18886117
An Effective Human Motion Classification Approach using Knowledge Representation in Qualitative Normalised Templates
Classification of human motion in video data is essential in numerous applications. However, problems arise as the human exhibits complex and dynamic motion that is nonlinear and time varying. In this paper, we propose a knowledge-based human motion classification framework that employs fuzzy qualitative reasoning to address these problems. Our approach utilises the rich contextual information (e.g. structural and transitional characteristic of human motion) captured in video sequence to effectively study and recognise human motion. With the aid of domain knowledge, a set of fuzzy rules are defined in the knowledge base. This work is in contrast with previous attempts that depend solely on the trajectories of the body parts. Experimental results on two classes of motion (e.g. walking and running) that result in similar motions; and a comparison with the conventional method has demonstrated and validated the effectiveness of the proposed method in improving the perception of human motion.
35589713
Time Discretisation Applied to Anomaly Detection in a Marine Engine
An introduction to the problems associated with anomaly detection in a marine engine, explaining the benefits that the SAX representation brings to the field. Despite limitations in accuracy of the SAX representation in comparison with the normalised time series, we conclude that because of the reduction in data points that should be processed SAX should be considered further as a valid and efficient representation. Finally, a continuation of the work to make the approach more viable in the real world is briefly noted based upon Markov Chaining and Support Vector Machines.
37115701
Qualitative classification of descent phases in commercial flight data
Flight data from commercial aircraft in the descent is analysed using one-class classification techniques to identify possible unstable approaches. The method considers snapshots of flight parameters at certain heights in the descent and identifies any abnormalities. Combination rules are used to analyse the flight as a whole and it is found that it is possible to detect abnormal flights with a good degree of accuracy.
34728116
Travel Speed Prediction Using Fuzzy Reasoning
The speed prediction algorithm introduced in this paper takes advantage of fuzzy systems that are insensitive to random noise, robust to uncertainties, and transparent to interpretation. The proposed algorithm for outlier detection selects the potential outliers based on the density rather than the deviation adopted in conventional approaches. To evaluate the developed system, a seris of experiments conducted on the real world data. The result of the comparison performed to evaluate the outliler detection method proposed reveals the benefit from the consideration of density. The cross validation results indicate the effectiveness of the fuzzy inference system developed.
27826765
Analysing Flight Data Using Clustering Methods
This paper reviews existing forms of density-based, partitional and hierarchical clustering methods in the context of flight data analysis. Advantages and disadvantages are fully explored with a focus on proposing a clustering-based ensemble framework for monitoring flight data in order to search for anomalies during flight operation. Case studies in selected flight scenarios are provided to demonstrate the potential of clustering methods and their integration with reasoning techniques in detecting abnormal flights.
18397185
Motor Fault Diagnosis Based on Wavelet Energy and Immune Neural Network
Motor fault diagnosis methods are crucial in acquiring safe and reliable operation in motor drive systems. In this paper, a new method for the motor fault diagnosis is proposed based on wavelet packet transform (WPT) and artificial neural network (ANN). The energy of the vibration signals of motor can be obtained by the multi-decomposition of WPT and used as feature values of ANN inputs for fault diagnosis system. The artificial immune algorithm (AIA) for data clustering is employed to adaptively choose the centers and widths of the hidden layer centers of the radial basis function neural network (RBFNN). The simulation experiment results show the applicability and effectiveness of the proposed method to motor fault diagnosis.
10827335
A novel approach for analyzing dynamics in neural networks with saturated characteristics
Current theories about the dynamics of neural networks with nonlinear characteristics and parameterized by set of parameters are mostly based on approximations in one way or another. In this paper we first introduce a rigorous approach which allows us to check in which parameter region a given saturated state is an attractor of the dynamics: a saturated state w=(wi, i=1,...,N)∈{-1,1}N is an attractor of the dynamics if and only if there is a local field gap between neurons in J+(w)={i, wi=1} and J-(w)={i, wi=−1}. Then we apply the result to analyze several models in neural networks. In particular in the Hopfield model we calculate the capacity and give an exact relation between the capacity and the threshold.
4634224
Structural analysis of the KGD sequence loop of barbourin, an αIIbβ3-specific disintegrin
Disintegrins constitute a class of small proteins that inhibit platelet aggregation by binding to the fibrinogen receptor, also referred to as integrin αIIbβ3. Contrarily to other disintegrins that bind to a series of integrins via their Arg-Gly-Asp domain, the recognition site of barbourin contains a Lys-Gly-Asp sequence that ensures its specificity towards αIIbβ3. In this article, a three-dimensional model of barbourin is proposed using homology modeling and large-scale molecular dynamics simulations. The conformations of the Lys-Gly-Asp sequence of barbourin are analyzed and compared to those of peptidomimetics that exhibit similar specificity towards αIIbβ3. The tryptophan residue following the Lys-Gly-Asp sequence of the binding domain is shown to play a crucial role in the biological activity and the specificity of barbourin. Our results suggest that this disintegrin anchors to the binding pocket of the γ-chain of fibrinogen rather than to those of the Arg-Gly-Asp sequence.
877766
Inhibitory inputs increase a neurons's firing rate
Abstract Neurons are typically thought of as receiving information primarily through excitatory inputs, with inhibitory inputs playing a gating or regulating role. In this paper we demonstrate that increasing the strength of inhibitory inputs to the Hodgkin–Huxley and FitzHugh–Nagumo models can induce them to fire faster. This result is counter-intuitive and important in neural network modelling where inhibitory inputs are often neglected.
28101453
HCI Professional Involvement in k-12 Education: On Target or Missing the Mark?
Abstract. The state of learning across geographic, socioeconomic, age, and gender boundaries can be enhanced greatly by Human-Computer Information (HCI) infusion into blended learning [1][2][3] or Course Management System (CMS) software [4][3][5]. The major thrust of this paper is to examine problematic issues examined in popular software such as MoodleTM in which the HCI community could be beneficial. By regarding the ultimate students' goal, i.e. grades, and the desirable benefit of course material understanding, one can develop an understanding of what CMS software needs and CMS software users expect on the high school level.
16581818
A Case Study of Software Process Improvement During Development
We present a case study of the use of a software process improvement method which is based on the analysis of defect data. The first step of the method is the classification of software defects using attributes which relate defects to specific process activities. Such classification captures the semantics of the defects in a fashion which is useful for process correction. The second step utilizes a machine-assisted approach to data exploration which allows a project team to discover such knowledge from defect data as is useful for process correction. We show that such analysis of defect data can readily lead a project team to improve their process during development. >