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.     

E-kernel: an embedding kernel on the IBM victor V256 multiprocessorfor program mapping and network reconfiguration

We present the design of E-kernel, an embedding kernel on the Victor V256 message-passing partitionable multiprocessor, developed for the support of program mapping and network reconfiguration. E-kernel supports the embedding of a new network topology onto Victor's 2D mesh and also the embedding of a task graph onto the 2D mesh network or the reconfigured network. In the current implementation, the reconfigured network can be a line or an even-size ring, and the task graphs meshes or tori of a variety of dimensions and shapes or graphs with similar topologies. For application programs having these task graph topologies and that are designed according to the communication model of E-kernel, they can be run without any change on partitions connected by the 2D mesh, line, or ring. Further, E-kernel attempts the communication optimization of these programs on the different networks automatically, thus making both the network topology and the communication optimization attempt completely transparent to the application programs. Many of the embeddings used in E-kernel are optimal or asymptotically optimal (with respect to minimum dilation cost). The implementation of E-kernel translated some of the many theoretical results in graph embeddings into practical tools for program mapping and network reconfiguration in a parallel system. E-kernel is functional on Victor V256. Measurements of E-kernel's performance on V256 are also included     

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.     

Active,passive and transpassive dissolution of a nickel base super alloy in concentrated acid mixture solution

The electrochemical and corrosion behaviour of a nickel base super alloy (C-263) has been investigated in the deaerated binary and ternary solution mixture of concentrated phosphoric acid, acetic acid, sulphuric acid, nitric acid or water using potentiostatic technique at 35°C. The possibilities of electropolishing of this alloy in these solution mixtures have been also explored. The alloy showed distinct active, passive and transpassive behaviour in the experimental solutions. The alloy remained active and turned passive in the negative potential region. Transpassive dissolution of the alloy is observed and electropolishing is achieved in this region. The best electropolishing is obtained in 50% H₃PO₄ + 40% CH₃COOH + 10% H₂SO₄. Higher content of water in the electrolytic solution is not useful for electropolishing of the alloy The experimental results also suggest that a current plateau in the transpassive potential region is not a sufficient condition to achieve electropolishing.