Ingeniería

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https://hdl.handle.net/10669/1422

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2D SLAM Algorithms Characterization, Calibration, and Comparison Considering Pose Error, Map Accuracy, CPU Usage, and Memory Usage
(2022) Trejos Vargas, Kevin Francisco; Rincón Riveros, Laura Camila; Bolaños Torres, Miguel Eduardo; Fallas Pizarro, José Ariel; Marín Paniagua, Leonardo José
The present work proposes a method to characterize, calibrate, and compare, any 2D SLAM algorithm, providing strong statistical evidence, based on descriptive and inferential statistics to bring confidence levels about overall behavior of the algorithms and their comparisons. This work focuses on characterize, calibrate, and compare Cartographer, Gmapping, HECTOR-SLAM, KARTO-SLAM, and RTAB-Map SLAM algorithms, there were four metrics in place, these are pose error, map accuracy, CPU usage, and memory usage, from these four metrics, to characterize them, Plackett-Burman and factorial experiments were performed, and enhancement after characterization and calibration was granted by using hypothesis tests besides central limit theorem.
A Comparative Study on Denoising Algorithms for Footsteps Sounds as Biometric in Noisy Environments
(2022-08-03) Caravaca Mora, Ronald; Brenes Jiménez, Carlos; Coto Jiménez, Marvin
Biometrics is the automated identification of a person based on distinctive characteristics, such as fingerprints, face, voice, or the sound of footsteps. This last characteristic has significant challenges considering the background noise present in any real-life application, where microphones would record footsteps sounds and different types of noise. For this reason, it is crucial to consider not only the capacity of classification algorithms for recognizing a person using foostetps sounds, but also at least one stage of denoising algorithms that can reduce the background sounds before the classification. In this paper we study the possibilities of a two-stage approach for this problem: a denoising stage followed by a classification process. The work focuses on discovering the proper strategy for applying combinations of both stages for specific noise types and levels. Results vary according to the type and level of noise, e.g., for White noise at signal-to-noise ratio level, accuracy can increase from 0.96 to 1.00 by applying deep learning based-filters, but the same option does not benefit the cases of signals with low level natural noises, where Wiener filtering can increase accuracy from 0.6 to 0.77 at the highest level of noise. The results represent a baseline for developing real-life implementations of footstep biometrics.
A Comparison between a Relational Database and a Graph Database in the context of a Personalized Cancer Treatment Application
(2016) Martínez Porras, Alexandra; Mora Rodríguez, Rodrigo Antonio; Alvarado González, Daniel; López Herrera, Gustavo; Quirós Barrantes, Steve
This paper presents a performance comparison between a relational database (implemented in MySQL) and a graph database (implemented in Neo4j). Unlike traditional benchmarks, this comparison is made in the context of a real health application which was developed in Costa Rica. The comparison encompassed twelve queries and three data size configurations.The results of the comparison indicate that MySQL performs better than Neo4j in most cases, but has a poor performance when data size is large and the queries have multiple join operations.
A first approach to acoustic characterization of Costa Rican children’s speech
(2020-03-27) Coto Jiménez, Marvin; Morales Rodríguez, Maribel; Vargas Díaz, Daniel Alfredo
As human interaction with computers becomes more pervasive, the value of developing automatic speech recognition, text-to-speech synthesis, and related speech technologies become more important for people of all ages, accents, and conditions. One of the groups that represent bigger challenges is children, due to the difficulties in recording enough speech, and the lack of characterization of their speech, which is particular of every language and accent. This paper presents the first approach to acoustic analyses of Costa Rican children aged from six to twelve years. These analyses aimed to achieve a better understanding of the characteristics of speech produced by this group, in terms of providing future development and enhancement of automatic speech recognizers and speaker identification systems. For this purpose, we record the speech consisting of isolated words of three children, and compare the results with three adults, in terms of the vowel’s formants. The formants give information about the vocal track of the speaker, and it is an important method to provide the first analysis of these signals. Results show noticeable differences between the children and adults and may provide useful information about future trends to adapt and develop the current speech technologies for this population.
