842 resultados para Training control
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The construction industry is a crucial component of the Hong Kong economy, and the safety and efficiency of workers are two of its main concerns. The current approach to training workers relies primarily on instilling practice and experience in conventional teacher-apprentice settings on and off site. Both have their limitations however, on-site training is very inefficient and interferes with progress on site, while off-site training provides little opportunity to develop the practical skills and awareness needed through hands-on experience. A more effective way is to train workers in safety awareness and efficient working by current novel information technologies. This paper describes a new and innovative prototype system – the Proactive Construction Management System (PCMS) – to train precast installation workers to be highly productive while being fully aware of the hazards involved. PCMS uses Chirp-Spread-Spectrum-based (CSS) real-time location technology and Unity3D-based data visualisation technology to track construction resources (people, equipment, materials, etc.) and provide real-time feedback and post-event visualisation analysis in a training environment. A trial of a precast facade installation on a real site demonstrates the benefits gained by PCMS in comparison with equivalent training using conventional methods. It is concluded that, although the study is based on specific industrial conditions found in Hong Kong construction projects, PCMS may well attract wider interest and use in future.
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This thesis was concerned with the protective mechanisms of first aid training in the context of peer support. Using a randomised control trial design the current program of research explores first aid training in the school setting and identifies the key components of effective school-based first aid training programs. In particular, examining whether first aid training and associated knowledge could be protective for early adolescents. This broader framing considered whether first aid impacted on increasing behaviour and attitudes towards helping an injured friend, and reducing personal risk taking and related injury.
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This paper details the development of an online adaptive control system, designed to learn from the actions of an instructing pilot. Three learning architectures, single layer neural networks (SLNN), multi-layer neural networks (MLNN), and fuzzy associative memories (FAM) are considerd. Each method has been tested in simulation. While the SLNN and MLNN provided adequate control under some simulation conditions, the addition of pilot noise and pilot variation during simulation training caused these methods to fail.
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The effect of 18 months of training on the ovarian hormone concentrations and bone mineral density (BMD) accrual was assessed longitudinally in 14 adolescent rowers and 10 matched controls, aged 14–15 years. Ovarian hormone levels were assessed by urinary estrone glucuronide (E1G) and pregnanediol glucuronide (PdG) excretion rates, classifying the menstrual cycles as ovulatory or anovulatory. Total body (TB), total proximal femur (PF), femoral neck (FN) and lumbar spine (LS) (L2–4) bone mass were measured at baseline and 18 months using dual-energy X-ray densitometry. Results were expressed as bone mineral content (BMC), BMD and bone mineral apparent density (BMAD). Five rowers had anovulatory menstrual cycles compared with zero prevalence for the control subjects. Baseline TB BMD was significantly higher in the ovulatory rowers, with PF BMD, FN BMD and LS BMD similar for all groups. At completion, the LS bone accrual of the ovulatory rowers was significantly greater (BMC 8.1%, BMD 6.2%, BMAD 6.2%) than that of the anovulatory rowers (BMC 1.1%, BMD 3.9%, BMAD 1.6%) and ovulatory controls (BMC 0.5%, BMD 1.1%, BMAD 1.1%). No difference in TB, PF or FN bone accrual was observed among groups. This study demonstrated an osteogenic response to mechanical loading, with the rowers accruing greater bone mass than the controls at the lumbar spine. However, the exercise-induced osteogenic benefits were less when rowing training was associated with low estrogen and progesterone metabolite excretion.
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BACKGROUND High magnitude loads and unusual loading regimes are two important determinants for increasing bone mass. Past research demonstrated that positive Gz-induced loading, providing high loads in an unaccustomed manner, had an osteogenic effect on bone. Another determinant of bone mass is that the bone response to loading is site specific. This study sought to further investigate the site specific bone response to loading, examining the cervical spine response, the site suspected of experiencing the greatest loading, to high performance flight. METHODS Bone mineral density (BMD) and bone mineral content (BMC) was monitored in 9 RAAF trainee fighter pilots completing an 8-mo flight training course on a PC-9 and 10 age-height-weight-matched controls. RESULTS At completion of the course, the pilots had a significant increase in cervical spine BMD and total body BMC. No significant changes were found for the control group. CONCLUSIONS This study demonstrated that the physical environment associated with flight training may have contributed to a significant increase in cervical spine bone mass in the trainee PC-9 pilots. The increase in bone mass was possibly a response to the strain generated by the daily wearing of helmet and mask assembly under the influence of positive sustained accelerative forces.
