Relevant bibliographies by topics / Motor Intelligence

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
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Academic literature on the topic 'Motor Intelligence'

Author: Grafiati
Published: 10 March 2023

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Journal articles on the topic "Motor Intelligence"

1

Aschieri, Pierluigi. "Motor Intelligence." Revista de Artes Marciales Asiáticas 11, no. 2s (September 29, 2016): 10. http://dx.doi.org/10.18002/rama.v11i2s.4149.

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Bucur, C. "Artificial intelligence driven speed controller for DC motor in series." Scientific Bulletin of Naval Academy XIV, no. 2 (December 15, 2021): 83–88. http://dx.doi.org/10.21279/1454-864x-21-i2-007.

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Recently a lot of work have been done to implement artificial intelligence controllers in the field of electrical motors. This paper presents a novel speed controller, developed through Reinforcement learning techniques, applied to series dc motors. We emphasize the ease of developed controller in available off the shelf hardware for industrial use. We used the open- source Python package gym-electric-motor [1] for environment setup, pytorch framework for developing the controller and .NET for performance evaluation.
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Machrus Ali, Agus Raikhani, Hendi Sopian, and Izzatul Umami. "Optimasi Pengaturan Kecepatan Motor Shunt Berbasis Imperalist Competitive Algorithm (ICA)." Jurnal Intake : Jurnal Penelitian Ilmu Teknik dan Terapan 9, no. 1 (April 23, 2019): 26–31. http://dx.doi.org/10.48056/jintake.v9i1.38.

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Imperalist Competitive Algorithm (ICA) is one method of artificial intelligence inspired by competition for power. In system optimization this method gets better results than other artificial intelligence methods. DC shunt motors do not need a lot of space because of the small wire diameter, but the output power is very small because the amplifier current is small. A good shunt motor setting is needed to produce the desired motor speed. In this study PID controls were tuned using ICA. This good PID guide will get a good system optimization. As a comparison, the control of the shunt motor speed without control, with PID control, with detuning ICA PID control (PID-ICA). The results showed that the results of PID-ICA had the smallest overshot and undershot, with a speed of 500.00 rpm and the fastest settling time : 1201 s. This research will be developed using other artificial intelligence methods.
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Ali, Machrus, Agus Raikhani, Hendi Sopian, and Izzatul Umami. "Optimasi Pengaturan Kecepatan Motor Shunt Berbasis Imperalist Competitive Algorithm (ICA)." Jurnal Intake : Jurnal Penelitian Ilmu Teknik dan Terapan 9, no. 1 (April 20, 2020): 26–31. http://dx.doi.org/10.32492/jintake.v9i1.756.

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Imperalist Competitive Algorithm (ICA) is one method of artificial intelligence inspired by competition for power. In system optimization this method gets better results than other artificial intelligence methods. DC shunt motors do not need a lot of space because of the small wire diameter, but the output power is very small because the amplifier current is small. A good shunt motor setting is needed to produce the desired motor speed. In this study PID controls were tuned using ICA. This good PID guide will get a good system optimization. As a comparison, the control of the shunt motor speed without control, with PID control, with detuning ICA PID control (PID-ICA). The results showed that the results of PID-ICA had the smallest overshot and undershot, with a speed of 500.00 rpm and the fastest settling time : 1201 s. This research will be developed using other artificial intelligence methods.
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Roberto Cabral da Silva, Edison, Hubert Razik, Lane Maria Rabelo Baccarini, Maurício Beltrão de Rossiter Corrêa, and Cursino Brandão Jacobina. "Application Of Some Artificial Intelligence Techniques In Induction Motor Fault Diagnosis." Eletrônica de Potência 16, no. 3 (August 1, 2011): 241–48. http://dx.doi.org/10.18618/rep.20113.241248.

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Horička, Pavol, and Jaromír Šimonek. "Relationship between motor learning and general intelligence." Studia sportiva 16, no. 1 (August 1, 2022): 44–53. http://dx.doi.org/10.5817/sts2022-1-5.

