The Influence of the Amount of Fluoride Catalyst on the Morphological Properties of the Anilinepropylsilica Xerogel Prepared in Basic Medium

Anilinepropylsilica hybrid powder was synthesized by a sol-gel route in basic medium using HF as catalyst. The effect of the amount of HF catalyst on the morphologies and on organic content was studied. The xerogels were characterized using FTIR, SEM and N₂ adsorption-desorption isotherms. The increase in the HF quantity results in an slight increase in organic content and changes in the particle size, surface area and pore structure.     

Distributed memory systems for simulating artificial neural networks

In executing tasks involving intelligent information processing, the human brain performs better than the digital computer. The human brain derives its power from a large number [O(10¹¹)] of neurons which are interconnected by a dense interconnection network [O(10⁵) connections per neuron]. Artificial neural network (ANN) paradigms adopt the structure of the brain to try to emulate the intelligent information processing methods of the brain. ANN techniques are being employed to solve problems in areas such as pattern recognition, and robotic processing. Simulation of ANNs involves implementation of large number of neurons and a massive interconnection network. In this paper, we discuss various simulation models of ANNs and their implementation on distributed memory systems. Our investigations reveal that communication-efficient networks of distributed memory systems perform better than other topologies in implementing ANNs.     

Fundamental Limitations of Continuous-Time Delta–Sigma Modulators Due to Clock Jitter

We examine noise due to clock jitter in single-loop low-pass continuous-time delta-sigma (Delta Sigma) modulators (CT-DSMs) employing nonreturn to zero (NRZ) feedback digital-to-analog converters (DACs). Using the discrete-time version of the Bode sensitivity integral, we derive a lower bound on jitter noise and its relationship to the noise transfer function (NTF) of the modulator. We show that NTFs with optimized zeros result in lower jitter noise than those with all zeros at the origin. We give intuition to a recent observation (arrived through numerical optimization) that NTFs with peaking in their passbands have lower jitter noise than maximally flat NTFs. We propose a design procedure that minimizes the sum of the quantization and jitter noise. The arguments regarding Delta Sigma analog-to-digital converters are extended to Delta Sigma DACs and measurement results are presented.     

An integrated modeling approach to predict flooding on urban basin.

Correct prediction of flood extents in urban catchments has become a challenging issue. The traditional urban drainage models that consider only the sewerage-network are able to simulate the drainage system correctly until there is no overflow from the network inlet or manhole. When such overflows exist due to insufficient drainage capacity of downstream pipes or channels, it becomes difficult to reproduce the actual flood extents using these traditional one-phase simulation techniques. On the other hand, the traditional 2D models that simulate the surface flooding resulting from rainfall and/or levee break do not consider the sewerage network. As a result, the correct flooding situation is rarely addressed from those available traditional 1D and 2D models. This paper presents an integrated model that simultaneously simulates the sewerage network, river network and 2D mesh network to get correct flood extents. The model has been successfully applied into the Tenpaku basin (Nagoya, Japan), which experienced severe flooding with a maximum flood depth more than 1.5 m on September 11, 2000 when heavy rainfall, 580 mm in 28 hrs (return period > 100 yr), occurred over the catchments. Close agreements between the simulated flood depths and observed data ensure that the present integrated modeling approach is able to reproduce the urban flooding situation accurately, which rarely can be obtained through the traditional 1D and 2D modeling approaches.