Diseño geométrico, estructura de pavimento rígido y drenaje menor de 700 metros lineales de calles, del barrio Francisco Rivera Quintero, ubicado en el municipio de Estelí, por el método de AASHTO-93, 2021

El estudio presenta el Diseño geométrico de la estructura de pavimento rígido y drenaje menor de 700 metros lineales de calles, del Barrio Francisco Rivera Quintero, ubicado en el municipio de Estelí, por el método de AASHTO-93, 2021

Implementation of a piezo-diagnostics approach for damage detection based on PCA in a linux-based embedded platform

The implementation of damage-detection methods for continuously assessing structural integrity entails systems with attractive features such as storage capabilities, memory capacity, computational complexity and time-consuming processing. In this sense, embedded hardware platforms are a promising technology for developing integrated solutions in Structural Health Monitoring. In this paper, design, test, and specifications for a standalone inspection prototype are presented, which take advantage of piezo-diagnostics principle, statistical processing via Principal Component Analysis (PCA) and embedded systems. The equipment corresponds to a piezoelectric active system with the capability to detect defects in structures, by using a PCA-based algorithm embedded in the Odroid-U3 ARM Linux platform. The operation of the equipment consists of applying, at one side of the structure, wide guided waves by means of piezoelectric devices operated in actuation mode and to record the wave response in another side of the structure by using the same kind of piezoelectric devices operated in sensor mode. Based on the nominal response of the guide wave (no damages), represented by means of a PCA statistical model, the system can detect damages between the actuated/sensed points through squared prediction error (Q-statistical index). The system performance was evaluated in a pipe test bench where two kinds of damages were studied: first, a mass is added to the pipe surface, and then leaks are provoked to the pipe structure by means of a drill tool. The experiments were conducted on two lab structures: (i) a meter carbon-steel pipe section and (ii) a pipe loop structure. The wave response was recorded between the instrumented points for two conditions: (i) The pipe in nominal conditions, where several repetitions will be applied to build the nominal statistical model and (ii) when damage is caused to the pipe (mass adding or leak). Damage conditions were graphically recognized through the Q-statistic chart. Thus, the feasibility to implement an automated real-time diagnostic system is demonstrated with minimum processing resources and hardware flexibility.Peer ReviewedPostprint (published version

Estado del arte en monitorización de salud estructural: Un enfoque basado en agentes inteligentes

This article presents a review of the state-of-the-art on damage detection and damage location techniques commonly used for Structural Health Monitoring and some of the electronic systems used for it. On another hand, a review of intelligent agents’ applications is shown, focusing on the solution of distributed information problems. Finally, a review of intelligent agents’ applications on Structural Health Monitoring is presented to obtain the systems´ tendencies and define the unsolved problems on this area.Este artículo presenta una revisión del estado del arte reportado en literatura sobre las técnicas utilizadas en Monitorización de Salud Estructural para detectar y localizar daños, así como los dispositivos electrónicos que se usan para efectuarla. Además, incluye una revisión de las aplicaciones de los agentes inteligentes en diferentes áreas de la ingeniería para solucionar problemas con información distribuida. Por último, revisa las aplicaciones de los sistemas de multiagentes inteligentes en Monitorización de Salud Estructural, con el fin de encontrar las tendencias de los sistemas de monitorización y determinar los problemas que no han sido solucionados en esta área

Aviatur

Nota: Las actividades se encuentran en el documento adjuntoNota: Este documento está sujeto a la Advertencia legal y condiciones de uso sobre las bases de datos de objetos de aprendizaje.En este documento se encuentra el caso de la compañía Aviatur. La agencia ofrecía servicios como venta de tiquetes de todas las empresas aéreas del mundo, cambio de moneda, excursiones, trámite de documentos de viaje, en especial para los viajeros de negocios .Universidad EAN. Facultad de Administración, Finanzas y Ciencias Económicas. Grupo de Investigación en Gerencia de la Gran, Pequeña y Mediana Empresa - G3pyme

Influence of climatic variables on wireless: case study Base-Station Receiver

The development of this research is done with the aim of finding the relationship betweenweather conditions and the loss of wireless connection. The data were obtained by ameteorological center of the area and a telecommunications company that operates in the sameplace. We studied different models based on fuzzy logic due to the easy interpretation the easyinterpretation of the rules and data management. We used the Weka application that providestools for pre-processing of data and Keel software tool for data classification. Nine classifiersbased on fuzzy rules were applied, where the Furia-C was that better results obtained in orderto quality and quantity of rules. In this scenario, a preprocessing of data were computed, wheresome techniques to improve the information was performed. Some of the obtained rulerscorroborate the influence of heavy rain over the loss of the signal, but other relationships thatincorporate new knowledge in the area, such as dew point and the average relative humidityappear

Multidimensional big data processing for damage detection in real pipelines using a smart pig tool