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AIM: The aim of the research was to find out the differences in the level of motor learning (ML) and general intelligence (IQ). The research sample included 120 boys and girls of primary school and grammar school aged 12-17 years and the subsequent identification of a possible relationship between the two indicators. METHODS: 120 students Elementary school (ES) and Secondary Grammar School (SGS) took part in testing the level of motor learning and intelligence (n = 120). We evaluated the level of ML in boys and girls in the demonstration of learned gymnastic elements. We used the intelligence test to determine the level of general intelligence [1]. RESULTS: The results did not show significant differences in the level of motor learning and intelligence between the genders in either age category. Correlation analysis confirmed a significant relationship between ML and IQ excluding the gender factor (r = -0.297). When gender was taken into account, the relationship was seen only in boys (r = -0.312). We note that we found a lower rate of ML in students with a higher level of intelligence. CONCLUSION: We assume the continuity of certain mental and motor processes, which is called motor intelligence. The results of our research did not show significant differences in the level of ML and IQ in both genders. Boys slightly dominated in ML, girls in IQ. This difference decreases with increasing age.
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Ardiansyah, Ardiansyah. "MENGEMBANGKAN KECERDASAN MULTIPLE INTELLEGENCE ANAK USIA DINI." Musawa: Journal for Gender Studies 13, no. 1 (June 30, 2021): 106–33. http://dx.doi.org/10.24239/msw.v13i1.742.

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The golden age is a period that cannot be repeated again. This period also determines the life of a human being in the future. When learning there are aspects that experience development, namely cognitive, abstract thinking, creative thinking, social-emotional, motor, language or communication, and can also develop creativity. So from this aspect it can improve the development of children's multiple intelligences. Multiple Intelligences include verbal linguistics, logical-mathematical, visual spatial, musical, kinetic, intrapersonal, interpersonal, naturalist and existential. The purpose of this study is to analyze how multiple intelligences can be developed in early childhood. With this research, parents can recognize the intelligence of children and even direct and develop intelligence to the fullest. This research is a qualitative research with literature study. The results of this study are Multiple Intelligence in the aspect of linguistic intelligence and Interpersonal intelligence is very important to be developed in early childhood, because it becomes a bridge in developing children's intelligence, the development of linguistic intelligence provides communication and socialization skills and expresses children to the outside world, while Interpersonal intelligence provides the ability to manage emotional-social so that it becomes a controller for children in thinking and acting towards maturity.
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Ardiansyah, Ardiansyah, and Moh. Alamsyah. "MENGEMBANGKAN KECERDASAN MULTIPLE INTELLEGENCE ANAK USIA DINI." Musawa: Journal for Gender Studies 13, no. 1 (June 30, 2021): 106–33. http://dx.doi.org/10.24239/msw.v13i1.746.

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The golden age is a period that cannot be repeated again. This period also determines the life of a human being in the future. When learning there are aspects that experience development, namely cognitive, abstract thinking, creative thinking, social-emotional, motor, language or communication, and can also develop creativity. So from this aspect it can improve the development of children's multiple intelligences. Multiple Intelligences include verbal linguistics, logical-mathematical, visual spatial, musical, kinetic, intrapersonal, interpersonal, naturalist and existential. The purpose of this study is to analyze how multiple intelligences can be developed in early childhood. With this research, parents can recognize the intelligence of children and even direct and develop intelligence to the fullest. This research is a qualitative research with literature study. The results of this study are Multiple Intelligence in the aspect of linguistic intelligence and Interpersonal intelligence is very important to be developed in early childhood, because it becomes a bridge in developing children's intelligence, the development of linguistic intelligence provides communication and socialization skills and expresses children to the outside world, while Interpersonal intelligence provides the ability to manage emotional-social so that it becomes a controller for children in thinking and acting towards maturity.
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Oktariana, Riza, Anita Yus, and Sanusi Hasibuan. "Bakiak and Interpersonal Intelligence on Physical Motor of Children in Khairani Kindergarten of Aceh Besar." Britain International of Humanities and Social Sciences (BIoHS) Journal 1, no. 2 (October 10, 2019): 205–12. http://dx.doi.org/10.33258/biohs.v1i2.53.

