Glottal Source Cepstrum Coefficients Applied to NIST SRE 2010

Through the present paper, a novel feature set for speaker recognition based on glottal estimate information is presented. An iterative algorithm is used to derive the vocal tract and glottal source estimations from speech signal. In order to test the importance of glottal source information in speaker characterization, the novel feature set has been tested in the 2010 NIST Speaker Recognition Evaluation (NIST SRE10). The proposed system uses glottal estimate parameter templates and classical cepstral information to build a model for each speaker involved in the recognition process. ALIZE [1] open-source software has been used to create the GMM models for both background and target speakers. Compared to using mel-frequency cepstrum coefficients (MFCC), the misclassification rate for the NIST SRE 2010 reduced from 29.43% to 27.15% when glottal source features are use

Elaboración de un manual de procesos basados en la estandarización de procedimientos y actividades para el correcto levantamiento de información de los médicos de primer nivel de atención del Ministerio de Salud Pública del Ecuador, 2018-2019

The purpose of this Intervention Plan is to prepare a process manual for the general medical service portfolio in the first level care units of the Ministry of Public Health Since the main problem lies in the lack of control in the information raised by professionals not complying with parameters or protocols established in the Comprehensive Health Care Manual (MAIS)...El presente Plan de Intervención tiene como objeto la elaboración de un manual de procesos para la cartera de servicio de medicina general en las unidades de primer nivel de atención del Ministerio de Salud Pública..

Myopia and Other Visual Disorders in Children

Depto. de Optometría y VisiónFac. de Óptica y OptometríaTRUEpu

Prevalence of Dry Eyes Symptoms in Association with Contact Lenses and Refractive Status in Portugal

Background: Determine whether the presence of ocular symptoms in soft-contact-lens wearers changes depending on the refractive status. Methods: During the months of January to March 2022, the CLDEQ-8 questionnaire was administered to soft-contact-lens wearers. The statistical analysis was carried out using the SPSS 27.0 computer program (SPSS Inc., Chicago, IL, USA). Results: A total of 251 subjects participated in the study, with a higher percentage of myopes than hyperopes (82.1% versus 16.7%; p < 0.001). Out of all total participants, 21.5% suffered from dry-eye symptoms. It was noted that hyperopes presented a higher rate of dry-eye symptoms (p = 0.041). At the same time, the spherical equivalent was more positive in the participants with dry-eye symptoms (p = 0.014). Significant differences were found based on the symptoms present with contact lenses and the degree of myopia. The intensity of visual disturbances was higher in the participants with medium myopia (median [IQR]: 1/5 [2]) compared to those with low (median [IQR]: 0/5 [2]) and high myopia (median [IQR]: 0/5 [1]) (p = 0.009). Conclusions: Contact-lens wearers with hyperopia showed a higher rate of ocular dryness than those with myopia. In turn, wearing daily-replacement lenses could be one of the reasons for the lesser presence of ocular dryness compared to monthly-replacement lenses.Sección Deptal. de Óptica (Óptica)Fac. de Óptica y OptometríaTRUEpu

On the use of algorithms to discover motifs in DNA sequences

Many approaches are currently devoted to find DNA motifs in nucleotide sequences. However, this task remains challenging for specialists nowadays due to the difficulties they find to deeply understand gene regulatory mechanisms, especially when analyzing binding sites in DNA. These sites or specific nucleotide sequences are known to be responsible for transcription processes. Thus, this work aims at providing an updated overview on strategies developed to discover meaningful motifs in DNA-related sequences, and, in particular, their attempts to find out relevant binding sites. From all existing approaches, this work is focused on dictionary, ensemble, and artificial intelligence-based algorithms since they represent the classical and the leading ones, respectively.Ministerio de Ciencia y Tecnología TIN2007- 68084-C-00Junta de Andalucia P07-TIC- 02611

Determining the best set of seismicity indicators to predict earthquakes. Two case studies: Chile and the Iberian Peninsula

