Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

Evolution and conservation of immunological activity

Paraphrasing what Gregory Bateson says on evolution, we might say that: "Immunology has long been badly taught. In particular, students - and even professional immunologists - acquire theories of immunological activity without any deep understanding of what problems these theories attempt to solve."

Classification and hearing evolution of patients with sudden sensorineural hearing loss

The aim of this study was to analyze clinical aspects, hearing evolution and efficacy of clinical treatment of patients with sudden sensorineural hearing loss (SSNHL). This was a prospective clinical study of 136 consecutive patients with SSNHL divided into three groups after diagnostic evaluation: patients with defined etiology (DE, N = 13, 10%), concurrent diseases (CD, N = 63, 46.04%) and idiopathic sudden sensorineural hearing loss (ISSHL, N = 60, 43.9%). Initial treatment consisted of prednisone and pentoxifylline. Clinical aspects and hearing evolution for up to 6 months were evaluated. Group CD comprised 73% of patients with metabolic decompensation in the initial evaluation and was significantly older (53.80 years) than groups DE (41.93 years) and ISSHL (39.13 years). Comparison of the mean initial and final hearing loss of the three groups revealed a significant hearing improvement for group CD (P = 0.001) and group ISSHL (P = 0.001). Group DE did not present a significant difference in thresholds. The clinical classification for SSNHL allows the identification of significant differences regarding age, initial and final hearing impairment and likelihood of response to therapy. Elevated age and presence of coexisting disease were associated with a greater initial hearing impact and poorer hearing recovery after 6 months. Patients with defined etiology presented a much more limited response to therapy. The occurrence of decompensated metabolic and cardiovascular diseases and the possibility of first manifestation of auto-immune disease and cerebello-pontine angle tumors justify an adequate protocol for investigation of SSNHL.

Comparison of I-FISH and G-banding for the detection of chromosomal abnormalities during the evolution of myelodysplastic syndrome

Myelodysplastic syndrome (MDS) patients with a normal karyotype constitute a heterogeneous group from a biological standpoint and their outcome is often unpredictable. Interphase fluorescence in situ hybridization (I-FISH) studies could increase the rate of detection of abnormalities, but previous reports in the literature have been contradictory. We performed I-FISH and conventional karyotyping (G-banding) on 50 MDS patients at diagnosis, after 6 and 12 months or at any time if a transformation to acute myeloid leukemia (AML) was detected. Applying a probe-panel targeting the centromere of chromosomes 7 and 8, 5q31, 5p15.2 and 7q31, we observed one case with 5q deletion not identified by G-banding. I-FISH at 6 and 12 months confirmed the karyotype results. Eight cases transformed to AML during follow-up, but no hidden clone was detected by I-FISH in any of them. The inclusion of I-FISH during follow-up of MDS resulted in a small improvement in abnormality detection when compared with conventional G-banding.

Hydration kinetics, physicochemical composition, and textural changes of transgenic corn kernels of flint, semi-flint, and dent varieties

The hydration kinetics of transgenic corn types flint DKB 245PRO, semi-flint DKB 390PRO, and dent DKB 240PRO was studied at temperatures of 30, 40, 50, and 67 °C. The concentrated parameters model was used, and it fits the experimental data well for all three cultivars. The chemical composition of the corn kernels was also evaluated. The corn cultivar influenced the initial rate of absorption and the water equilibrium concentration, and the dent corn absorbed more water than the other cultivars at the four temperatures analyzed. The effect of hydration on the kernel texture was also studied, and it was observed that there was no significant difference in the deformation force required for all three corn types analyzed with longer hydration period.

Characterization of commercial cooked hams according to physicochemical, sensory, and textural parameters using chemometrics

Cooked ham is considered a high-value product due to the quality of its raw material. Although its consumption is still low in Brazil, it is increasing due to the rising purchasing power of sectors of the population. This study aimed to assess the microbiological, physicochemical, rheological, and sensory quality of cooked hams (n=11) marketed in Brazil. All samples showed microbiological results within the standards established by Brazilian legislation. Eight of the eleven samples studied met all the legal requirements; two samples violated the standards due to the addition of starch; one sample had lower protein content than the minimum required, and another one had sodium content higher than that stated on the label. The use of Hierarchical Cluster Analysis allowed the agglomeration of the samples into three groups with distinct quality traits and with significant differences in moisture content, chromaticity, syneresis, and heating and freezing loss. Principal Component Analysis showed that the samples which correlated to higher sensory acceptance regarding flavor and overall acceptability were those with higher moisture, protein, fat, and luminosity values. This study confirmed the efficacy of multivariate statistical techniques in assessing the quality of commercial cooked hams and in indicating the physicochemical parameters associated with the perception of product quality.

Effect of huitlacoche (Ustilago maydis DC Corda) paste addition on functional, chemical and textural properties of tortilla chips

AbstractThis study analyzed the addition of huitlacoche paste (HP) in baked tortilla chips (TC), evaluating its effects on functional, physicochemical and structural changes during processing. Two blue corn grains were nixtamalized, stone milled, air dried and milled to obtain flour; commercial blue corn flour (TM1) and commercial TC (TM2) were used as controls. Additions of 0, 3, 6 and 9% of HP were formulated; masas were prepared at 55% moisture content (MC), precooked and baked in an industrial machine. TC crispiness was influenced by grain characteristics and percentage of HP. Huitlacoche paste addition caused an increase in total dietary fiber (from 5.27 to 14.54%), total soluble phenolics content (from 17.52 to 37.60 mg GAE/100 g) and antioxidant capacity (from 6.74 to 7.98 μmol TE/g) in TC. Results suggest that tortilla chips added with huitlacoche can be an alternative to prepare this traditional edible fungus and produce healthier snacks, not fried and enriched with bioactive compounds.