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Place recognition has long been an incompletely solved problem in that all approaches involve significant compromises. Current methods address many but never all of the critical challenges of place recognition – viewpoint-invariance, condition-invariance and minimizing training requirements. Here we present an approach that adapts state-of-the-art object proposal techniques to identify potential landmarks within an image for place recognition. We use the astonishing power of convolutional neural network features to identify matching landmark proposals between images to perform place recognition over extreme appearance and viewpoint variations. Our system does not require any form of training, all components are generic enough to be used off-the-shelf. We present a range of challenging experiments in varied viewpoint and environmental conditions. We demonstrate superior performance to current state-of-the- art techniques. Furthermore, by building on existing and widely used recognition frameworks, this approach provides a highly compatible place recognition system with the potential for easy integration of other techniques such as object detection and semantic scene interpretation.
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Objective The aim of this systematic review and meta-analysis was to determine the overall effect of resistance training (RT) on measures of muscular strength in people with Parkinson’s disease (PD). Methods Controlled trials with parallel-group-design were identified from computerized literature searching and citation tracking performed until August 2014. Two reviewers independently screened for eligibility and assessed the quality of the studies using the Cochrane risk-of-bias-tool. For each study, mean differences (MD) or standardized mean differences (SMD) and 95% confidence intervals (CI) were calculated for continuous outcomes based on between-group comparisons using post-intervention data. Subgroup analysis was conducted based on differences in study design. Results Nine studies met the inclusion criteria; all had a moderate to high risk of bias. Pooled data showed that knee extension, knee flexion and leg press strength were significantly greater in PD patients who undertook RT compared to control groups with or without interventions. Subgroups were: RT vs. control-without-intervention, RT vs. control-with-intervention, RT-with-other-form-of-exercise vs. control-without-intervention, RT-with-other-form-of-exercise vs. control-with-intervention. Pooled subgroup analysis showed that RT combined with aerobic/balance/stretching exercise resulted in significantly greater knee extension, knee flexion and leg press strength compared with no-intervention. Compared to treadmill or balance exercise it resulted in greater knee flexion, but not knee extension or leg press strength. RT alone resulted in greater knee extension and flexion strength compared to stretching, but not in greater leg press strength compared to no-intervention. Discussion Overall, the current evidence suggests that exercise interventions that contain RT may be effective in improving muscular strength in people with PD compared with no exercise. However, depending on muscle group and/or training dose, RT may not be superior to other exercise types. Interventions which combine RT with other exercise may be most effective. Findings should be interpreted with caution due to the relatively high risk of bias of most studies.
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Purpose To determine i) the architectural adaptations of the biceps femoris long head (BFlf) following concentric or eccentric strength training interventions; ii) the time course of adaptation during training and detraining. Methods Participants in this randomized controlled trial (control [n=28], concentric training group [n=14], eccentric training group [n=14], males) completed a 4-week control period, followed by 6 weeks of either concentric- or eccentric-only knee flexor training on an isokinetic dynamometer and finished with 28 days of detraining. Architectural characteristics of BFlf were assessed at rest and during graded isometric contractions utilizing two-dimensional ultrasonography at 28 days pre-baseline, baseline, days 14, 21 and 42 of the intervention and then again following 28 days of detraining. Results BFlf fascicle length was significantly longer in the eccentric training group (p<0.05, d range: 2.65 to 2.98) and shorter in the concentric training group (p<0.05, d range: -1.62 to -0.96) after 42 days of training compared to baseline at all isometric contraction intensities. Following the 28-day detraining period, BFlf fascicle length was significantly reduced in the eccentric training group at all contraction intensities compared to the end of the intervention (p<0.05, d range: -1.73 to -1.55). There was no significant change in fascicle length of the concentric training group following the detraining period. Conclusions These results provide evidence that short term resistance training can lead to architectural alterations in the BFlf. In addition, the eccentric training-induced lengthening of BFlf fascicle length was reversed and returned to baseline values following 28 days of detraining. The contraction mode specific adaptations in this study may have implications for injury prevention and rehabilitation.
