Experimental estimate of self-irradiation of building bricks due to incorporated radionuclides

A method is described for experimentally determining the dose rate created in building bricks by incorporated natural radionuclides. It was established using the thermoluminescence dosimetry method that the measured dose rate depends on the detector thickness, the mass of the ceramic product investigated, and the irradiation geometry. The contributions to the measured dose of weakly penetrating α and β radiation and hard ψ radiation are separated, the ratio between them depending on the experimental conditions. Translated from Izmeritel'naya Tekhnika, No. 7, pp. 62–66, July, 1996.     

Application of neural networks and machine learning in networkdesign

Communication network design is becoming increasingly complex, involving making networks more usable, affordable, and reliable. To help with this, we have proposed an expert network designer (END) for configuring, modeling, simulating, and evaluating large structured computer networks, employing artificial intelligence, knowledge representation, and network simulation tools. We present a neural network/knowledge acquisition machine-learning approach to improve the END's efficiency in solving the network design problem and to extend its scope to acquire new networking technologies, learn new network design techniques, and update the specifications of existing technologies     

Series equivalence/operation of current-controlled boost-typesingle-phase voltage source converters for bidirectional power flow

Single-phase voltage source power converters (VSCs) under consideration are AC-DC current-controlled boost-type power converters with bidirectional power-handling capability. Equivalence between two series-connected two-level power converters and a single three-level power converter is considered here. Further considered is the series operation of three-level power converters. Simulation results and experimental verification for both are provided. Economical configurations of three-level power converters leading to multilevel waveforms are presented thereafter     

Conditions for reliable dewatering systems based on voidless drainage in slightly permeable soils

Conclusions 1. Use of dewatering systems based on voidless drainage is most effective when dewatering slightly permeable soils in regions with a deep seasonal frost. 2. Two-story drainage with the upper and lower stories spaced 30 m apart accelerates the discharge of gravitational water from the arable layer. Results of observations on two-story drainage in experimental-production sections indicated that it discharges 2 – 3.8 times more water than systematic tubular drainage with an interdrain spacing of 10 m and a 0.2-m thick three-dimensional filter of a sandy-gravelly mixture. 3. It is recommended to use crushed stone and porous-clay gravel with a fineness of 10 – 20 mm as a filler. In that case, protection of the drain filler is, as a rule, required only from the intrusion of soil from above during construction in cohesive soils with a plasticity indexW _p≥7. 4. seepage rate in a voidless drain should be lower than the scouring velocity for the soil in which the voidless drainage is placed. In the opposite case, it is necessary to lower the grade of the drains or select a filler gradation such that the seepage rate in the drain be lower than the scouring velocity. Translated from Gidrotekhnicheskoe Stroitel’stvo, No. 8, pp. 41–43, August, 1998.     

Quantization effects in digitally behaving circuit implementationsof Kohonen networks

Implementing a neural network on a digital or mixed analog and digital chip yields the quantization of the synaptic weights dynamics. This paper addresses this topic in the case of Kohonen's self-organizing maps. We first study qualitatively how the quantization affects the convergence and the properties, and deduce from this analysis the way to choose the parameters of the network (adaptation gain and neighborhood). We show that a spatially decreasing neighborhood function is far more preferable than the usually rectangular neighborhood function, because of the weight quantization. Based on these results, an analog nonlinear network, integrated in a standard CMOS technology, and implementing this spatially decreasing neighborhood function is then presented. It can be used in a mixed analog and digital circuit implementation.     

Genetic evolution of the topology and weight distribution of neuralnetworks

This paper proposes a system based on a parallel genetic algorithm with enhanced encoding and operational abilities. The system, used to evolve feedforward artificial neural networks, has been applied to two widely different problem areas: Boolean function learning and robot control. It is shown that the good results obtained in both cases are due to two factors: first, the enhanced exploration abilities provided by the search-space reducing evolution of both coding granularity and network topology, and, second, the enhanced exploitational abilities due to a recently proposed cooperative local optimizing genetic operator.     

Large-deviation inequalities for parameter estimators in stochastic systems

Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 95–112, March–April, 1994.