ABSTRACT Aquifer storage and recovery (ASR) is used world-wide to supplement available water supplies by storing surplus water in aquifers and recovering it during periods of drought and increased demand. The use of ASR as an option for increasing available municipal irrigation and fresh water supplies is threatened as a result of the mobilization of arsenic in some aquifers during ASR. Arsenic is liberated from arsenic-bearing sulfide minerals as a result of the mixing of oxidizing injected water with reducing insitu groundwater. Fracture networks can have significant influence on the migration and distribution of arsenic in the Upper Floridan Aquifer (UFA) during ASR operations through effects on fluid flow, chemical reactions, and transport characteristics. To characterize fracture flow and associated mass transport, numerical three-dimensional models constructed with MODFLOW and FracMan are used to represent fractures in equivalent continuum, discontinuum, and stochastic discontinuum or discrete fracture network (DFN) dual porosity or hybrid models. The geochemical reaction (PHREEQC-2) and transport (MT3DMS) models are coupled to the three dimensional numerical flow model (MODFLOW 2000) as PHT3D- 2003, and utilized to simulate the flow, transport, and inorganic reactions associated with the injection of oxidized water into the UFA of Southwest Florida during ASR cycles. The discrete fractures, implicitly simulated in MODFLOW as high flow zones, are model layers of varying thicknesses with uniform hydraulic conductivity and storage parameters, and as stochastically-generated horizontal and vertical fractures with varying physical attributes including orientation, aperture widths, fracture intensity, and fracture distributions, distributed within a lower conductivity matrix. Discrete fracture networks are simulated with FracMan and the results imported into MODFLOW. Although each fracture zone layer is assigned a unique stochastic distribution of hydraulic conductivity, each model represents a single realization. The FracMan output of stochastic distributions of hydraulic conductance and storage parameters is "upscaled" for use in MODFLOW. The vertical migration of solute due to variations in the density of injectate and groundwater does not appear to be a significant characteristic of the modeled flow system. The modeling results support the hypothesis that arsenopyrite, which is stable under reducing conditions, liberates arsenic during recharge cycles as a result of oxidation. The results also indicate that fracture flow significantly controls the distribution of all solutes affected by the ASR flow system due to the significantly higher transmissivity of the fractures compared to the matrix. The simulated distribution of arsenic in the matrix is significantly less than in the fractures as a result of the limited penetration of oxidized recharge waters into the inter-fracture matrix. Under the simulated aquifer and geochemical conditions, arsenic travels farther from the injection well via fractures than is observed in monitor wells, suggesting that the partially-penetrating monitoring well network does not intercept many of the fractures. The modeled increases in concentrations of arsenic in the ASR wells during the recovery cycles are also consistent with observations. Explicit representation of fracture zones in numerical transport models provides an increased understanding of the flow system and the potential occurrence and distribution of arsenic in groundwater.

Alkali-silica reaction (ASR) and delayed ettringite formation (DEF) are expansive reactions that can lead to the premature deterioration of concrete structures. Both have been implicated in the deterioration of numerous structures around the world, including many transportation structures in Texas. As a result of considerable research advances, ASR and DEF are now avoidable in new construction, but evaluating and managing the existing stock of structures damaged by these mechanisms remains a challenge. While the published guidance for evaluating structures is very effective at diagnosing the presence of ASR and DEF, there remain significant weaknesses with respect to the evaluation of structural safety and serviceability and nondestructive testing (NDT) is a minor component of the evaluation process. The research described in this dissertation involved a wide range of tests on plain and reinforced concrete at multiple scales. This included small cylinders and prisms, larger plain and reinforced concrete specimens in outdoor exposure, full-scale reinforced concrete beams, and core samples from the outdoor exposure specimens and full-scale reinforced concrete beams. Nondestructive test methods were applied at all scales, and the full-scale beams were also tested in four-point flexure to determine the effects of ASR and DEF on flexural strength and serviceability. Severe expansions from ASR and DEF did not reduce the strength of the full-scale beams or result in excessive deflections under live loads, despite significant decreases in the compressive strength and elastic modulus measured from core samples. Most NDT methods were found to be effective at low expansions but had difficulty correlating to larger expansions. Two promising NDT methods have been identified for future research and development, and guidance regarding existing test methods is offered. / text

