796 results on '"Ricardo A. Ramirez"'
Search Results
2. Optimizing industrial transport with a connected automated vehicle demonstrator for assembly systems and end-of-line production
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Luis A. Curiel-Ramirez, Tobias Adlon, Peter Burggräf, Ricardo A. Ramirez-Mendoza, Moritz Beyer, and Denny Gert
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Autonomous driving ,Intelligent transport systems ,Smart factory ,Vehicle manufacturing ,Self-driving vehicle ,Connected automated vehicle ,Medicine ,Science - Abstract
Abstract In recent years, the automotive industry has witnessed significant progress in the development of automated driving technologies. The integration of advanced sensors and systems in vehicles has led to the emergence of various functionalities, such as driving assistance and autonomous driving. Applying these technologies on the assembly line can enhance the efficiency, safety, and speed of transportation, especially at end-of-line production. This work presents a connected automated vehicle (CAV) demonstrator for generating autonomous driving systems and services for the automotive industry. Our prototype electric vehicle is equipped with state-of-the-art sensors and systems for perception, localization, navigation, and control. We tested various algorithms and tools for transforming the vehicle into a self-driving platform, and the prototype was simulated and tested in an industrial environment as proof of concept for integration into assembly systems and end-of-line transport. Our results show the successful integration of self-driving vehicle platforms in the automotive industry, particularly in factory halls. We demonstrate the localization, navigation, and communication capabilities of our prototype in a demo area. This work anticipates a significant increase in efficiency and operating cost reduction in vehicle manufacturing, despite challenges such as current low traveling speeds and high equipment costs. Ongoing research aims to enhance safety for higher vehicle speeds, making it a more viable business case for manufacturers, considering the increasing standardization of automated driving equipment in cars. The main contribution of this paper lies in introducing the general concept architecture of the integration of automated driving functionalities in end-of-line assembly and production systems. Showing a case study of the effective development and implementation of such functionalities with a CAV demonstrator in a more standardized industrial operational design domain.
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- 2024
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3. Synthesis analysis for data driven model predictive control
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Hong Jianwang and Ricardo A. Ramirez-Mendoza
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Synthesis analysis ,data driven model predictive control ,persistent excitation ,output predictor ,stability analysis ,Control engineering systems. Automatic machinery (General) ,TJ212-225 ,Systems engineering ,TA168 - Abstract
This paper shows our new contributions on data driven model predictive control, such as persistent excitation, optimal state feedback controller, output predictor and stability. After reviewing the definition of persistent excitation and its important property, the idea of data driven is introduced in model predictive control to construct our considered data driven model predictive control, whose state information and output variable are generated by measured data online. Variation tool is applied to obtain the optimal controller or predictive controller through our own derivation. Furthermore, for the cost function in data driven model predictive control, its preliminary stability is analysed by using the linear matrix inequality and one single optimal state feedback controller is given. To bridge the gap between our derived results and other control strategies, output predictor is constructed from the point of data driven idea, i.e. using some collected input–output data from one experiment to establish the output predictor at any later time instant. Finally, one simulation example is given to prove the efficiency of our derived results.
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- 2022
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4. Direct Data Driven Model Reference Control for Flight Simulation Table
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Wang Jianhong and Ricardo A. Ramirez-Mendoza
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Model reference control ,direct data driven ,flight simulation table ,synthesis analysis ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
We present a direct data driven model reference control framework for flight simulation table from both the theoretical analysis and engineering application. Sate of the art direct driven model reference control designs the unknown controller based on the input-output data and guarantees the actual model converge to the reference model, under a case of no any priori knowledge for the unknown plant. We improve this direct data driven model reference control strategy by considering its stability validation and synthesis analysis for nonlinear controller. The resulting direct data driven model reference control scheme can be implemented to ensure flight simulation table rotate accuracy, resulting in improved performance index. As the main technical contribution, we show that the proposed direct data driven model reference control framework also ensures closed loop stability and suitable extension for nonlinear controller.
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- 2022
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5. Data Driven Strategy for Linear Parameter Varying Control Design
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Wang Jianhong, Ricardo A. Ramirez-Mendoza, and Wang Yanxiang
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Linear parameter varying system or controller ,data driven strategy ,nonparametric and parametric estimation ,optimal input signal ,power spectral ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
In this paper, we propose a novel data driven strategy framework for linear parameter varying closed loop system which consists of linear parameter varying system and linear parameter varying controller simultaneously. Firstly, we consider the model based control framework whose controller design is dependent of the considered system. In particular, due to the unknown system and unknown controller, data driven strategy is applied to obtain the system and controller respectively in their nonparametric and parametric forms. Such two different forms are related with system identification, power spectral and numerical optimization,etc. with a choice of the optimal input signal design. Secondly, to avoid the identification process of that system, data driven strategy is modified to design the controller directly from the observed input-output data sequence without providing any priori information on the considered system. We show that various techniques for data driven strategy to identify system or design controller, such as system identification, numerical optimization, power spectral and optimal input design etc within the proposed general framework.
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- 2022
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6. Direct Data Driven Scheme for UAV Flight Control
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Wang JIanhong, Zhang Ying, and Ricardo A. Ramirez-Mendoza
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Direct data driven control ,controller validation ,UAV flight control ,iterative idea ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
Consider one special closed loop system structure with one unknown plant and two unknown controllers,i.e. feed forward controller and feedback controllers, our missions are to identify this plant and design these two controllers without any physical principles. Based on the measured input-output data sequence, direct data driven scheme is proposed to achieve these dual goals. For the case of parameterized plant and two parameterized controllers, two kinds of unknown parameter vectors are estimated from the data sequence, and the iterative idea is applied to identify them recursively until to be convergence. In addition, controller validation modular is added to testify whether the designed controllers are satisfied, being from the idea of model validation in system identification. Then theoretical analysis on direct data driven scheme can be implemented to guarantee UAV flight control structure work well, bringing the detailed UAV flight control performance.
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- 2022
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7. On Online Adaptive Direct Data Driven Control
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Wang Jianhong and Ricardo A. Ramirez-Mendoza
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Adaptive direct data driven control ,passive analysis ,safety controller ,online ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
Based on our recent contributions on direct data driven control scheme, this paper continues to do some new research on direct data driven control, paving another way for latter future work on advanced control theory. Firstly, adaptive idea is combined with direct data driven control, one parameter adjustment mechanism is constructed to design the parameterized controller online. Secondly, to show the input-output property for the considered closed loop system, passive analysis is studied to be similar with stability. Thirdly, to validate whether the designed controller is better or not, another safety controller modular is added to achieve the designed or expected control input with the essence of model predictive control. Finally, one simulation example confirms our proposed theories. More generally, this paper studies not only the controller design and passive analysis, but also some online algorithm, such as recursive parameter identification and online subgradient descent algorithm. Furthermore, safety controller modular is firstly introduced in direct data driven control scheme.
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- 2022
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8. An Angular Speed and Position FLL-Based Estimator Using Linear Hall-Effect Sensors
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Luis Ibarra, Renato Galluzzi, Gerardo Escobar, and Ricardo A. Ramirez-Mendoza
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Angular position ,position feedback ,frequency-locked loop ,phase-locked loop ,harmonic oscillator ,unbalance ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
This paper proposes using a frequency-locked loop-based detector to estimate rotational speed and angle position for an electric machine rotor shaft. The measurement system consists of arrays of permanent magnets fixed to the rotor shaft together with linear Hall-effect sensors attached to a fixed frame. Parametric uncertainties on the sensor assembly lead to significantly noisy signals, exhibiting unbalance and harmonic distortion. To accurately estimate rotational speed and angle, it is proposed to use a frequency-locked loop scheme based on a fourth-order harmonic oscillator (FOHO) to allow the processing of the symmetric components, thus dealing with the unbalance. The scheme also includes an adaptive law to reconstruct the fundamental frequency. Moreover, a harmonic compensation mechanism comprising parallel FOHOs is included; each FOHO is tuned at the spectral component under concern for its cancellation. The proposed algorithm delivers a clean estimate of the positive sequence fundamental component despite the disturbances at the signals provided by the Hall-effect sensor, which is used to reconstruct the rotation angle. The described approach could enhance low-cost sensing solutions in applications where position feedback is mandatory and sensorless control is impossible, not requiring special installation considerations.
