Matched case-control study evaluating the frequency of the main agents associated with neonatal diarrhea in piglets

A case-control study was carried out in litters of 1 to 7-day-old piglets to identify the main infectious agents involved with neonatal diarrhea in pigs. Fecal samples (n=276) from piglets were collected on pig farms in the State of Rio Grande do Sul, Brazil, from May to September 2007. Litters with diarrhea were considered cases (n=129) and normal litters (n=147) controls. The samples were examined by latex agglutination test, PAGE, conventional isolating techniques, ELISA, PCR, and microscopic methods in order to detect rotavirus, bacterial pathogens (Escherichia coli, Clostridium perfringens type A and C, and Clostridium difficile), and parasites (Coccidian and Cryptosporidium spp.). Outbreaks of diarrhea were not observed during sampling. At least one agent was detected in fecal samples on 25 out of 28 farms (89.3%) and in 16 farms (57.1%) more than one agent was found. The main agents diagnosed were Coccidia (42.86%) and rotavirus (39.29%). The main agents identified in litters with diarrhea were Clostridium difficile (10.6%), Clostridium perfringens type A (8.8%) and rotavirus (7.5%); in control litters, Clostridium difficile (16.6%) and Coccidian (8.5%). Beta hemolytic Escherichia coli and Clostridium perfringens type C were not detected. When compared with controls, no agent was significantly associated with diarrhea in case litters. These findings stress the need for caution in the interpretation of laboratorial diagnosis of mild diarrhea in neonatal pigs, as the sole detection of an agent does not necessarily indicate that it is the cause of the problem.

Detection of renal dysfunction based on serum creatinine levels in a Brazilian community: the Bambuí Health and Ageing Study

There are few population-based studies of renal dysfunction and none conducted in developing countries. In the present study the prevalence and predictors of elevated serum creatinine levels (SCr > or = 1.3 mg/dl for men and 1.1 mg/dl for women) were determined among Brazilian adults (18-59 years) and older adults (>60 years). Participants included all older adults (N = 1742) and a probabilistic sample of adults (N = 818) from Bambuí town, MG, Southeast Brazil. Predictors were investigated using multiple logistic regression. Mean SCr levels were 0.77 ± 0.15 mg/dl for adults, 1.02 ± 0.39 mg/dl for older men, and 0.81 ± 0.17 mg/dl for older women. Because there were only 4 cases (0.48%) with elevated SCr levels among adults, the analysis of elevated SCr levels was restricted to older adults. The overall prevalence of elevated SCr levels among the elderly was 5.09% (76/1494). The prevalence of hypercreatinemia increased significantly with age (chi² = 26.17, P = 0.000), being higher for older men (8.19%) than for older women (5.29%, chi² = 5.00, P = 0.02). Elevated SCr levels were associated with age 70-79 years (odds ratio [OR] = 2.25, 95% confidence interval [CI]: 1.15-4.42), hypertension (OR = 3.04, 95% CI: 1.34-6.92), use of antihypertensive drugs (OR = 2.46, 95% CI: 1.26-4.82), chest pain (OR = 3.37, 95% CI: 1.31-8.74), and claudication (OR = 3.43, 95% CI: 1.30-9.09) among men, and with age >80 years (OR = 4.88, 95% CI: 2.24-10.65), use of antihypertensive drugs (OR = 4.06, 95% CI: 1.67-9.86), physical inactivity (OR = 2.11, 95% CI: 1.11-4.02) and myocardial infarction (OR = 3.89, 95% CI: 1.58-9.62) among women. The prevalence of renal dysfunction observed was much lower than that reported in other population-based studies, but predictors were similar. New investigations are needed to confirm the variability in prevalence and associated factors of renal dysfunction among populations.

