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Irawan, Denny, and Pressa Perdana SS. "Kontrol Motor Brushless DC (BLDC) Berbasis Algoritma AI - PID." Jurnal Teknik Elektro dan Komputasi (ELKOM) 2, no. 1 (March 31, 2020): 41–48. http://dx.doi.org/10.32528/elkom.v2i1.3146.
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Popularitas motor DC brushless (BLDC) semakin meningkat karena memiliki kepadatan energi yang tinggi, biaya pembuatan bahan magnet permanen seperti Samarium Cobalt (Sm-Co) dan Nd-Fe-B yang semakin murah dan kemajuan dalam desain inovasi semakin efisien [7]. Kelebihan motor BLDC yang memberikan respons lebih cepat, membutuhkan pengontrol untuk pengaturan kecepatan yang cepat dan akurat. Kontroler PID yang telah banyak digunakan dalam peralatan kontrol industri dapat diandalkan dengan menyetel oleh algoritma AI untuk menentukan Kp, Ki dan Kd. Dalam penelitian ini, motor BLDC akan dikontrol kecepatan menggunakan algoritma Artifical Intelligence (AI) untuk tuning PID, yang dijalankan dengan mikrokontroler STM 32 F4 Discovery. Popularitas motor DC brushless (BLDC) semakin meningkat karena memiliki kepadatan energi yang tinggi, biaya pembuatan bahan magnet permanen seperti Samarium Cobalt (Sm-Co) dan Nd-Fe-B yang semakin murah dan kemajuan dalam desain inovasi semakin efisien [7]. Kelebihan motor BLDC yang memberikan respons lebih cepat, membutuhkan pengontrol untuk pengaturan kecepatan yang cepat dan akurat. Kontroler PID yang telah banyak digunakan dalam peralatan kontrol industri dapat diandalkan dengan menyetel oleh algoritma AI untuk menentukan Kp, Ki dan Kd. Dalam penelitian ini, motor BLDC akan dikontrol kecepatan menggunakan algoritma Artifical Intelligence (AI) untuk tuning PID, yang dijalankan dengan mikrokontroler STM 32 F4 Discovery.
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Vovk, M., and O. Kutsiak. "AI-Technology of Motor Functions Diagnostics after a Stroke." Kibernetika i vyčislitelʹnaâ tehnika 2021, no. 2(204) (June 1, 2021): 84–100. http://dx.doi.org/10.15407/kvt204.02.084.
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Romanova, Victoria, and Sergey Khromov. "Effect of asymmetry of supply voltages on asynchronous motor operation modes." E3S Web of Conferences 58 (2018): 03013. http://dx.doi.org/10.1051/e3sconf/20185803013.
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Effect of asymmetry of supply voltages on asynchronous motor operation modes was investigated using the computer-aided simulation experiments, the software complex Matlab and the package program Simulink. Publication relevance is determined by the necessity for performance of comparative analysis of the level of effect of asymmetry of supply voltages on asynchronous motors of different series and power capacities. Six motors of three different power capacities (5.5, 55, 160 kW) and of two different series (4A, AI) were modeled for investigation. The value of asymmetry of supply voltages was changed from 0 to 5%. The motor shaft load was changed from 0 to 120% of the motor rated load. Comparison of dependencies of the phase currents on the voltage unbalance ratio by reverse sequence (K2U) of asynchronous motors with short-circuited rotor series 4A and AI was made. The analysis and discussion of obtained investigation results were performed, recommendations on operation of asynchronous motors series 4A and AI in conditions of asymmetry of supply voltages were given.
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Sibley, Krista G., Christine Girges, Ehsan Hoque, and Thomas Foltynie. "Video-Based Analyses of Parkinson’s Disease Severity: A Brief Review." Journal of Parkinson's Disease 11, s1 (July 16, 2021): S83—S93. http://dx.doi.org/10.3233/jpd-202402.
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Remote and objective assessment of the motor symptoms of Parkinson’s disease is an area of great interest particularly since the COVID-19 crisis emerged. In this paper, we focus on a) the challenges of assessing motor severity via videos and b) the use of emerging video-based Artificial Intelligence (AI)/Machine Learning techniques to quantitate human movement and its potential utility in assessing motor severity in patients with Parkinson’s disease. While we conclude that video-based assessment may be an accessible and useful way of monitoring motor severity of Parkinson’s disease, the potential of video-based AI to diagnose and quantify disease severity in the clinical context is dependent on research with large, diverse samples, and further validation using carefully considered performance standards.
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Shanthi, L. Jessi Sahaya, R. Arumugam, M. Nilesh Tawri, and S. Prem Kumar. "Comparison of AI Based Position Estimation Techniques for Switched Reluctance Motor." International Journal of Computer Applications 1, no. 26 (February 25, 2010): 44–50. http://dx.doi.org/10.5120/481-791.
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Beno, M. Marsaline, and N. S. Marimuthu. "AI Based Rotor Position Estimation Techniques for Switched Reluctance Motor Drives." i-manager's Journal on Electrical Engineering 1, no. 3 (March 15, 2008): 58–63. http://dx.doi.org/10.26634/jee.1.3.423.
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Filippetti, F., G. Franceschini, C. Tassoni, and P. Vas. "Recent developments of induction motor drives fault diagnosis using AI techniques." IEEE Transactions on Industrial Electronics 47, no. 5 (2000): 994–1004. http://dx.doi.org/10.1109/41.873207.
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Liu, Yawu, Jari O. Karonen, Juho Nuutinen, Esko Vanninen, Jyrki T. Kuikka, and Ritva L. Vanninen. "Crossed Cerebellar Diaschisis in Acute Ischemic Stroke: A Study with Serial SPECT and MRI." Journal of Cerebral Blood Flow & Metabolism 27, no. 10 (February 21, 2007): 1724–32. http://dx.doi.org/10.1038/sj.jcbfm.9600467.
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This study evaluated the relationship between crossed cerebellar diaschisis (CCD) and (1) lesion volume and location in the acute phase and 1 week after stroke onset and (2) clinical outcome. Twenty-two patients with cerebral ischemic stroke underwent single-photon emission computed tomography (SPECT) and magnetic resonance imaging (MRI) within 48 h and on day 8 from onset. Interhemispheric asymmetric indices (AI) on SPECT were calculated for medial, intermediate, and lateral zones of the cerebellum. Lesion volumes and locations were obtained from diffusion-weighted MRI. Neurological status and 3-month clinical outcome were evaluated. Within 48 h, lesion locations in the temporal association cortex and pyramidal tract of the corona radiata were independent determinants for the AI of the medial zone ( R2 = 0.439). Lesion locations in the primary, premotor, and supplementary motor cortices, primary somatosensory cortex, and anterior part of the posterior limb of the internal capsule were determinants for the AI of the intermediate zone ( R2 = 0.785). Lesions in the primary motor cortex, premotor, and supplementary motor cortices and in the genu of the internal capsule were determinants for the AI of the lateral zone ( R2 = 0.746). On day 8, the associations were decreased. The AIs of the intermediate and lateral zones and lesion location in the parietal association cortex were independently associated with the 3-month clinical outcome ( R2 > 0.555). Acute CCD is a result of functional deafference, while in the subacute phase, transneuronal degeneration might contribute to CCD. CCD in the intermediate and later zones is a better indicator than that in the medial zone.
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Hanumanthakari, Sudheer, S. F. Kodad, and Sarvesh Botlaguduru. "Sensorless Direct Torque Control of Induction Motor Using AI Based Duty Ratio Controllers." International Review on Modelling and Simulations (IREMOS) 9, no. 5 (October 31, 2016): 339. http://dx.doi.org/10.15866/iremos.v9i5.10034.
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Reñones, Anibal, and Marta Galende. "F.A.I.R. open dataset of brushed DC motor faults for testing of AI algorithms." ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal 9, no. 4 (December 15, 2020): 83–94. http://dx.doi.org/10.14201/adcaij2020948394.
