The Experts below are selected from a list of 42042 Experts worldwide ranked by ideXlab platform
Sheeraz Ahmad - One of the best experts on this subject based on the ideXlab platform.
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Active sensing as bayes optimal sequential decision making
Uncertainty in Artificial Intelligence, 2013Co-Authors: Sheeraz AhmadAbstract:Sensory inference under conditions of uncertainty is a major problem in both machine learning and computational neuroscience. An important but poorly understood aspect of sensory processing is the role of Active sensing. Here, we present a Bayes-optimal inference and control framework for Active sensing, C-DAC (Context-Dependent Active Controller). Unlike previously proposed algorithms that optimize abstract statistical objectives such as information maximization (Infomax) [Butko and Movellan, 2010] or one-step look-ahead accuracy [Najemnik and Geisler, 2005], our Active sensing model directly minimizes a combination of behavioral costs, such as temporal delay, response error, and sensor repositioning cost. We simulate these algorithms on a simple visual search task to illustrate scenarios in which context-sensitivity is particularly beneficial and optimization with respect to generic statistical objectives particularly inadequate. Motivated by the geometric properties of the C-DAC policy, we present both parametric and non-parametric approximations, which retain context-sensitivity while significantly reducing computational complexity. These approximations enable us to investigate a more complex search problem involving peripheral vision, and we notice that the performance advantage of C-DAC over generic statistical policies is even more evident in this scenario.
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Active sensing as bayes optimal sequential decision making
arXiv: Artificial Intelligence, 2013Co-Authors: Sheeraz AhmadAbstract:Sensory inference under conditions of uncertainty is a major problem in both machine learning and computational neuroscience. An important but poorly understood aspect of sensory processing is the role of Active sensing. Here, we present a Bayes-optimal inference and control framework for Active sensing, C-DAC (Context-Dependent Active Controller). Unlike previously proposed algorithms that optimize abstract statistical objectives such as information maximization (Infomax) [Butko & Movellan, 2010] or one-step look-ahead accuracy [Najemnik & Geisler, 2005], our Active sensing model directly minimizes a combination of behavioral costs, such as temporal delay, response error, and effort. We simulate these algorithms on a simple visual search task to illustrate scenarios in which context-sensitivity is particularly beneficial and optimization with respect to generic statistical objectives particularly inadequate. Motivated by the geometric properties of the C-DAC policy, we present both parametric and non-parametric approximations, which retain context-sensitivity while significantly reducing computational complexity. These approximations enable us to investigate the more complex problem involving peripheral vision, and we notice that the difference between C-DAC and statistical policies becomes even more evident in this scenario.
Jiming Chen - One of the best experts on this subject based on the ideXlab platform.
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cooperative and Active sensing in mobile sensor networks for scalar field mapping
Systems Man and Cybernetics, 2015Co-Authors: Weihua Sheng, Jiming ChenAbstract:Scalar field mapping has many applications including environmental monitoring, search and rescue, etc. In such applications, there is a need to achieve a certain level of confidence regarding the estimates of the scalar field. In this paper, a cooperative and Active sensing framework is developed to enable scalar field mapping using multiple mobile sensor nodes. The cooperative and Active Controller is designed via the real-time feedback of the sensing performance to steer the mobile sensors to new locations in order to improve the sensing quality. During the movement of the mobile sensors, the measurements from each sensor node and its neighbors are fused with the corresponding confidences using distributed consensus filters. As a result, an online map of the scalar field is built while achieving a certain level of confidence of the estimates. We conducted computer simulations to validate and evaluate our proposed algorithms.
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cooperative and Active sensing in mobile sensor networks for scalar field mapping
Conference on Automation Science and Engineering, 2013Co-Authors: Weihua Sheng, Jiming ChenAbstract:Scalar field mapping has many applications including environmental monitoring, search and rescue, etc. In such applications there is a need to achieve a certain level of confidence regarding the estimates at each location. In this paper, a cooperative and Active sensing framework is developed to enable scalar field mapping using multiple mobile sensor nodes. The cooperative and Active Controller is designed via the real-time feedback of the sensing performance to steer the mobile sensors to new locations in order to improve the sensing quality. During the movement of the mobile sensors, the measurements from each sensor node and its neighbors are taken and fused with the corresponding confidences using distributed consensus filters. As a result an online map of the scalar field is built with a certain level of confidence of the estimates. We conducted computer simulations to validate and evaluate our proposed algorithms.
Uwe Dethlefsen - One of the best experts on this subject based on the ideXlab platform.