The problem of national integration in plural societies : a case study of Pakistan, 1947-71 /|nMuhammed A. Quddus. -- 260 St. Catharines [Ont. : s. n.],

Pakistan had a plural society per excellence. Its people were divided geographically between two separate regions, spoke different languages, had different cultures and economic structures. Like other plural societies elsewhere, Pakistan also faced the problem of national integration. Cleavages along the lines of traditional attachments are fundamental to any plural society, as they were in Pakistan. But their political manifestation could have been kept within managable limits if the Central Government, overwhelmingly composed of the West Pakistanis, was seriously committed to the task. All that Pakistan needed to maintain her integrated existence was deliberate, calculated and conscious efforts on the part of the Central Government to give the Bengalis, the majority linguistic and geographic group in the country, a partnership in the state of Pakistan, an effective power in the decision-making process of the country, a reasonable share from the economic resources of the country, and to show respect to their hopes and aspirations. In addition, Pakistan needed a national platform to bring her divergent linguistic and geographic groups toge~her for some common, national purpos~s. Political parties were the only institutions which could have served this purpose. Pakistan miserably failed to sustain national political parties and failed to satisfy Bengalis' demands. This failure eventually resulted in the falling apart of the political system of Pakistan in 1971.

An exploratory study for the discovery of non-invasive hepatocellular carcinoma biomarkers among high-risk hepatitis C virus infected patients

Hepatocellular Carcinoma (HCC) is a major healthcare problem, representing the third most common cause of cancer-related mortality worldwide. Chronic infections with Hepatitis B virus (HBV) and/or Hepatitis C virus (HCV) are the major risk factors for the development of HCC. The incidence of HBV -associated HCC is in decline as a result of an effective HBV vaccine; however, since an equally effective HCV vaccine has not yet been developed, there are 130 million HCV infected patients worldwide who are at a high-risk for developing HCC. Because reliable parameters and/or tools for the early detection of HCC among high-risk individuals are severely lacking, HCC patients are always diagnosed at a late stage where surgical solutions or effective treatment are not possible. Using urine as a non-invasive sample source, two different approaches (proteomic-based and genomic-based approaches) were pursued with the common goal of discovering potential biomarker candidates for the early detection of HCC among high-risk chronic HCV infected patients. Urine was collected from 106 HCV infected Egyptian patients, 32 of whom had already developed HCC and 74 patients who were diagnosed as HCC-free at the time of initial sample collection. In addition to these patients, urine samples were also collected from 12 healthy control individuals. Total urinary proteins, Trans-renal nucleic acid (Tr-NA) and microRNA (miRNA) were isolated from urine using novel methodologies and silicon carbide-loaded spin columns. In the first, "proteomic-based", approach, liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) was used to identify potential candidates from pooled urine samples. This was followed by validating relative expression levels of proteins present in urine among all the patients using quantitative real time-PCR (qRT-PCR). This approach revealed that significant over-expression of three proteins: DJ-1, Chromatin Assembly Factor-1 (CAF-1) and 11 Moemen Abdalla HCC Biomarkers Heat Shock Protein 60 (HSP60), were characteristic events among HCC-post HCV infected patients. As a single-based HCC biomarker, CAF-1 over-expression identified HCC among HCV infected patients with a specificity of 90%, sensitivity of 66% and with an overall diagnostic accuracy of 78%. Moreover, the CAF-lIHSP60 tandem identified HCC among HCV infected patients with a specificity of 92%, sensitivity of 61 % and with an overall diagnostic accuracy of 77%. In the second genomic-based approach, two different approaches were processed. The first approach was the miRNA-based approach. The expression levels of miRNAs isolated from urine were studied using the Illumina MicroRNA Expression Profiling Assay. This was followed by qRT-PCR-based validation of deregulated expression of identified miRNA candidates among all the patients. This approach shed the light on the deregulated expression of a number of miRNAs, which may have a role in either the development of HCC among HCV infected patients (i.e. miR-640, miR-765, miR-200a, miR-521 and miR-520) or may allow for a better understanding of the viral-host interaction (miR-152, miR-486, miR-219, miR452, miR-425, miR-154 and miR-31). Moreover, the deregulated expression of both miR-618 and miR-650 appeared to be a common event among HCC-post HCV infected patients. The results of the search for putative targets of these two miRNA suggested that miR-618 may be a potent oncogene, as it targets the tumor-suppressor gene Low density lipoprotein-related protein 12 (LPR12), while miR-650 may be a potent tumor-suppressor gene, as it is supposed to downregulate the TNF receptor-associated factor-4 (TRAF4) oncogene. The specificity of miR-618 and miR-650 deregulated expression patterns for the early detection of HCC among HCV infected patients was 68% and 58%, respectively, whereas the sensitivity was 64% and 72%, respectively. When the deregulated expression of both miRNAs was combined as a tandem biomarker, the specificity and the sensitivity were 75% and 58% respectively. 111 Moemen Abdalla HCC Biomarkers In the second, "Trans-renal nucleic acid-based", approach, the urinary apoptotic nucleic acid (uaNA) levels of 70ng/mL or more were found to be a good predictor of HCC among chronic HCV infected patients. The specificity and the sensitivity of this diagnostic approach were 76% and 86%, respectively, with an overall diagnostic value of 81 %. The uaNA levels positively correlated to HCC disease progression as monitored by epigenetic changes of a panel of eight tumor-suppressor genes (TSGs) using methylation-sensitive PCR. Moreover, the pairing of high uaNA levels (:::: 70 ng/mL) and CAF-1 over-expreSSIOn produced a highly specific (l 00%) multiple-based HCC biomarker with an acceptable sensitivity of 64%, and with a diagnostic accuracy of 82%. In comparison to the previous pairing, the uaNA levels (:::: 70 ng/mL) in tandem with HSP60 over-expression was less specific (89%) but highly sensitive (72%), resulting in a diagnostic accuracy of 64%. The specificities of miR-650 deregulated expression in combination with either high uaNA content or HSP 60 over-expression were 82% and 79%, respectively, whereas, the sensitivities of these combinations were 64% and 58%, respectively. The potential biomarkers identified in this study compare favorably with the diagnostic accuracy of the a-fetoprotein levels test, which has a specificity of 75%, sensitivity of 68% and an overall diagnostic accuracy of 70%. Here we present an intriguing study which shows the significance of using urine as a noninvasive sample source for the identification of promising HCC biomarkers. We have also introduced new techniques for the isolation of different urinary macromolecules, especially miRNA, from urine. Furthermore, we strongly recommend the potential biomarkers indentified in this study as focal points of any future research on HCC diagnosis. A larger testing pool will determine if their use is practical for mass population screening. This explorative study identified potential targets that merit further investigation for the development of diagnostically accurate biomarkers isolated from 1-2 mL urine samples that were acquired in a non-invasive manner.