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Physical motor development is one of the five aspects of early childhood development, to achieve the motoric development, especially rough motoric is done through games. Play activities can stimulate a children’s physical motor development , and become one of the other important factors in improving a children’s psychic interpersonal intelligence. Based on this background, the researchers chose the title “Bakiak and Interpersonal Intelligence on Physical Motor of Children in Khairani Kindergarten of Aceh Besar”. Problems formulation in this study are: Is there any effect of bakiak game on children’s physical motor development , is there any effect of interpersonal intelligence on a children's physical motor development, and is there any interaction of bakiak game and interpersonal intelligence on a children’s physical motor development. The research objectives are: To determine the effect of bakiak game on children's physical motor, to determine the effect of interpersonal intelligence on children's physical motor development and to determine the interaction of bakiak game and interpersonal intelligence on children’s physical motor development . The location of the study was conducted at Khairani Kindergarten in Aceh Besar located in Lubok Batee village, Ingin Jaya Subdistricr, Aceh Besar District. This study was conducted on 15 October to 15 December 2018. The research subject of children's group B which amounted to 30 people, consisting of B1 (15 people) and B2 (15 people). This study was conducted by using experimental methods and research design with treatment by level 2 x 2. The research instrument used were bakiak game, interpersonal intelligence observation sheets and motor physical development tests. Research procedures are pretest, treatment, posttest, data processing, data analysis and conclusion. Meet the instrument validity and reliability standards. Data analysis techniques use descriptive data released by Mean, Median, Mode, frequency distribution table and histogram. Testing the analysis prerequisites that is normality and homogeneity data. From the results of data analysis obtained by this study shows the effect of bakiak game and interpersonal intelligence on physical motor of children in Khairani Kindergarten of Aceh Besar
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Real-Pérez, Mateo, Juan Gavala-González, Mar Artacho Silva, and José Carlos Fernández-García. "“Cognition, Intelligence and Movement”: Extracurricular Physical Activity as a Promoter of Intelligence in Schoolchildren." Sustainability 14, no. 7 (March 29, 2022): 4061. http://dx.doi.org/10.3390/su14074061.

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The main objective of this study was to assess the existence of significant relationships between motor capacity, academic performance and intelligence in a sample of 67 pre-adolescent children, between the ages of 8 and 11 years. Speed tests were carried out (10 × 5 m shuttle run and plate tapping test), and academic grades in Spanish Language and Literature, Mathematics, Natural Sciences, Foreign Language (English) and Physical Education were considered. The Raven test was administered to estimate the intelligence of the subjects. The results showed significant correlations, mainly between the motor capacities and intelligence variables but not with academic performance. Significant differences were also observed in subjects who participated in sports, with better results in motor capacities and intelligence tests compared to those who did not. The data reveal that engaging in intense physical activity and sports in general may improve academic performance.
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Dissertations / Theses on the topic "Motor Intelligence"

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Knight, Peter Robin. "Artificial intelligence and mathematical models for intelligent management of aircraft data." Thesis, University of Southampton, 2012. https://eprints.soton.ac.uk/355717/.

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Increasingly, large volumes of aircraft data are being recorded in an effort to adapt aircraft maintenance procedures from being time-based towards condition-based techniques. This study uses techniques of artificial intelligence and develops mathematical models to analyse this data to enable improvements to be made in aircraft management, affordability, availability, airworthiness and performance. In addition, it highlights the need to assess the integrity of data before further analysis and presents the benefits of fusing all relevant data sources together. The research effort consists of three separate investigations that were undertaken and brought together in order to provide a unified set of methods aimed at providing a safe, reliable, effective and efficient overall procedure. The three investigations are: 1. The management of helicopter Health Usage Monitoring System (HUMS) Condition Indicators (CIs) and their analysis, using a number of techniques, including adaptive thresholds and clustering. These techniques were applied to millions of CI values from Chinook HUMS data. 2. The identification of fixed-wing turbojet engine performance degradation, using anomaly detection techniques, applied to thousands of in-service engine runs from Tornado aircraft. 3. The creation of models to identify unusual aircraft behaviour, such as uncommanded flight control movements. Two Chinook helicopter systems were modelled and the models were applied to over seven hundred in-service flights. In each case, the existing techniques were directed toward a condition-based maintenance approach, giving improved detection and earlier warning of faults.
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Gadoue, Shady Mostafa. "Artificial intelligence applied to speed sensorless induction motor drives." Thesis, University of Newcastle Upon Tyne, 2009. http://hdl.handle.net/10443/1613.