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- 2021
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9. Target tracking algorithms for multi-UAVs formation cooperative detection
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Wang Jianhong, Ricardo A. Ramirez-Mendoza, and Tang Xiaojun
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multi-uavs formation ,cooperative detection ,target tracking ,unscented kalman filter ,Control engineering systems. Automatic machinery (General) ,TJ212-225 ,Systems engineering ,TA168 - Abstract
This paper considers the problem of the ground target positioning and tracking algorithm for multi UAVs formation cooperative detection, and a real time and fast algorithm is proposed based on UAV airborne electro optical sensors. One state estimation problem for nonlinear stochastic system is studied by means of the unscented Kalman filter algorithm from target tracking process. To extend the single target tracking to multiple target tracking, one improved unscented Kalman filter algorithm is advised based on iterative multiple models. Furthermore, to relax the strict condition on white noise in Kalman filtering, the target tracking or state estimation is reduced to derive the inner and outer ellipsoidal approximations for the state in case of unknown but bounded noise. Finally, one simulation example confirms our theoretical results.
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- 2021
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10. Robust analysis for data-driven model predictive control
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Hong Jianwang, Ricardo A. Ramirez-Mendoza, and Tang Xiaojun
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model predictive control ,data driven ,nonlinear estimation ,robust analysis ,Control engineering systems. Automatic machinery (General) ,TJ212-225 ,Systems engineering ,TA168 - Abstract
Here the idea of data driven is introduced in model predictive control to establish our proposed data-driven model predictive control. Considering one first-order discrete time nonlinear dynamical system, the main essence of data driven means the actual output value in cost function for model predictive control is identified through input–output observed data in case of unknown but bounded noise and martingale difference sequence. After substituting the identified actual output in cost function, the total cost function in model predictive control is reformulated as its standard form, i.e. one quadratic program problem with input and output constraints. Then semidefinite relaxation scheme is used to derive a lower bound for its optimal value, and the robust counterpart of an uncertain quadratic program is reduced to one conic quadratic problem. The above semidefinite relaxation scheme and conic quadratic problem correspond to the similar robust analysis based on convex optimization theory. Finally, one simulation example is used to prove the efficiency of our proposed theory.
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- 2021
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11. Vehicle and Driver Monitoring System Using On-Board and Remote Sensors
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Andres E. Campos-Ferreira, Jorge de J. Lozoya-Santos, Juan C. Tudon-Martinez, Ricardo A. Ramirez Mendoza, Adriana Vargas-Martínez, Ruben Morales-Menendez, and Diego Lozano
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ADAS ,driver monitoring ,fuel consumption ,driving style ,emissions ,Chemical technology ,TP1-1185 - Abstract
This paper presents an integrated monitoring system for the driver and the vehicle in a single case of study easy to configure and replicate. On-board vehicle sensors and remote sensors are combined to model algorithms for estimating polluting emissions, fuel consumption, driving style and driver’s health. The main contribution of this paper is the analysis of interactions among the above monitored features highlighting the influence of the driver in the vehicle performance and vice versa. This analysis was carried out experimentally using one vehicle with different drivers and routes and implemented on a mobile application. Compared to commercial driver and vehicle monitoring systems, this approach is not customized, uses classical sensor measurements, and is based on simple algorithms that have been already proven but not in an interactive environment with other algorithms. In the procedure design of this global vehicle and driver monitoring system, a principal component analysis was carried out to reduce the variables used in the training/testing algorithms with objective to decrease the transfer data via Bluetooth between the used devices: a biometric wristband, a smartphone and the vehicle’s central computer. Experimental results show that the proposed vehicle and driver monitoring system predicts correctly the fuel consumption index in 84%, the polluting emissions 89%, and the driving style 89%. Indeed, interesting correlation results between the driver’s heart condition and vehicular traffic have been found in this analysis.
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- 2023
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12. Controller design for the closed loop system with non-interaction condition
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Wang Jianhong and Ricardo A. Ramirez-Mendoza
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non-interaction ,closed loop ,controller design ,optimality ,Control engineering systems. Automatic machinery (General) ,TJ212-225 ,Systems engineering ,TA168 - Abstract
For some complex systems with several controlled variables and with interaction between these controlled variables, one complex mathematical model is established to include lots of elements in the control matrix. In order to reduce the number of elements in the control matrix and increase real-time property in designing the unknown controllers, an idea of non-interaction property is introduced to simplify our mentioned closed loop system with many variables. To achieve the non-interaction property, some conditions are derived to guarantee one controlled input only influences one output. Based on this simplified model, the prediction error method coming from system identification field is applied to design the optimal controllers. The advantage of our prediction error method is that the optimal controller is a constant ratio of two polynomials. Finally one simulation example confirms our theoretical results.
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- 2020
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13. Zonotope parameter identification for piecewise affine system
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Hong Jianwang and Ricardo A. Ramirez-Mendoza
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piecewise affine system ,multi-class classification ,zonotope ,parameter identification ,Control engineering systems. Automatic machinery (General) ,TJ212-225 ,Systems engineering ,TA168 - Abstract
This paper studies one identification problem for a piecewise affine system which is a special nonlinear system. As the difficulty in identifying the piecewise affine system is to determine each separated region and each unknown parameter vector simultaneously, here we propose a multi-class classification process to determine each separated region. This multi-class classification process is similar to the classical data clustering process, and the merit of our strategy is that the first-order algorithm of convex optimization can be applied to achieve this classification process. Furthermore, to relax the strict probabilistic description on external noise and identify each unknown parameter vector, a zonotope parameter identification algorithm is proposed to compute a set that contains the parameter vector, consistent with the measured output and the given bound of the noise. To guarantee our derived zonotope not growing unbounded with iterations, a sufficient condition for this requirement to hold may be formulated as one linear matrix inequality. Finally, a numerical example confirms our theoretical results.
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- 2020
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14. Stability analysis for nonlinear closed loop system structure
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Wang Jianhong and Ricardo A. Ramirez-Mendoza
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stability analysis ,nonlinear closed loop ,finite gain stability ,inequality condition ,lipschitz continuous ,Control engineering systems. Automatic machinery (General) ,TJ212-225 ,Systems engineering ,TA168 - Abstract
In this paper, stability analysis is studied for the nonlinear closed loop system with a nonlinear plant and a nonlinear controller. Without the linearizing process for the nonlinear plant and the nonlinear controller, a Lipschitz continuous assumption of nonlinear plant is added and the notion of finite gain stability is defined. Then some inequalities about Lipschitz constants are derived to guarantee that the nonlinear system outputs are finite gain stability. To avoid the construction of the Lyapunov function, the convergence properties about the geometric series are applied to obtain two inequality conditions on the defined finite gain stability. Furthermore, one more complicated system, coming from engineering practice, is used to extend the nonlinear closed loop system, where the inner loop is applied to help another two controllers in achieving the desired tracking accuracy. Then the controller design for one flight simulation platform with six degrees of freedom confirms the theoretical results.