Heuristics for the Critical Node Detection Problem in Large Complex Networks

Complex networks have recently attracted a significant amount of research attention due to their ability to model real world phenomena. One important problem often encountered is to limit diffusive processes spread over the network, for example mitigating pandemic disease or computer virus spread. A number of problem formulations have been proposed that aim to solve such problems based on desired network characteristics, such as maintaining the largest network component after node removal. The recently formulated critical node detection problem aims to remove a small subset of vertices from the network such that the residual network has minimum pairwise connectivity. Unfortunately, the problem is NP-hard and also the number of constraints is cubic in number of vertices, making very large scale problems impossible to solve with traditional mathematical programming techniques. Even many approximation algorithm strategies such as dynamic programming, evolutionary algorithms, etc. all are unusable for networks that contain thousands to millions of vertices. A computationally efficient and simple approach is required in such circumstances, but none currently exist. In this thesis, such an algorithm is proposed. The methodology is based on a depth-first search traversal of the network, and a specially designed ranking function that considers information local to each vertex. Due to the variety of network structures, a number of characteristics must be taken into consideration and combined into a single rank that measures the utility of removing each vertex. Since removing a vertex in sequential fashion impacts the network structure, an efficient post-processing algorithm is also proposed to quickly re-rank vertices. Experiments on a range of common complex network models with varying number of vertices are considered, in addition to real world networks. The proposed algorithm, DFSH, is shown to be highly competitive and often outperforms existing strategies such as Google PageRank for minimizing pairwise connectivity.

Development and use of a multiplex real-time quantitative polymerase chain reaction assay for detection and differentiation of Porcine circovirus-2 genotypes 2a and 2b in an epidemiological survey.

