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Excerpt: An unpublished song by Blind Alfred Reed, transcribed by Reed’s granddaughter Delores Crawford.

Les travaux de cette thèse portent sur la cryptanalyse d'un système de chiffrement simple, mais important : le registre filtré. Ils concernent les deux principales familles d'attaques que sont les attaques algébriques et les attaques probabilistes. Pour les attaques algébriques, il est important de pouvoir calculer efficacement l'immunité algèbrique de la fonction booléenne par laquelle le registre est filtré. Cette quantité est intimement liée au comportement des codes de Reed-Muller sur le canal à effacements et son étude a permis la découverte de plusieurs résultats qui s'expriment naturellement dans le cadre de la théorie des codes correcteurs. Nous avons ainsi construit une nouvelle borne sur la probabilité de pouvoir compenser un nombre d'effacements fixé. Cette borne montre que l'immunité algébrique d'une fonction booléenne aléatoire est presque toujours maximale. Nous avons également explicité une méthode de décodage fondée sur des algorithmes d'algèbre linéaire creuse (comme l'algorithme de Wiedemann) qui donne un des algorithmes les plus efficace pour calculer l'immunité algébrique. Pour les attaques probabilistes, un outil très important est de parvenir à trouver efficacement de nombreux multiples de poids faible du registre à décalage du système. Un nouvel algorithme fondé sur les logarithmes discrets à été proposé. Il est particulièrement interessant pour les multiples de poids 4, améliorant dans de nombreux cas pratiques le meilleur algorithme connu. Ce travail s'est poursuivi par une nouvelle cryptanalyse probabiliste du registre filtré qui utilise ces multiples de poids faible pour reconnaître les entrées nulles de la fonction de filtrage. Cette attaque est l'une des plus efficaces connue à l'heure actuelle.

<p>We study the problem of list decoding with focus on the case when we have a list size limited to two. Under this restriction we derive general lower bounds on the maximum possible size of a list-of-2-decodable code. We study the set of correctable error patterns in an attempt to obtain a characterization. For a special family of Reed-Solomon codes - which we identify and name 'class-I codes' - we give a weight-based characterization of the correctable error patterns under list-of-2 decoding. As a tool in this analysis we use the theoretical framework of Sudan's algorithm. The characterization is used in an exact calculation of the probability of transmission error in the symmetric channel when list-of-2 decoding is used. The results from the analysis and complementary simulations for QAM-systems show that a list-of-2 decoding gain of nearly 1 dB can be achieved.</p><p>Further we study Sudan's algorithm for list decoding of Reed-Solomon codes for the special case of the class-I codes. For these codes algorithms are suggested for both the first and second step of Sudan's algorithm. Hardware solutions for both steps based on the derived algorithms are presented.</p>

We study the problem of list decoding with focus on the case when we have a list size limited to two. Under this restriction we derive general lower bounds on the maximum possible size of a list-of-2-decodable code. We study the set of correctable error patterns in an attempt to obtain a characterization. For a special family of Reed-Solomon codes - which we identify and name 'class-I codes' - we give a weight-based characterization of the correctable error patterns under list-of-2 decoding. As a tool in this analysis we use the theoretical framework of Sudan's algorithm. The characterization is used in an exact calculation of the probability of transmission error in the symmetric channel when list-of-2 decoding is used. The results from the analysis and complementary simulations for QAM-systems show that a list-of-2 decoding gain of nearly 1 dB can be achieved. Further we study Sudan's algorithm for list decoding of Reed-Solomon codes for the special case of the class-I codes. For these codes algorithms are suggested for both the first and second step of Sudan's algorithm. Hardware solutions for both steps based on the derived algorithms are presented.