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Practical research in AI often lacks of available and reliable datasets so the practitioners can try different algorithms. The field of predictive maintenance is particularly challenging in this aspect as many researchers don't have access to full-size industrial equipment or there is not available datasets representing a rich information content in different evolutions of faults. In this paper, it is presented a dataset with evolution of typical faults (commutator, winding and brush wear) in inexpensive DC motors under extensive monitoring (vibration, temperature, voltage, current and noise). These motors exhibit a particularly short useful life when operating out of nominal conditions (from 30 minutes to 6 hours) which make them very interesting to test different signal processing algorithms and introduce students and researchers into signal processing, fault detection and predictive maintenance. The paper explains in detail the experimentation and the structure of the real, un-processed, dataset published in the AI4EU platform with the aim of complying with the FAIR principle so the dataset is Findable, Accessible, Interoperable and Reusable.
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Fawcett, Kindann, Clark Sims, Rosemary Gaitliff, Ginger McCorkle, Jayne Bellando, Joshua Phelps, and Aline Andres. "Associations Between Maternal Dietary Choline Intake During Pregnancy and Developmental Outcomes in Toddlers." Current Developments in Nutrition 4, Supplement_2 (May 29, 2020): 980. http://dx.doi.org/10.1093/cdn/nzaa054_052.
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Abstract Objectives Recent studies indicate that adequate choline intake in pregnancy results in increased cognitive, motor, language, and behavioral scores in toddlers. The objective was to examine the relationship between maternal choline intake during pregnancy and children's developmental scores during the first two years of life. Methods De-identified secondary data from a longitudinal study (NCT#0,328,1851) involving women with normal weight, overweight, and class I obesity (BMI:18.5- 35 kg/m,2 N = 251) during pregnancy and their children were analyzed using Pearson's correlations and linear models. Dietary choline intake was obtained by analyzing 3-day food records at each trimester using the Nutrient Data System for Research. Cognitive, motor, language, social emotional, and adaptive behavioral scores at 1 and 2 years of age were derived from the administration of the Bayley Scales of Infant and Toddler Development, Third Edition (Bayley-III). Results Adequate Intake (AI) for average maternal choline intake was only met by 4 of the 251 participants. Mean intake of maternal choline during pregnancy (281 mg/day) was significantly lower than the AI level of pregnant women (AI = 450 mg/day). Mean standard scores for Bayley-III domains were all within the normal range (102 for cognitive, 101 for motor, 96 for language, 109 for social-emotional, and 94 for adaptive behavior). Higher maternal choline intake yielded lower adaptive development at 12 months of age (P < 0.001) and 24 months of age (P = 0.044) after adjusting for gestational age and birthweight. There were no associations between maternal choline intake and cognitive, motor, language and social-emotional scores at both ages. Conclusions In this cohort from Arkansas, maternal choline intake was not associated with four of the children's neurodevelopmental outcomes. Maternal Choline intake was negatively associated with the self-reported adaptive behavior scope, which is in contrast to previously published literature. It is important to note that infant development scores were all within normal range despite 98% of women not meeting the AI recommendations for dietary choline during pregnancy. Analyses of choline serum concentration from this cohort is underway to confirm these results. Funding Sources USDA ARS Project # 6026–51,000-012–06S, NIH R01 DK107516.
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Vélez-Guerrero, Manuel Andrés, Mauro Callejas-Cuervo, and Stefano Mazzoleni. "Artificial Intelligence-Based Wearable Robotic Exoskeletons for Upper Limb Rehabilitation: A Review." Sensors 21, no. 6 (March 18, 2021): 2146. http://dx.doi.org/10.3390/s21062146.
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Processing and control systems based on artificial intelligence (AI) have progressively improved mobile robotic exoskeletons used in upper-limb motor rehabilitation. This systematic review presents the advances and trends of those technologies. A literature search was performed in Scopus, IEEE Xplore, Web of Science, and PubMed using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology with three main inclusion criteria: (a) motor or neuromotor rehabilitation for upper limbs, (b) mobile robotic exoskeletons, and (c) AI. The period under investigation spanned from 2016 to 2020, resulting in 30 articles that met the criteria. The literature showed the use of artificial neural networks (40%), adaptive algorithms (20%), and other mixed AI techniques (40%). Additionally, it was found that in only 16% of the articles, developments focused on neuromotor rehabilitation. The main trend in the research is the development of wearable robotic exoskeletons (53%) and the fusion of data collected from multiple sensors that enrich the training of intelligent algorithms. There is a latent need to develop more reliable systems through clinical validation and improvement of technical characteristics, such as weight/dimensions of devices, in order to have positive impacts on the rehabilitation process and improve the interactions among patients, teams of health professionals, and technology.
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Hale, J. P., and M. Burrows. "Innervation patterns of inhibitory motor neurones in the thorax of the locust." Journal of Experimental Biology 117, no. 1 (July 1, 1985): 401–13. http://dx.doi.org/10.1242/jeb.117.1.401.
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The innervation pattern of inhibitory motor neurones of the locust has been revealed by intracellular recording from their cell bodies in the meso- and metathoracic ganglion and simultaneous recording from muscle fibres in a middle, or in a hind leg. Three neurones in each ganglion, the common inhibitor (CI = CI1), the anterior inhibitor (AI = CI2), and the posterior inhibitor (PI = CI3) innervate several muscles in one leg and are thus common inhibitory neurones. Metathoracic CI innervates 13 muscles in one hind leg and mesothoracic CI innervates 12 muscles in one middle leg. The muscles are all in the proximal parts of the legs and move the coxa, the trochanter and the tibia. Metathoracic AI and PI innervate four muscles in the more distal parts of one hind leg that move the tibia, the tarsus and the unguis. None of these muscles is innervated by CI. Each inhibitor innervates muscles that have different and often antagonistic actions during movements of a leg. AI and PI receive many synaptic inputs in common and show similar patterns of spikes during imposed movements of a tibia. Tests fail, however, to reveal evidence for any electrical or synaptic coupling between them. A revised scheme of nomenclature for these inhibitory neurones is proposed.
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Smith, Norris L., and Oussama H. Hamid. "Embodied Cognition and Human-Machine Coexistence." UKH Journal of Science and Engineering 1, no. 1 (December 23, 2017): 67–71. http://dx.doi.org/10.25079/ukhjse.v1n1y2017.pp67-71.
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Recently, we discussed the relative importance of direct perception, embodiment, metaphors, and ethics for cooperative human-machine coexistence. The present paper deepens the examination of embodiment and direct perception by considering differences between computational and representational models on one hand and embodied cognition on the other. We found that to achieve true artificial intelligence (AI) and, hence, a cooperative human-machine coexistence, research must overcome the limitations of computational and representational models. This can be reached by connecting machines to the world through bodies that exhibit sensory and motor skills as demonstrated by embodied cognition. Furthermore, substantial improvement in AI could be achieved by adopting a hybrid framework in which embodiedcognition, for example, may contain representational, abstract, and symbolic aspects. The adoption of such a “both and” instead of “either or” view is a more realistic approach for progress in AI applications.
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G. Madhusudhana Rao, A. Raghu Ram, Ch Vinay Kumar,. "AI based Vector Control Method for BLDC Motor with Multi Switch Three-Phase Topology." Psychology and Education Journal 58, no. 1 (January 1, 2021): 3132–41. http://dx.doi.org/10.17762/pae.v58i1.1218.