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During the last two decades there has been considerable development of sensorless vector controlled induction motor drives for high performance industrial applications. Such control strategies reduce the drive's cost, size and maintenance requirements while increasing the system's reliability and robustness. Parameter sensitivity, high computational effort and instability at low and zero speed can be the main shortcomings of sensorless control. Sensorless drives have been successfully applied for medium and high speed operation, but low and zero speed operation is still a critical problem. Much recent research effort is focused on extending the operating region of sensorless drives near zero stator frequency. Several strategies have been proposed for rotor speed estimation in sensorless induction motor drives based on the machine fundamental excitation model. Among these techniques Model Reference Adaptive Systems (MRAS) schemes are the most common strategies employed due to their relative simplicity and low computational effort. Rotor flux-MRAS is the most popular MRAS strategy and significant attempts have been made to improve the performance of this scheme at low speed. Artificial Intelligence (AI) techniques have attracted much attention in the past few years as powerful tools to solve many control problems. Common AI strategies include neural networks, fuzzy logic and genetic algorithms. The mam purpose of this work is to show that AI can be used to improve the sensorless performance of the well-established MRAS observers in the critical low and zero speed region of operation. This thesis proposes various novel methods based on AI combined with MRAS observers. These methods have been implemented via simulation but also on an experimental drive based around a commercial induction machine. Detailed simulations and experimental tests are carried out to investigate the performance of the proposed schemes when compared to the conventional rotor fluxMRAS. Various schemes are implemented and tested in real time using a 7.5 kW induction machine and a dSP ACE DS 1103 controller board. The results presented for these new schemes show the great improvement in the performance of the MRAS observer in both open loop and sensorless modes of operation at low and zero speed.
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Shergold, Carol. "Sensory-motor coordination : adapting to disruptions." Thesis, University of Sussex, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.341079.

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Ben, Amor Heni. "Imitation Learning of Motor Skills for Synthetic Humanoids." Doctoral thesis, Technische Universitaet Bergakademie Freiberg Universitaetsbibliothek "Georgius Agricola", 2010. http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-62877.

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This thesis addresses the question of how to teach dynamic motor skills to synthetic humanoids. A general approach based on imitation learning is presented and evaluated on a number of synthetic humanoids, as well as a number of different motor skills. The approach allows for intuitive and natural specification of motor skills without the need for expert knowledge. Using this approach we show that various important problems in robotics and computer animation can be tackled, including the synthesis of natural grasping, the synthesis of locomotion behavior or the physical interaction between humans and robots.
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Lucchetta, Linda. "La Business Intelligence per il monitoraggio delle vendite: il caso Ducati Motor Holding." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/11733/.

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“La Business Intelligence per il monitoraggio delle vendite: il caso Ducati Motor Holding”. L’obiettivo di questa tesi è quello di illustrare cos’è la Business Intelligence e di mostrare i cambiamenti verificatisi in Ducati Motor Holding, in seguito alla sua adozione, in termini di realizzazione di report e dashboard per il monitoraggio delle vendite. L’elaborato inizia con una panoramica generale sulla storia e gli utilizzi della Business Intelligence nella quale vengono toccati i principali fondamenti teorici: Data Warehouse, data mining, analisi what-if, rappresentazione multidimensionale dei dati, costruzione del team di BI eccetera. Si proseguirà mediante un focus sui Big Data convogliando l’attenzione sul loro utilizzo e utilità nel settore dell’automotive (inteso nella sua accezione più generica e cioè non solo come mercato delle auto, ma anche delle moto), portando in questo modo ad un naturale collegamento con la realtà Ducati. Si apre così una breve overview sull’azienda descrivendone la storia, la struttura commerciale attraverso la quale vengono gestite le vendite e la gamma dei prodotti. Dal quarto capitolo si entra nel vivo dell’argomento: la Business Intelligence in Ducati. Si inizia descrivendo le fasi che hanno fino ad ora caratterizzato il progetto di Business Analytics (il cui obiettivo è per l'appunto introdurre la BI i azienda) per poi concentrarsi, a livello prima teorico e poi pratico, sul reporting sales e cioè sulla reportistica basata sul monitoraggio delle vendite.
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Baqqar, Mabrouka. "Machine performance and condition monitoring using motor operating parameters through artificial intelligence techniques." Thesis, University of Huddersfield, 2015. http://eprints.hud.ac.uk/id/eprint/28315/.