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- 2020
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15. Maize Inbred Line B96 Is the Source of Large-Effect Loci for Resistance to Generalist but Not Specialist Spider Mites
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Huyen Bui, Robert Greenhalgh, Gunbharpur S. Gill, Meiyuan Ji, Andre H. Kurlovs, Christian Ronnow, Sarah Lee, Ricardo A. Ramirez, and Richard M. Clark
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two-spotted spider mite (Tetranychus urticae) ,Tetranychus cinnabarinus ,Banks grass mite ,bulked segregant analysis (BSA) ,antibiosis ,Oligonychus pratensis ,Plant culture ,SB1-1110 - Abstract
Maize (Zea mays subsp. mays) yield loss from arthropod herbivory is substantial. While the basis of resistance to major insect herbivores has been comparatively well-studied in maize, less is known about resistance to spider mite herbivores, which are distantly related to insects and feed by a different mechanism. Two spider mites, the generalist Tetranychus urticae, and the grass-specialist Oligonychus pratensis, are notable pests of maize, especially during drought conditions. We assessed resistance (antibiosis) to both mites of 38 highly diverse maize lines, including several previously reported to be resistant to one or the other mite species. We found that line B96, as well as its derivatives B49 and B75, were highly resistant to T. urticae. In contrast, neither these three lines, nor any others included in our study, were notably resistant to the specialist O. pratensis. Quantitative trait locus (QTL) mapping with replicate populations from crosses of B49, B75, and B96 to susceptible B73 identified a QTL in the same genomic interval on chromosome 6 for T. urticae resistance in each of the three resistant lines, and an additional resistance QTL on chromosome 1 was unique to B96. Single-locus genotyping with a marker coincident with the chromosome 6 QTL in crosses of both B49 and B75 to B73 revealed that the respective QTL was large-effect; it explained ∼70% of the variance in resistance, and resistance alleles from B49 and B75 acted recessively as compared to B73. Finally, a genome-wide haplotype analysis using genome sequence data generated for B49, B75, and B96 identified an identical haplotype, likely of initial origin from B96, as the source of T. urticae resistance on chromosome 6 in each of the B49, B75, and B96 lines. Our findings uncover the relationship between intraspecific variation in maize defenses and resistance to its major generalist and specialist spider mite herbivores, and we identified loci for use in breeding programs and for genetic studies of resistance to T. urticae, the most widespread spider mite pest of maize.
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- 2021
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16. Environment Classification Using Machine Learning Methods for Eco-Driving Strategies in Intelligent Vehicles
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Jose del C. Julio-Rodríguez, Carlos A. Rojas-Ruiz, Alfredo Santana-Díaz, M. Rogelio Bustamante-Bello, and Ricardo A. Ramirez-Mendoza
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electric vehicles ,driving environment classification ,machine learning ,electromobility ,energy consumption ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
This work presents the development of a classification method that can contribute to precise and increased awareness of the situational context of vehicles, for it to be used in autonomous driving applications. This work aims to obtain a method for machine-learning-based driving environment classification that does not involve computer vision but instead makes use of dynamics variables from Inertial-Measurement-Unit (IMU) sensors and instantaneous energy consumption measurements. This article includes details about the data acquisition, the electric vehicle used for the experiments, and the pre-processing methods employed. This explores the viability of a method for classifying a vehicle’s driving environment. The results of such a system can potentially be used to provide precise information for path planning, energy optimization, or safety purposes. Information about the driving context could be also used to decide if the conditions are safe for autonomous driving or if human intervention is recommended or required. In this work, the feature selection process and statistical data pre-processing methods are evaluated. The pre-processed data are used to compare 13 different classification algorithms and then the best three are selected for further testing and data dimensionality reduction. Two approaches for feature selection based on feature importance and final classification scores are tested, achieving a classification mean accuracy of 93 percent with a real testing dataset that included three driving scenarios and eight different drivers. The obtained results and high classification accuracy represent a first approach for the further development of such classification systems and the potential for direct implementation into autonomous driving technology.
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- 2022
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17. Complementing cell taxonomies with a multicellular functional analysis of tissues
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Flores, Ricardo Omar Ramirez, Schäfer, Philipp Sven Lars, Küchenhoff, Leonie, and Saez-Rodriguez, Julio
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Quantitative Biology - Tissues and Organs ,Quantitative Biology - Cell Behavior - Abstract
The application of single-cell molecular profiling coupled with spatial technologies has enabled charting cellular heterogeneity in reference tissues and in disease. This new wave of molecular data has highlighted the expected diversity of single-cell dynamics upon shared external queues and spatial organizations. However, little is known about the relationship between single cell heterogeneity and the emergence and maintenance of robust multicellular processes in developed tissues and its role in (patho)physiology. Here, we present emerging computational modeling strategies that use increasingly available large-scale cross-condition single cell and spatial datasets, to study multicellular organization in tissues and complement cell taxonomies. This perspective should enable us to better understand how cells within tissues collectively process information and adapt synchronized responses in disease contexts and to bridge the gap between structural changes and functions in tissues., Comment: 36 pages, 4 figures
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- 2024
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18. Visualizing Street Pavement Anomalies through Fog Computing V2I Networks and Machine Learning
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Rogelio Bustamante-Bello, Alec García-Barba, Luis A. Arce-Saenz, Luis A. Curiel-Ramirez, Javier Izquierdo-Reyes, and Ricardo A. Ramirez-Mendoza
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smart mobility ,V2I ,fog computing ,smart cities ,intelligent transport systems ,Chemical technology ,TP1-1185 - Abstract
Analyzing data related to the conditions of city streets and avenues could help to make better decisions about public spending on mobility. Generally, streets and avenues are fixed as soon as they have a citizen report or when a major incident occurs. However, it is uncommon for cities to have real-time reactive systems that detect the different problems they have to fix on the pavement. This work proposes a solution to detect anomalies in streets through state analysis using sensors within the vehicles that travel daily and connecting them to a fog-computing architecture on a V2I network. The system detects and classifies the main road problems or abnormal conditions in streets and avenues using Machine Learning Algorithms (MLA), comparing roughness against a flat reference. An instrumented vehicle obtained the reference through accelerometry sensors and then sent the data through a mid-range communication system. With these data, the system compared an Artificial Neural Network (supervised MLA) and a K-Nearest Neighbor (Supervised MLA) to select the best option to handle the acquired data. This system makes it desirable to visualize the streets’ quality and map the areas with the most significant anomalies.
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- 2022
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19. Artificial Intelligence for Stability Control of Actuated In–Wheel Electric Vehicles with CarSim® Validation
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Riccardo Cespi, Renato Galluzzi, Ricardo A. Ramirez-Mendoza, and Stefano Di Gennaro
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electric vehicles ,in–wheel ,neural network ,inverse optimal control ,extended Kalman filter ,electric motors ,Mathematics ,QA1-939 - Abstract
This paper presents an active controller for electric vehicles in which active front steering and torque vectoring are control actions combined to improve the vehicle driving safety. The electric powertrain consists of four independent in–wheel electric motors situated on each corner. The control approach relies on an inverse optimal controller based on a neural network identifier of the vehicle plant. Moreover, to minimize the number of sensors needed for control purposes, the authors present a discrete–time reduced–order state observer for the estimation of vehicle lateral and roll dynamics. The use of a neural network identifier presents some interesting advantages. Notably, unlike standard strategies, the proposed approach avoids the use of tire lateral forces or Pacejka’s tire parameters. In fact, the neural identification provides an input–affine model in which these quantities are absorbed by neural synaptic weights adapted online by an extended Kalman filter. From a practical standpoint, this eliminates the need of additional sensors, model tuning, or estimation stages. In addition, the yaw angle command given by the controller is converted into electric motor torques in order to ensure safe driving conditions. The mathematical models used to describe the electric machines are able to reproduce the dynamic behavior of Elaphe M700 in–wheel electric motors. Finally, quality and performances of the proposed control strategy are discussed in simulation, using a CarSim® full vehicle model running through a double–lane change maneuver.