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Objective To compare two neck strength training modalities. Background Neck injury in pilots flying high performance aircraft is a concern in aviation medicine. Strength training may be an effective means to strengthen the neck and decrease injury risk. Methods The cohort consisted of 32 age-height-weight matched participants, divided into two experimental groups; the Multi-Cervical Unit (MCU) and Thera-Band tubing groups (THER), and a control (CTRL) group. Ten weeks of training were undertaken and pre-and post isometric strength testing for all groups was performed on the MCU. Comparisons between the three groups were made using a Kruskal-Wallis test and effect sizes between the MCU and the THER groups and the THER and CTRL groups were also calculated. Results The MCU group displayed the greatest increase in isometric strength (flexion 64.4%, extension 62.9%, left lateral flexion 53.3%, right lateral flexion 49.1%) and differences were only statistically significant (p<0.05) when compared to the CTRL group. Increases in neck strength for the THER group were lower than that shown in the MCU group (flexion 42.0%, extension 29.9%, left lateral flexion 26.7%, right lateral flexion 24.1%). Moderate to large effect sizes were found between the MCU and THER as well as the THER and CTRL groups. Conclusions This study demonstrated that the MCU was the most effective training modality to increase isometric cervical muscle strength. Thera-Band tubing did however, produce moderate gains in isometric neck strength
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This paper introduces a machine learning based system for controlling a robotic manipulator with visual perception only. The capability to autonomously learn robot controllers solely from raw-pixel images and without any prior knowledge of configuration is shown for the first time. We build upon the success of recent deep reinforcement learning and develop a system for learning target reaching with a three-joint robot manipulator using external visual observation. A Deep Q Network (DQN) was demonstrated to perform target reaching after training in simulation. Transferring the network to real hardware and real observation in a naive approach failed, but experiments show that the network works when replacing camera images with synthetic images.
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Previous research has shown that action tendencies to approach alcohol may be modified using computerized ApproacheAvoidance Task (AAT), and that this impacted on subsequent consumption. A recent paper in this journal (Becker, Jostman, Wiers, & Holland, 2015) failed to show significant training effects for food in three studies: Nor did it find effects on subsequent consumption. However, avoidance training to high calorie foods was tested against a control rather than Approach training. The present study used a more comparable paradigm to the alcohol studies. It randomly assigned 90 participants to ‘approach’ or ‘avoid’ chocolate images on the AAT, and then asked them to taste and rate chocolates. A significant interaction of condition and time showed that training to avoid chocolate resulted in faster avoidance responses to chocolate images, compared with training to approach it. Consistent with Becker et al.'s Study 3, no effect was found on amounts of chocolate consumed, although a newly published study in this journal (Schumacher, Kemps, & Tiggemann, 2016) did do so. The collective evidence does not as yet provide solid basis for the application of AAT training to reduction of problematic food consumption, although clinical trials have yet to be conducted.
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Tämä työ tarkastelee kansallista ja paikallista omistajuutta Namibian opetussektorin kehittämisohjelmassa. Opetussektorin kehittämisohjelma ETSIP on 15-vuotinen sektoriohjelma vuosille 2005-2015 ja sen tavoitteena on edesauttaa Namibian kehittymistä tietoyhteiskunnaksi. Tutkimuksen tarkoituksena on selvittää miten kansallinen ja paikallinen omistajuus on toteutunut ETSIP prosessin aikana. Erityisesti pyritään selvittämään paikallistason opetussektorin virkamiesten näkemyksiä ETSIP prosessista, heidän roolistaan siinä ja siitä millaisia vaikuttamisen ja hallinnan mahdollisuuksia heillä on ollut prosessin aikana. Tutkimuksen lähtökohta on laadullinen ja lähestymistapa konstruktionistinen: tutkimus tarkastelee todellisuutta ihmisten kokemusten, näkemysten ja toiminnan kautta. Tutkimusaineisto koostuu haastatteluista, epävirallisista keskusteluista, lehtiartikkeleista ja ETSIP dokumenteista. Tutkimus osoittaa että kansallinen omistajuus on epämääräinen käsite sillä kansallisia toimijoita ja näkemyksiä on useita. Tutkimus vahvistaa Castel-Brancon huomion siitä, että omistajuutta on tarkasteltava kontekstissaan: muuttuvana ja kilpailtuna. ETSIPin rinnalle ollaan valmistelemassa uutta strategista ohjelmaa opetusministeriölle mikä saattaa muuttaa omistajuutta ETSIPiin. ETSIP dokumenttien omistajuusretoriikka myötäilee kansainvälisiä sitoumuksia avun vaikuttavuuden parantamiseksi mutta niistä puuttuu syvällisempi analyysi siitä, miten