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Condition monitoring (CM) of gearboxes is a necessary activity due to the crucial importance of gearboxes in power transmission in most industrial applications. There has long been pressure to improve measuring techniques and develop analytical tools for early fault detection in gearboxes. This thesis develops new gearbox monitoring methods by demonstrating that operating parameters (static data) obtained from machine control processes can be used, rather than parameters obtained from vibration and acoustic measurements. Such a development has important implications for the future of CM techniques because it could greatly simplify the measurement process. To monitor the gearbox under different operating and fault conditions based on the static data, three artificial intelligence (AI) techniques: a general regression neural network (GRNN), a back propagation neural network (BPNN), and an adaptive neuro-fuzzy inference system (ANFIS) have been used successfully to capture nonlinear variations of the electric motor current and control parameters such as load settings and temperatures. The three AI systems are taught the expected values of current; load and temperature for the gearbox in a given condition, and then measured values obtained from the gearbox with a known fault introduced are assessed by each of the AI models to indicate the presence of this abnormal condition. The experimental results show that each of GRNN, BPNN and ANFIS are adequate and are able to serve as an effective tool for gearbox condition monitoring and fault detection. The main contributions of this study is to examine the performance of a model based condition monitoring approach by using just operating parameters for fault detection in a two stage gearbox. A model for current prediction is developed using an ANFIS, GRNN and BPNN which captures the complicated inter-relations between measured variables, and uses direct comparison between the measured and predicted values for fault detection.
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PONTE, CHIARA. "Motor learning in Parkinson's Disease." Doctoral thesis, Università degli studi di Genova, 2022. http://hdl.handle.net/11567/1094283.

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The primary objective of these studies was to investigate motor learning processes through innovative approaches: (i) a new combined take that integrates motor sequence learning and motor adaptation; (ii) developing a computational model able to mimic real healthy subjects data. In this work, we first investigated the interaction of visuomotor adaptation and sequence learning in the early acquisition phase. Our results showed that simultaneous learning selectively affects both in different ways compared to sequence learning and rotation adaptation alone. Furthermore, our results showed significant differences in the number of anticipatory movements by comparing the combined task with the sequence learning alone. In particular, at the end of the training phase, subjects better anticipate the sequence in the explicit task alone. This finding corroborates a higher verbal score in the explicit task than combined. A second study aimed to understand motor learning processes in their early stage by computing a computational model that mimics the neurophysiological mechanism underpinning motor learning. We developed an integrated model (characterized by a combination of supervised and reinforcement learning) that exhibits a faster learning process concerning the classic reinforcement learning model. This faster learning process of the integrated model was due to its improved exploration strategy. In particular, since the model gets the reward for the first time, the supervised component can learn a first coarse trajectory to reach the target. This trajectory affects the exploration by reducing its randomness and making it more focused on the target. The RL component then gradually improves the sub-optimal initial solution trial after trial while avoiding unneeded explorations as in the pure RL model. Similarly, the SL component gradually improves its behavior by receiving a better teaching signal (trajectories) from the RL processes. This mutual training between SL and RL thus produced a faster learning process.
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Muñoz, Mauro Enrique de Souza. "Desenvolvimento artificial autônomo de um grafo sensório-motor auto-organizável." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/3/3142/tde-28062016-081717/.

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A teoria de Jean Piaget sobre o desenvolvimento da inteligência tem sido utilizada na área de inteligência computacional como inspiração para a proposição de modelos de agentes cognitivos. Embora os modelos propostos implementem aspectos básicos importantes da teoria de Piaget, como a estrutura do esquema cognitivo, não consideram o problema da fundamentação simbólica e, portanto, não se preocupam com os aspectos da teoria que levam à aquisição autônoma da semântica básica para a organização cognitiva do mundo externo, como é o caso da aquisição da noção de objeto. Neste trabalho apresentamos um modelo computacional de esquema cognitivo inspirado na teoria de Piaget sobre a inteligência sensório-motora que se desenvolve autonomamente construindo mecanismos por meio de princípios computacionais pautados pelo problema da fundamentação simbólica. O modelo de esquema proposto tem como base a classificação de situações sensório-motoras utilizadas para a percepção, captação e armazenamento das relações causais determiníscas de menor granularidade. Estas causalidades são então expandidas espaço-temporalmente por estruturas mais complexas que se utilizam das anteriores e que também são projetadas de forma a possibilitar que outras estruturas computacionais autônomas mais complexas se utilizem delas. O modelo proposto é implementado por uma rede neural artificial feed-forward cujos elementos da camada de saída se auto-organizam para gerar um grafo sensóriomotor objetivado. Alguns mecanismos computacionais já existentes na área de inteligência computacional foram modificados para se enquadrarem aos paradigmas de semântica nula e do desenvolvimento mental autônomo, tomados como base para lidar com o problema da fundamentação simbólica. O grafo sensório-motor auto-organizável que implementa um modelo de esquema inspirado na teoria de Piaget proposto neste trabalho, conjuntamente com os princípios computacionais utilizados para sua concepção caminha na direção da busca pelo desenvolvimento cognitivo artificial autônomo da noção de objeto.
In artificial intelligence some cognitive agent models based on Jean Piaget\'s intelligence development theory have been proposed. Although the proposed models implement some fundamental aspects of this theory, like the cognitive schema struture, they do not consider the symbol grounding problem. Therefore, they are not concerned about the theoretical aspects that lead to the autonomous aquisition of the basic semantics needed by the cognitive organization of the agent\'s external world, as for the object concept aquisition. A computational cognitive scheme model inspired on Piaget\'s theory of the sensorimotor intelligence is presented. The scheme is autonomously built by computational mechanisms using principles considering the symbol grounding problem. The proposed scheme model uses sensory-motor situations to perceive, capture and store the finest grain deterministic causal relations. These causal relations are then expanded in time and space by more complex computational structures using the first ones. Those complex structures itselves are also designed in a way they can be used by more complex structures, expanding even further the causal relations in time and space. The proposed scheme model is implemented by an artificial neural network using feedforward architecture. The neural network output layer units progressively organized to compose a sensory-motor graph. Some known computational mechanisms from artificial inteligence were modified to fit to the zero semantic and the autonomous mental development paradigms, conceived in this work as the premises to handle the symbol grounding problem. The scheme model inspired by Piaget\'s theory implemented by the proposed self organizing sensorimotor graph in conjunction with the computational principles used, goes toward to the artificial autonomous cognitive development of the object concept.
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Doss, Roger Ron. "The Relationship Between Low Achievement and Bodily-kinesthetic Intelligence in Fourth and Fifth Graders." Thesis, University of North Texas, 1992. https://digital.library.unt.edu/ark:/67531/metadc332760/.

