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Change impact must be accounted for during effort estimation to provide for adequate decision making at the appropriate moment in the software lifecycle. Existing effort estimation approaches, like the Use Case Point method and the Constructive COst MOdeL, estimate the effort only if the change occurs at one level, for example when a new functionality is added (at functional level). However, they...
While online learning is already a part of university education and didactics, not all students have the necessary self-regulation competency to really learn on their own efficiently and effectively. In classroom a teacher can take over a moderating part, set intermediate goals and give feedback to one's progress, but participants of online learning courses (e.g. in blended scenarios or Massive Open...
Drilled well control is a process that incorporates the assessment of well status through the monitoring of its physical parameters. This management allows the detection of well anomalies such as gas kick and mud loss. In this paper is developed a gas kick/ well loss early detection model that determines the well condition and early predicts possible anomaly. The developed model insures the system...
Multiple Model Adaptive Estimator (MMAE) which is the simplest robust estimator, relies on a finite number of time-invariant models which approximate the true mode of a system. Filters in MMAE update relative importance of their estimate, when new measurements are available. However, MMAE has got a basic drawback; each filter in MMAE is associated with a time-invariant model of the system. Furthermore,...
This study explored the use of plant images to perform fractal analysis of plant architecture and growth to estimate above ground biomass. Fractal analysis of plant architectures was performed to quantify and describe functional obligations of plants. The methods used for this study included a) the assimilation of various plant species' images, b) computation of fractal dimensions and derived measures...
Due to the extensive and various information that natural images contain, it is very challenging to estimate the sparsity for an image. In this paper, we propose an adaptive sparsity estimation model for image patches, which consists of an offline training phase and online estimation phase. In offline training, for the training patch, MOEA/D is applied to obtain a group of Pareto solutions and determine...
This paper is concerned with state filtering and the parameter estimation problem of noisy Hodgkin-Huxley neuronal model. The Cubature Kalman filter is applied to solve the joint estimation problem as an effective means of dealing with system noise and observation noise. The proposed state filtering method is based on the only measurable variable - membrane potential. In addition, the method is applicable...
One of the main aims of lifelong learning architectures is to efficiently and reliably cope with the stability-plasticity dilemma. A viable solution of this dilemma combines a static offline classifier, which preserves ground knowledge that should be respected during training, with an incremental online learning of new or specific information encountered during use. A feasible realisation has been...
In this paper; a comparative study approach is proposed between Feed Forward Neural Network (ANN) and accommodative Adaptive Neuro-Fuzzy Inference System (ANFIS) rule model to find the fault of 3-ph transmission line using MATLAB Toolbox. Post fault current is the key requirement of the technique and its features are extracted using DWT ‘DB4’ as mother wavelet. These features are then used to train...
For a data center, it is very valuable to predict its storage volume value. According to the trend of current and previous storage volume data, we can predict its future value. However, the real storage volume series is always "dirty", which means it contains noise, missing data and outliers. Hence extracting its main trend is necessary for making an accurate prediction. Otherwise, the "dirty"...
Video content management methods had been studied based on the priority (e.g., the number of accesses and the elapsed time) in a video content distribution system (VCDS). However, these methods cannot adapt to the variable model of the practical accesses. Then, this paper proposes a cached video content management method with priority estimation according to the content property. Basically, this method...
Internal model control (IMC) offers an intuitive control structure and simple tuning philosophy, which makes it appealing to industrial applications. In our recent work [1], we proposed composite adaptive IMC (CAIMC) which simultaneously identified the model and the inverse in the IMC structure. It demonstrates good performance and auto-tuning capability in simulations and experiments. In this paper,...
Target tracking is an essential part in automotive driver assistance systems. Most maneuvering target tracking algorithms are based on model, and an accurate model can enhance the tracking performance. Compared with constant velocity (CV) model, constant acceleration (CA) model and Singer model, the current statistical (CS) model matches well with the actual motion of target vehicle. But when a target...
Engine performance deterioration mitigation control system is designed for performance deterioration during usage. Engine performance mitigation control is realized through that inner loop controls rotor speed and outer loop controls thrust. Thrust estimator is designed as the input of Kalman Alter, combined with clustering and LS-SVR model. This model can adapt to variation of all parameter in flight...
This paper discusses assessment of faculty performance. Based on the structure oriented evaluation model a corresponding methodology is presented. The advantage of this approach is that the evaluation is oriented towards the logical structure of evaluation goal whereby in contrast to linear evaluation models the use of weight factors can be avoided.
This paper proposes an effective model predictive direct torque control approach (MP DTC) for a three phase induction motor (IM) drive. With the proposed formulation, main features of new strategy as well as merits and drawbacks with respect to other control strategies developed for the three-phase IM like classic DTC, field oriented control, sliding mode control, and so on can be easily and promptly...
Recently, parametric models of predicting video subjective quality by exploiting packet layer or bit stream layer information at decoder side has achieved significant progress. In contrast, there are few works on estimating subjective quality in the stage of video encoding, partially because of limited and outdated dataset. In this paper, we contribute a new 4K video dataset with full subjective scores...
The main goal of this paper is to provide a novel method of parallel rotor resistance and rotor speed estimation for sensorless indirect field oriented controlled induction motor drive. In this scheme, a parallel model reference adaptive system (MRAS) is designed to simultaneous estimation of rotor speed and rotor resistance in order to achieve high-precise control in a wide range of motor speed....
In Global Navigation Satellite Systems, receivers have to cope with ionospheric scintillation, which is of paramount importance for high-precision positioning applications. However, the design of robust carrier tracking techniques under these condition still remains an open problem. The time-varying correlated scintillation phase can be modeled as an AR(p) process, whose linear nature fits very well...
This paper focuses on biomimetic hybrid feedback feedforward (HFF) learning for robot motion control. Existing HFF robot motion control approaches have a major problem that accurate estimation of the robotic dynamics, which is crucial for mimicking biological control, is not taken into account. In this study, a composite learning technique is presented to achieve fast and accurate estimation of the...
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