Simulation of an industrial nylon 6 tubular reactor

A commonly used energy-efficient nylon 6 reactor is simulated under steady-state conditions. The effects of various operating conditions and parameters, e.g., feed composition, temperature and flow rate, heat transfer coefficients, and reactor dimensions, on the temperature and molecular weight profiles are studied. A temperature maximum is observed in the reactor under usual conditions of operation. The maximum value of the temperature is sensitive to the feed conditions, and one has to ensure that degradation reactions speeded up at high temperatures do not affect product characteristics. The model and the numerical technique used are fairly simple and account for most of the important features of industrial reactors. Hence, these can be used in the development of digital-control algorithms in the future.     

Gravity optimised particle filter for hand tracking

This paper presents a gravity optimised particle filter (GOPF) where the magnitude of the gravitational force for every particle is proportional to its weight. GOPF attracts nearby particles and replicates new particles as if moving the particles towards the peak of the likelihood distribution, improving the sampling efficiency. GOPF is incorporated into a technique for hand features tracking. A fast approach to hand features detection and labelling using convexity defects is also presented. Experimental results show that GOPF outperforms the standard particle filter and its variants, as well as state-of-the-art CamShift guided particle filter using a significantly reduced number of particles.     

Fusion of ANNs as decoder of retinal spike trains for scene reconstruction

Applied Intelligence - The retina is one of the most developed sensing organs in the human body. However, the knowledge on the coding and decoding of the retinal neurons are still rather limited....     

Model updating improves MRAC performance

The performance of an MRAC design can be improved by using the model-updating concept, which places the state of the system into the reference model at regular time intervals. This paper discusses criteria for determining this updating and a proof is given to show that model updating does not influence the stability properties of an MRAC design. A typical example indicates an improvement in the control performance obtained by the application of model updating.     

An Efficient Crossing-Line Crowd Counting Algorithm with Two-Stage Detection

Crowd counting is a challenging task in crowded scenes due to heavy occlusions, appearance variations and perspective distortions. Current crowd counting methods typically operate on an image patch level with overlaps, then sum over the patches to get the final count. In this paper we describe a real-time pedestrian counting framework based on a two-stage human detection algorithm. Existing works with overhead cameras is mainly based on visual tracking, and their robustness is rather limited. On the other hand, some works, which focus on improving the performances, are too complicated to be realistic. By adopting a line sampling process, a temporal slice image can be obtained for pedestrian counting without the need for visual tracking. Only ten low level features are extracted from the input image to establish a feature vector. As a result, our algorithm is more efficient and accurate than existing methods. Pedestrians in the temporal slice image are then located by the two-stage detection algorithm, which is largely based on support vector machine and affinity propagation clustering. Moreover, a novel algorithm is proposed to determine the moving directions of pedestrians by comparing the centers of them in two temporal slice images. Extensive experiments reveal that our system achieves satisfaction performances in terms of both robustness and efficiency.     

Bounded diffusion for multiscale edge detection using regularizedcubic B-spline fitting

This paper shows that in edge detection the regularization factor alpha is a better scale parameter than the standard deviation (sigma) of the Gaussian pre-filter. The alpha scale space, which exhibits the evolutionary behaviour of an edge in various scales, is the basis for the design of a multiscale edge detector (MRCBS). In MRCBS, the scale is determined adaptively according to the local noise level; the thresholds which control the amount of edge details are adjusted according to the scale; and the anisotropic diffusion is applied in the finest scale to further suppress noise.     

Multiview camera-calibration framework for nonparametric distortions removal

This paper proposes a technique that uses a planar calibration object and projective constraints to calibrate parametric and nonparametric distortions. An iterative surface fitting is first used to constrain a B-spline distortion model by fusing the corrective distortion maps obtained from multiple views. The model is then refined within the whole camera-calibration process.     

Investigation of ferromagnetic phase in austenitic steels

Conclusion We propose the suspension method for revealing the ferrite distribution in austenitic acid-resisting steels. The major advantages of this method are its simplicity, speed, and reproducibility of the results.This paper was presented at the Jubilee All-Union Scientific-Technical Conference on New and progressive heat-treatment methods held in Tbilisi in May, 1967. Research Institute of Ferrous Metals, Budapest. Translated from Metallovedenie i Termicheskaya Obrabotka Metallov, No. 9, pp. 16–17, September, 1967.     

Adaptability analysis of genetic network programming with reinforcement learning in dynamically changing environments

Genetic network programming (GNP) has been proposed as one of the evolutionary algorithms and extended with reinforcement learning (GNP-RL). The combination of evolution and learning can efficiently evolve programs and the fitness improvement has been confirmed in the simulations of tileworld problems, elevator group supervisory control systems, stock trading models and wall following behavior of Khepera robot. However, its adaptability in testing environments, where the situations dynamically change, has not been analyzed in detail yet. In this paper, the adaptation mechanism in the testing environment is introduced and it is confirmed that GNP-RL can adapt to the environmental changes using a robot simulator WEBOTS, especially when unexperienced sensor troubles suddenly occur. The simulation results show that GNP-RL works well in the testing even if wrong sensor information is given because GNP-RL has a function to automatically change programs using alternative actions. In addition, the analysis on the effects of the parameters of GNP-RL is carried out in both training and testing simulations.