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The problem of this study was an examination of the relationship between low achievement and physical abilities.This study focuses on the areas of musical, interpersonal, intrapersonal, spatial and bodily-kinesthetic abilities. This correlational study found that low achievers as a group, identified by achievement test scores, scored above the mean on a measure of motor ability. For children who are struggling to achieve in school, it would seem prudent to explore their strengths in other areas of intelligence. Further research is suggested in the areas of high and average achieving students' motor development.
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Ogunoiki, Adebola Oluwaseyi. "Artificial road input data generation tool for vehicle durability assessment using artificial intelligence." Thesis, University of Birmingham, 2015. http://etheses.bham.ac.uk//id/eprint/6156/.

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Vehicle durability assessment in the automotive industry requires a good knowledge of the road load input the vehicle will experience while in service. This research explores the approach of artificial intelligence for predicting the road load input for road load simulation in the CAE environment prior to the development of a vehicle prototype. The multi-body dynamics (MBD) simulation of a quarter vehicle test rig, built with the specification of a commercial SUV, and the full vehicle of the same SUV were modelled and validated in SIMPACK using a simple tyre model developed using the tri-axial tyre test rig at the University of Birmingham. The models were used to carry out a road load data characterisation based on the variation in vehicle parameters. An artificial road input tool (ARIT) based on an optimised NARX artificial neural network architecture was developed to predict the road input for variants of vehicle for a particular vehicle behaviour over a road event. The results of the ARIT were used to run MBD simulations and compared with those from drive file iteration. The results of this research show a successful method of artificial intelligence for the generation of road load data from CAE simulations.
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Books on the topic "Motor Intelligence"

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Heuer, Herbert. Motor Behavior: Programming, Control, and Acquisition. Berlin, Heidelberg: Springer Berlin Heidelberg, 1985.

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Intelligenz und Psychomotorik: Vergleich von Schülern differenter Schultypen. Idstein: Schulz-Kirchner Verlag, 1985.

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L' intelligenza del corpo: Scuola e movimento. Teramo: Giunti & Lisciani, 1985.

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Lowrie, James. The Autonomous Land Vehicle (ALV) program: Third quarterly report. Fort Belvoir, Va: U.S. Army Engineer Topographic Laboratories, 1986.

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Dolezal, Michael J. A simulation study of a speed control system for autonomous on-road operation of automotive vehicles. Monterey, Calif: Naval Postgraduate School, 1987.

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Lowrie, James. The autonomous land vehicle: 2nd quarterly report. Fort Belvoir, Va: U.S. Army Engineer Topographic Laboratories, 1986.

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Lowrie, James. The autonomous land vehicle: 1st quarterly report. Fort Belvoir, Va: U.S. Army Engineer Topographic Laboratories, 1986.

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Pierre, Bessière, Laugier Christian, and Siegwart Roland, eds. Probabilistic reasoning and decision making in sensory-motor systems. Berlin: Springer, 2008.