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- 2021
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20. Campus City Project: Challenge Living Lab for Smart Cities
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José I. Huertas, Jürgen Mahlknecht, Jorge de J. Lozoya-Santos, Sergio Uribe, Enrique A. López-Guajardo, and Ricardo A. Ramirez-Mendoza
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smart water/energy/mobility ,open innovation ,challenge living lab ,smart city ,challenge-based learning ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
This work presents the Campus City initiative followed by the Challenge Living Lab platform to promote research, innovation, and entrepreneurship with the intention to create urban infrastructure and creative talent (human resources) that solves different community, industrial and government Pain Points within a Smart City ecosystem. The main contribution of this work is to present a working model and the open innovation ecosystem used in Tecnologico de Monterrey that could be used as both, a learning mechanism as well as a base model for scaling it up into a Smart Campus and Smart City. Moreover, this work presents the Smart Energy challenge as an example of a pedagogic opportunity for the development of competencies. This included the pedagogic design of the challenge, the methodology followed by the students and the results. Finally, a discussion on the findings and learnings of the model and challenge implementation. Results showed that Campus City initiative and the Challenge Living Lab allows the identification of highly relevant and meaningful challenges while providing a pedagogic framework in which students are highly motivated, engaged, and prepared to tackle different problems that involve government, community, industry, and academia.
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- 2021
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21. Seeking Alfalfa Resistance to a Rhizophagous Pest, the Clover Root Curculio (Sitona hispidulus F.)
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Kaitlin Rim, Jamie Crawford, Steven J. Price, Donald R. Viands, and Ricardo A. Ramirez
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host-plant resistance ,screening ,feeding behavior ,oviposition ,belowground ,soil ,Science - Abstract
Since the cancellation of broad-spectrum soil-active insecticides in alfalfa (Medicago sativa L.) production, clover root curculio (Sitona hispidulus F.) (CRC) larval root damage has increased. Current CRC management practices are limited in their ability to suppress larval feeding belowground. First, we field screened developmental alfalfa populations for CRC damage. Subsequently, we developed a soil-less arena to observe nodule feeding and development (head capsule width) of larvae in the lab. This method was used to evaluate five alfalfa populations (two CRC-susceptible (control) and three CRC-resistant populations) against larvae. Further, one CRC-resistant population paired with its genetically similar susceptible population were tested against adult leaf consumption and oviposition in the greenhouse. Field screening revealed that the alfalfa populations selected for little or no larval root feeding damage were more resistant to CRC larval feeding than their corresponding unselected cultivars and significantly more resistant than populations selected for susceptibility. The development of a soil-less arena provided a useful method for evaluation of root-larva interactions. Although larval development was similar across susceptible and resistant alfalfa populations, one CRC-resistant population (NY1713) displayed overall increased nodulation and, thus, had a significantly lower proportion of nodules consumed by larvae. Adult feeding and oviposition aboveground were similar across all populations tested. These results provide possible candidates and screening method for the development and evaluation of alfalfa cultivars that may reduce the impacts of larval feeding and that offer an additional option for CRC management.
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- 2021
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22. Characterizing Billbug (Sphenophorus spp.) Seasonal Biology Using DNA Barcodes and a Simple Morphometric Analysis
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Marian M. Rodriguez-Soto, Douglas S. Richmond, Ricardo A. Ramirez, Xi Xiong, and Laramy S. Enders
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turfgrass ,IPM ,species complex ,COI ,18S ,ITS2 ,Science - Abstract
Billbugs (Sphenophorus spp.) are a complex of grass-feeding weevil species that reduce the aesthetic and functional qualities of turfgrass. Effective billbug monitoring and management programs rely on a clear understanding of their seasonal biology. However, our limited understanding of regional variation in the species compositions and seasonal biology of billbugs, stemming primarily from our inability to identify the damaging larval stage to species level, has hindered efforts to articulate efficient IPM strategies to growers. We used a combination of DNA barcoding methods and morphometric measures to begin filling critical gaps in our understanding of the seasonal biology of the billbug species complex across a broad geographic range. First, we developed a DNA barcoding reference library using cytochrome oxidase subunit 1 (COI) sequences from morphologically identified adult billbugs collected across Indiana, Missouri, Utah and Arizona. Next, we used our reference library for comparison and identification of unknown larval specimens collected across the growing season in Utah and Indiana. Finally, we combined our DNA barcoding approach with larval head capsule diameter, a proxy for developmental instar, to develop larval phenology charts. Adult COI sequences varied among billbug species, but variation was not influenced by geography, indicating that this locus alone was useful for resolving larval species identity. Overlaid with head capsule diameter data from specimens collected across the growing season, a better visualization of billbug species composition and seasonal biology emerged. This approach will provide researchers with the tools necessary to fill critical gaps in our understanding of billbug biology and facilitate the development of turfgrass pest management programs.
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- 2021
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23. The practical analysis for closed-loop system identification
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Wang Jianhong and Ricardo A. Ramirez-Mendoza
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closed loop system identification ,practical analysis ,optimal feedback controller ,Engineering (General). Civil engineering (General) ,TA1-2040 - Abstract
As the existed theories for closed-loop system identification are very mature, and in this short note, one common closed-loopclosed-loop system is considered, then the classical prediction error identification is reviewed for closed-loop system identification. Based on above-existed results on closed-loop system identification, here we continue to do some research on closed-loop system identification from the practical perspective. It means all mathematical derivations and results, proposed here are more general than those existed results from references, and all results are more suited for the practical application. More specifically, the cost function, used to minimize with respect to the unknown parameter, is derived again to its more simplified form. The identification for the unknown plant is obtained again from the point of its usual spectral analysis estimation. After choosing one suited coefficient matrix into the explicit expression about the cost function, one optimal feedback controller or optimal control input is derived to be global minimum. Our derived spectral analysis estimation, simplified cost function, and optimal feedback controller are beneficial for embodying the relations with all input– output signal and other variables, such as the true plant, parameter estimator, spectral analysis estimation etc. Finally, one simulation example has been performed to demonstrate the effectiveness of the theories proposed in this paper.
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- 2020
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24. A Systematic Review of Technologies, Control Methods, and Optimization for Extended-Range Electric Vehicles
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David Sebastian Puma-Benavides, Javier Izquierdo-Reyes, Juan de Dios Calderon-Najera, and Ricardo A. Ramirez-Mendoza
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extended range electric vehicle ,technologies ,optimization methods ,EREV key components ,level optimization ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
For smart cities using clean energy, optimal energy management has made the development of electric vehicles more popular. However, the fear of range anxiety—that a vehicle has insufficient range to reach its destination—is slowing down the adoption of EVs. The integration of an auxiliary power unit (APU) can extend the range of a vehicle, making them more attractive to consumers. The increased interest in optimizing electric vehicles is generating research around range extenders. These days, many systems and configurations of extended-range electric vehicles (EREVs) have been proposed to recover energy. However, it is necessary to summarize all those efforts made by researchers and industry to find the optimal solution regarding range extenders. This paper analyzes the most relevant technologies that recover energy, the current topologies and configurations of EREVs, and the state-of-the-art in control methods used to manage energy. The analysis presented mainly focuses on finding maximum fuel economy, reducing emissions, minimizing the system’s costs, and providing optimal driving performance. Our summary and evaluation of range extenders for electric vehicles seeks to guide researchers and automakers to generate new topologies and configurations for EVs with optimized range, improved functionality, and low emissions.
