximal common function. The final part of this dissertation is concerned with the study of DNA-based secure data storage. In this problem, a user (Alice) would like to store her data within a pool of (synthetic) DNA molecules so as to be reliably retrieved by an authorized party (Bob) while ensuring that an unauthorized party (Eve) gets almost no information from her (Eve's) observations. We propose a strategy for making DNA-based data storage information-theoretically secure through the use of wiretap channel coding. This motivates us to extend the shuffling-sampling channel model of Shomorony and Heckel (2021) to include a wiretapper. The main contribution is a characterization of the secure storage capacity of our DNA wiretap channel model, which is the maximum rate at which Alice can securely store her data within a pool of DNA molecules.

Lee Kit Ying.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2004.
Includes bibliographical references (leaves 115-117).
Abstracts in English and Chinese.
Abstract --- p.i
Acknowledgement --- p.iv
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- Project Background --- p.1
Chapter 1.2 --- Problem Specifications --- p.3
Chapter 1.3 --- Contributions --- p.5
Chapter 1.4 --- Thesis Organization --- p.6
Chapter 2 --- Background --- p.8
Chapter 2.1 --- Medical Data Mining --- p.8
Chapter 2.1.1 --- General Information --- p.9
Chapter 2.1.2 --- Related Research --- p.10
Chapter 2.1.3 --- Characteristics and Difficulties Encountered --- p.11
Chapter 2.2 --- DNA Sequence Analysis --- p.13
Chapter 2.3 --- Hepatitis B Virus --- p.14
Chapter 2.3.1 --- Virus Characteristics --- p.15
Chapter 2.3.2 --- Important Findings on the Virus --- p.17
Chapter 2.4 --- Bayesian Network and its Classifiers --- p.17
Chapter 2.4.1 --- Formal Definition --- p.18
Chapter 2.4.2 --- Existing Learning Algorithms --- p.19
Chapter 2.4.3 --- Evolutionary Algorithms and Hybrid EP (HEP) --- p.22
Chapter 2.4.4 --- Bayesian Network Classifiers --- p.25
Chapter 2.4.5 --- Learning Algorithms for BN Classifiers --- p.32
Chapter 3 --- Bayesian Network Classifier for Clinical Data --- p.35
Chapter 3.1 --- Related Work --- p.36
Chapter 3.2 --- Proposed BN-augmented Naive Bayes Classifier (BAN) --- p.38
Chapter 3.2.1 --- Definition --- p.38
Chapter 3.2.2 --- Learning Algorithm with HEP --- p.39
Chapter 3.2.3 --- Modifications on HEP --- p.39
Chapter 3.3 --- Proposed General Bayesian Network with Markov Blan- ket (GBN) --- p.40
Chapter 3.3.1 --- Definition --- p.41
Chapter 3.3.2 --- Learning Algorithm with HEP --- p.41
Chapter 3.4 --- Findings on Bayesian Network Parameters Calculation --- p.43
Chapter 3.4.1 --- Situation and Errors --- p.43
Chapter 3.4.2 --- Proposed Solution --- p.46
Chapter 3.5 --- Performance Analysis on Proposed BN Classifier Learn- ing Algorithms --- p.47
Chapter 3.5.1 --- Experimental Methodology --- p.47
Chapter 3.5.2 --- Benchmark Data --- p.48
Chapter 3.5.3 --- Clinical Data --- p.50
Chapter 3.5.4 --- Discussion --- p.55
Chapter 3.6 --- Summary --- p.56
Chapter 4 --- Classification in DNA Analysis --- p.57
Chapter 4.1 --- Related Work --- p.58
Chapter 4.2 --- Problem Definition --- p.59
Chapter 4.3 --- Proposed Methodology Architecture --- p.60
Chapter 4.3.1 --- Overall Design --- p.60
Chapter 4.3.2 --- Important Components --- p.62
Chapter 4.4 --- Clustering --- p.63
Chapter 4.5 --- Feature Selection Algorithms --- p.65
Chapter 4.5.1 --- Information Gain --- p.66
Chapter 4.5.2 --- Other Approaches --- p.67