Alkali Silica Reaction (ASR) is a deleterious, expansive reaction in concrete. Several ASTM methods test potential aggregates for ASR risk. One method uses NaOH digestion, followed by spectroscopic methods, to estimate the amount of reactive silica present in an aggregate. NaOH, however, can digest both crystalline (i.e. quartz) and non-crystalline (e.g. opal), or poorly crystalline silica, potentially yielding falsely high estimates of reactive silica. Studies in soil and plant sciences have used Tiron, an alkaline chelating agent (C6H4S2O8Na2), as a method of digesting opaline silica for spectroscopic analysis. Here we test this approach by analyzing reactive silica in road aggregate. Tiron extraction of reactive silica is more selective, in some cases extracting only ~ 30% of the silica compared to the harsher NaOH extraction: variation is due to differences in aggregate mineralogy, specifically SiO2. In conducting chelation analyses, UV/VIS seems to be a better approach than AA.

Šis darbas yra apie įrenginį, kuris siaurina garsinio signalo dinaminį diapazoną. Darbe lyginami automatinio stiprinimo reguliavimo metodai, bei jų taikymai pramoniniuose garso kompresoriuose. Ieškoma būdų šiuos įrenginius patobulinti. / This article is about apparatus that intentionally reduces the dynamic range of audio signals. The goal is to compare methods of automatic gain reduction, talk their implementation in industry standard hardware compressors and look for possible circuit modifications.

Aquifer storage and recovery (ASR) is a particular scheme of artificial recharge of groundwater by injecting fresh water into aquifers and subsequently recovering the stored water during times of peak demand or extended drought. In the era of combating climate change, ASR, as an effective means for water reuse and sustainable management of water resources in concert with the natural environment, represents a huge opportunity for climate change adaptation to mitigate water availability stress.The success of an ASR scheme is quantified by the recovery efficiency (RE), defined as the volume of stored water that can be recovered for supply purposes divided by the total volume injected. It is not uncommon that RE may be significantly lower than 100% because of the water quality changes as a consequence of the mixing between the injected water and native groundwater and the interaction between injected water and soil. Thus, the key of a successful ASR scheme is (1) to select appropriate aquifers and (2) to design optimal operational processes to build up a bubble of injected water with minimized negative impact from such mixing and interaction. To achieve this, this thesis develops an integrated knowledge base with sound interdisciplinary science and understanding of the mixing processes under operational ASR management in aquifers with various hydrogeological conditions. Analytical and numerical modeling are conducted to improve the scientific understanding of mixing processes involved in ASR schemes and to provide specific technical guidance for improving ASR efficiency under complex hydrogeological conditions. (1) An efficient approach is developed to analytically evaluate solute transport in a horizontal radial flow field with a multistep pumping and examine the ASR performance in homogeneous, isotropic aquifer with advective and dispersive transport processes. (2) Numerical and analytical studies are conducted to investigate the efficiency of an ASR system in dual-domain aquifers with mass transfer limitations under various hydrogeological and operational conditions. Simple and effective relationships between transport parameters and ASR operational parameters are derived to quantify the effectiveness and ascertain the potential of ASR systems with mass transfer limitations.(3) Effects of hydrogeological and operational parameters on ASR efficiency are assessed in homogeneous/stratified, isotropic/anisotropic coastal aquifers. Effects of transverse dispersion are particularly investigated in such aquifers.(4) Finally, we test and study an innovative ASR scheme for improving the RE in brackish aquifers: injection through a fully-penetrated well and recovery through a partially-penetrated well.

Grapheme-based speech recognition systems are faster to develop, but typically do not reach the same level of performance as phoneme-based systems. Using Afrikaans speech recognition as a case study, we first analyse the reasons for the discrepancy in performance, before introducing a technique for improving the performance of standard grapheme-based systems. It is found that by handling a relatively small number of irregular words through phoneme-to-grapheme (P2G) transliteration – transforming the original orthography of irregular words to an ‘idealised’ orthography – grapheme-based accuracy can be improved. An analysis of speech recognition accuracy based on word categories shows that P2G transliteration succeeds in improving certain word categories in which grapheme-based systems typically perform poorly, and that the problematic categories can be identified prior to system development. An evaluation is offered of when category-based P2G transliteration is beneficial and methods to implement the technique in practice are discussed. Comparative results are obtained for a second language (Vietnamese) in order to determine whether the technique can be generalised. / MSc (Computer Science) North-West University, Vaal Triangle Campus, 2014