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- 2021
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25. Individual Drive-Wheel Energy Management for Rear-Traction Electric Vehicles with In-Wheel Motors
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Jose del C. Julio-Rodríguez, Alfredo Santana-Díaz., and Ricardo A. Ramirez-Mendoza
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electric vehicles ,electromobility ,in-wheel motors ,electronic differential ,wheel-speed control ,powertrain ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
In-wheel motor technology has reduced the number of components required in a vehicle’s power train system, but it has also led to several additional technological challenges. According to kinematic laws, during the turning maneuvers of a vehicle, the tires must turn at adequate rotational speeds to provide an instantaneous center of rotation. An Electronic Differential System (EDS) controlling these speeds is necessary to ensure speeds on the rear axle wheels, always guaranteeing a tractive effort to move the vehicle with the least possible energy. In this work, we present an EDS developed, implemented, and tested in a virtual environment using MATLAB™, with the proposed developments then implemented in a test car. Exhaustive experimental testing demonstrated that the proposed EDS design significantly improves the test vehicle’s longitudinal dynamics and energy consumption. This paper’s main contribution consists of designing an EDS for an in-wheel motor electric vehicle (IWMEV), with motors directly connected to the rear axle. The design demonstrated effective energy management, with savings of up to 21.4% over a vehicle without EDS, while at the same time improving longitudinal dynamic performance.
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- 2021
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26. GBUO: 'The Good, the Bad, and the Ugly' Optimizer
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Hadi Givi, Mohammad Dehghani, Zeinab Montazeri, Ruben Morales-Menendez, Ricardo A. Ramirez-Mendoza, and Nima Nouri
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optimization ,optimization algorithm ,population-based algorithm ,exploration ,exploitation ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
Optimization problems in various fields of science and engineering should be solved using appropriate methods. Stochastic search-based optimization algorithms are a widely used approach for solving optimization problems. In this paper, a new optimization algorithm called “the good, the bad, and the ugly” optimizer (GBUO) is introduced, based on the effect of three members of the population on the population updates. In the proposed GBUO, the algorithm population moves towards the good member and avoids the bad member. In the proposed algorithm, a new member called ugly member is also introduced, which plays an essential role in updating the population. In a challenging move, the ugly member leads the population to situations contrary to society’s movement. GBUO is mathematically modeled, and its equations are presented. GBUO is implemented on a set of twenty-three standard objective functions to evaluate the proposed optimizer’s performance for solving optimization problems. The mentioned standard objective functions can be classified into three groups: unimodal, multimodal with high-dimension, and multimodal with fixed dimension functions. There was a further analysis carried-out for eight well-known optimization algorithms. The simulation results show that the proposed algorithm has a good performance in solving different optimization problems models and is superior to the mentioned optimization algorithms.
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- 2021
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27. Binary Spring Search Algorithm for Solving Various Optimization Problems
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Mohammad Dehghani, Zeinab Montazeri, Ali Dehghani, Om P. Malik, Ruben Morales-Menendez, Gaurav Dhiman, Nima Nouri, Ali Ehsanifar, Josep M. Guerrero, and Ricardo A. Ramirez-Mendoza
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optimization ,Hooke’s law ,binary ,spring search algorithm ,binary spring search algorithm ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
One of the most powerful tools for solving optimization problems is optimization algorithms (inspired by nature) based on populations. These algorithms provide a solution to a problem by randomly searching in the search space. The design’s central idea is derived from various natural phenomena, the behavior and living conditions of living organisms, laws of physics, etc. A new population-based optimization algorithm called the Binary Spring Search Algorithm (BSSA) is introduced to solve optimization problems. BSSA is an algorithm based on a simulation of the famous Hooke’s law (physics) for the traditional weights and springs system. In this proposal, the population comprises weights that are connected by unique springs. The mathematical modeling of the proposed algorithm is presented to be used to achieve solutions to optimization problems. The results were thoroughly validated in different unimodal and multimodal functions; additionally, the BSSA was compared with high-performance algorithms: binary grasshopper optimization algorithm, binary dragonfly algorithm, binary bat algorithm, binary gravitational search algorithm, binary particle swarm optimization, and binary genetic algorithm. The results show the superiority of the BSSA. The results of the Friedman test corroborate that the BSSA is more competitive.
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- 2021
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28. Systematic Review of Exoskeletons towards a General Categorization Model Proposal
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Javier A. de la Tejera, Rogelio Bustamante-Bello, Ricardo A. Ramirez-Mendoza, and Javier Izquierdo-Reyes
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exoskeletons ,bioengineering ,biomechanics ,biomechatronics ,rehabilitation robotics ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
Exoskeletons are an essential part of humankind’s future. The first records regarding the subject were published several decades ago, and the field has been expanding ever since. Their developments will be imperative for humans in the coming decades due to our constant pursuit of physical enhancement, and the physical constraints the human body has. The principal purpose of this article is to formalize research in the field of exoskeletons and introduce the field to more researchers in hopes of expanding research in the area. Exoskeletons can assist and/or aid in the rehabilitation of a person. Recovery exoskeletons are mostly used in medical and research areas; performance exoskeletons can be used in any area. This systematic review explains the precedents of the exoskeletons and gives a general perspective on their general present-day use, and provides a general categorization model with a brief description of each category. Finally, this paper provides a discussion of the state-of-the-art, and the current control techniques used in exoskeletons.
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- 2020
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29. DM: Dehghani Method for Modifying Optimization Algorithms
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Mohammad Dehghani, Zeinab Montazeri, Ali Dehghani, Haidar Samet, Carlos Sotelo, David Sotelo, Ali Ehsanifar, Om Parkash Malik, Josep M. Guerrero, Gaurav Dhiman, and Ricardo A. Ramirez-Mendoza
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optimization ,Dehghani method ,modifying ,optimization algorithm ,population-based algorithm ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
In recent decades, many optimization algorithms have been proposed by researchers to solve optimization problems in various branches of science. Optimization algorithms are designed based on various phenomena in nature, the laws of physics, the rules of individual and group games, the behaviors of animals, plants and other living things. Implementation of optimization algorithms on some objective functions has been successful and in others has led to failure. Improving the optimization process and adding modification phases to the optimization algorithms can lead to more acceptable and appropriate solution. In this paper, a new method called Dehghani method (DM) is introduced to improve optimization algorithms. DM effects on the location of the best member of the population using information of population location. In fact, DM shows that all members of a population, even the worst one, can contribute to the development of the population. DM has been mathematically modeled and its effect has been investigated on several optimization algorithms including: genetic algorithm (GA), particle swarm optimization (PSO), gravitational search algorithm (GSA), teaching-learning-based optimization (TLBO), and grey wolf optimizer (GWO). In order to evaluate the ability of the proposed method to improve the performance of optimization algorithms, the mentioned algorithms have been implemented in both version of original and improved by DM on a set of twenty-three standard objective functions. The simulation results show that the modified optimization algorithms with DM provide more acceptable and competitive performance than the original versions in solving optimization problems.