Chapter 4.6 --- Classification Algorithms --- p.67
Chapter 4.6.1 --- Naive Bayes Classifier --- p.68
Chapter 4.6.2 --- Decision Tree --- p.68
Chapter 4.6.3 --- Neural Networks --- p.68
Chapter 4.6.4 --- Other Approaches --- p.69
Chapter 4.7 --- Important Points on Evaluation --- p.69
Chapter 4.7.1 --- Errors --- p.70
Chapter 4.7.2 --- Independent Test --- p.70
Chapter 4.8 --- Performance Analysis on Classification of DNA Data --- p.71
Chapter 4.8.1 --- Experimental Methodology --- p.71
Chapter 4.8.2 --- Using Naive-Bayes Classifier --- p.73
Chapter 4.8.3 --- Using Decision Tree --- p.73
Chapter 4.8.4 --- Using Neural Network --- p.74
Chapter 4.8.5 --- Discussion --- p.76
Chapter 4.9 --- Summary --- p.77
Chapter 5 --- Adaptive HEP for Learning Bayesian Network Struc- ture --- p.78
Chapter 5.1 --- Background --- p.79
Chapter 5.1.1 --- Objective --- p.79
Chapter 5.1.2 --- Related Work - AEGA --- p.79
Chapter 5.2 --- Feasibility Study --- p.80
Chapter 5.3 --- Proposed A-HEP Algorithm --- p.82
Chapter 5.3.1 --- Structural Dissimilarity Comparison --- p.82
Chapter 5.3.2 --- Dynamic Population Size --- p.83
Chapter 5.4 --- Evaluation on Proposed Algorithm --- p.88
Chapter 5.4.1 --- Experimental Methodology --- p.89
Chapter 5.4.2 --- Comparison on Running Time --- p.93
Chapter 5.4.3 --- Comparison on Fitness of Final Network --- p.94
Chapter 5.4.4 --- Comparison on Similarity to the Original Network --- p.95
Chapter 5.4.5 --- Parameter Study --- p.96
Chapter 5.5 --- Applications on Medical Domain --- p.100
Chapter 5.5.1 --- Discussion --- p.100
Chapter 5.5.2 --- An Example --- p.101
Chapter 5.6 --- Summary --- p.105
Chapter 6 --- Conclusion --- p.107
Chapter 6.1 --- Summary --- p.107
Chapter 6.2 --- Future Work --- p.109
Bibliography --- p.117

博士
國立交通大學
材料科學與工程學系所
101
This study describes an approach about improving the characteristics of photopolymer for holographic data storage. First of all, the diffraction efficiency (ηmax) and dynamic range (M#) of 9,10-phenanthrenequinone (PQ)–doped poly(methyl methacrylate) (PMMA) both improved significantly by co-doping five kinds of lanthanide organometallic ion lutetium (Lu3+), ytterbium (Yb3+), erbium (Er3+), neodymium (Nd3+) and cerium (Ce3+) into 9,10-phenanthrenequinone (PQ) / Poly ( hydroxyethyl methacrylate-co-methyl methacrylate) photopolymer. The diffraction efficiency and dynamic range (M #) was measured by 532nm the laser. The experimental results indicated that the performance for holographic data recording follows the order as: Lu(ac)3 > Yb(ac)3 > Er(ac)3 > PQ > Nd(ac)3 > Ce(ac)3. This order is corresponding to that of their atomic number (Lu > Yb > Er > Nd > Ce), but to the opposite order of the ionic radius(Lu+3 ＜ Yb+3＜ Er+3 ＜ Nd+3 ＜Ce+3) . Comparing that with the PQ singly doped P(HEMA-co-MMA) photopolymer samples, the maximal diffraction efficiency has been improved by 3.4 times to 98.3%, M/# had been improved by 2 times to 3.86, and the sensitivity was improved by 1.5 times. We also investigated the mechabism of Lu(ac)3-induced improvement in optical storage performance using FT-IR and X-ray photoelectron spectrocopyanalysis. In addition, we found that DMNA: PQ / PMMA photopolymer can be recorded by the 647nm red laser for holographic storage recording its maximum ~ 43% diffraction efficiency. A sinc-squared Bragg selection curve has been obtained and an image hologram reconstruction are also demonstrated. These experimental results support recording material for volume holographic applications in extended red spectral range.