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This paper presents a knee torque estimation in non-pathological gait cycle at stance phase. Comparative modelling by using dynamics model and neural network model is discussed. Dynamics modelling is constructed by using simple two degree of freedom dynamics with Newtonian calculation approach and more complex four degree of freedom dynamics with Lagrangian calculation approach. Neural network based...
This paper aims at construction of a system which assumes food textures. The system consists of equipment for obtaining the load and the sound signals while the probe is stabbing the food, and the neural network model infers the degree of the food texture. In the experiment, the validity of our proposed system is discussed.
Step change is a key factor affecting the user trajectory and distance, to determine the trajectory of the user is a common indoor positioning method based on inertial navigation line calculation model, the prediction step is mainly based on the linear sensor, acceleration sensor data and the movement of the periodic estimation of pedestrians every step of the displacement distance. In order to improve...
Software Defined Networking (SDN) is a new promising networking concept which has a centralized control over the network and separates the data and control planes. This new approach provides abstraction of lower-level functionality and allows the network administrators to initialize, control, change, and manage network behavior programmatically. The centralized control, being the major advantage of...
Facial recognition applications present a great interest in the area of computer vision, with various methods and approaches that provide impressive performance. However, not all studies investigate the possibilities of using proper feature extraction methods with efficient classifiers, for applications that facial expression is not required for detection. In this sense, we propose another facial...
Huge amount of data in today's world are stored in the form of electronic documents. Text mining is the process of extracting the information out of those textual documents. Text classification is the process of classifying text documents into fixed number of predefined classes. The application of text classification includes spam filtering, email routing, sentiment analysis, language identification...
A machine learning approach for the operational situational awareness (OSA) in flight operations is presented. The spacecraft health and safety telemetry are generally time dependent and periodical. The machine learning algorithms, such as neural networks, are used to capture the time dependent trend of the telemetry datasets characterized by their data patterns and noise level, which provides a direct...
Automated, efficient and accurate classification of skin diseases using digital images of skin is very important for bio-medical image analysis. Various techniques have already been developed by many researchers. In this work, a technique based on meta-heuristic supported artificial neural network has been proposed to classify images. Here 3 common skin diseases have been considered namely angioma,...
Recent studies suggest that epidural stimulation of the spinal cord could increase the motor pattern both in motor and sensory complete spinal cord injury (SCI) patients. However, choosing the optimal epidural stimulation variables, such as the frequency, intensity, and location of the stimulation, significantly affects maximal motor functionality. This paper presents a novel technique using machine...
Committees of multilayer neural networks were used to estimate the appropriate surface area and thickness of RF absorbing material needed to achieve a desired quality factor (Q) inside a reverberation chamber. The networks were trained with Bayesian Regularization to avoid overfitting. Monte Carlo cross-validation was used to develop confidence bounds on the accuracy of the network committees.
This paper presents nonlinear filters that are obtained from extensions of morphological filters. The proposed nonlinear filter consists of a convex and concave filter that are extensions of the dilation and erosion of morphological filter with the maxout activation function. Maxout can approximate arbitrary convex functions as piecewise linear functions, including the max function of the morphological...
In advanced wireless communication systems that require spectrally efficient modulation schemes, the modulated signal with a high peak-to-average power ratio (PAPR) drives the power amplifier (PA) to operate near the saturation region and introduces serious nonlinearity of the PA. Digital predistortion (DPD) is one of the most promising techniques for PA linearization. In this paper, we propose a...
Heart disease affects seriously to human health. ECG signal is critical information to help doctor with heart diagnose prediction. In previous studies on ECG classifier, state-of-art method use MIT dataset to evaluate prediction result and record a high accuracy. However, the dataset has a long tail phenomenon where the number of normal beats is cover 83,6% of all dataset whereas some diagnose beats...
Neural network is a kind of machine learning algorithm, applied in many ways. The traditional predictive guidance of aerocraft is hard to resolve the contradiction among robustness, real-time and the guidance of precision. The paper provides a predictive guidance algorithm for aerocraft, by combining neural network with predictive guidance to solve this problem. This research about the new style guidance...
To make full use of the data information and improve the classification performance, a new evidential neural network classifier is proposed and a novel implementation of multiple classifier systems based on the new evidential neural network classifier is presented in this paper. The ambiguous data contained in the training data is considered as a new class — compound class and the training data is...
The goal of the Internet of Things (IoT) is to transform any thing around us, such as a trash can or a street light, into a smart thing. A smart thing has the ability of sensing, processing, communicating and/or actuating. In order to achieve the goal of a smart IoT application, such as minimizing waste transportation costs or reducing energy consumption, the smart things in the application scenario...
This paper discusses the method for shirt version intelligent recommendation through combining human body data analysis and apparel loose quantity setting analysis. Firstly, we get the weight of each factor by Analytic Hierarchy Process (AHP) and realize the recommendation of the best shirt shape through the garment size. Then by using the Back Propagation(BP) neural network, we input net body size...
Understanding temporal expressions is the important foundation of many NLP tasks. However, the varied representations of temporal expressions is difficulty in analysis and understanding. To parsing expressions, an effective classification method of temporal expressions is significant. A temporal expression may belong to one or more classes, but the classification usually requires manual annotation...
In order to accomplish the fault prediction of complicated and enormous mechanical equipment, this paper proposed a fault prediction model for complicated mechanical equipment that based on rough sets theory and BP neural network . Firstly,the discretization of continuous data was implemented by the discretization algorithm based on dynamic hierarchical clustering in rough set theory;secondly, an...
Spare parts are indispensable resources to ensure equipment the normal operation and continuous production, especially for urban raü vehicles. When the spare parts storage is insufficient, the equipment can't be replaced or repair ed in time, which can cause serious loss. Therefore, it is important to forecast the demand of the urban rail vehicle spare parts. A combination forecasting method based...
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