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concomitant therapy with cineole eucalyptole reduces exacerbations in copd a placebo controlled double blind trial
Respiratory Research, 2009Co-Authors: Heinrich Worth, Christian Schacher, Uwe DethlefsenAbstract:The clinical effects of mucolytics in patients with chronic obstructive pulmonary disease (COPD) are discussed controversially. Cineole is the main constituent of eucalyptus oil and mainly used in inflammatory airway diseases as a mucolytic agent. We hypothesised that its known mucolytic, bronchodilating and anti-inflammatory effects as concomitant therapy would reduce the exacerbation rate and show benefits on pulmonary function tests as well as quality of life in patients with COPD. In this double-blind, placebo-controlled multi-center-study we randomly assigned 242 patients with stable COPD to receive 200 mg of cineole or placebo 3 times daily as concomitant therapy for 6 months during winter-time. The frequency, duration and severity of exacerbations were combined as primary outcome measures for testing as multiple criteria. Secondary outcome measures included changes of lung function, respiratory symptoms and quality of life as well as the single parameters of the exacerbations. Baseline demographics, lung function and standard medication of both groups were comparable. During the treatment period of 6 months the multiple criteria frequency, severity and duration of exacerbations were significantly lower in the group treated with cineole in comparison to placebo. Secondary outcome measures validated these findings. Improvement of lung function, dyspnea and quality of life as multiple criteria were statistically significant relative to placebo. Adverse events were comparable in both groups. Concomitant therapy with cineole reduces exacerbations as well as dyspnea and improves lung function and health status. This study further suggests cineole as an Active Controller of airway inflammation in COPD by intervening in the pathophysiology of airway inflammation of the mucus membrane. ISRCTN07600011
Weihua Sheng - One of the best experts on this subject based on the ideXlab platform.
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cooperative and Active sensing in mobile sensor networks for scalar field mapping
Systems Man and Cybernetics, 2015Co-Authors: Weihua Sheng, Jiming ChenAbstract:Scalar field mapping has many applications including environmental monitoring, search and rescue, etc. In such applications, there is a need to achieve a certain level of confidence regarding the estimates of the scalar field. In this paper, a cooperative and Active sensing framework is developed to enable scalar field mapping using multiple mobile sensor nodes. The cooperative and Active Controller is designed via the real-time feedback of the sensing performance to steer the mobile sensors to new locations in order to improve the sensing quality. During the movement of the mobile sensors, the measurements from each sensor node and its neighbors are fused with the corresponding confidences using distributed consensus filters. As a result, an online map of the scalar field is built while achieving a certain level of confidence of the estimates. We conducted computer simulations to validate and evaluate our proposed algorithms.
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cooperative and Active sensing in mobile sensor networks for scalar field mapping
Conference on Automation Science and Engineering, 2013Co-Authors: Weihua Sheng, Jiming ChenAbstract:Scalar field mapping has many applications including environmental monitoring, search and rescue, etc. In such applications there is a need to achieve a certain level of confidence regarding the estimates at each location. In this paper, a cooperative and Active sensing framework is developed to enable scalar field mapping using multiple mobile sensor nodes. The cooperative and Active Controller is designed via the real-time feedback of the sensing performance to steer the mobile sensors to new locations in order to improve the sensing quality. During the movement of the mobile sensors, the measurements from each sensor node and its neighbors are taken and fused with the corresponding confidences using distributed consensus filters. As a result an online map of the scalar field is built with a certain level of confidence of the estimates. We conducted computer simulations to validate and evaluate our proposed algorithms.
Bangji Zhang - One of the best experts on this subject based on the ideXlab platform.
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disturbance observer based takagi sugeno fuzzy control for an Active seat suspension
Mechanical Systems and Signal Processing, 2017Co-Authors: Donghong Ning, Shuaishuai Sun, Fei Zhang, Bangji ZhangAbstract:Abstract In this paper, a disturbance observer based Takagi-Sugeno (TS) fuzzy Controller is proposed for an Active seat suspension; both simulations and experiments have been performed verifying the performance enhancement and stability of the proposed Controller. The Controller incorporates closed-loop feedback control using the measured acceleration of the seat and deflection of the suspension; these two variables can be easily measured in practical applications, thus allowing the proposed Controller to be robust and adaptable. A disturbance observer that can estimate the disturbance caused by friction, model simplification, and Controller output error has also been used to compensate a H ∞ state feedback Controller. The TS fuzzy control method is applied to enhance the Controller’s performance by considering the variation of driver’s weight during operation. The vibration of a heavy duty vehicle seat is largest in the frequency range between 2 Hz and 4 Hz, in the vertical direction; therefore, it is reasonable to focus on controlling low frequency vibration amplitudes and maintain the seat suspensions passivity at high frequency. Moreover, both the simulation and experimental results show that the Active seat suspension with the proposed Controller can effectively isolate unwanted vibration amplitudes below 4.5 Hz, when compared with a well-tuned passive seat suspension. The Active Controller has been further validated under bump and random road tests with both a 55 kg and a 70 kg loads. The bump road test demonstrated the Controller has good transient response capabilities. The random road test result has been presented both in the time domain and the frequency domain. When with the above two loads, the controlled seat suspensions root-mean-square (RMS) accelerations were reduced by 45.5% and 49.5%, respectively, compared with a well-tuned passive seat suspension. The proposed Active seat suspension Controller has great potential and is very practical for application as it can significantly improve heavy duty driver’s ride comfort.