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Brushless direct current (BLDC) Motors are extensively used because of their characteristics. Such characteristics are high dynamic response and high-power density. BLDCM control system is a nonlinear, multi-variable, strong-coupling system. In this paper it is proposed that a neural network controller is used for the five level switch of the BLDC motor to enhance the power factor and reduce the current distortions with respect to its rise time, startup torque. This method is also done in comparison with the PID controllers. The working principle of the BLDC is with the help of five-switch control scheme can be implemented here. The different values of load were used to consider the total operation of the BLDC motor is to be controlled. After the completion of the training and testing of the neural network, it might be maintain the constant load values and its variables. To calculate the duty ratio of the DC-DC converter, it will be adjusted to regulate the speed of the BLDC motor. However the DC link of the five switching inverter is used here for the boosting of the voltage. The effectiveness of the proposed control technique can be realized with help of the speed sensor. Various tests have been conducted in the simulation the proposed technology is the robust technology and it is proven that very effective and suitable control technique.
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Hore, Debirupa. "Fuzzy Logic Based Advance Speed Control of Induction Motor." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 4, no. 1 (February 1, 2013): 124–28. http://dx.doi.org/10.24297/ijct.v4i1c.3113.
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The speed control of Induction motor is done using the advance AI Technique methods. In this System the vector control scheme in the stator flux oriented reference frame is used for controlling the variable speed Induction motor. For this the conventional Speed PI controller and Current PI Controllers are tuned and the responses are observed. The Conventional Speed PI Controller is then replaced by the Fuzzy Logic Speed Controller to observe the various responses of the system. The fuzzy Logic Speed Controller is designed and tuned in such a way to obtain better and fast sped responses of the system. Simulation results reveal that the fuzzy-controller improves the performance of variable speed Induction Motor in terms of speed and Power factor
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Venu Gopal, B. T., and E. G. Shivakumar. "A Comparative Performance Analysis of Indirect Vector Controlled Induction Motor Drive Using Optimized AI Techniques." Journal of Computational and Theoretical Nanoscience 17, no. 1 (January 1, 2020): 464–72. http://dx.doi.org/10.1166/jctn.2020.8692.
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This paper exhibits a point by point comparison between Neuro Fuzzy and Genetic Algorithm GA based control systems of Induction Motor drive, underlining favorable circumstances and drawbacks. Industries are advancing and upgrading generation line to enhance efficiency and quality. Induction machines are considered by nonlinear, time varying dynamics, inaccessibility of few states and thus can be considered as a challenging issue. In this paper, a novel method using modified GA is presented to limit electric losses of Induction Motor and it is compared with Neuro Fuzzy Controller. GA is a subordinate of AI, whose principle relies upon Darwin’s theory—struggle for existence and the survival of the fittest. The technique for deciding the gain parameters of PI controller utilizing GA whose output is utilized to control the torque applied to the Induction Motor in this way controlling its speed. The gains of PI controller are improved with the assistance of GA to upgrade the performance of IM drive. The results are simulated in MATLAB Simulink and are related with the conventional PI controller and Adaptive Neuro Fuzzy controller (NFC). NFC is less complicated and gives great speed precision yet GA based PI controller produces significantly reduced torque and speed ripples compared with other controllers, in this way limiting losses in IM drives.
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Damázio, Laila Cristina Moreira, Raphael Teixeira Rocha Melo, Maira de Castro Lima, Vanessa Guedes Pereira, Rosy Iara Maciel de Azambuja Ribeiro, Natália Ribeiro Alves, Betânia Souza Monteiro, Antônio José Natali, Ricardo Junqueira Del Carlo, and Izabel Regina dos Santos Costa Maldonado. "Exercício físico promove neuroproteção estrutural e funcional em ratos com isquemia cerebral." Revista Neurociências 23, no. 4 (December 31, 2015): 581–88. http://dx.doi.org/10.34024/rnc.2015.v23.7978.
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Objetivo. O presente estudo investigou o desempenho motor e o volume de infarto cerebral em ratos sedentários ou que praticaram exercício físico antes e após a isquemia cerebral, promovida por oclusão transitória da artéria cerebral média (OACM). Método. Quarenta e oito ratos Wistar, foram randomizados em dois grupos, um submetido à OACM e o outro apresentando ausência da isquemia. Ambos os grupos foram subdivididos em AI (n=6): animais que realizaram exercício físico prévio a OACM; DI (n=6): animais que realizaram exercício físico após a OACM; ADI (n=6): animais que realizaram exercício físico antes e após a OACM e SI (n=6): animais que não realizaram exercício. O treinamento físico na esteira foi realizado por 6 semanas (30 min/dia), 5 dias na semana. Resultados. Os resultados demonstraram perda de peso nos animais SI após o procedimento de OACM (81 dias) e no final do experimento no grupo ADI (p<0,0001). Os animais dos grupos AI e ADI apresentaram menor frequência de erros no teste passo em falso e barras paralelas aos 76 dias. Conclusão. Ao final do experimento o grupo ADI apresentou melhor desempenho motor nos testes funcionais e menor volume de infarto cerebral.
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Kirlik, Alex. "Rediscovering Turing's brain." Behavioral and Brain Sciences 20, no. 4 (December 1997): 752–53. http://dx.doi.org/10.1017/s0140525x97351619.
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The embodied AI paradigm represents a distinct shift toward an ecological perspective on intelligent behavior. I outline how Ballard et al. have made a promising advance in expanding the seat of intelligence to include sensory and motor systems, but they have not gone far enough. Sustained growth toward truly generalizable accounts of intelligent systems will also require expanding the locus of intelligence to include the environmental structure participating in intelligent behavior.
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Astakhov, Sergey. "Phenomenology vs Symbolic AI: Hubert Dreyfus’s Philosophy of Skill Acquisition." Philosophical Literary Journal Logos 30, no. 2 (2020): 157–93. http://dx.doi.org/10.22394/0869-5377-2020-2-157-190.
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A conflict between artificial intelligence (AI) researchers and phenomenologist Hubert Dreyfus arose in the 1960s and continued until the 2000s. The creators of the first AI programs believed that skill acquisition is a matter of solving problems by using particular mental representations,or heuristics. Dreyfus set out to prove that heuristics are not needed for skill acquisition because the human mind and body are capable of reacting to problematic situations in a flexible way without any mental representations. By clarifying the backstory of the conflict and analyzing the fundamental contradictions between the two theories of skill, the article shows how the phenomenology of skill acquisition originated from a critique of symbolic AI. Dreyfus developed his understanding of interconnections between mind and body in opposition to the associationism in the theories of Herbert Simon, Allen Newell and Edward Feigenbaum. He maintained that human beings have fringe consciousness, insight and tolerance of ambiguity and that they have a specific body structure and needs which make it possible to discriminate between relevant and irrelevant features in the environment and get a maximum grip of it. The author analyzes how theories of learning created within symbolic AI influenced Dreyfus’s five-stage model of skill acquisition. That model explained why programs by Simon and his colleagues achieved initial success, but it also exposed their limitations. To clarify the teleology of skill, Dreyfus explored how the idea of motor intentionality is connected with neural network modelling. Two perspectives on the role of Dreyfus in the history of AI are outlined together with the reasons why his philosophy had almost no effect on the AI community even though it was influential in the social sciences and humanities. Finally, current challenges facing the phenomenology of skill acquisition are explored.
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Romanova, Victoria, and Sergey Khromov. "Operational reliability of low-voltage asynchronous motors at asymmetrical supply voltage." E3S Web of Conferences 139 (2019): 01053. http://dx.doi.org/10.1051/e3sconf/201913901053.
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Issues of operating modes of 4A series asynchronous squirrel-cage motors and AI serried motors at asymmetrical supply voltage for different values of motor shaft load are considered on the basis of simulation using Matlab software package and Simulink package. In the simulation, currents in asynchronous motor phases were evaluated as a function of K2U, KZ, and based on these results, permissible operation parameters were evaluated for induction motors. The results obtained are the basis for technical solutions aimed at improving operational reliability of asynchronous motors, they will allow taking into account permissible operating parameters of asynchronous motors not only in the design, but also in operation in power supply systems of various facilities.
