Derivation and implementation of a cone-beam reconstruction algorithm for nonplanar orbits

B.D. Smith (ibid., vol.MI-4, p.15-25, 1985; Opt. Eng., vol.29, p.524-34, 1990) and P. Grangeat (These de doctorat, 1987; Lecture Notes in Mathematics 1497, p.66-97, 1991) derived a cone-beam inversion formula that can be applied when a nonplanar orbit satisfying the completeness condition is used. Although Grangeat's inversion formula is mathematically different from Smith's one, they have similar overall structures to each other. The contribution of the present paper is two-fold. First, based on the derivation of Smith, the authors point out that Grangeat's inversion formula and Smith's one can be conveniently described using a single formula (the Smith-Grangeat inversion formula) that is in the form of space-variant filtering followed by cone-beam back projection. Furthermore, the resulting formula is reformulated for data acquisition systems with a planar detector to obtain a new reconstruction algorithm. Second, the authors make two significant modifications to the new algorithm to reduce artifacts and numerical errors encountered in direct implementation of the new algorithm. As for exactness of the new algorithm, the following fact can be stated. The algorithm based on Grangeat's intermediate function is exact for any complete orbit, whereas that based on Smith's intermediate function should be considered as an approximate inverse excepting the special case where almost every plane in 3D space meets the orbit. The validity of the new algorithm is demonstrated by simulation studies.     

A reduction method of dynamic false contour utilizing the frame‐rate‐control method with suppression of the side effect on PDPs

Abstract— The plasma‐display panel (PDP) is a type of flat‐panel display that can display a high‐quality image. However, when moving images are displayed, annoying disturbances such as false contour noise occurs. This noise is called dynamic false contour (DFC). To achieve a higher‐quality image, DFC has to be reduced. Therefore, a new method to reduce DFC is proposed. To find a way to reduce DFC, a new evaluation value for it has been defined: the evaluation value of dynamic false contour (EVDFC). This value is defined on the basis of a person's subjective evaluation. By applying this value, the cause that generates DFC can be identified. On the basis of these studies, a new method for reducing DFC by applying frame‐rate control (FRC) with suppression of the side effect is proposed. This improved method can be used to provide high‐quality images.     

Discharge properties and chemical stability of SrZrO films

Abstract— MgO thin film is currently used as a surface protective layer for dielectric materials because MgO has a high resistance during ion sputtering and exhibits effective secondary electron emission. The secondary‐electron‐emission coefficient γ of MgO is high for Ne ions; however, it is low for Xe ions. The Xe content of the discharge gas of PDPs needs to be raised in order to increase the luminous efficiency. Thus, the development of high‐γ materials replacing MgO is required. The discharge properties and chemical surface stability of SrO containing Zr (SrZrO) as the candidate high‐γ protective layer for noble PDPs have been characterized. SrZrO films have superior chemical stability, especially the resistance to carbonation because of the existence of a few adsorption sites due to their amorphous structure. The firing voltage is 60 V lower than that of MgO films for a discharge gas of Ne/Xe = 85/15 at 60 kPa.     

A procedure to analyze surface profiles of the protein molecules visualized by quick-freeze deep-etch replica electron microscopy

Quick-freeze deep-etch replica electron microscopy gives high contrast snapshots of individual protein molecules under physiological conditions in vitro or in situ. The images show delicate internal pattern, possibly reflecting the rotary-shadowed surface profile of the molecule. As a step to build the new system for the "Structural analysis of single molecules", we propose a procedure to quantitatively characterize the structural property of individual molecules; e.g. conformational type and precise view-angle of the molecules, if the crystallographic structure of the target molecule is available. This paper presents a framework to determine the observed face of the protein molecule by analyzing the surface profile of individual molecules visualized in freeze-replica specimens. A comprehensive set of rotary-shadowed views of the protein molecule was artificially generated from the available atomic coordinates using light-rendering software. Exploiting new mathematical morphology-based image filter, characteristic features were extracted from each image and stored as template. Similar features were extracted from the true replica image and the most likely projection angle and the conformation of the observed particle were determined by quantitative comparison with a set of archived images. The performance and the robustness of the procedure were examined with myosin head structure in defined configuration for actual application.     

On-line neuro-expert monitoring system for Borssele Nuclear Power Plant

A new method for an on-line monitoring system for the nuclear power plants has been developed utilizing the neural networks and the expert system. The integration of them is expected to enhance a substantial potential of the functionality as operators support.

The recurrent neural network and the feed-forward neural network with adaptive learning are selected for the plant modeling and anomaly detection because of the high capability of modeling for dynamic behavior. The expert system is used as a decision agent, which works on the information space of both the neural networks and the human operators. The information of other sensory signals is also fed to the expert system, together with the outputs that the neural networks generate from the measured plant signals. The expert system can treat almost all known correlation between plant status patterns and operation modes as a priori set of rules.

From the off-line test at Borssele Nuclear Power Plant (PWR 480 MWe) in the Netherlands, it was shown that the neuro-expert system successfully monitored the plant status. The expert system worked satisfactorily in diagnosing the system status by using the outputs of the neural networks and a priori knowledge base from the PWR simulator. The electric power coefficient is simultaneously monitored from the measured reactive and active electric power signals.     

Effect of the dilation caused by helium bubbles on edge dislocation motion in α-iron: molecular dynamics simulation

Various types of nanometric defects such as voids and helium (He) bubbles produced by high-energy neutron irradiations are known to degrade the mechanical properties of irradiated materials. In this study, we have evaluated the obstacle strength of He bubbles to the mobility of an edge dislocation in α-iron for 2 and 4 nm bubbles with He-to-vacancy (He/V) ratios ranging from 0 to 1 at 300 and 500 K, by molecular dynamics simulation. Results showed that as the He/V ratio increases, the obstacle strength needed for the release of a dislocation from the bubble becomes stronger up to a moderate He/V ratio (0.6 and 0.4 for 2 and 4 nm bubbles, respectively, at both temperatures), and a further increase in the He/V ratio leads to weakening of the obstacle strength. For He/V = 1, the obstacle strengths are 10–30% weaker than those at moderate He/V ratios depending on the bubble size and temperature. The extent of obstacle strength was found to be correlated with the dilation caused by He bubbles depending on the bubble size, He/V ratio, and temperature.     

Efficient action recognition via local position offset of 3D skeletal body joints

To accurately recognize human actions in less computational time is one important aspect for practical usage. This paper presents an efficient framework for recognizing actions by a RGB-D camera. The novel action patterns in the framework are extracted via computing position offset of 3D skeletal body joints locally in the temporal extent of video. Action recognition is then performed by assembling these offset vectors using a bag-of-words framework and also by considering the spatial independence of body joints. We conducted extensive experiments on two benchmarking datasets: UCF dataset and MSRC-12 dataset, to demonstrate the effectiveness of the proposed framework. Experimental results suggest that the proposed framework 1) is very fast to extract action patterns and very simple in implementation; and 2) can achieve a comparable or a better performance in recognition accuracy compared with the state-of-the-art approaches.