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Skill acquisition rates and patterns: Issues and training implications. New York: Springer-Verlag, 1987.

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The important early years: Intelligence through movement experiences. Reston, VA: American Alliance for Health, Physical Education, Recreation and Dance, 1991.

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Book chapters on the topic "Motor Intelligence"

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Goertzel, Ben. "Motor Learning." In The Structure of Intelligence, 141–47. New York, NY: Springer New York, 1993. http://dx.doi.org/10.1007/978-1-4612-4336-6_11.

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Mylopoulos, Myrto. "The Intelligence of Motor Control." In The Routledge Handbook of Philosophy of Skill And Expertise, 258–68. Abingdon, Oxon; New York, NY: Routledge, 2021. | Series: Routledge handbooks in philosophy: Routledge, 2020. http://dx.doi.org/10.4324/9781315180809-25.

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Huang, Guo-Qing, and Xin Wu. "Analysis of Permanent-Magnet Synchronous Motor Chaos System." In Artificial Intelligence and Computational Intelligence, 257–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23881-9_33.

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Wen, Chuanbo, and Yun Liang. "A New Fault Detection Method of Induction Motor." In Artificial Intelligence and Computational Intelligence, 1–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16527-6_1.

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Karpathy, Andrej, and Michiel van de Panne. "Curriculum Learning for Motor Skills." In Advances in Artificial Intelligence, 325–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30353-1_31.

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Xue, Heng, Chunlan Jiang, and Zaicheng Wang. "Design and Experimental Study on Spinning Solid Rocket Motor." In Artificial Intelligence and Computational Intelligence, 715–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-05253-8_78.

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Nguyen, Phuoc, Dat Tran, Xu Huang, and Wanli Ma. "Motor Imagery EEG-Based Person Verification." In Advances in Computational Intelligence, 430–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38682-4_46.

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Chen, Jingyao, Chen Wang, Pu Zhang, Zeng-Guang Hou, Pingye Deng, Ningcun Xu, and Chutian Zhang. "An Intelligent Assessment System for Human Motor Functions of Stroke Patients." In Artificial Intelligence, 291–302. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-20500-2_24.

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Kakkos, Ioannis, Stavros-Theofanis Miloulis, Kostakis Gkiatis, Georgios N. Dimitrakopoulos, and George K. Matsopoulos. "Human–Machine Interfaces for Motor Rehabilitation." In Advanced Computational Intelligence in Healthcare-7, 1–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-61114-2_1.

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Zhang, Yinhai, Jinfa Ge, Weixia Liu, and Qin Wang. "An Experimental Research on Vector Control of Induction Motor Based on Simple Model." In Artificial Intelligence and Computational Intelligence, 1–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-05253-8_1.

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Conference papers on the topic "Motor Intelligence"

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Inoue, Daisuke, Arif Rashedul Kabir, and Akira Kakugo. "Intelligence of reconstructed biomolecular motor system." In 9th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS). ACM, 2016. http://dx.doi.org/10.4108/eai.3-12-2015.2262588.

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Abu-Rub, Haithem, Abdel Karim Awwad, and Noreddin Motan. "Artificial Intelligence Sensorless Control of Induction Motor." In 2007 Compatibility in Power Electronics. IEEE, 2007. http://dx.doi.org/10.1109/cpe.2007.4296530.

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Mediouni, Hamza, Soumia El Hani, Mustapha Ouadghiri, Imad Aboudrar, and Ilias Ouachtouk. "Artificial intelligence techniques for induction motor drives." In 2017 IEEE International Electric Machines and Drives Conference (IEMDC). IEEE, 2017. http://dx.doi.org/10.1109/iemdc.2017.8002127.

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Wen, Xin, David J. Brown, and Qizheng Liao. "Online motor fault diagnosis using hybrid intelligence techniques." In 2010 IEEE Symposium on Industrial Electronics and Applications (ISIEA 2010). IEEE, 2010. http://dx.doi.org/10.1109/isiea.2010.5679442.

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Morozova, Elena V., Alexander N. Samoilenko, Ruslan V. Baranouski, and Anastasia S. Morozova. "An Induction Motor Control System Based on Artificial Intelligence." In 2020 XXIII International Conference on Soft Computing and Measurements (SCM). IEEE, 2020. http://dx.doi.org/10.1109/scm50615.2020.9198812.

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Chidong Qiu, Yue Tan, and Guang Ren. "Motor Online Fault Diagnosis Based on Artificial Intelligence Techniques." In 2006 6th World Congress on Intelligent Control and Automation. IEEE, 2006. http://dx.doi.org/10.1109/wcica.2006.1714192.