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Sy, B. K., and J. R. Deller. "An AI-based communication system for motor and speech disabled persons: design methodology and prototype testing." IEEE Transactions on Biomedical Engineering 36, no. 5 (May 1989): 565–71. http://dx.doi.org/10.1109/10.24260.
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Borz, Stelian Alexandru. "Development of a Modality-Invariant Multi-Layer Perceptron to Predict Operational Events in Motor-Manual Willow Felling Operations." Forests 12, no. 4 (March 29, 2021): 406. http://dx.doi.org/10.3390/f12040406.
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Motor-manual operations are commonly implemented in the traditional and short rotation forestry. Deep knowledge of their performance is needed for various strategic, tactical and operational decisions that rely on large amounts of data. To overcome the limitations of traditional analytical methods, Artificial Intelligence (AI) has been lately used to deal with various types of signals and problems to be solved. However, the reliability of AI models depends largely on the quality of the signals and on the sensing modalities used. Multimodal sensing was found to be suitable in developing AI models able to learn time and location-related data dependencies. For many reasons, such as the uncertainty of preserving the sensing location and the inter- and intra-variability of operational conditions and work behavior, the approach is particularly useful for monitoring motor-manual operations. The main aim of this study was to check if the use of acceleration data sensed at two locations on a brush cutter could provide a robust AI model characterized by invariance to data sensing location. As such, a Multi-Layer Perceptron (MLP) with backpropagation was developed and used to learn and classify operational events from bimodally-collected acceleration data. The data needed for training and testing was collected in the central part of Romania. Data collection modalities were treated by fusion in the training dataset, then four single-modality testing datasets were used to check the performance of the model on a binary classification problem. Fine tuning of the regularization parameters (α term) has led to acceptable testing and generalization errors of the model measured as the binary cross-entropy (log loss). Irrespective of the hyperparameters’ tunning strategy, the classification accuracy (CA) was found to be very high, in many cases approaching 100%. However, the best models were those characterized by α set at 0.0001 and 0.1, for which the CA in the test datasets ranged from 99.1% to 99.9% and from 99.5% to 99.9%, respectively. Hence, data fusion in the training set was found to be a good strategy to build a robust model, able to deal with data collected by single modalities. As such, the developed MLP model not only removes the problem of sensor placement in such applications, but also automatically classifies the events in the time domain, enabling the integration of data collection, handling and analysis in a simple less resource-demanding workflow, and making it a feasible alternative to the traditional approach to the problem.
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Malhotra, Shveta, Amee J. Hall, and Stephen G. Lomber. "Cortical Control of Sound Localization in the Cat: Unilateral Cooling Deactivation of 19 Cerebral Areas." Journal of Neurophysiology 92, no. 3 (September 2004): 1625–43. http://dx.doi.org/10.1152/jn.01205.2003.
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We examined the ability of mature cats to accurately orient to, and approach, an acoustic stimulus during unilateral reversible cooling deactivation of primary auditory cortex (AI) or 1 of 18 other cerebral loci. After attending to a central visual stimulus, the cats learned to orient to a 100-ms broad-band, white-noise stimulus emitted from a central speaker or 1 of 12 peripheral sites (at 15° intervals) positioned along the horizontal plane. Twenty-eight cats had two to six cryoloops implanted over multiple cerebral loci. Within auditory cortex, unilateral deactivation of AI, the posterior auditory field (PAF) or the anterior ectosylvian sulcus (AES) resulted in orienting deficits throughout the contralateral field. However, unilateral deactivation of the anterior auditory field, the second auditory cortex, or the ventroposterior auditory field resulted in no deficits on the orienting task. In multisensory cortex, unilateral deactivation of neither ventral or dorsal posterior ectosylvian cortices nor anterior or posterior area 7 resulted in any deficits. No deficits were identified during unilateral cooling of the five visual regions flanking auditory or multisensory cortices: posterior or anterior ii suprasylvian sulcus, posterior suprasylvian sulcus or dorsal or ventral posterior suprasylvian gyrus. In motor cortex, we identified contralateral orienting deficits during unilateral cooling of lateral area 5 (5L) or medial area 6 (6m) but not medial area 5 or lateral area 6. In a control visual-orienting task, areas 5L and 6m also yielded deficits to visual stimuli presented in the contralateral field. Thus the sound-localization deficits identified during unilateral deactivation of area 5L or 6m were not unimodal and are most likely the result of motor rather than perceptual impairments. Overall, three regions in auditory cortex (AI, PAF, AES) are critical for accurate sound localization as assessed by orienting.
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Markov, Vladimir, Vyacheslav Kamaltdinov, Larisa Bykovskaya, and Bowen Sa. "Performance of a diesel engine running on mixed biofuels with the addition of gasoline." E3S Web of Conferences 140 (2019): 11004. http://dx.doi.org/10.1051/e3sconf/201914011004.
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The significance of the paper is confirmed by the need to replace petroleum motor fuels with fuels produced from alternative energy sources. Biofuels derived from various vegetable resources are considered as promising alternative fuels for diesel engines. These fuels offer significant advantages with respect to the renewability of their raw materials and good emission performances when burned in ICEs. The main problem of using vegetable oils as biofuels for diesel engines is their high viscosity. This problem can be resolved by using mixed biofuels with the addition of gasoline. The analysis of physico-chemical properties of petroleum diesel fuel (DF) and mixed biofuels containing petroleum DF, rapeseed oil (RO) and AI-80 automotive gasoline was conducted. Experimental studies of the D-245.12S diesel fuelled with these mixed fuels were carried out. The mixed fuels were prepared from 80% DF + 20% RO, from 75% DF + 20% RO + 5% AI-80, and from 70% DF + 20% RO + 10% AI-80. It was shown that the addition of gasoline to mixed biofuels could improve two main toxicity indicators of exhaust gases exhaust gases smoke and emissions of nitrogen oxides. The best emission performance was achieved for the mixture of 70% DF, 20% RO and 10% AI-80. When the diesel engine was switched from the mixture of 80% DF and 20% RO to the mixture of 70% DF, 20% RO and 10% AI-80, the exhaust gases smoke at maximum torque mode decreased from 17.5 to 14.5% on the Hartridge scale, i.e. by 17.1%. The specific emissions of nitrogen oxides decreased from 6.559 to 6.154 g/(kW·h), i.e. by 6.2%.
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Balderas, David, Pedro Ponce, Diego Lopez-Bernal, and Arturo Molina. "Education 4.0: Teaching the Basis of Motor Imagery Classification Algorithms for Brain-Computer Interfaces." Future Internet 13, no. 8 (August 3, 2021): 202. http://dx.doi.org/10.3390/fi13080202.
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Education 4.0 is looking to prepare future scientists and engineers not only by granting them with knowledge and skills but also by giving them the ability to apply them to solve real life problems through the implementation of disruptive technologies. As a consequence, there is a growing demand for educational material that introduces science and engineering students to technologies, such as Artificial Intelligence (AI) and Brain–Computer Interfaces (BCI). Thus, our contribution towards the development of this material is to create a test bench for BCI given the basis and analysis on how they can be discriminated against. This is shown using different AI methods: Fisher Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), Artificial Neural Networks (ANN), Restricted Boltzmann Machines (RBM) and Self-Organizing Maps (SOM), allowing students to see how input changes alter their performance. These tests were done against a two-class Motor Image database. First, using a large frequency band and no filtering eye movement. Secondly, the band was reduced and the eye movement was filtered. The accuracy was analyzed obtaining values around 70∼80% for all methods, excluding SVM and SOM mapping. Accuracy and mapping differentiability increased for some subjects for the second scenario 70∼85%, meaning either their band with the most significant information is on that limited space or the contamination because of eye movement was better mitigated by the regression method. This can be translated to saying that these methods work better under limited spaces. The outcome of this work is useful to show future scientists and engineers how BCI experiments are conducted while teaching them the basics of some AI techniques that can be used in this and other several experiments that can be carried on the framework of Education 4.0.
