Applying soft computing for remote sensing data composite algorithms

Remote sensing of the earth’s surface using satellite-mounted sensor data is one of the most important methods for global environmental monitoring today. However, when using satellite sensor data, clouds in the atmosphere can interfere with the remote sensing, and specific land points may not be correctly monitored on any given day. In order to overcome this problem, a common alternative is to use multiple day composite data. Multiple day composite data use several consecutive days’ remote sensing data, and choose the most accurate data within the temporal dataset for the same land point. This allows the creation of a more complete dataset by patching together data which have had no cloud interference during a specified time period in order to create a clearer, more usable dataset. In this article, we propose the application of soft computing, namely fuzzy logic, in order to select the clearest data in the temporal interval to use for the composite data. Moderate resolution remote sensing data of areas in Japan were used for the evaluation, and the results were compared with previous composite methods.     

Single‐Jet Precipitation of Silver Nanocrystals in the Presence of Poly(acrylic) Acid

Precipitation of silver nanocrystals was carried out in a poly(acrylic) acid (PAA) solution by using a single‐jet crystallizer. The influence of the feeding rate, the injection position and the PAA dosage on the crystal size distribution (CSD) was clarified. The precipitated silver nanocrystals agglomerate with each other, forming an agglomerated microcrystal. In the presented case, smaller feeding rates caused smaller crystal sizes and narrower CSD widths. PAA, which is a water‐soluble polyelectrolyte, successfully inhibited agglomeration and crystal growth, and decreased the crystal size and the CSD width. Thus, this idea may also facilitate the production of other nano‐/microcrystalline particles.     

Enhancing the generalization ability of neural networks through controlling the hidden layers

In this paper we proposed two new variants of backpropagation algorithm. The common point of these two new algorithms is that the outputs of nodes in the hidden layers are controlled with the aim to solve the moving target problem and the distributed weights problem. One algorithm (AlgoRobust) is not so insensitive to the noises in the data, the second one (AlgoGS) is through using Gauss–Schmidt algorithm to determine in each epoch which weight should be updated, while the other weights are kept unchanged in this epoch. In this way a better generalization can be obtained. Some theoretical explanations are also provided. In addition, simulation comparisons are made between Gaussian regularizer, optimal brain damage (OBD) and the proposed algorithms. Simulation results confirm that the new proposed algorithms perform better than that of Gaussian regularizer, and the first algorithm AlgoRobust performs better than the second algorithm AlgoGS in the noisy data. On the other hand AlgoGS performs better than the AlgoRobust on the data without noise and the final structure obtained by two new algorithms is comparable to that obtained by using OBD.     

Coincidence timing of Schottky CdTe detectors for tomographic imaging

Schottky CdTe detectors are good candidates for large pixel array imagers. For use of such arrays in Positron Emission Tomography (PET) the coincidence timing of the detectors is very important, since it reduces the background from random coincidences. The coincidence timing of a small 2×2×1 mm³ detector has been measured as 11.6 ns, and thus is not much worse than the timing of BGO scintillators, commonly used in PET.     

Use of compact shield tunneling method in urban underground construction

In Tokyo Metropolis, the rehabilitation and renewal of sewer systems is an urgent issue due to the aged sewers and increases in wastewater and stormwater runoff. In such urban area, shield tunneling confronts various problems, such as high construction costs, adverse effects on living environments, and densely used surface and underground spaces. To solve these problems, the authors developed a new shield tunneling method, which is called the “compact shield” method. This paper describes the concepts used for the construction of shield sewer tunnels without inner linings and an overview of the segments and a shield machine that were newly developed.     

Preparation and characterization of dicesium tetravalent plutonium hexanitrate

In experiments on U crystallization in a dissolver solution containing Cs, there is concern that Cs and Pu(IV) nitrate complex are deposited on the UNH crystal in the dissolver solution at the time of the U crystallization. The characteristics of generation of Cs and Pu(IV) nitrate complex with dissolver solution of MOX fuel were examined. This complex was obtained as a precipitate by mixing dissolver solution of MOX fuel and CsNO₃ solution, and was identified as dicesium tetravalent plutonium hexanitrate, Cs₂Pu(NO₃)₆ by concentration analysis and XRD. The precipitate has a tendency to be generated at high HNO₃ concentrations. Thermal analysis shows that the precipitate is stable below 245 °C, and a weight loss of 10.29 ± 0.23% is observed between 245 and 297 °C. This result indicates the decomposition of Cs₂Pu(NO₃)₆ to Cs₂PuO₂(NO₃)₄. With these properties, the UNH crystal should melt at the condition between 60 and 100 °C and be separable from the Cs complex by filtration. This suggests a new method of crystal purification allowing higher decontamination of UNH crystal in the U crystallization process.     