A genetic algorithm based framework for software effort prediction
(2017) Murillo Morera, Juan; Quesada López, Christian Ulises; Castro Herrera, Carlos; Jenkins Coronas, Marcelo
Background: Several prediction models have been proposed in the literature using different techniques obtaining different results in different contexts. The need for accurate effort predictions for projects is one of the most critical and complex issues in the software industry. The automated selection and the combination of techniques in alternative ways could improve the overall accuracy of the prediction models. Objectives: In this study, we validate an automated genetic framework, and then conduct a sensitivity analysis across different genetic configurations. Following is the comparison of the framework with a baseline random guessing and an exhaustive framework. Lastly, we investigate the performance results of the best learning schemes. Methods: In total, six hundred learning schemes that include the combination of eight data preprocessors, five attribute selectors and fifteen modeling techniques represent our search space. The genetic framework, through the elitism technique, selects the best learning schemes automatically. The best learning scheme in this context means the combination of data preprocessing + attribute selection + learning algorithm with the highest coefficient correlation possible. The selected learning schemes are applied to eight datasets extracted from the ISBSG R12 Dataset. Results: The genetic framework performs as good as an exhaustive framework. The analysis of the standardized accuracy (SA) measure revealed that all best learning schemes selected by the genetic framework outperforms the baseline random guessing by 45–80%. The sensitivity analysis confirms the stability between different genetic configurations. Conclusions: The genetic framework is stable, performs better than a random guessing approach, and is as good as an exhaustive framework. Our results confirm previous ones in the field, simple regression techniques with transformations could perform as well as nonlinear techniques, and ensembles of learning machines techniques such as SMO, M5P or M5R could optimize effort predictions.
A mechano-biocatalytic one-pot approach to release sugars from lignocellulosic materials
(2020) Zhong, Yuan; Frost, Henry; Bustamante Román, Mauricio; Li, Song; Liu, Yan; Liao, Wei
A novel, mechano-biocatalytic one-pot process was developed by this study to efficiently release monosaccharides from lignocellulosic materials in an environmentally-friendly manner. The process synergistically integrates ball milling and enzymatic hydrolysis to complete pretreatment and hydrolysis of lignocellulosic materials in a single step without chemical supplements. High sugar titer and conversion from lignocellulosic materials were simultaneously achieved. Among four studied feedstocks (solid digestate, corn stover, switchgrass, and miscanthus), corn stover demonstrated much better sugar concentration and conversion. Under the preferred reaction condition, the glucose concentration reached 55.20 g/L with a glucose conversion of 88.63%. The corresponding xylose concentration was 20.06 g/L with a xylose conversion of 67.34%. The energy and exergy analyses further indicate that the studied process had better energy and exergy profiles than the conventional combined hydrolysis process. The average energy consumption of the mechano-biocatalytic process for four feedstocks was 1.05 kWh-e/kg dry biomass that was 56% lower than the average energy consumption (2.37 kWh-e/kg dry biomass) of the conventional process. The corresponding average exergy efficiency of the mechano-biocatalytic process was 67% that was much higher than the average efficiency (52%) of the conventional process. These results show that the mechano-biocatalytic one-pot process as an environmentally friendly approach can significantly simplify the pretreatment and hydrolysis and enhance their efficiencies for advanced fuel and chemical production.
A mobile application that allows children in the early childhood to program robots
(2016) Ramírez Benavides, Kryscia Daviana; López Herrera, Gustavo; Guerrero Blanco, Luis Alberto
Children born in the Information Age are digital natives; this characteristic should be exploited to improve the learning process through the use of technology. This paper addresses the design, construction, and evaluation process of TITIBOTS, a programming assistance tool for mobile devices that allows children in the early childhood to create programs and execute them using robots. We present the results of using TITIBOTS in different scenarios with children between 4 and 6 years old. The insight obtained in the development and evaluation of the tool could be useful when creating applications for children in the early childhood. The results were promising; children liked the application and were willing to continue using it to program robots to solve specific tasks, developing the skills of the 21st century.
A Novel Control System for Medium-Voltage Hexverter-Based Drives
(2020-09-23) Espinoza Bolaños, Mauricio; Donoso M., Felipe; Díaz D., Matías; Urrutia O., Matías; Cárdenas Dobson, Roberto
In this paper, a novel control system for the Hexverter-based drive is proposed and analysed. Unlike previously proposed control schemes, the proposed one does not require the information of the machine variables to regulate the converter floating capacitors, as required in high-performance drive applications. The feasibility of the proposed control system is demonstrated by using simulation results of an Hexverter-based drive driving a medium-voltage machine, including the whole frequency range and high starting torque loads.
