


Vol 26, No 2 (2017)
- Year: 2017
- Articles: 9
- URL: https://journals.rcsi.science/1060-992X/issue/view/12241
Article
Polynomial algorithm for exact calculation of partition function for binary spin model on planar graphs
Abstract
In this paper we propose and realize an algorithm for exact calculation of partition function for planar graph models with binary variables. The complexity of the algorithm is O(N2) Experiments show good agreement with Onsager’s analytical solution for the two-dimensional Ising model of infinite size.



Neural network approach to intricate problems solving for ordinary differential equations
Abstract
We consider the problems arising in the construction of the solutions of singularly perturbed differential equations. Usually, the decision of such problems by standard methods encounters significant difficulties of various kinds. The use of a common neural network approach is demonstrated in three model problems for ordinary differential equations. The conducted computational experiments confirm the effectiveness of this approach.



A model of pulsed oscillator network and the perspectives of its application to the problems of information routing in wireless sensor networks
Abstract
Development of performance principles of wireless sensor networks (WSN) and the methods of information routing in the networks, providing a capability of self-organized and automatic style of the WSN network work, is currently of substantial interest. The attraction of associated model of pulsed oscillator networks seems to be helpful for the design of adaptive synchronization-based information routing in the WSN. An oscillatory network model with pulsed oscillator dynamics and pulsed oscillator interaction is proposed. The initial version of information transfer in the WSN with the help of synchronization of an associated oscillatory network is discussed.



Farsi/Arabic handwritten digit recognition using quantum neural networks and bag of visual words method
Abstract
Handwritten digit recognition has long been a challenging problem in the field of optical character recognition and of great importance in industry. This paper develops a new approach for handwritten digit recognition that uses a small number of patterns for training phase. To improve performance of isolated Farsi/Arabic handwritten digit recognition, we use Bag of Visual Words (BoVW) technique to construct images feature vectors. Each visual word is described by Scale Invariant Feature Transform (SIFT) method. For learning feature vectors, Quantum Neural Networks (QNN) classifier is used. Experimental results on a very popular Farsi/Arabic handwritten digit dataset (HODA dataset) show that proposed method can achieve the highest recognition rate compared to other state of the arts methods.



Deep neural networks and maximum likelihood search for approximate nearest neighbor in video-based image recognition
Abstract
We analyzed the way to increase computational efficiency of video-based image recognition methods with matching of high dimensional feature vectors extracted by deep convolutional neural networks. We proposed an algorithm for approximate nearest neighbor search. At the first step, for a given video frame the algorithm verifies a reference image obtained when recognizing the previous frame. After that the frame is compared with a few number of reference images. Each next examined reference image is chosen so that to maximize conditional probability density of distances to the reference instances tested at previous steps. To decrease the required memory space we beforehand calculate only distances from all the images to small number of instances (pivots). When experimenting with either face photos from Labeled Faces in the Wild and PubFig83 datasets or with video data from YouTube Faces we showed that our algorithm allows accelerating the recognition procedure by 1.4–4 times comparing with known approximate nearest neighbor methods.



A differential image compression method using adaptive parameterized extrapolation
Abstract
The paper deals with an image compression method using differential pulse-code modulation (DPCM) with an adaptive extrapolator capable of adjusting itself to local distinctions of image contours (boundaries). A negative effect of quantization on the optimization of the adaptive extrapolator is investigated. Even so the experiment has shown that the use of an adaptive extrapolator is more effective than the use of prototypes. We have studied the method as a whole with close consideration given to the coding of the quantized signal. The maximal error criterion and a Waterloo grey set of real patterns are used to compare the method with the JPEG technique.



An electric field sensor based on reflected light intensity modulation from electro-optical media
Abstract
An optical sensor of an alternating electric field is described. The sensing element is a crystal quartz plate which reflects incident light by its front surface. Reflected light intensity is modulated by the tested electric field by means of changing the refractive index of the plate. Modulation of the reflection coefficient of the quartz by the tested electric field occurs due to the electro-optic effect. It is noted that the main advantage of the sensor working on the modulation of the reflected light is the ability to use opaque electro-optical media and thin films.



Gravitation and radiation
Abstract
Gravitation is one of the most intriguing forces in space that govern all the interstellar spectacles motion in this universe. In this article we have shown there is a profound relationship between gravitational fields with respect to its converted energy. Since time is an inevitable element in every aspect of science; we have developed a partial differential equation from Einstein’s energy equation in which we show that gravitational field can be coupling with its diverging energy radiation. We have also shown that energy to mass conversion in principle is conceivable by means of energy convergent operation (i.e., in-flow) into a unit space. In fact this could have been happen by the eventuality of a black hole explosion, as remains to be observed.



Extraordinary spin momenta in birefringent structures
Abstract
Mechanical action caused by the optical forces connected with the canonical momentum density associated with the local wave vector or classical spin angular momentum, the helicity dependent and the helicity independent forces determined by spin momenta of different nature open attractive prospects to use optical structures for manipulating with nanoobjects of different nature. The main finding of our study consists in demonstration of mechanical action of extraordinary transverse component of the spin angular momentum arising in an evanescent light wave due to the total internal reflection of linearly polarized probing beam with azimuth 45° at the interface ‘birefringent plate–air’.