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AlShorman, Omar, Muhammad Irfan, Nordin Saad, D. Zhen, Noman Haider, Adam Glowacz, and Ahmad AlShorman. "A Review of Artificial Intelligence Methods for Condition Monitoring and Fault Diagnosis of Rolling Element Bearings for Induction Motor." Shock and Vibration 2020 (November 4, 2020): 1–20. http://dx.doi.org/10.1155/2020/8843759.
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The fault detection and diagnosis (FDD) along with condition monitoring (CM) and of rotating machinery (RM) have critical importance for early diagnosis to prevent severe damage of infrastructure in industrial environments. Importantly, valuable industrial equipment needs continuous monitoring to enhance the safety, reliability, and availability and to decrease the cost of maintenance of modern industrial systems and applications. However, induction motor (IM) has been extensively used in several industrial processes because it is cheap, reliable, and robust. Rolling bearings are considered to be the main component of IM. Undoubtedly, any failure of this basic component can lead to a serious breakdown of IM and for whole industrial system. Thus, many current methods based on different techniques are employed as a fault prognosis and diagnosis of rolling elements bearing of IM. Moreover, these techniques include signal/image processing, intelligent diagnostics, data fusion, data mining, and expert systems for time and frequency as well as time-frequency domains. Artificial intelligence (AI) techniques have proven their significance in every field of digital technology. Industrial machines, automation, and processes are the net frontiers of AI adaptation. There are quite developed literatures that have been approaching the issues using signals and data processing techniques. However, the key contribution of this work is to present an extensive review of CM and FDD of the IM, especially for rolling elements bearings, based on artificial intelligent (AI) methods. This study highlights the advantages and performance limitations of each method. Finally, challenges and future trends are also highlighted.
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Matusik, Edyta, Aldona Augustak, and Jacek Durmala. "Functional Mobility and Basic Motor Skills in Patients with Multiple Sclerosis and Its Relation to the Anthropometrical Status and Body Composition Parameters." Medicina 55, no. 12 (December 4, 2019): 773. http://dx.doi.org/10.3390/medicina55120773.
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Background and objectives: Patients with multiple sclerosis (MS) have many potential risk factors (spasticity, immobilization, glucocorticoids use) which can deteriorate the anthropometrical status and body composition and may have a potential negative impact on functional mobility and basic motor skill improvement after physiotherapy. The aim of the study was to assess the functional mobility and basic motor skills in patients with MS and to correlate them with disability and anthropometrical status and body composition parameters. Materials and Methods: Timed Up-and-Go Test (TUG) and six-min walk test (6MWT) were performed in 36 patients with MS before and after 4 weeks of physiotherapy. Body mass index (BMI), waist-to-height ratio (W/HtR), and waist-to-hip ratio (WHR) were assessed in this group. Body composition was evaluated by bioelectrical impedance analysis (BIA) and fat mass (FAT), fat free mass (FFM), total body water (TBW), and predicted muscle mass (PMM) were expressed as percentage of body mass. Clinical status was assessed by Expanded Disability Status Scale (EDSS) and Ambulatory Index (AI) scales. Results: After physiotherapy, there was a significant improvement in functional mobility and basic motor skills assessed by total distance in 6MWT (p < 0.001) and in TUG trials (p < 0.001). Positive significant correlations were found between the results obtained in both tests (either before and after physiotherapy) vs. FFM, TBW, and PMM, whilst worse results in functional mobility and basic motor skills correlated significantly with higher WHtR, WHR, and FAT (p < 0.05). Clinical status (EDSS) was significantly related to the WHtR and body composition parameters with the same manner as the results in the either 6MWT and TUG. However, there were no significant relationships between BMI vs. either clinical status (EDSS, AI) or functional mobility tests results in patients with MS. Conclusions: Functional mobility and basic motor skills may be significantly improved during physiotherapy, but they are related to the anthropometrical status and body composition of MS patients. Moreover, disability status is also significantly related to these parameters. Body composition deterioration seems to be the important target for the therapeutic intervention in MS patients. For proper nutritional status assessment in patients with MS, body composition analysis or WHtR instead BMI should to be used.
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Öztürk, Pinar, and Axel Tidemann. "A review of case-based reasoning in cognition–action continuum: a step toward bridging symbolic and non-symbolic artificial intelligence." Knowledge Engineering Review 29, no. 1 (March 21, 2013): 51–77. http://dx.doi.org/10.1017/s0269888913000076.
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AbstractIn theories and models of computational intelligence, cognition and action have historically been investigated on separate grounds. We conjecture that the main mechanism of case-based reasoning (CBR) applies to cognitive tasks at various levels and of various granularity, and hence can represent a bridge—or a continuum—between the higher and lower levels of cognition. CBR is an artificial intelligence (AI) method that draws upon the idea of solving a new problem reusing similar past experiences. In this paper, we re-formulate the notion of CBR to highlight the commonalities between higher-level cognitive tasks such as diagnosis, and lower-level control such as voluntary movements of an arm. In this view, CBR is envisaged as a generic process independent from the content and the detailed format of cases. Diagnostic cases and internal representations underlying motor control constitute two instantiations of the case representation. In order to claim such a generic mechanism, the account of CBR needs to be revised so that its position in non-symbolic AI becomes clearer. The paper reviews the CBR literature that targets lower levels of cognition to show how CBR may be considered as a step toward bridging the gap between symbolic and non-symbolic AI.
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Asad, Bilal, Toomas Vaimann, Anouar Belahcen, Ants Kallaste, Anton Rassõlkin, and M. Naveed Iqbal. "The Cluster Computation-Based Hybrid FEM–Analytical Model of Induction Motor for Fault Diagnostics." Applied Sciences 10, no. 21 (October 27, 2020): 7572. http://dx.doi.org/10.3390/app10217572.
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This paper presents a hybrid finite element method (FEM)–analytical model of a three-phase squirrel cage induction motor solved using parallel processing for reducing the simulation time. The growing development in artificial intelligence (AI) techniques can lead towards more reliable diagnostic algorithms. The biggest challenge for AI techniques is that they need a big amount of data under various conditions to train them. These data are difficult to obtain from the industries because they contain low numbers of possible faulty cases, as well as from laboratories because a limited number of motors can be broken for testing purposes. The only feasible solution is mathematical models, which in the long run can become part of advanced diagnostic techniques. The benefits of analytical and FEM models for their speed and accuracy respectively can be exploited by making a hybrid model. Moreover, the concept of cloud computing can be utilized to reduce the simulation time of the FEM model. In this paper, a hybrid model being solved on multiple processors in a parallel fashion is presented. The results depict that by dividing the rotor steps among several processors working in parallel, the simulation time reduces considerably. The simulation results under healthy and broken rotor bar cases are compared with those taken from a laboratory setup for validation.
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Rychtyckyj, Nestor, Venkatesh Raman, Baskaran Sankaranarayanan, P. Sreenivasa Kuma, and Deepak Khemani. "Ontology Re-Engineering: A Case Study from the Automotive Industry." AI Magazine 38, no. 1 (March 31, 2017): 49–60. http://dx.doi.org/10.1609/aimag.v38i1.2712.
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For over twenty-five years Ford Motor Company has been utilizing an AI-based system to manage process planning for vehicle assembly at its assembly plants around the world. The scope of the AI system, known originally as the Direct Labor Management System and now as the Global Study Process Allocation System (GSPAS), has increased over the years to include additional functionality on Ergonomics and Powertrain Assembly (Engines and Transmission plants). The knowledge about Ford’s manufacturing processes is contained in an ontology originally developed using the KL-ONE representation language and methodology. To preserve the viability of the GSPAS ontology and to make it easily usable for other applications within Ford, we needed to re-engineer and convert the KL-ONE ontology into a semantic web OWL/RDF format. In this article, we will discuss the process by which we re-engineered the existing GSPAS KL-ONE ontology and deployed semantic web technology in our application.