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- 2020
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30. A Spring Search Algorithm Applied to Engineering Optimization Problems
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Mohammad Dehghani, Zeinab Montazeri, Gaurav Dhiman, O. P. Malik, Ruben Morales-Menendez, Ricardo A. Ramirez-Mendoza, Ali Dehghani, Josep M. Guerrero, and Lizeth Parra-Arroyo
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heuristic algorithms ,optimization ,spring force ,spring search ,spring ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
At present, optimization algorithms are used extensively. One particular type of such algorithms includes random-based heuristic population optimization algorithms, which may be created by modeling scientific phenomena, like, for example, physical processes. The present article proposes a novel optimization algorithm based on Hooke’s law, called the spring search algorithm (SSA), which aims to solve single-objective constrained optimization problems. In the SSA, search agents are weights joined through springs, which, as Hooke’s law states, possess a force that corresponds to its length. The mathematics behind the algorithm are presented in the text. In order to test its functionality, it is executed on 38 established benchmark test functions and weighed against eight other optimization algorithms: a genetic algorithm (GA), a gravitational search algorithm (GSA), a grasshopper optimization algorithm (GOA), particle swarm optimization (PSO), teaching–learning-based optimization (TLBO), a grey wolf optimizer (GWO), a spotted hyena optimizer (SHO), as well as an emperor penguin optimizer (EPO). To test the SSA’s usability, it is employed on five engineering optimization problems. The SSA delivered better fitting results than the other algorithms in unimodal objective function, multimodal objective functions, CEC 2015, in addition to the optimization problems in engineering.
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- 2020
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31. A New 'Doctor and Patient' Optimization Algorithm: An Application to Energy Commitment Problem
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Mohammad Dehghani, Mohammad Mardaneh, Josep M. Guerrero, Om Parkash Malik, Ricardo A. Ramirez-Mendoza, José Matas, Juan C. Vasquez, and Lizeth Parra-Arroyo
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optimization ,energy commitment (EC) ,doctor and patient optimization (DPO) ,power system ,energy carriers ,energy ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
Regular assessments of events taking place around the globe can be a conduit for the development of new ideas, contributing to the research world. In this study, the authors present a new optimization algorithm named doctor and patient optimization (DPO). DPO is designed by simulating the process of treating patients by a physician. The treatment process has three phases, including vaccination, drug administration, and surgery. The efficiency of the proposed algorithm in solving optimization problems compared to eight other optimization algorithms on a benchmark standard test function with 23 objective functions is been evaluated. The results obtained from this comparison indicate the superiority and quality of DPO in solving optimization problems in various sciences. The proposed algorithm is successfully applied to solve the energy commitment problem for a power system supplied by a multiple energy carriers system.
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- 2020
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32. Energy Commitment for a Power System Supplied by Multiple Energy Carriers System using Following Optimization Algorithm
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Mohammad Dehghani, Mohammad Mardaneh, Om Parkash Malik, Josep M. Guerrero, Ruben Morales-Menendez, Ricardo A. Ramirez-Mendoza, José Matas, and Abdullah Abusorrah
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energy ,energy commitment ,energy carrier ,multi-carrier energy ,following optimization algorithm ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
In today’s world, the development and continuation of life require energy. Supplying this energy demand requires careful and scientific planning of the energy provided by a variety of products, such as oil, gas, coal, electricity, etc. A new study on the operation of energy carriers called Energy Commitment (EC) is proposed. The purpose of the EC is to set a pattern for the use of energy carriers to supply energy demand, considering technical and economic constraints. EC is a constrained optimization problem that can be solved by using optimization methods. This study suggests the Following Optimization Algorithm (FOA) to solve the EC problem to achieve technical and economic benefits. Minimizing energy supply costs for the total study period is considered as an objective function. The FOA simulates social relationships among the community members who try to improve their community by following each other. Simulation is carried out on a 10-unit energy system supplied by various types of energy carriers that includes transportation, agriculture, industrial, residential, commercial, and public sectors. The results show that the optimal energy supply for a grid with 0.15447 Millions of Barrels of Oil Equivalent (MBOE) of energy demand costs 9.0922 millions dollar for a 24-h study period. However, if the energy supply is not optimal, the costs of operating energy carriers will increase and move away from the optimal economic situation. The economic distribution of electrical demand between 10 power plants and the amount of production units per hour of the study period is determined. The EC outputs are presented, which include an appropriate pattern of energy carrier utilization, energy demand supply costs, appropriate combination of units, and power plant production. The behavior and process of achieving the answer in the convergence curve for the implementation of FOA on EC indicates the exploration and exploitation capacity of FOA. Based on the simulated results, EC provides more information than Unit Commitment (UC) and analyzes the network more efficiently and deeply.
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- 2020
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33. Novel Design Methodology for DC-DC Converters Applying Metaheuristic Optimization for Inductance Selection
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Efrain Mendez, Israel Macias, Alexandro Ortiz, Pedro Ponce, Adriana Vargas-Martinez, Jorge de Jesús Lozoya-Santos, Ricardo A. Ramirez-Mendoza, Ruben Morales-Menendez, and Arturo Molina
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multi-objective optimization ,DC-DC converters ,energy harvesting ,EA ,ITAE ,small-signal ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
Nowadays in modern industrial applications, where the power supply efficiency is more important than the output noise performance, DC-DC converters are widely used in order to fulfill the requirements. Yet, component selection and precise estimation of parameters can improve the converter’s performance, leading to smaller and more efficient designs. Hence, metaheuristic optimization algorithms can be applied using the mathematical model of DC-DC converters, in order to optimize their performance through an optimal inductance selection. Therefore, this work presents a novel design methodology for DC-DC converters, where the inductance selection is optimized, in order to achieve an optimal relation between the inductance size and the required energy. Moreover, a multi-objective metaheuristic optimization is presented through the Earthquake Algorithm, for parameter estimation and component selection, using the inductance of a buck DC-DC converter as a case study. The experimental results validate the design methodology, showing ripple improvement and operating power range extension, which are key features to have an efficient performance in DC-DC converters. Results also confirm the Small-Signal Model of the circuit, as a correct objective function for the parameter optimization, achieving more than 90% of accuracy on the presented behavior.
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- 2020
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34. Design and Implementation of an IoT-Oriented Strain Smart Sensor with Exploratory Capabilities on Energy Harvesting and Magnetorheological Elastomer Transducers
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Jorge de-J. Lozoya-Santos, L. C. Félix-Herrán, Juan C. Tudón-Martínez, Adriana Vargas-Martinez, and Ricardo A. Ramirez-Mendoza
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smart sensor ,magnetorheological elastomer ,energy harvesting ,piezoelectric ,IoT ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
This work designed and implemented a new low-cost, Internet of Things-oriented, wireless smart sensor prototype to measure mechanical strain. The research effort explores the use of smart materials as transducers, e.g., a magnetorheological elastomer as an electrical-resistance sensor, and a cantilever beam with piezoelectric sensors to harvest energy from vibrations. The study includes subsequent and validated results with a magnetorheological elastomer transducer that contained multiwall carbon nanotubes with iron particles, generated voltage tests from an energy-harvesting system that functions with an array of piezoelectric sensors embedded in a rubber-based cantilever beam, wireless communication to send data from the sensor’s central processing unit towards a website that displays and stores the handled data, and an integrated manufactured prototype. Experiments showed that electrical-resistivity variation versus measured strain, and the voltage-generation capability from vibrations have the potential to be employed in smart sensors that could be integrated into commercial solutions to measure strain in automotive and aircraft systems, and civil structures. The reported experiments included cloud-computing capabilities towards a potential Internet of Things application of the smart sensor in the context of monitoring automotive-chassis vibrations and airfoil damage for further analysis and diagnostics, and in general structural-health-monitoring applications.