A practical method for considering shading on photovoltaics systems energy yield
(2023-10-01) Vega Garita, Víctor; Alpízar Gutiérrez, Verónica; Alpízar Castillo, Joel
Along with the widespread adoption of solar energy, it is fundamental to develop methods and tools that help practitioners during the design phase of photovoltaic (PV) systems. Currently, multiple commercial software can quantify a particular location’s annual energy yield while including the horizon’s shading effect (e.g., mountains, buildings, and trees). To do so, precise information about the PV system’s surroundings is necessary. This information is gathered by specialized equipment or by having access to satellite imagery. Therefore, to offer a more practical approach, we propose a method that requires only a cellphone camera, a fixed point for taking a panoramic photograph, and a compass. Once the panoramic image is taken, the obstacles’ width, height, and altitude are calculated, and the skyline is built. With this information, the method correlates the position of the sun with meteorological data to include the effect of shading on direct irradiation. The method was tested using one–year meteorological data to determine the best orientation of a PV system. The image processing method and the general method were validated by getting PV power generation data and aerial images and comparing them to the method’s predictions. Therefore, we introduce a method that, with low computational complexity, facilitates the study of shading on the performance of PV systems.
A self-sustaining high-strength wastewater treatment system using solar-bio-hybrid power generation
(2017-06) Bustamante Román, Mauricio; Liao, Wei
This study focuses on system analysis of a self-sustaining high-strength wastewater treatment concept combining solar technologies, anaerobic digestion, and aerobic treatment to reclaim water. A solar bio-hybrid power generation unit was adopted to power the wastewater treatment. Concentrated solar power (CSP) and photovoltaics (PV) were combined with biogas energy from anaerobic digestion. Biogas is also used to store the extra energy generated by the hybrid power unit and ensure stable and continuous wastewater treatment. It was determined from the energy balance analysis that the PV-bio hybrid power unit is the preferred energy unit to realize the self-sustaining high-strength wastewater treatment. With short-term solar energy storage, the PV-bio-hybrid power unit in Phoenix, AZ requires solar collection area (4032 m2) and biogas storage (35 m3), while the same unit in Lansing, MI needs bigger solar collection area and biogas storage (5821 m2 and 105 m3, respectively) due to the cold climate.
A Strong-Motion Database of Costa Rica: 20 Years of Digital Records
(2020-09-09) Moya Fernández, César Aarón; Pinzón Ureña, Luis; Schmidt Díaz, Víctor; Hidalgo Leiva, Diego Antonio; Pujades Beneit, Luis Gonzaga
In this article, we present a strong-motion database from earthquakes recorded by the Earthquake Engineering Laboratory at the University of Costa Rica. The database consists of 2471 three-component accelerograms from 155 digitally recorded events. It covers the last 20 yr of measurements, including records from the 5 September 2012 Mw 7.6 Nicoya earthquake. The engineering and seismological communities can use this data either to conduct new research or to improve seismic hazard studies in the region. A catalog is also available with metadata of each record containing several intensity measures from the ground-motion time histories.
A sustainable lignocellulosic biodiesel production integrating solar- and bio-power generation
(2016-06-04) Zanotti, Michael; Ruan, Zhenhua; Bustamante Román, Mauricio; Li, Yan; Liao, Wei; Liu, Yan
A solar-bio-powered refining concept has been developed to establish sustainable lignocellulosic biodiesel production. The refining concept applies a combined hydrolysis process without detoxification to release sugars from corn stover, uses aerobic oleaginous fungal fermentation to accumulate lipids on the hydrolysate for biodiesel production, and implements solar-bio-power generation to satisfy the energy demand. The results demonstrate that system integration of solar-bio-power generation and fungal lipid accumulation is an effective approach to create a sustainable lignocellulosic biodiesel production. Compared to concentrated solar power (CSP) units, photovoltaics (PV) are a more suitable solar technology to satisfy the energy needs of the lignocellulosic biodiesel production. The PV-bio-powered lignocellulosic biodiesel production has a net energy output of 28.70 MJ kg−1 biodiesel produced, and a net energy ratio (NER) of 1.08.