Universal learning network and its application to robust control

Universal learning networks (ULNs) and robust control system design are discussed, ULNs provide a generalized framework to model and control complex systems. They consist of a number of interconnected nodes where the nodes may have any continuously differentiable nonlinear functions in them and each pair of nodes can be connected by multiple branches with arbitrary time delays. Therefore, physical systems which can be described by differential or difference equations and also their controllers can be modeled in a unified way. So, ULNs constitute a superset of neural networks or fuzzy neural networks. In order to optimize the systems, a generalized learning algorithm is derived for the ULNs, in which both the first order derivatives (gradients) and the higher order derivatives are incorporated. The derivatives are calculated by using forward or backward propagation schemes. These algorithms for calculating the derivatives are extended versions of back propagation through time (BPTT) and real time recurrent learning (RTRL) by Williams in the sense that generalized nonlinear functions and higher order derivatives are dealt with. As an application of ULNs, the higher order derivative, one of the distinguished features of ULNs, is applied to realizing a robust control system in this paper. In addition, it is shown that the higher order derivatives are effective tools to realize sophisticated control of nonlinear systems. Other features of ULNs such as multiple branches with arbitrary time delays and using a priori information will be discussed in other papers.     

Microstructure of organic–inorganic composite coatings studied by TEM and XANES

Chromate coatings on Zn or Zn alloy coated steel sheets often include silica for the aim to improve corrosion resistance. In the case of dry-in-place chromate coatings containing acrylic resin (hereafter referred to as an organic–inorganic composite coating), an addition of silica, however, did not show an improvement in corrosion resistance. The microstructures of the organic–inorganic composite coatings were observed by transmission electron microscopy (TEM) and the chemical states of Cr were investigated by the total electron yield X-ray absorption near edge structure (TEY-XANES) method. TEM samples were successfully prepared by dry ultramicrotomy preventing water-soluble components in the coatings fromdissolving out. TEY-XANES revealed the chemical states of components even in the organic matrix. Using these methods, it was found that the addition of silica changed just the morphology of the chromium compound in the organic–inorganic composite coating but not the chemical state of Cr. This is a reason for the addition of silica being not effective at improving corrosion resistance. The combination of dry ultramicrotomy-TEM and TEY-XANES spectroscopy was proven to be a powerful tool for characterizing organic–inorganic composite coatings.     

Cardiovascular modeling of congenital heart disease based on neonatal echocardiographic images

This paper proposes a 3-D cardiovascular modeling system based on neonatal echocardiographic images. With the system, medical doctors can interactively construct patient-specific cardiovascular models, and share the complex topology and the shape information. For the construction of cardiovascular models with a variety of congenital heart diseases, we propose a set of algorithms and interface that enable editing of the topology and shape of the 3-D models. In order to facilitate interactivity, the centerline and radius of the vessels are used to edit the surface of the heart vessels. This forms a skeleton where the centerlines of blood vessel serve as the nodes and edges, while the radius of the blood vessel is given as an attribute value to each node. Moreover, parent-child relationships are given to each skeleton. They are expressed as the directed acyclic graph, where the skeletons are viewed as graph nodes and the connecting points are graph edges. The cardiovascular models generated from some patient data confirmed that the developed technique is capable of constructing cardiovascular disease models in a tolerable timeframe. It is successful in representing the important structures of the patient-specific heart vessels for better understanding in preoperative planning and electric medical recording of the congenital heart disease.     

Fast computation of Q‐value‐based dynamic programming on road networks

One of the essential components of vehicle navigation systems is route planning. The single shortest path problem and multiple shortest path problem have been widely studied for route planning. This paper introduces a Q‐value‐based dynamic programming using the division concept for solving both single and multiple shortest path problems on road networks. The proposed algorithm divides the whole network into different divisions, and the updating of Q values in each division is one stage for searching the optimal routes on road networks. The proposed algorithm can greatly save the computational time without any preprocessing on the road networks. The proposed algorithm is also systematically studied in various sizes of road networks. The simulation results show the efficiency and effectiveness of the proposed algorithm on large‐scale road networks. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.