By the end of 2004, the Canadian swine population had experienced a severe 2 increase in the incidence of Porcine circovirus-associated disease (PCVAD), a problem that was 3 associated with the emergence of a new Porcine circovirus-2 genotype (PCV-2b), previously 4 unrecovered in North America. Thus it became important to develop a diagnostic tool that could 5 differentiate between the old and new circulating genotypes (PCV-2a and -2b, respectively). 6 Consequently, a multiplex real-time quantitative polymerase chain reaction (mrtqPCR) assay that 7 could sensitively and specifically identify and differentiate PCV-2 genotypes was developed. A 8 retrospective epidemiological survey that used the mrtqPCR assay was performed to determine if 9 cofactors could affect the risk of PCVAD. From 121 PCV-2–positive cases gathered for this 10 study, 4.13%, 92.56% and 3.31% were positive for PCV-2a, PCV-2b, and both genotypes, 11 respectively. In a data analysis using univariate logistic regressions, PCVAD compatible 12 (PCVAD/c) score was significantly associated with the presence of Porcine reproductive and 13 respiratory syndrome virus (PRRSV), PRRSV viral load, PCV-2 viral load, and PCV-2 14 immunohistochemistry (IHC) results. Polytomous logistic regression analysis revealed that 15 PCVAD/c score was affected by PCV-2 viral load (P = 0.0161) and IHC (P = 0.0128), but not by 16 the PRRSV variables (P > 0.9); suggesting that mrtqPCR in tissue is a reliable alternative to IHC. 17 Logistic regression analyses revealed that PCV-2 increased the odds ratio of isolating 2 major 18 swine pathogens of the respiratory tract, Actinobacillus pleuropneumoniae and Streptococcus 19 suis serotypes 1/2, 1, 2, 3, 4, and 7, which are serotypes commonly associated with clinical 20 diseases.

A heuristic algorithm for the Capacitated Vehicle Routing Problem with Synchronized Pick-ups and Drop-offs : a case study for medications delivery and supervision in DR Congo

Dans des contextes de post-urgence tels que le vit la partie occidentale de la République Démocratique du Congo (RDC), l’un des défis cruciaux auxquels font face les hôpitaux ruraux est de maintenir un niveau de médicaments essentiels dans la pharmacie. Sans ces médicaments pour traiter les maladies graves, l’impact sur la santé de la population est significatif. Les hôpitaux encourent également des pertes financières dues à la péremption lorsque trop de médicaments sont commandés. De plus, les coûts du transport des médicaments ainsi que du superviseur sont très élevés pour les hôpitaux isolés ; les coûts du transport peuvent à eux seuls dépasser ceux des médicaments. En utilisant la province du Bandundu, RDC pour une étude de cas, notre recherche tente de déterminer la faisabilité (en termes et de la complexité du problème et des économies potentielles) d’un problème de routage synchronisé pour la livraison de médicaments et pour les visites de supervision. Nous proposons une formulation du problème de tournées de véhicules avec capacité limitée qui gère plusieurs exigences nouvelles, soit la synchronisation des activités, la préséance et deux fréquences d’activités. Nous mettons en œuvre une heuristique « cluster first, route second » avec une base de données géospatiales qui permet de résoudre le problème. Nous présentons également un outil Internet qui permet de visualiser les solutions sur des cartes. Les résultats préliminaires de notre étude suggèrent qu’une solution synchronisée pourrait offrir la possibilité aux hôpitaux ruraux d’augmenter l’accessibilité des services médicaux aux populations rurales avec une augmentation modique du coût de transport actuel.

Development of Free Space Method for Material Characterisation and GPR Study & A Case Study on Biological Samples