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Kujala, Tuomo, and Pertti Saariluoma. "Cognitive Mimetics for Designing Intelligent Technologies." Advances in Human-Computer Interaction 2018 (August 1, 2018): 1–9. http://dx.doi.org/10.1155/2018/9215863.
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Design mimetics is an important method of creation in technology design. Here, we review design mimetics as a plausible approach to address the problem of how to design generally intelligent technology. We argue that design mimetics can be conceptually divided into three levels based on the source of imitation. Biomimetics focuses on the structural similarities between systems in nature and technical solutions for solving design problems. In robotics, the sensory-motor systems of humans and animals are a source of design solutions. At the highest level, we introduce the concept of cognitive mimetics, in which the source for imitation is human information processing. We review and discuss some historical examples of cognitive mimetics, its potential uses, methods, levels, and current applications, and how to test its success. We conclude by a practical example showing how cognitive mimetics can be a highly valuable complimentary approach for pattern matching and machine learning based design of artificial intelligence (AI) for solving specific human-AI interaction design problems.
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Alshorman, Omar, and Ahmad Alshorman. "A review of intelligent methods for condition monitoring and fault diagnosis of stator and rotor faults of induction machines." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 4 (August 1, 2021): 2820. http://dx.doi.org/10.11591/ijece.v11i4.pp2820-2829.
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Nowadays, induction motor (IM) is extensively used in industry, including mechanical and electrical applications. However, three main types of IM faults have been discussed in the literature, bearing, stator, and rotor. Importantly, stator and rotor faults represent approximately 50%. Traditional condition monitoring (CM) and fault diagnosis (FD) methods require a high processing cost and much experience knowledge. To tackle this challenge, artificial intelligent (AI) based CM and FD techniques are extensively developed. However, there have been many review research papers for intelligent CM and FD machine learning methods of rolling elements bearings of IM in the literature. Whereas there is a lack in the literature, and there are not many review papers for both stator and rotor intelligent CM and FD. Thus, the proposed study's main contribution is in reviewing the CM and FD of IM, especially for the stator and the rotor, based on AI methods. The paper also provides discussions on the main challenges and possible future works.
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Matsushita, Kojiro, Hiroshi Yokoi, and Tamio Arai. "Plastic-Bottle-Based Robots in Educational Robotics Courses – Understanding Embodied Artificial Intelligence –." Journal of Robotics and Mechatronics 19, no. 2 (April 20, 2007): 212–22. http://dx.doi.org/10.20965/jrm.2007.p0212.
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In this paper, we introduce an educational robotics approach featuring a unique robotic development kit - hardware, software, and instructions - that concretely encourages student interest in and curiosity about science and technology. The kit was developed based on practical policies: easy construction, low cost, creative activity, and enjoyable education. It uses common materials such as plastic bottles, RC servomotors, and hot glue, and provides three different controllers with instructions - a sensor-motor controller, an electromyography (EMG) interface controller, and a teaching-playback controller. The kit thus offers more custom access to both robot structure and control architecture than similar kits and encourages students to become engaged creatively. The three robotics courses for undergraduates and graduates we have conducted thus far to provide an understanding of robotics and embodied artificial intelligence (AI) have confirmed that some of locomotive robots explicitly exploit their own dynamics - also known as “morph-functionality” - an embodied AI concept. An evaluation of this approach for course hours, task achievement, student interest, and the influence of assistance confirmed conclusively that students experienced creativity in such robotics courses.
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Angelo da Silva, Luiz Antônio, and Patricia Maria de Moraes Barros Fucs. "Soft tissue surgery as an initial treatment for hip displacement in spastic cerebral palsy." SICOT-J 6 (2020): 38. http://dx.doi.org/10.1051/sicotj/2020036.
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Objective: To use the measurement of migration percentage (MP) to evaluate the long-term radiographic results of soft tissue surgery as the first treatment for hip displacement in spastic bilateral cerebral palsy. A secondary objective was to identify predictive factors of stability (i.e., less than 30% of MP in the long term), after surgical correction. Methods: In this longitudinal cohort study, we reviewed the electronic medical records and radiographs of all consecutive patients with cerebral palsy operated for the correction of hip displacement between 1984 and 2013 in a referral orthopedic public hospital in Brazil. Patients were included if they had received, as the first surgical procedure, soft-tissue release. All surgeries were bilateral and symmetrical. We used the available radiographs to evaluate the migration percentage (MP), acetabular index (AI), pelvic obliquity (PO) angle, head-shaft angle (HSA), congruence and femoral head sphericity, and function using the GMFCS (Gross Motor Function Classification System). Results: we included 93 patients, all operated before being 12 years old, with follow-up of 10 years in average, 73 (78%) of them with good results (MP < 30%). We found association between preoperative MP ≤ 40%, AI ≤ 25°, and postoperative symmetry with good results, with a cut-off value of 38% of MP and 27° of acetabular index being predictive. Discussion: The role of soft tissue releases remains controversial owing to small sample sizes, heterogeneity, variety range of ages, definitions used for outcome, and lack of statistical quality. Our results were better in combined tenotomies, in diparetic patients aged more than six years, and in patients with lower initial values of MP and AI. Radiographic variables had good correlation with each other and association with results, with cut-off values for MP and AI PRE.
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Syahrulyati, Teti, Singgih Irianto, and Yusup Suhendi. "Reserve Potential Sandy Clay as a Raw Materials Cement Village Hambalang, County Citeureup District Bogor Province Jawabarat – Indonesia." International Journal of Engineering & Technology 7, no. 3.20 (September 1, 2018): 398. http://dx.doi.org/10.14419/ijet.v7i3.20.20580.
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Administratively the research area is in Hambalang Village Kec. Citeureup Kab. Bogor West Java, travel time to the location of the city of Bogor for 60 minutes by motor vehicle, the area of research around 1732 ha. The existence of sedimentary rocks in the form of limestones and batulempung is utilized by one cement factory in Indonesia as raw material of cement. Measurement and sampling is done to know the amount of measured reserves. Analysis of the content of oxide compounds is done by AAS method to determine the levels of the compounds they contain. The results of the calculations of SiO2 and Al2O3 are abbreviated as (AI = alumina Index) and the pattern of distribution is made with the aim that the mining process becomes effective, efficient and directed. The method use to principle of the concept of three-point method is used as the basis for making contours of the distribution of compounds contained. Drilling data, chemical analysis, DTM (Digital Terain Modeling) data and Isoline data generated were obtained using Autoclan 3D map 2015 and Autoplan Geomo. The calculation of reserves (AI / Alumina Indek 3.21 - 3.70%) with the highest reserves 1,643,814 Tones. The smallest reserve (AI quality 5.00 - 6.01%) is 199,980 Tones. This research resulted in a map of the distribution of Alumina index, so as to facilitate the extraction and very helpful in executing the area / block that must be mined.
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Sakthi, V., and A. Sivasubramanian. "Torque and Flux Ripple Minimization of Induction Motor Using Hybrid Neuro Fuzzy Controller." International Journal of Engineering & Technology 7, no. 4.6 (September 25, 2018): 377. http://dx.doi.org/10.14419/ijet.v7i4.6.28445.
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This paper proposed to design, implementation and simulation of Direct Torque Control of Induction Motor drive system is to minimize stator current distortion, electromagnetic torque and flux ripples. In this paper, Hybrid Neuro-Fuzzy Controller is proposed to replace the conventional PI torque and flux controller to achieve desired torque and flux with zero steady state error and also with good dynamic fast response. Neuro-Fuzzy based torque and flux controllers are designed to optimize the stator voltages in d-q reference frame that applied to Direct Torque Control. Simulation and the performance of the proposed Hybrid NFC are analyzed. Simulation results showed that a significant improvement in dynamic torque and speed response in both steady and transient states and also a considerable reduction in torque and flux minimization compared to the other AI techniques.