A user interaction bug analyzer based on image processing
(2016-08) Méndez Porras, Abel; Alfaro Velásco, Jorge; Jenkins Coronas, Marcelo; Martínez Porras, Alexandra
Mobile applications support a set of user-interaction features that are independent of the application logic. Rotating the device, scrolling, or zooming are examples of such features. Some bugs in mobile applications can be attributed to user-interaction features. Objective: This paper proposes and evaluates a bug analyzer based on userinteraction features that uses digital image processing to find bugs. Method: Our bug analyzer detects bugs by comparing the similarity between images taken before and after a user-interaction. SURF, an interest point detector and descriptor, is used to compare the images. To evaluate the bug analyzer, we conducted a case study with 15 randomly selected mobile applications. First, we identified user-interaction bugs by manually testing the applications. Images were captured before and after applying each user-interaction feature. Then, image pairs were processed with SURF to obtain interest points, from which a similarity percentage was computed, to finally decide whether there was a bug. Results: We performed a total of 49 user-interaction feature tests. When manually testing the applications, 17 bugs were found, whereas when using image processing, 15 bugs were detected. Conclusions: 8 out of 15 mobile applications tested had bugs associated to user-interaction features. Our bug analyzer based on image processing was able to detect 88% (15 out of 17) of the user-interaction bugs found with manual testing.
A Virtual Repository of Learning Objects to Support Literacy of SEN Children
(2015-01) Guerrero Blanco, Luis Alberto; Jadán Guerrero, Janio
Literacy development is an essential process for special education needs children. Otherwise, they will have additional difficulties in their daily life activities and hence their social inclusion. It is a big challenge for parents and teachers, but it is easier if the process begins since childhood. In this paper, we present Tic@ula, a virtual repository for creating, centralizing, and sharing learning objects based on the IEEE learning object metadata standard. The framework aims to enhance the adaptation of the resources for literacy to the Costa Rican reality and extend its application to children with moderate intellectual disability. The educational resources are based on the literacy method proposed by Spanish authors in their book Down Syndrome: Reading and Writing. The method and the resources were evaluated in a case study. The preliminary results showed that the method cannot only be applied in local context but also assists teachers and parents in the design and use of literacy resources for special education.
Acceptance of Serious Games to Develop Digital Competencies in Higher Education
(2022) Sandí Delgado, Juan Carlos; Sanz, Cecilia Verónica; Lovos, Edith Noemi
Serious games are the focus of the current research agenda. They show promise for allowing students to learn and practice skills. In fewer studies, they are used for the development of academic competencies. Therefore, it is of interest to deepen the research on the benefits of serious games in academic education and training. This article presents a study using serious games aimed at higher education academics’ training for the development of digital competencies. The study was carried out with 56 academics, using the serious game called AstroCódigo. The study analyzed the level of acceptance of serious games using the TAM model and what factors the academics believe affect this acceptance. It is important to know possible barriers that affect the development of actions oriented to the formation of academic competencies through serious games, which can also affect the adoption of games as a resource for teaching situations. None of prior studies have focused on analyzing the technological acceptance of serious games used for the development of academic competencies. The results of this research indicate that participants believe that using serious games can be beneficial to drive digital competencies. However, there are aspects such as the highest academic qualification, work experience, professional development, perceived usefulness, ease of use, and fear of change associated with age rank which can play a negative role in the use and acceptance of digital technologies by academics, particularly serious games. These results may be a clue to the barriers linked to the fact that most of the participants in this study do not use serious games in their classes or for their digital skills training. Additionally, the possibility to try and fail and the increased level of challenges proposed in the serious games, related to enjoyment, were valued by academics, during the sessions with AstroCódigo. These findings open the door to organize strategies for academic training in digital competencies within higher education institutions. They can also impact the design decisions of new serious games.
Aesthetics of Comfort: A Third Moment in Costa Rican Histories of Tropical Architecture
(2020) Solano Meza, Natalia
Histories of tropical architecture in Costa Rica could be constructed around three moments: the settlement of the United Fruit Company (UFCO) in 1889, the visit of Otto H. Koenigsberger, director of the Department of Development and Tropical Studies during the opening of the School of Architecture of the University of Costa Rica in 1970, and finally, the constitution of a set of formal principles and images guiding the work of many architects in Costa Rica and justified by the need to provide comfort—or sensory contentment—in the tropical climate: an aesthetics of comfort. Although it is often considered a technical term, in our work, comfort operates also as a historical and aesthetic concept. Our research suggests that the aesthetics of comfort has been disseminated through journals and exhibitions since the 1990s, while also absorbing experiences from the two previous moments. Consequently, it cannot be separated from histories of colonialism, extractivism, hygiene, and interventionism. It is present, although in different forms and with different purposes, in the work of architects such as Édgar Brenes, Víctor Cañas and Bruno Stagno. In the media, their prominent achievements are presented as the result of responsiveness to nature, building technology, site adaptation and the ability to offer contentment. From our analysis, we claim that the aesthetics of comfort functions as a validation mechanism, one that praises technical knowledge and formal adaptation but tends to ignore histories of colonialism and knowledge production.