The languages spoken in developing countries are diverse and most are currently under-resourced from an automatic speech recognition (ASR) perspective. In South Africa alone, 10 of the 11 official languages belong to this category. Given the potential for future applications of speech-based information systems such as spoken dialog system (SDSs) in these countries, the design of minimal ASR audio corpora is an important research area. Specifically, current ASR systems utilise acoustic models to represent acoustic variability, and effective ASR corpus design aims to optimise the amount of relevant variation within training data while minimising the size of the corpus. Therefore an investigation of the effect that different amounts and types of training data have on these models is needed. With this dissertation specific consideration is given to the data sufficiency principals that apply to the training of acoustic models. The investigation of this task lead to the following main achievements: 1) We define a new stability measurement protocol that provides the capability to view the variability of ASR training data. 2) This protocol allows for the investigation of the effect that various acoustic model complexities and ASR normalisation techniques have on ASR training data requirements. Specific trends with regard to the data requirements for different phone categories and how these are affected by various modelling strategies are observed. 3) Based on this analysis acoustic distances between phones are estimated across language borders, paving the way for further research in cross-language data sharing. Finally the knowledge obtained from these experiments is applied to perform a data sufficiency analysis of a new speech recognition corpus of South African languages: The Lwazi ASR corpus. The findings correlate well with initial phone recognition results and yield insight into the sufficient number of speakers required for the development of minimal telephone ASR corpora. / Thesis (M. Ing. (Computer and Electronical Engineering))--North-West University, Potchefstroom Campus, 2009.

The languages spoken in developing countries are diverse and most are currently under-resourced from an automatic speech recognition (ASR) perspective. In South Africa alone, 10 of the 11 official languages belong to this category. Given the potential for future applications of speech-based information systems such as spoken dialog system (SDSs) in these countries, the design of minimal ASR audio corpora is an important research area. Specifically, current ASR systems utilise acoustic models to represent acoustic variability, and effective ASR corpus design aims to optimise the amount of relevant variation within training data while minimising the size of the corpus. Therefore an investigation of the effect that different amounts and types of training data have on these models is needed. With this dissertation specific consideration is given to the data sufficiency principals that apply to the training of acoustic models. The investigation of this task lead to the following main achievements: 1) We define a new stability measurement protocol that provides the capability to view the variability of ASR training data. 2) This protocol allows for the investigation of the effect that various acoustic model complexities and ASR normalisation techniques have on ASR training data requirements. Specific trends with regard to the data requirements for different phone categories and how these are affected by various modelling strategies are observed. 3) Based on this analysis acoustic distances between phones are estimated across language borders, paving the way for further research in cross-language data sharing. Finally the knowledge obtained from these experiments is applied to perform a data sufficiency analysis of a new speech recognition corpus of South African languages: The Lwazi ASR corpus. The findings correlate well with initial phone recognition results and yield insight into the sufficient number of speakers required for the development of minimal telephone ASR corpora. / Thesis (M. Ing. (Computer and Electronical Engineering))--North-West University, Potchefstroom Campus, 2009.