kansallinen ja paikallinen omistajuus toteutuisi käytännössä. Avunantajien näkemys omistajuudesta on suppea: omistajuus nähdään lähinnä sitoutumisena ennalta määrättyyn politiikkaohjelmaan. Haastatteluaineistosta nousee esiin Whitfieldin ja Frazerin jaottelu suppeista ja laajoista omistajuuskäsityksistä. Sitoutumista ETSIP ohjelmaan pidetään tärkeänä mutta riittämättömänä määritteenä omistajuudelle. Paikallisella tasolla sitoutuminen ETSIP ohjelman periaatteisiin ja tavoitteisiin on toteutunut melko hyvin mutta jos omistajuutta tarkastellaan laajemmin vaikutusvallan ja hallinnan käsitteiden kautta voidaan todeta että omistajuus on ollut heikkoa. Paikallisella tasolla ei ole ollut juurikaan vaikutusvaltaa ETSIP ohjelman sisältöön eikä mahdollisuutta hallita ohjelman toteutusta ja päättää siitä mitä hankkeita ohjelman kautta rahoitetaan. Tujanin demokraattisen omistajuuden käsite kuvaa tarvetta muuttaa ja laajentaa omistajuusajattelua huomioiden paikallisen tason paremmin. Tämä tutkimus viittaa siihen että omistajuuden toteutuminen paikallisella tasolla edellyttäisi institutionaalisen kulttuurin muutosta ja institutionaalisen legitimiteetin vahvistamista. Omistajuuden mahdollistamiseksi paikallisella tasolla tarvittaisiin poliittista johtajuutta, luottamusta, vastuullisuuden kulttuurin kehittämistä, tehokkaampaa tiedonjakoa, laajaa osallistumista, vuoropuhelua ja yhteistyötä. Ennen kaikkea tarvittaisiin paikallisen tason vaikutusvaltaa päätöksenteossa ja kontrollia resurssien käytöstä. Tälle muutokselle on selvä tarve ja tilaus.
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Fuzzy logic control (FLC) systems have been applied as an effective control system in various fields, including vibration control of structures. The advantage of this approach is its inherent robustness and ability to handle non‐linearities and uncertainties in structural behavior and loading. The study evaluates the three‐dimensional benchmark control problem for a seismically excited highway bridge using an ANFIS driven hydraulic actuators. An ANN based training strategy that considers both velocity and acceleration feedback together with a fuzzy logic rule base is developed. Present study needs only 4 accelerometers and 4 fuzzy rule bases to determine the control force, instead of 8 accelerometers and 4 displacement transducers used in the benchmark study problem. The results obtained are better than that obtained from the benchmark control algorithm.
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This paper presents the design and implementation of a learning controller for the Automatic Generation Control (AGC) in power systems based on a reinforcement learning (RL) framework. In contrast to the recent RL scheme for AGC proposed by us, the present method permits handling of power system variables such as Area Control Error (ACE) and deviations from scheduled frequency and tie-line flows as continuous variables. (In the earlier scheme, these variables have to be quantized into finitely many levels). The optimal control law is arrived at in the RL framework by making use of Q-learning strategy. Since the state variables are continuous, we propose the use of Radial Basis Function (RBF) neural networks to compute the Q-values for a given input state. Since, in this application we cannot provide training data appropriate for the standard supervised learning framework, a reinforcement learning algorithm is employed to train the RBF network. We also employ a novel exploration strategy, based on a Learning Automata algorithm,for generating training samples during Q-learning. The proposed scheme, in addition to being simple to implement, inherits all the attractive features of an RL scheme such as model independent design, flexibility in control objective specification, robustness etc. Two implementations of the proposed approach are presented. Through simulation studies the attractiveness of this approach is demonstrated.
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In this letter, we analyze the Diversity Multiplexinggain Tradeoff (DMT) performance of a training-based reciprocal Single Input Multiple Output (SIMO) system. Assuming Channel State Information (CSI) is available at the Receiver (CSIR), we propose a channel-dependent power-controlled Reverse Channel Training (RCT) scheme that enables the transmitter to directly estimate the power control parameter to be used for the forwardlink data transmission. We show that, with an RCT power of (P) over bar (gamma), gamma > 0 and a forward data transmission power of (P) over bar, our proposed scheme achieves an infinite diversity order for 0 <= g(m) < L-c-L-B,L-tau/L-c min(gamma, 1) and r > 2, where g(m) is the multiplexing gain, L-c is the channel coherence time, L-B,L-tau is the RCT duration and r is the number of receive antennas. We also derive an upper bound on the outage probability and show that it goes to zero asymptotically as exp(-(P) over bar (E)), where E (sic) (gamma - g(m)L(c)/L-c-L-B,L-tau), at high (P) over bar. Thus, the proposed scheme achieves a significantly better DMT performance compared to the finite diversity order achieved by channel-agnostic, fixed-power RCT schemes.