Alternative and augmentative communication for people with disabilities and language problems: an eye gaze tracking approach
(2016) Arias Soto, Emmanuel; López Herrera, Gustavo; Quesada Quirós, Luis; Guerrero Blanco, Luis Alberto
Alternative and augmentative communications encapsulates the use of technology to provide communication means for people with some sort of disability. In this paper, we present a prototype that provides both pictographic and alphabetic options to allow communication. Our system was originally designed for people that suffer physical disabilities and are not able to move their body. To allow interaction we provide an eye gazed based interaction. Our system was evaluated with an experienced test subject, because the system requires training to be used. However, evaluations results demonstrated that a skilled user requires less than two seconds (average) to select a pictogram or letter (i.e., in less than a minute, a 30 characters long phrase or up to two semantically correct sentences using pictograms can be produced).
An empirical evaluation of NASA-MDP data sets using a genetic defect-proneness prediction framework
(2016-11-09) Murillo Morera, Juan; Quesada López, Christian Ulises; Castro Herrera, Carlos; Jenkins Coronas, Marcelo
In software engineering, software quality is an important research area. Automated generation of learning schemes plays an important role and represents an efficient way to detect defects in software projects, thus avoiding high costs and long delivery times. This study carries out an empirical evaluation to validate two versions with different levels of noise of NASAMDP data sets. The main objective of this paper is to determine the stability of our framework. In all, 864 learning schemes were studied (8 data preprocessors x 6 attribute selectors x 18 learning algorithms). In line with statistical tests, our framework reported stable results between the analyzed versions. Results reported that evaluation and prediction phases were similar. Furthermore, the performance of the phases of evaluation and prediction between versions of data sets were stable. This means that the differences between versions did not affect the performance of our framework
An Experimental Study on Speech Enhancement Based on a Combination of Wavelets and Deep Learning
(2022-06-20) Gutiérrez Muñoz, Michelle; Coto Jiménez, Marvin
The purpose of speech enhancement is to improve the quality of speech signals degraded by noise, reverberation, or other artifacts that can affect the intelligibility, automatic recognition, or other attributes involved in speech technologies and telecommunications, among others. In such applications, it is essential to provide methods to enhance the signals to allow the understanding of the messages or adequate processing of the speech. For this purpose, during the past few decades, several techniques have been proposed and implemented for the abundance of possible conditions and applications. Recently, those methods based on deep learning seem to outperform previous proposals even on real-time processing. Among the new explorations found in the literature, the hybrid approaches have been presented as a possibility to extend the capacity of individual methods, and therefore increase their capacity for the applications. In this paper, we evaluate a hybrid approach that combines both deep learning and wavelet transformation. The extensive experimentation performed to select the proper wavelets and the training of neural networks allowed us to assess whether the hybrid approach is of benefit or not for the speech enhancement task under several types and levels of noise, providing relevant information for future implementations.
Análisis acústico de vocales de niños costarricenses
(2020-06-23) Coto Jiménez, Marvin; Morales Rodríguez, Maribel
En este artículo se presenta un análisis acústico de vocales pronunciadas por niños costarricenses con edades entre los 6 y los 12 años. Estos análisis tienen como objetivo lograr una mejor comprensión de las características del habla producidas por este grupo en particular y, de esta manera, brindar información importante para la mejora de los reconocedores automáticos del habla y la identificación del hablante. Para este propósito, se construyó una base de datos con palabras aisladas que contemplan los fonemas, de acuerdo con varias etapas del desarrollo del lenguaje. Adicionalmente, se desarrolló una estrategia para la interacción con los niños. Los resultados confirman y complementan los resultados reportados en la literatura, pues muestran que existe una mayor variabilidad en parámetros como los formantes, la duración y el tono de las vocales emitidas por los niños, en comparación con los adultos. Los resultados permiten caracterizar cuantitativamente estos sonidos del habla, y establecer futuras investigaciones en áreas como el reconocimiento de habla y su dependencia del género y la edad dentro de esta comunidad.

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