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Chang, Ching-Lung, Shuo-Tsung Chen, Chuan-Yu Chang, and You-Chen Jhou. "Application of Machine Learning in Air Hockey Interactive Control System." Sensors 20, no. 24 (December 17, 2020): 7233. http://dx.doi.org/10.3390/s20247233.
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In recent years, chip design technology and AI (artificial intelligence) have made significant progress. This forces all of fields to investigate how to increase the competitiveness of products with machine learning technology. In this work, we mainly use deep learning coupled with motor control to realize the real-time interactive system of air hockey, and to verify the feasibility of machine learning in the real-time interactive system. In particular, we use the convolutional neural network YOLO (“you only look once”) to capture the hockey current position. At the same time, the law of reflection and neural networking are applied to predict the end position of the puck Based on the predicted location, the system will control the stepping motor to move the linear slide to realize the real-time interactive air hockey system. Finally, we discuss and verify the accuracy of the prediction of the puck end position and improve the system response time to meet the system requirements.
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Paramasivam, S., S. Vijayan, M. Vasudevan, R. Arumugam, and R. Krishnan. "Real-Time Verification of AI Based Rotor Position Estimation Techniques for a 6/4 Pole Switched Reluctance Motor Drive." IEEE Transactions on Magnetics 43, no. 7 (July 2007): 3209–22. http://dx.doi.org/10.1109/tmag.2006.888811.
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Kurt, Emine Eda, Buket Büyükturan, Öznur Büyükturan, Hatice Rana Erdem, and Figen Tuncay. "Effects of Ai Chi on balance, quality of life, functional mobility, and motor impairment in patients with Parkinson’s disease." Disability and Rehabilitation 40, no. 7 (January 13, 2017): 791–97. http://dx.doi.org/10.1080/09638288.2016.1276972.
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Ali, Mohamed M. Ismail. "Efficiency optimisation with PI gain adaptation of field-oriented control applied on five phase induction motor using AI technique." International Journal of Modelling, Identification and Control 20, no. 4 (2013): 344. http://dx.doi.org/10.1504/ijmic.2013.057568.
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Saito, Ken. "Development of World Smallest Insect-Type Robot with Implementation of Silicon Device." Impact 2020, no. 2 (April 15, 2020): 24–26. http://dx.doi.org/10.21820/23987073.2020.2.24.
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Robotics will play an increasingly important role in our society in the future. This field is already extremely important, especially in industry. Robots are often found performing complex assemblies, conducting large-scale experiments helping in various industrial processes. These are all tasks that require high precision and are typically repetitive; tasks that most humans do not excel at. Similarly, artificial intelligence (AI) is already integrated into many processes. These tend to involve the performance of long and complex calculations in a short amount of time; again, something humans – and nature – do not love. Increasingly, however robotics and AI will be turned to fulfil roles that have been typically filled by people or nature. In order to do this, both the robotics and the intelligence will need to be inspired by how nature does things. This is a design method known as biomimicry. One area of important robotics and AI research is microrobotics. This is a field that is aiming to create extremely small robots that are able to navigate and perform their function automatously. Associate Professor Ken Saito of Nihon University, Japan, is an expert in microrobotics. He is developing solutions in two essential areas. Firstly, how such a small robot moves itself. It is not obvious how to fit a fully functioning motor and actuator device inside a robot that is merely millimetres in dimension. Additionally, it is difficult to manufacture accurately on such small scales. Secondly, he is tackling the problem of how, once capable of movement, such a microrobot might navigate itself independently of any controller.
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Буряченко, Анна Григорьевна, Дмитрий Сергеевич Бурунов, Вячеслав Михайлович Грудинкин, and Андрей Олегович Таранишин. "СТЕНД-ИМИТАТОР АВИАДВИГАТЕЛЯ КАК УНИВЕРСАЛЬНОЕ СРЕДСТВО ОБЕСПЕЧЕНИЯ РАЗРАБОТКИ И ИСПЫТАНИЙ РЕГУЛЯТОРОВ." Aerospace technic and technology, no. 7 (August 31, 2020): 83–88. http://dx.doi.org/10.32620/aktt.2020.7.12.
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There is described the work on the project, carried out at the enterprise Element JSC for the creation of aircraft gas turbine engine simulator stands, for the maintenance and testing of some digital regulators for helicopter and aircraft engines (turboshaft and turboprops), which the company is the developer and manufacturer of. Compact simulator stands test all the functions of the regulator and allows you to abandon the use of bulky semi-natural stands, at least for 95% of the tests. The stand simulator is a hardware-software complex that simulates the engine as a system interacting with the regulator by simulating all analog, discrete and digital signals. The stand imitates the signals arriving at the regulator from sensors, aggregates, and engine systems that provide reception of control signals from the regulator. Besides, stand performs calculations and generates sets of interdependent parameter values (in the form of analog, discrete, and digital signals), each of which corresponds to one of the engine operating modes according to predetermined functional dependencies that reflect the characteristics of the engine – a mathematical model of the engine. The stands undergo certification in the scope of the program agreed with the State Enterprise “Zaporizhiastandardmetrology” and are verified by comparing the test results of the regulator on a simulator stand and as part of the motor stands of the Customer (engine developer). It is shown that the modular structure of the first of the simulator stands (basic) developed at the enterprise and the reserve provided for in its structure helped simplify its subsequent adaptation to the implementation of models of new types of engines. There is given the information on the stands simulating the AI-450M, AI-450S, AI-450S-1, AI-450T engines (for an unmanned aerial vehicle), and MS-500V-02S. It has been shown that simulator stands provide a set of tests for the development and serial production of regulators RDC-450M, RDTs-450M-S, RDTs-450M-S-1, RDTs-450M-C-T-P, RDTs-450S-500 at the enterprise.
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Bacon, Pierre-Luc, and Doina Precup. "Constructing Temporal Abstractions Autonomously in Reinforcement Learning." AI Magazine 39, no. 1 (March 27, 2018): 39–50. http://dx.doi.org/10.1609/aimag.v39i1.2780.
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The idea of temporal abstraction, i.e. learning, planning and representing the world at multiple time scales, has been a constant thread in AI research, spanning sub-fields from classical planning and search to control and reinforcement learning. For example, programming a robot typically involves making decisions over a set of controllers, rather than working at the level of motor torques. While temporal abstraction is a very natural concept, learning such abstractions with no human input has proved quite daunting. In this paper, we present a general architecture, called option-critic, which allows learning temporal abstractions automatically, end-to-end, simply from the agent’s experience. This approach allows continual learning and provides interesting qualitative and quantitative results in several tasks.
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Banda, Gururaj, and Sri Gowri Kolli. "An Intelligent Adaptive Neural Network Controller for a Direct Torque Controlled eCAR Propulsion System." World Electric Vehicle Journal 12, no. 1 (March 17, 2021): 44. http://dx.doi.org/10.3390/wevj12010044.
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This article deals with an intelligent adaptive neural network (ANN) controller for a direct torque controlled (DTC) electric vehicle (EV) propulsion system. With the realization of artificial intelligence (AI) conferred adaptive controllers, the torque control of an electric car (eCAR) propulsion motor can be achieved by estimating the stator reference flux voltage used to synthesize the space vector pulse width modulation (SVPWM) for a DTC scheme. The proposed ANN tool optimizes the parameters of a proportional integral (PI) controller with real-time data and offers splendid dynamic stability. The response of an ANN controller is examined over standard drive cycles to validate the performance of an eCAR in terms of drive range and energy efficiency using MATLAB simulation software.
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Dale, Jim E. "A Smooth-Cone Spreader for Application of Dry Herbicide Formulations." Weed Science 35, no. 3 (May 1987): 438–43. http://dx.doi.org/10.1017/s0043174500053960.