While significant progress has been made in automatic speech recognition (ASR) during the last few decades, recognizing and understanding unconstrained conversational speech remains a challenging problem. In this dissertation, five methods/systems are proposed towards a robust conversational speech recognition and understanding system. I. A non-uniform minimum classification error (MCE) approach is proposed which can achieve consistent and significant keyword spotting performance gains on both English and Mandarin large-scale spontaneous conversational speech tasks (Switchboard and HKUST Mandarin CTS). II. A hybrid recurrent DNN-HMM system is proposed for robust acoustic modeling and a new way of backpropagation through time (BPTT) is introduced. The proposed system achieves state-of-the-art performances on two benchmark datasets, the 2nd CHiME challenge (track 2) and Aurora-4, without front-end preprocessing, speaker adaptive training or multiple decoding passes. III. To study the specific case of conversational speech recognition in the presence of competing talkers, several multi-style training setups of DNNs are investigated and a joint decoder operating on multi-talker speech is introduced. The proposed combined system improves upon the previous state-of-the-art IBM superhuman system by 2.8% absolute on the 2006 speech separation challenge dataset. IV. Latent semantic rational kernels (LSRKs) are proposed for spotting the semantic notions on conversational speech. The proposed framework is generalized using tf-idf weighting, latent semantic analysis, WordNet, probabilistic topic models and neural network learned representations and is shown to achieve substantial topic spotting performance gains on two conversational speech tasks, Switchboard and AT&T HMIHY initial collection. V. Non-uniform sequential discriminative training (DT) of DNNs with LSRKs is proposed which directly links the information of the proposed LSRK framework to the objective function of the DT. The experimental results on the subset of Switchboard show the proposed method can lead the acoustic modeling to a more robust system with respect to the semantic decoder.

Um dos graves obstáculos para a manutenção e estabilidade da produção nacional de arroz (Oryza sativa) reside na susceptibilidade dos genótipos existentes a estresses abióticos. Tendo em vista a importância social e econômica do arroz e os efeitos extremamente danosos desses estresses sobre a agricultura, o conhecimento detalhado das interações entre os estresses abióticos e as respostas dos vegetais frente a esses estímulos ambientais faz-se necessário. O alumínio (Al) é considerado um dos principais fatores limitantes na produção agrícola, inibindo o crescimento das raízes e a absorção de minerais. A toxicidade do Al em plantas ocorre pela sua solubilização em solos com pH baixo ou solos ácidos. Os genes ASR (ABA, Stress and Ripening) são induzidos por estresse e ácido abscísico (ABA) em plantas, e seus níveis de expressão são rapidamente aumentados em resposta à salinidade e seca. Recentemente, foi demonstrado que o gene que codifica a proteína ASR5 é responsivo ao Al em raízes de arroz. Apesar do arroz ser considerado um dos cereais mais resistentes a Al, os mecanismos básicos de tolerância a este metal são pouco conhecidos no arroz em comparação a outros cereais. Por meio do presente trabalho objetivamos: i) a caracterização funcional dos membros da família gênica ASR de arroz em reposta ao Al; e ii) a construção de vetores binários de transformação de plantas visando o estudo da localização subcelular da proteína codificada pelo gene OsASR5, e o silenciamento gênico da família ASR de arroz. As análises dos transcritos por qRT-PCR mostraram que todos os genes da família ASR de arroz ssp Japonica respondem ao Al. Por outro lado, OsASR5 não sofre modulação de sua expressão em resposta ao Al em raízes de arroz ssp Indica. Essas diferenças de respostas dos genes OsASR5 em distintas variedades pode refletir diferenças no grau de tolerância ao Al de cada um desses genótipos. / One of the major obstacles to maintain the stability of the national production of rice (Oryza sativa) lies on the susceptibility of the different genotypes to abiotic stress. In view of the social and economic importance of rice and due to the extremely harmful effects of stress in agriculture, detailed knowledge of the interactions between these stresses and plant responses to environmental stimuli is necessary. Aluminum (Al) is considered one of the main limitation factors for agricultural productivity, inhibiting root growth and mineral absorption. Al toxicity occurs by its solubilization in soils with low pH or acid soils. The ASR (ABA, Stress and Ripening) genes are induced by stress and abscisic acid (ABA) in plants, and their expression levels are quickly increased in response to salinity and drought. Recently, it was demonstrated that the ASR5 gene is responsive to Al in rice roots. Despite the fact that rice is considered one of the most resistant crops to Al, the basic mechanisms of tolerance to this metal are poorly known when compared to other crops. This study aimed the functional characterization of the gene expression of rice ASR family members in response to Al, and the construction of binary vectors for the subcellular localization of the protein codified by the OsASR5 gene, and the construction of a gene silencing binary vector for the ASR family. Analyses of transcripts by qRT-PCR showed that in the ssp Japonica, all ASR genes responded to Al. In contrast, OsASR5 do not suffer expression modulation in response to Al in rice roots of ssp Indica. These differences in response of the OsASR5 gene in distinct varieties may reflect differences in the degree of Al tolerance in each genotype.