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Naga Sujatha, K., K. Vaisakh, and G. Anand. "Artificial intelligence based speed control of brushless DC motor." In Energy Society General Meeting. IEEE, 2010. http://dx.doi.org/10.1109/pes.2010.5589927.

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Yudanto. "Effect of Multiple Intelligence based Perceptual Motor Activity Model on Motor Skill of Kindergarten Student." In The 3rd Yogyakarta International Seminar on Health, Physical Education, and Sport Science (YISHPESS 2019) in conjunction with The 2nd Conference on Interdisciplinary Approach in Sports (CoIS 2019). SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0009789605120516.

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Son, Young Ik, Dae Sik Choi, Kyoung Hoon Cho, In Hyuk Kim, and Sang Hee Kang. "Robust Cascade Control of Electric Motor Drives using PI Observers." In Artificial Intelligence and Applications. Calgary,AB,Canada: ACTAPRESS, 2013. http://dx.doi.org/10.2316/p.2013.794-057.

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Or Rashid, Md Mamun, and Mohiuddin Ahmad. "Multiclass motor imagery classification for BCI application." In 2016 International Workshop on Computational Intelligence (IWCI). IEEE, 2016. http://dx.doi.org/10.1109/iwci.2016.7860335.

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Reports on the topic "Motor Intelligence"

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Ozcelik, Selahattin, and Michael Blackburn. Intelligent Control of a Highly Flexible Robotic Structure With Hundreds of Motor Elements. Fort Belvoir, VA: Defense Technical Information Center, January 2005. http://dx.doi.org/10.21236/ada442046.

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Samuelsson, Joakim. Artificiell intelligens i matematikundervisningen: En studie av utveckling av flyt på grundläggande talkombinationer. Linköping University Electroninc Press, January 2023. http://dx.doi.org/10.3384/9789180750639.

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I denna studie studeras hur flyt på grundläggande talkombinationer utvecklas när elever övar upp sitt flyt med stöd av artificiell intelligens. Det finns flera skäl till att studera detta område. Dels handlar det om att artificiell intelligens börjar användas alltmer inom matematikutbildning, dels att flyt på talkombinationer är en central aspekt av aritmetiken samt att tidigare studier har visat att elever i behov av särskilt stöd i matematik har problem med flyt på grundläggande talkombinationer I denna studie prövas tre olika interventioner för att utveckla flyt på talkombinationer i årskurs 2. Resultatet visar att den grupp som utvecklar sitt flyt mest under interventionsperioden är den som övar på grundläggande talkombinationer med AI-motor. Näst bäst utvecklas gruppen som endast övat med matematiska symboler därefter de som övat med bildstöd och minst utvecklas kontrollgruppen.
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Development of an Adaptive Efficient Thermal/Electric Skipping Control Strategy Applied to a Parallel Plug-in Hybrid Electric Vehicle. SAE International, March 2022. http://dx.doi.org/10.4271/2022-01-0737.

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In recent years automobile manufacturers focused on an increasing degree of electrification of the powertrains with the aim to reduce pollutants and CO2 emissions. Despite more complex design processes and control strategies, these powertrains offer improved fuel exploitation compared to conventional vehicles thanks to intelligent energy management. A simulation study is here presented aiming at developing a new control strategy for a P3 parallel plug-in hybrid electric vehicle. The simulation model is implemented using vehicle modeling and simulation toolboxes in MATLAB/Simulink. The proposed control strategy is based on an alternative utilization of the electric motor and thermal engine to satisfy the vehicle power demand at the wheels (Efficient Thermal/Electric Skipping Strategy - ETESS). The choice between the two units is realized through a comparison between two equivalent fuel rates, one related to the thermal engine and the other related to the electric consumption. An adaptive function is introduced to develop a charge-blended control strategy. The novel adaptive control strategy (A-ETESS) is applied to estimate fuel consumption along different driving cycles. The control algorithm is implemented on a dedicated microcontroller unit performing a Processor-In-the-Loop (PIL) simulation. To demonstrate the reliability and effectiveness of the A-ETESS, the same adaptive function is built on the Equivalent Consumption Minimization Strategy (ECMS). The PIL results showed that the proposed strategy ensures a fuel economy similar to ECMS (worse of about 2% on average) and a computational effort reduced by 99% on average. This last feature reveals the potential for real-time on-vehicle applications.
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