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- 2020
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35. End-to-End Automated Guided Modular Vehicle
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Luis A. Curiel-Ramirez, Ricardo A. Ramirez-Mendoza, Rolando Bautista-Montesano, M. Rogelio Bustamante-Bello, Hugo G. Gonzalez-Hernandez, Jorge A. Reyes-Avedaño, and Edgar Cortes Gallardo-Medina
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autonomous vehicle ,intelligent transportation systems ,deep learning ,automated guided vehicle ,end-to-end learning ,self-driving cars ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
Autonomous Vehicles (AVs) have caught people’s attention in recent years, not only from an academic or developmental viewpoint but also because of the wide range of applications that these vehicles may entail, such as intelligent mobility and logistics, as well as for industrial purposes, among others. The open literature contains a variety of works related to the subject. They employ a diversity of techniques ranging from probabilistic to ones based on Artificial Intelligence. The increase in computing capacity, well known to many, has opened plentiful opportunities for the algorithmic processing needed by these applications, making way for the development of autonomous navigation, in many cases with astounding results. The following paper presents a low-cost but high-performance minimal sensor open architecture implemented in a modular vehicle. It was developed in a short period of time, surpassing many of the currently available solutions found in the literature. Diverse experiments were carried out in the controlled and circumscribed environment of an autonomous circuit that demonstrates the efficiency of the applicability of the developed solution.
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- 2020
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36. Analytical Design and Optimization of an Automotive Rubber Bushing
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Jonathan Rivas-Torres, Juan C. Tudon-Martinez, Jorge de-J. Lozoya-Santos, Ricardo A. Ramirez-Mendoza, and Andrea Spaggiari
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Physics ,QC1-999 - Abstract
The ride comfort, driving safety, and handling of the vehicle should be designed and tuned to achieve the expectations defined in the company’s design. The ideal method of tuning the characteristics of the vehicle is to modify the bushings and mounts used in the chassis system. To deal with the noise, vibration and harshness on automobiles, elastomeric materials in mounts and bushings are determinant in the automotive components design, particularly those related to the suspension system. For most designs, stiffness is a key design parameter. Determination of stiffness is often necessary in order to ensure that excessive forces or deflections do not occur. Many companies use trial and error method to meet the requirements of stiffness curves. Optimization algorithms are an effective solution to this type of design problems. This paper presents a simulation-based methodology to design an automotive bushing with specific characteristic curves. Using an optimum design formulation, a mathematical model is proposed to design and then optimize structural parameters using a genetic algorithm. To validate the resulting data, a finite element analysis (FEA) is carried out with the optimized values. At the end, results between optimization, FEA, and characteristic curves are compared and discussed to establish the correlation among them.
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- 2019
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37. Combing Instrumental Variable and Variance Matching for Aircraft Flutter Model Parameters Identification
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Hong Jianwang, Ricardo A. Ramirez-Mendoza, and Jorge de J. Lozoya Santos
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Physics ,QC1-999 - Abstract
When the observed input-output data are corrupted by the observed noises in the aircraft flutter stochastic model, we need to obtain the more exact aircraft flutter model parameters to predict the flutter boundary accuracy and assure flight safety. So, here we combine the instrumental variable method in system identification theory and variance matching in modern spectrum theory to propose a new identification strategy: instrumental variable variance method. In the aircraft flutter stochastic model, after introducing instrumental variable to develop a covariance function, a new criterion function, composed by a difference between the theory value and actual estimation value of the covariance function, is established. Now, the new criterion function based on the covariance function can be used to identify the unknown parameter vector in the transfer function form. Finally, we apply this new instrumental variable variance method to identify the transfer function in one electrical current loop of flight simulator and aircraft flutter model parameters. Several simulation experiments have been performed to demonstrate the effectiveness of the algorithm proposed in this paper.
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- 2019
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38. Disturbance Rejection in a One-Half Semiactive Vehicle Suspension by means of a Fuzzy-H∞ Controller
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L. C. Félix-Herrán, Driss Mehdi, José de Jesús Rodríguez-Ortiz, Victor H. Benitez, Ricardo A. Ramirez‐Mendoza, and Rogelio Soto
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Physics ,QC1-999 - Abstract
A fuzzy-H∞ control, improved with weighting functions, has been designed and applied to a novel model of a one-half semiactive lateral vehicle (OHSLV) suspension. The herein contribution resides in the development and computation of an H∞ controller with parallel distributed compensation (PDC) designed from a highly nonlinear system modelled via the Takagi–Sugeno (T-S) fuzzy approach. A fuzzy-H∞ controller is synthesized for an OHSLV T-S fuzzy model of a suspension with two magnetorheological (MR) dampers including actuators’ nonlinear dynamics. The realism of results has been improved by considering the MR damper’s behaviours (viscoplasticity, hysteresis, and saturation) and the handling of the phase angle of the sinusoidal disturbance, not included in other reported work. Time-domain tests remark transient time achievements, whereas precise performance criterion indices in the frequency domain are employed to assess the generated outcomes. The proposed solution complies with all performance criteria compared with a benchmark passive average suspension that fails in satisfying most of the performance criteria.
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- 2019
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39. Generalist and Specialist Mite Herbivores Induce Similar Defense Responses in Maize and Barley but Differ in Susceptibility to Benzoxazinoids
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Huyen Bui, Robert Greenhalgh, Alice Ruckert, Gunbharpur S. Gill, Sarah Lee, Ricardo A. Ramirez, and Richard M. Clark
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Maize (Zea mays L.) ,Hordeum vulgare ,Tetranychus urticae ,Oligonychus pratensis ,benzoxazinoid ,spider mite ,Plant culture ,SB1-1110 - Abstract
While substantial progress has been made in understanding defense responses of cereals to insect herbivores, comparatively little is known about responses to feeding by spider mites. Nevertheless, several spider mite species, including the generalist Tetranychus urticae and the grass specialist Oligonychus pratensis, cause damage on cereals such as maize and wheat, especially during drought stress. To understand defense responses of cereals to spider mites, we characterized the transcriptomic responses of maize and barley to herbivory by both mite species, and included a wounding control against which modulation of defenses could be tested. T. urticae and O. pratensis induced highly correlated changes in gene expression on both maize and barley. Within 2 h, hundreds of genes were upregulated, and thousands of genes were up- or downregulated after 24 h. In general, expression changes were similar to those induced by wounding, including for genes associated with jasmonic acid biosynthesis and signaling. Many genes encoding proteins involved in direct defenses, or those required for herbivore-induced plant volatiles, were strongly upregulated in response to mite herbivory. Further, biosynthesis genes for benzoxazinoids, which are specialized compounds of Poaceae with known roles in deterring insect herbivores, were induced in maize. Compared to chewing insects, spider mites are cell content feeders and cause grossly different patterns of tissue damage. Nonetheless, the gene expression responses of maize to both mite herbivores, including for phytohormone signaling pathways and for the synthesis of the benzoxazinoid 2-hydroxy-4,7-dimethoxy-1,4-benzoxazin-3-one glucoside, a known defensive metabolite against caterpillars, resembled those reported for a generalist chewing insect, Spodoptera exigua. On maize plants harboring mutations in several benzoxazinoid biosynthesis genes, T. urticae performance dramatically increased compared to wild-type plants. In contrast, no difference in performance was observed between mutant and wild-type plants for the specialist O. pratensis. Collectively, our data provide little evidence that maize and barley defense responses differentiate herbivory between T. urticae and O. pratensis. Further, our work suggests that the likely route to specialization for O. pratensis involved the evolution of a robust mechanism to cope with the benzoxazinoid defenses of its cereal hosts.