This study investigated the role of an invasive tall cane, Arundo donax L. (Arundo), in the riparian water cycle. Four 100 meter transects were arrayed perpendicular to the lower Rio Grande in southwest Texas. The first objective was to determine the primary water source for Arundo by using naturally occurring stable isotopes. Surface soil, river water, groundwater, precipitation and rhizome samples were collected every month during 2010 and 2011 growing seasons, which coincided with a major flood that saturated soils in the first year followed by extreme drought in the second year. The second objective was to characterize how Arundo water use varied with water availability gradients in the riparian zone. Leaf gas exchange and leaf delta13C were measured along potential moisture gradients. The third objective was to understand the interaction between groundwater and surface water, and whether Arundo water use affected daily groundwater fluctuations. The isotope ratio of rhizome water was consistent with shallow soil moisture uptake and with previous observations of a relatively shallow, fibrous root system. Floodwater from July 2010 persisted in the soil for at least a year despite a severe drought, and became the dominant water source for Arundo during much of the study period. Although the alluvial water table in this floodplain was shallow (< 6 m) and subject to changes in river level, groundwater seemed not to be an important source for Arundo, so long as the soil moisture was sufficient. In this study, Arundo was not found to experience soil moisture limitation, and the spatial variability of Arundo transpiration was not associated with any soil moisture availability gradients. Arundo was found to close its stomata in response to increasing vapor pressure deficit (VPD), causing declining transpiration rate and increasing leaf delta13C composition. Significant exchange between the river and the alluvial groundwater was reflected in the similarity of isotopic compositions and the high correlation between river and groundwater elevations. Cross correlation analysis showed that over 50% of the diurnal groundwater fluctuations were caused by river stage changes. Consistent with the above ecophysiological and stable isotope results, Arundo water use was not found to influence daily groundwater fluctuations.

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In this dissertation, advanced channel decoding techniques based on bit-level soft information are studied. Two main approaches are proposed: bit-level probabilistic iterative decoding and bit-level algebraic soft-decision (list) decoding (ASD). In the first part of the dissertation, we first study iterative decoding for high density parity check (HDPC) codes. An iterative decoding algorithm, which uses the sum product algorithm (SPA) in conjunction with a binary parity check matrix adapted in each decoding iteration according to the bit-level reliabilities is proposed. In contrast to the common belief that iterative decoding is not suitable for HDPC codes, this bit-level reliability based adaptation procedure is critical to the conver-gence behavior of iterative decoding for HDPC codes and it significantly improves the iterative decoding performance of Reed-Solomon (RS) codes, whose parity check matrices are in general not sparse. We also present another iterative decoding scheme for cyclic codes by randomly shifting the bit-level reliability values in each iteration. The random shift based adaptation can also prevent iterative decoding from getting stuck with a significant complexity reduction compared with the reliability based parity check matrix adaptation and still provides reasonable good performance for short-length cyclic codes. In the second part of the dissertation, we investigate ASD for RS codes using bit-level soft information. In particular, we show that by carefully incorporating bit¬level soft information in the multiplicity assignment and the interpolation step, ASD can significantly outperform conventional hard decision decoding (HDD) for RS codes with a very small amount of complexity, even though the kernel of ASD is operating at the symbol-level. More importantly, the performance of the proposed bit-level ASD can be tightly upper bounded for practical high rate RS codes, which is in general not possible for other popular ASD schemes. Bit-level soft-decision decoding (SDD) serves as an efficient way to exploit the potential gain of many classical codes, and also facilitates the corresponding per-formance analysis. The proposed bit-level SDD schemes are potential and feasible alternatives to conventional symbol-level HDD schemes in many communication sys-tems.

Thesis (M.S.)--West Virginia University, 2001. / Title from document title page. Document formatted into pages; contains vi, 68 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 67-68).

Wetland value is threatened by invasive plant species such as Reed Canarygrass (Phalaris arundinacea). Hence the research objectives of this project were to determine if reed canarygrass abundance has an effect on plant species diversity and assess the effectiveness of novel treatments on reed canarygrass control in a constructed wetland. Four treatments (mowing, herbicide, mowing plus herbicide, and a control) followed by broadcast seeding were applied to regulate growth of reed canarygrass. Principal components analysis, biodiversity measures, and ANOVA were used to identify community composition, quantify biodiversity values and identify treatment differences respectively. Results indicated differences in species composition between east and west blocks of the study site, reed canarygrass abundance appears to keep plant species diversity low, indigenous species were rare, and reed canarygrass was resistant to treatments.The results of this study are not surprising considering there is little evidence that treatments for reed canarygrass control are effective.