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A new machine consisting of a detachable hopper of containerized granules with a preselected circular orifice to regulate flow of granules, and a revolving hollow-cone spreader turned by an electric motor, was tested. Flow of herbicide granules at typical use rates was linearly correlated with orifice diameter. Coefficients of determination for flow rates of alachlor [2-chloro-N-(2,6-diethylphenyl)-N-(methoxymethyl)acetamide], trifluralin [2,6-dinitro-N,N-dipropyl-4-(trifluoromethyl)benzenamine], and norflurazon [4-chloro-5-(methylamino)-2-(3-(trifluoromethyl)phenyl)-3 (2H)-pyridazinone] were 0.96 or greater. Based on patterns of distribution of commercial trifluralin granules parallel and perpendicular to a linear path, the machine could be used to apply herbicide granules in row crops. Control of johnsongrass [Sorghum halepense(L.) Pers. # SORHA] with alachlor plus oryzalin [4-(dipropylamino)-3,5-dinitrobenzenesulfonamide] applied preemergence (pre) as sprays and granules did not differ significantly in soybean [Glycine max(L.) Merr. ‘Forrest′]. Trifluralin granules applied preplant incorporated (ppi) at 1.1 kg ai/ha controlled 80 to 95% of the johnsongrass and doubled soybean yield compared to the cultivated control plot. Norflurazon plus alachlor pre at 1.7 to 2.2 plus 2.2 to 3.0 kg ai/ha controlled annual grasses and prickly sida (Sida spinosaL. # SIDSP) equally with sprays and granules.
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Magis-Weinberg, Lucía, Ruud Custers, and Iroise Dumontheil. "Rewards Enhance Proactive and Reactive Control in Adolescence and Adulthood." Social Cognitive and Affective Neuroscience 14, no. 11 (November 1, 2019): 1219–32. http://dx.doi.org/10.1093/scan/nsz093.
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Abstract Cognitive control allows the coordination of cognitive processes to achieve goals. Control may be sustained in anticipation of goal-relevant cues (proactive control) or transient in response to the cues themselves (reactive control). Adolescents typically exhibit a more reactive pattern than adults in the absence of incentives. We investigated how reward modulates cognitive control engagement in a letter-array working memory (WM) task in 30 adolescents (12–17 years) and 20 adults (23–30 years) using a mixed block- and event-related functional magnetic resonance imaging design. After a Baseline run without rewards, participants performed a Reward run where 50% trials were monetarily rewarded. Accuracy and reaction time (RT) differences between Reward and Baseline runs indicated engagement of proactive control, which was associated with increased sustained activity in the bilateral anterior insula (AI), right dorsolateral prefrontal cortex (PFC) and right posterior parietal cortex (PPC). RT differences between Reward and No reward trials of the Reward run suggested additional reactive engagement of cognitive control, accompanied with transient activation in bilateral AI, lateral PFC, PPC, supplementary motor area, anterior cingulate cortex, putamen and caudate. Despite behavioural and neural differences during Baseline WM task performance, adolescents and adults showed similar modulations of proactive and reactive control by reward.
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Oliveira, Carolina Camargo, Luma Azevedo Tovazi, and Milena Romero Neves. "TERAPIA POR CONTENSÃO INDUZIDA EM PACIENTE COM AVC INFANTIL: ESTUDO DE CASO CONSTRAINT-INDUCED MOVEMENT THERAPY IN PRESCHOOL CHILDREN WITH PEDIATRIC STROKE: A CASE STUDY." Ensaios USF 1, no. 1 (December 18, 2017): 14–24. http://dx.doi.org/10.24933/eusf.v1i1.26.
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RESUMO. O objetivo deste estudo foi valiar os efeitos da Terapia por Contensão Induzida (TCI) na função manual e amplitude de movimento (ADM) do membro superior parético (MSP) de criança com AVC. Trata-se de estudo de caso com paciente hemiparético à D, avaliado com o Pediatric Motor Activity Log (PMAL) e Goniometria do MSP, sendo realizada uma avaliação inicial (AI); avaliação final I (AFI) ao final da intervenção e avaliação final II (AFII) três meses após. A TCI teve duração de um mês, três dias por semana com duração de três horas cada, sendo estimulado a realizar exercícios fisioterapêuticos, atividades de vida diária, tarefas de lazer e escolares com o MSP. A AI foi comparada com a AFI em que pode-se observar aumento na pontuação principalmente em qualidade e, na comparação da AFI com a AFII, houve melhora principalmente na frequência, além de manutenção dos ganhos obtidos na AFI. Quanto à Goniometria, houve melhora principalmente da ADM ativa de alguns movimentos do membro e pouca diminuição de alguns movimentos na AFII. A TCI mostrou-se eficaz para melhora da função manual e na ADM do MSP em paciente com AVC infantil, podendo servir como base para estudos com amostras maiores.
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Dautova, Alʼbina Z., Valentina G. Shamratova, and Elena V. Vorobʼeva. "Lipid Profile of Plasma in Young Women Depending on Their Physical Activity and Hereditary Predisposition." Journal of Medical and Biological Research, no. 1 (February 10, 2021): 5–15. http://dx.doi.org/10.37482/2687-1491-z038.
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We studied the association of the polymorphic rs320 variant of the lipoprotein lipase (LPL) gene, rs2016520 variant of the peroxisome proliferator-activated receptor delta (PPARD) gene and rs670 variant of the apolipoprotein A1 (APOA1) gene with blood lipids in female athletes and women not involved in sports. Key indicators of the lipid spectrum – total cholesterol (TC), triglycerides (TG), highdensity lipoproteins (HDL) and low-density lipoproteins (LDL) in the blood serum – were determined by the enzymatic method using Cormay reagents (Germany) and Fluorat-02-ABLF-T analyser (Russia). Genotyping of the samples was carried out by means of the PCR-RFLP analysis. A direct correlation was found between the *H+ allele of the rs320 polymorphic variant of the LPL gene and the blood levels of TC (r = 0.17; p = 0.01), TG (r = 0.33; p = 0.000005), LDL (r = 0.16; p = 0.02), and atherogenic index (AI) (r = 0.28; p = 0.0002), as well as an inverse correlation between this allele and HDL (r = –0.19; p = 0.009) in women not involved in sports. The *A allele of the polymorphic variant rs670 of the APOA1 gene in this group showed a negative correlation with TC (r = –0.22; p = 0.004) and TG (r = –0.31; p = 0.00004), while the polymorphic variant rs2016520 of the PPARD gene revealed a linear correlation of the *C allele with LDL (r = 0.15; p = 0.02) and AI (r = 0.16; p = 0.01). Three alleles – *H of the LPL gene, *G of the APOA1 gene and *T of the PPARD gene – demonstrated an additive effect on the decrease in TG, LDL and AI and on the increase in HDL in women regardless of their level of motor activity. There were no statistically significant differences in the level of blood lipids in female athletes with different genotypes of the LPL, PPARD, and APOA1 genes. Further research is needed involving larger samples of athletes.
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Rychtyckyj, Nestor, and Craig Plesco. "Applying Automated Language Translation at a Global Enterprise Level." AI Magazine 34, no. 1 (December 6, 2012): 43. http://dx.doi.org/10.1609/aimag.v34i1.2436.
Full textAbstract:
In 2007 we presented a paper that described the application of Natural Language Processing (NLP) and Machine Translation (MT) for the automated translation of process build instructions from English to other languages to support Ford’s assembly plants in non-English speaking countries. This project has continued to evolve with the addition of new languages and improvements to the translation process. However, we discovered that there was a large demand for automated language translation across all of Ford Motor Company and we decided to expand the scope of our project to address these requirements. This paper will describe our efforts to meet all of Ford’s internal translation requirements with AI and MT technology and focus on the challenges and lessons that we learned from applying advanced technology across an entire corporation.