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- 2018
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40. Evaluation and Predictive Modeling of Removal Condition for Bioadsorption of Indigo Blue Dye by Spirulina platensis
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Felipe Robledo-Padilla, Osvaldo Aquines, Arisbe Silva-Núñez, Gibrán S. Alemán-Nava, Carlos Castillo-Zacarías, Ricardo A. Ramirez-Mendoza, Ricardo Zavala-Yoe, Hafiz M. N. Iqbal, and Roberto Parra-Saldívar
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indigo blue dye ,spirulina platensis ,dye removal ,linear modeling ,Biology (General) ,QH301-705.5 - Abstract
Among the different chemical and physical treatments used to remove the color of the textile effluents, bioremediation offers many benefits to the environment. In this study, we determined the potential of Spirulina platensis (S. platensis) for decolorizing indigo blue dye under different incubation conditions. The microalgae were incubated at different pH (from 4 to 10) to calibrate for the optimal discoloration condition; a pH of 4 was found to be optimal. The biomass concentration in all experiments was 1 g/L, which was able to decolorize the indigo blue dye by day 3. These results showed that S. platensis is capable of removing indigo blue dye at low biomass. However, this was dependent on the treatment conditions, where temperature played the most crucial role. Two theoretical adsorption models, namely (1) a first-order model equation and (2) a second-order rate equation, were compared with observed adsorption vs. time curves for different initial concentrations (from 25 to 100 mg/L). The comparison between models showed similar accuracy and agreement with the experimental values. The observed adsorption isotherms for three temperatures (30, 40, and 50 °C) were plotted, showing fairly linear behavior in the measured range. The adsorption equilibrium isotherms were estimated, providing an initial description of the dye removal capacity of S. platensis.
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- 2020
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41. Experimenting with Soft Robotics in Education: A Systematic Literature Review from 2006 to 2022
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Israel Ulises Cayetano-Jimenez, Erick Axel Martinez-Rios, Rogelio Bustamante-Bello, Ricardo A. Ramirez-Mendoza, and Maria Soledad Ramirez-Montoya
- Abstract
Educational robotics (ER) is a discipline of applied robotics focused on teaching robot design, analysis, application, and operation. Traditionally, ER has favored rigid robots, overlooking the potential of soft robots (SRs). While rigid robots offer insights into dynamics, kinematics, and control, they have limitations in exploring the depths of mechanical design and material properties. In this regard, SRs present an opportunity to expand educational topics and activities in robotics through their unique bioinspired properties and accessibility. Despite their promise, there is a notable lack of research on SRs as educational tools, limiting the identification of research avenues that could promote their adoption in educational settings. This study conducts a systematic literature review to elucidate the impact of SRs across academic levels, pedagogical strategies, prevalent artificial muscles, educational activities, and assessment methods. The findings indicate a significant focus on K-12 workshops utilizing soft pneumatic actuators. Furthermore, SRs have fostered the development of fabrication and mechanical design skills beyond mere programming tasks. However, there is a shortage of studies analyzing their use in higher education or their impact on learning outcomes, suggesting a critical need for comprehensive evaluations to determine their effectiveness, rather than solely relying on surveys for student feedback. Thus, there is an opportunity to explore and evaluate the use of SRs in more advanced settings and multidisciplinary activities, urging for rigorous assessments of their influence on learning outcomes. By undertaking this, we aim to provide a foundation for integrating SRs into the ER curriculum, potentially transforming teaching methodologies and enriching students' learning experiences.
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- 2024
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42. Production of cellulose nano/microfibers through simultaneous milling and enzymatic hydrolysis with an optimized cocktail of cellulase/xylanase/LPMO
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Chaves de Carvalho, Lívia da Silva, Brenes, Ricardo Gonzalo. Ramírez, Grieco, Maria Angela, Bojorge, Ninoska, and Pereira, Nei, Jr.
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- 2024
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43. B-mode ultrasonography and ARFI elastography of articular and peri-articular structures of the hip joint in non-dysplastic and dysplastic dogs as confirmed by radiographic examination
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Carneiro, Rafael Kretzer, da Cruz, Igor Cezar Kniphoff, Gasser, Beatriz, Lima, Bruna, Aires, Luiz Paulo Nogueira, Ferreira, Márcio Poletto, Uscategui, Ricardo Andres Ramirez, Giglio, Robson Fortes, Minto, Bruno Watanabe, and Rossi Feliciano, Marcus Antônio
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- 2023
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44. Abdominal perfusion in canine patients with pyometra and sepsis evaluated by Doppler and contrast-enhanced ultrasound
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Gasser, Beatriz, Uscategui, Ricardo Andres Ramirez, Aires, Luiz Paulo Nogueira, Yamada, Diego Iwao, Del’Aguila-Silva, Priscila, Lima, Bruna Bressianini, Silva, Priscila, da Cruz, Igor Cezar Kniphoff, Carneiro, Rafael Kretzer, and Feliciano, Marcus Antônio Rossi
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- 2023
- Full Text
- View/download PDF
45. Ultrasonography and elastography of the brain and cerebellum of English Bulldog fetuses
- Author
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Pavan, Letícia, Gasser, Beatriz, Maronezi, Marjury Cristina, Silva, Priscila, Uscategui, Ricardo Andrés Ramirez, Padilha-Nakaghi, Luciana Cristina, Lima, Bruna Bressianini, Miranda, Brenda Santos Pompeu de, and Feliciano, Marcus Antônio Rossi
- Published
- 2023
- Full Text
- View/download PDF
46. An online database for einkorn wheat to aid in gene discovery and functional genomics studies.
- Author
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Parva Kumar Sharma, Hanin Ibrahim Ahmed, Matthias Heuberger, Dal-Hoe Koo, Jesus Quiroz-Chavez, Laxman Adhikari, John Raupp, Stéphane Cauet, Nathalie Rodde, Charlotte Cravero, Caroline Callot, Inderjit Singh Yadav, Nagarajan Kathiresan, Naveenkumar Athiyannan, Ricardo H. Ramirez-Gonzalez, Cristobal Uauy, Thomas Wicker, Michael Abrouk, Yong Q. Gu, Jesse Poland, Simon G. Krattinger, Gerard R. Lazo, and Vijay K. Tiwari
- Published
- 2023
- Full Text
- View/download PDF
47. Accuracy of B-mode ultrasound and ARFI elastography in predicting malignancy of canine splenic lesions
- Author
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Maronezi, Marjury Cristina, Carneiro, Rafael Kretzer, da Cruz, Igor Cezar Kniphoff, de Oliveira, Ana Paula Luiz, De Nardi, Andrigo Barboza, Pavan, Letícia, Del’Aguila-Silva, Priscila, Uscategui, Ricardo Andrés Ramirez, and Feliciano, Marcus Antônio Rossi
- Published
- 2022
- Full Text
- View/download PDF
48. Explainable multiview framework for dissecting spatial relationships from highly multiplexed data
- Author
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Tanevski, Jovan, Flores, Ricardo Omar Ramirez, Gabor, Attila, Schapiro, Denis, and Saez-Rodriguez, Julio
- Published
- 2022
- Full Text
- View/download PDF
49. Malignancy prediction of cutaneous and subcutaneous neoplasms in canines using B-mode ultrasonography, Doppler, and ARFI elastography
- Author
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da Cruz, Igor Cezar Kniphoff, Carneiro, Rafael Kretzer, de Nardi, Andrigo Barboza, Uscategui, Ricardo Andrés Ramirez, Bortoluzzi, Eduarda Mazzardo, and Feliciano, Marcus Antônio Rossi
- Published
- 2022
- Full Text
- View/download PDF
50. Two-Dimensional Shear-Wave Elastography of the Thyroid in Clinically Healthy Dogs in Different Age Groups
- Author
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Ramos, Denise Jaques, primary, Disselli, Tamiris, additional, Gomes, Diego Rodrigues, additional, Aires, Luiz Paulo Nogueira, additional, Tinto, Stéfany Tagliatela, additional, Salazar, Diana Villa Verde, additional, Pereira, Mariane Magno Ferreira, additional, Miranda, Brenda Santos Pompeu de, additional, Oliveira, Ana Paula Luiz de, additional, Lima, Bruna Bressianini, additional, Uscategui, Ricardo Andres Ramirez, additional, and Feliciano, Marcus Antônio Rossi, additional
- Published
- 2024
- Full Text
- View/download PDF
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