The history of the hydrocarbons business in Colombia dates back to the early twentieth century where mining and energy sector has been one of the principal pillars for the its development. Thus, the pipelines currently in service have over 30 years and most of them are buried and phenomena like metal losses, corrosion, mechanical stress, strike by excavation machinery and other type of damages are presented. Since it can generate social and environmental problems, monitoring tools and programs should be developed in order to prevent catastrophic situations. However, the maintaining of these structures is very expensive and it is normally developed by foreign companies. In order to overcome this situation, recently the native research institute “Research Institute of Corrosion - CIC (Corporación para la Investigación de la Corrosión)” developed an in-line inspection tool to be operated in Colombian pipelines (especially gas) to get valuable information of their current state along of thousand kilometres. The recorded data is of big size and its processing demand a high computational cost and adequate tool analysis to determine a certain pipeline damage condition. On other hand, the author from UPC and UIS have been bringing its expertise in processing and analysing this type of big data by using mainly Principal Component Analysis (PCA) as an effective tool to detect and locate different damages. In previous papers, multidimensional data matrix was used to locate possible damages along the pipeline, however most of activated points were considered false alarms since they corresponded to weld points. Thus, in this paper it is proposed no considering piecewise weld points (tube sections) and an extension of PCA named Multiway PCA (MPCA) is applied for each each one of the tube sections that form the pipeline. Therefore, if a tube section is found outside from overall indices found by using the MPCA model, an alarm activated in that section and a precise location can be obtained by analyzing only data from that specific tube section.Postprint (author's final draft

Influence of climatic variables on wireless: case study Base-Station Receiver

The development of this research is done with the aim of finding the relationship betweenweather conditions and the loss of wireless connection. The data were obtained by ameteorological center of the area and a telecommunications company that operates in the sameplace. We studied different models based on fuzzy logic due to the easy interpretation the easyinterpretation of the rules and data management. We used the Weka application that providestools for pre-processing of data and Keel software tool for data classification. Nine classifiersbased on fuzzy rules were applied, where the Furia-C was that better results obtained in orderto quality and quantity of rules. In this scenario, a preprocessing of data were computed, wheresome techniques to improve the information was performed. Some of the obtained rulerscorroborate the influence of heavy rain over the loss of the signal, but other relationships thatincorporate new knowledge in the area, such as dew point and the average relative humidityappear

Relationship between force signal and superficial electromyographic signals associated to hand movements

The analysis of electromyographic signals is applied both to the diagnosis of pathologies and to the recognition of movement patterns. Variables such as force and speed of movement are factors that affect the characteristics of the signals of surface electromyography (SMEG). The naturalness of the movements of the hand are also associated with strength and speed. Current work assessment 96 records of SEMG -Force). The objective was to obtain a linear model that would allow the relation of the force signal with the tone of the forearm SEMG signals. The work results show models at the determination coefficient R2 - median 0.78. The SEMG signal would contribute to the variation of the strength signal. However, there are appreciable differences in relation to the model in each type of hand movement

AUTOMATIC IDENTIFICATION OF DYSPHONIAS USING MACHINE LEARNING ALGORITHMS

Dysphonia is a prevalent symptom of some respiratory diseases that affects voice quality, even for prolonged periods. For its diagnosis, speech-language pathologists make use of different acoustic parameters to perform objective evaluations on patients and determine the type of dysphonia that affects them, such as hyperfunctional and hypofunctional dysphonia, which is important because each type requires a different treatment. In the field of artificial intelligence this problem has been addressed through the use of acoustic parameters that are used as input data to train machine learning and deep learning models. However, its purpose is usually to identify whether a patient is ill or not, making binary classifications between healthy voices and voices with dysphonia, but not between dysphonias. In this paper, harmonic-to-noise ratio, cepstral peak prominence-smoothed, zero crossing rate and the means of the Mel frequency cepstral coefficients (2-19) are used to make multiclass classification of voices with euphony, hyperfunction and hypofunction by means of six machine learning algorithms, which are: Random Forest, K nearest neighbors, Logistic regression, Decision trees, Support vector machines and Naive Bayes. In order to evaluate which of them presents a better performance to identify the three voice classes, bootstrap.632 was used. It is concluded that the best confidence interval ranges from 87% to 92%, in terms of accuracy for the K Nearest Neighbors model. Results can be implemented in the development of a complementary application for the clinical diagnosis or monitoring of a patient under the supervision of a specialist

2-Bromo-2-methyl-N-(4-nitro­phen­yl)propanamide

The title compound, C10H11BrN2O3, exhibits a small twist between the amide residue and benzene ring [the C—N—C—C torsion angle = 12.7 (4)°]. The crystal structure is stabilized by weak N—H⋯O, C—H⋯Br and C—H⋯O inter­actions. These lead to supra­molecular layers in the bc plane