The thesis mainly focuses on material characterization in different environments: freely available samples taken in planar fonn, biological samples available in small quantities and buried objects.Free space method, finds many applications in the fields of industry, medicine and communication. As it is a non-contact method, it can be employed for monitoring the electrical properties of materials moving through a conveyor belt in real time. Also, measurement on such systems at high temperature is possible. NID theory can be applied to the characterization of thin films. Dielectric properties of thin films deposited on any dielectric substrate can be determined. ln chemical industry, the stages of a chemical reaction can be monitored online. Online monitoring will be more efficient as it saves time and avoids risk of sample collection.Dielectric contrast is one of the main factors, which decides the detectability of a system. lt could be noted that the two dielectric objects of same dielectric constant 3.2 (s, of plastic mine) placed in a medium of dielectric constant 2.56 (er of sand) could even be detected employing the time domain analysis of the reflected signal. This type of detection finds strategic importance as it provides solution to the problem of clearance of non-metallic mines. The demining of these mines using the conventional techniques had been proved futile. The studies on the detection of voids and leakage in pipes find many applications.The determined electrical properties of tissues can be used for numerical modeling of cells, microwave imaging, SAR test etc. All these techniques need the accurate determination of dielectric constant. ln the modem world, the use of cellular and other wireless communication systems is booming up. At the same time people are concemed about the hazardous effects of microwaves on living cells. The effect is usually studied on human phantom models. The construction of the models requires the knowledge of the dielectric parameters of the various body tissues. lt is in this context that the present study gains significance. The case study on biological samples shows that the properties of normal and infected body tissues are different. Even though the change in the dielectric properties of infected samples from that of normal one may not be a clear evidence of an ailment, it is an indication of some disorder.ln medical field, the free space method may be adapted for imaging the biological samples. This method can also be used in wireless technology. Evaluation of electrical properties and attenuation of obstacles in the path of RF waves can be done using free waves. An intelligent system for controlling the power output or frequency depending on the feed back values of the attenuation may be developed.The simulation employed in GPR can be extended for the exploration of the effects due to the factors such as the different proportion of water content in the soil, the level and roughness of the soil etc on the reflected signal. This may find applications in geological explorations. ln the detection of mines, a state-of-the art technique for scanning and imaging an active mine field can be developed using GPR. The probing antenna can be attached to a robotic arm capable of three degrees of rotation and the whole detecting system can be housed in a military vehicle. In industry, a system based on the GPR principle can be developed for monitoring liquid or gas through a pipe, as pipe with and without the sample gives different reflection responses. lt may also be implemented for the online monitoring of different stages of extraction and purification of crude petroleum in a plant.Since biological samples show fluctuation in the dielectric nature with time and other physiological conditions, more investigation in this direction should be done. The infected cells at various stages of advancement and the normal cells should be analysed. The results from these comparative studies can be utilized for the detection of the onset of such diseases. Studying the properties of infected tissues at different stages, the threshold of detectability of infected cells can be determined.

Development of semiconductor metal oxide gas sensors for the detection of NO2 and H2S gases

One of the main challenges in the development of metal-oxide gas sensors is enhancement of selectivity to a particular gas. Currently, two general approaches exist for enhancing the selective properties of sensors. The first one is aimed at preparing a material that is specifically sensitive to one compound and has low or zero cross-sensitivity to other compounds that may be present in the working atmosphere. To do this, the optimal temperature, doping elements, and their concentrations are investigated. Nonetheless, it is usually very difficult to achieve an absolutely selective metal oxide gas sensor in practice. Another approach is based on the preparation of materials for discrimination between several analyte in a mixture. It is impossible to do this by using one sensor signal. Therefore, it is usually done either by modulation of sensor temperature or by using sensor arrays. The present work focus on the characterization of n-type semiconducting metal oxides like Tungsten oxide (WO3), Zinc Oxide (ZnO) and Indium oxide (In2O3) for the gas sensing purpose. For the purpose of gas sensing thick as well as thin films were fabricated. Two different gases, NO2 and H2S gases were selected in order to study the gas sensing behaviour of these metal oxides. To study the problem associated with selectivity the metal oxides were doped with metals and the gas sensing characteristics were investigated. The present thesis is entitled “Development of semiconductor metal oxide gas sensors for the detection of NO2 and H2S gases” and consists of six chapters.

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.

Employment Realm in Technical Education in Kerala-A Study on the Problem of Unemployment among Engineers

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Problem-based learning and legal education : a case study in integrated experiential study

Resumen basado en el de la publicaci??n

Time misalignments in fault detection and diagnosis

El desalineamiento temporal es la incorrespondencia de dos señales debido a una distorsión en el eje temporal. La Detección y Diagnóstico de Fallas (Fault Detection and Diagnosis-FDD) permite la detección, el diagnóstico y la corrección de fallos en un proceso. La metodología usada en FDD está dividida en dos categorías: técnicas basadas en modelos y no basadas en modelos. Esta tesis doctoral trata sobre el estudio del efecto del desalineamiento temporal en FDD. Nuestra atención se enfoca en el análisis y el diseño de sistemas FDD en caso de problemas de comunicación de datos, como retardos y pérdidas. Se proponen dos técnicas para reducir estos problemas: una basada en programación dinámica y la otra en optimización. Los métodos propuestos han sido validados sobre diferentes sistemas dinámicos: control de posición de un motor de corriente continua, una planta de laboratorio y un problema de sistemas eléctricos conocido como hueco de tensión.