This work explores the use of different seismicity indicators as inputs for artificial neural networks. The combination of multiple indicators that have already been successfully used in different seismic zones by the application of feature selection techniques is proposed. These techniques evaluate every input and propose the best combination of them in terms of information gain. Once these sets have been obtained, artificial neural networks are applied to four Chilean zones (the most seismic country in the world) and to two zones of the Iberian Peninsula (a moderate seismicity area). To make the comparison to other models possible, the prediction problem has been turned into one of classification, thus allowing the application of other machine learning classifiers. Comparisons with original sets of inputs and different classifiers are reported to support the degree of success achieved. Statistical tests have also been applied to confirm that the results are significantly different than those of other classifiers. The main novelty of this work stems from the use of feature selection techniques for improving earthquake prediction methods. So, the infor-mation gain of different seismic indicators has been determined. Low ranked or null contribution seismic indicators have been removed, optimizing the method. The optimized prediction method proposed has a high performance. Finally, four Chilean zones and two zones of the Iberian Peninsula have been charac-terized by means of an information gain analysis obtained from different seismic indicators. The results confirm the methodology proposed as the best features in terms of information gain are the same for both regions.Ministerio de Ciencia y Tecnología BIA2004-01302Ministerio de Ciencia y Tecnología TIN2011-28956-C02-01Junta de Andalucía P11-TIC-752

Classification of Gene Expression Profiles: Comparison of K-means and Expectation Maximization Algorithms

Biomedical research has been revolutionized by high throughput techniques and the enormous amount of data they are able to generate. In particular technology has the capacity to monitor changes in RNA abundance for thou sands of genes simultaneously. The interest shown over microarray analysis methods has rapidly raised. Clustering is widely used in the analysis of microarray data to group genes of interest targeted from microarray experiments on the basis of similarity of expression patterns. In this work we apply two clustering algorithms, K-means and Expecta tion Maximization to particular a problem and we compare the groupings obtained on the basis of the cohesiveness of the gene products associated to the genes in each clusterMinisterio de Ciencia y Tecnología TIN-2006-12879Junta de Andalucía TIC-0278

Mining Quantitative Association Rules in Microarray Data Using Evolutive Algorithms

The microarray technique is able to monitor the change in concentration of RNA in thousands of genes simultaneously. The interest in this technique has grown exponentially in recent years and the difficulties in analyzing data from such experiments, which are characterized by the high number of genes to be analyzed in relation to the low number of experiments or samples available. In this paper we show the result of applying a data mining method based on quantitative association rules for microarray data. These rules work with intervals on the attributes, without discretizing the data before. The rules are generated by an evolutionary algorithm.Ministerio de Ciencia y Tecnología TIN2007-68084-C-00Junta de Andalucía P07-TIC-0261

Bio-inspired broad-class phonetic labelling

Recent studies have shown that the correct labeling of phonetic classes may help current Automatic Speech Recognition (ASR) when combined with classical parsing automata based on Hidden Markov Models (HMM).Through the present paper a method for Phonetic Class Labeling (PCL) based on bio-inspired speech processing is described. The methodology is based in the automatic detection of formants and formant trajectories after a careful separation of the vocal and glottal components of speech and in the operation of CF (Characteristic Frequency) neurons in the cochlear nucleus and cortical complex of the human auditory apparatus. Examples of phonetic class labeling are given and the applicability of the method to Speech Processing is discussed

Citation Network Analysis on the Influence of Vision on Academic Performance

Background: Proper vision is absolutely critical to children’s academic performance, as vision problems can drastically affect learning ability. Currently, the existing literature in this field is somewhat inconsistent and carries several controversies about the influence of vision on academic performance. In this study, citation networks were utilized in order to analyze the relationship between publications and authors, the most-cited publication, and the different research areas. Additionally, the most commonly utilized publication sources along with the most common research areas were also pinpointed. Methods: The aforementioned search was executed in the Web of Science database, with a time range beginning in 1941 and ending in 2022. In order to scrutinize the publications, VOSviewer, CiteSpace software, and the Citation Network Explorer were utilized for analysis about the most-cited publication and the different research areas. Results: Overall, 1342 papers were found in all fields along with 2187 citation networks. Moreover, 2020 was the year with the most publications, including 127 publications and 4 citation networks. Bull et al., published in 2008, was the most-cited work, reaching a citation index of 975. The clustering function managed to identity four groups with the most engaging research topics from researchers: motor visual skills, visual memory, the influence of vision on the different learning styles, and abnormal development of the visual system. Conclusions: In the end, the topic with the greatest interest was the influence of visual motor skills on academic performance. Ideally, this paper will assist fellow researchers in quickly noting which topics are of greatest interest and how research in this area has evolved.Depto. de Optometría y VisiónFac. de Óptica y OptometríaTRUEpu