Dynamic defocus and occlusion compensation of projected imagery by model-based optimal projector selection in multi-projection environment

This paper presents a novel model-based approach of dynamic defocus and occlusion compensation method in a multi-projection environment. Conventional defocus compensation research applies appearance-based method, which needs a point spread function (PSF) calibration when either position or orientation of an object to be projected is changed, thus cannot be applied to interactive applications in which the object dynamically moves. On the other hand, we propose a model-based method in which PSF and geometric calibrations are required only once in advance, and projector’s PSF is computed online based on geometric relationship between the projector and the object without any additional calibrations. We propose to distinguish the oblique blur (loss of high-spatial-frequency components according to the incidence angle of the projection light) from the defocus blur and to introduce it to the PSF computation. For each part of the object surfaces, we select an optimal projector that preserves the largest amount of high-spatial-frequency components of the original image to realize defocus-free projection. The geometric relationship can also be used to eliminate the cast shadows of the projection images in multi-projection environment. Our method is particularly useful in the interactive systems because the movement of the object (consequently geometric relationship between each projector and the object) is usually measured by an attached tracking sensor. This paper describes details about the proposed approach and a prototype implementation. We performed two proof-of-concept experiments to show the feasibility of our approach.     

Design of discrete time adaptive PID control systems with parallel feedforward compensator

This paper deals with the design of an adaptive PID control system with a parallel feedforward compensator (PFC) for discrete-time SISO systems and its application to water level control of a 3-tank system. The proposed method utilizes the characteristics of almost strict positive realness (ASPR) of the controlled plant. A conventional design scheme of a PFC which realizes an ASPR augmented controlled plant is also proposed. Further it is shown that the introduction of an internal model improves the control performance of the control system with the PFC. The effectiveness of the proposed method is confirmed through water level control experiments on a three-tank SISO system.     

An Interactive Design System of Free‐Formed Bamboo‐Copters

We present an interactive design system for designing free‐formed bamboo‐copters, where novices can easily design free‐formed, even asymmetric bamboo‐copters that successfully fly. The designed bamboo‐copters can be fabricated using digital fabrication equipment, such as a laser cutter. Our system provides two useful functions for facilitating this design activity. First, it visualizes a simulated flight trajectory of the current bamboo‐copter design, which is updated in real time during the user's editing. Second, it provides an optimization function that automatically tweaks the current bamboo‐copter design such that the spin quality—how stably it spins—and the flight quality—how high and long it flies—are enhanced. To enable these functions, we present non‐trivial extensions over existing techniques for designing free‐formed model airplanes [ UKSI14 ], including a wing discretization method tailored to free‐formed bamboo‐copters and an optimization scheme for achieving stable bamboo‐copters considering both spin and flight qualities.     

Estimation of a nonvisible field-of-view mobile target incorporating optical and acoustic sensors

This paper presents a nonvisible field-of-view (NFOV) target estimation approach that incorporates optical and acoustic sensors. An optical sensor can accurately localize a target in its field-of-view whereas the acoustic sensor could estimate the target location over a much larger space, but only with limited accuracy. A recursive Bayesian estimation framework where observations of the optical and acoustic sensors are probabilistically treated and fused is proposed in this paper. A technique to construct the observation likelihood when two microphones are used as the acoustic sensor is also described. The proposed technique derives and stores the interaural level difference of observations from the two microphones for different target positions in advance and constructs the likelihood through correlation. A parametric study of the proposed acoustic sensing technique in a controlled test environment, and experiments with an NFOV target in an actual indoor environment are presented to demonstrate the capability of the proposed technique.     

Compressive multi-spectral imaging using self-correlations of images based on hierarchical joint sparsity models

We propose a novel multi-spectral imaging method based on compressive sensing (CS). In CS theory, the enhancement of signal sparsity is important for accurate signal reconstruction. The main novelty of the proposed method is the employment of a self-correlation of an image, that is a local intensity similarity and multi-spectral correlation, to enhance the sparsity of the multi-spectral image to be recovered. Local intensity similarity, which is based on the concept that spatial changes in intensity are likely to be similar within local regions, contributes to sparsity enhancement. Furthermore, we exploit multi-spectral correlation to improve the sparsity of the multi-spectral components to be recovered. In order to simultaneously exploit different types of characteristics (i.e., local intensity similarity and multi-spectral correlation) for representing a signal as sufficiently sparse, we introduce a hierarchical joint sparsity model in the CS image recovery process. Our experiments show that the use of a self-correlation significantly improves the performance of multi-spectral image reconstruction.     

Performance of SOR methods on modern vector and scalar processors

The building-cube method (BCM) is a new generation algorithm for CFD simulations. The basic idea of BCM is to simplify the algorithm in all stages of flow computation to achieve large-scale simulations. Calculation of a pressure field using the Successive Over Relaxation (SOR) method consumes most of the total execution time required for BCM. In this paper, effective implementations on modern vector and scalar processors are investigated. NEC SX-9 and Intel Nehalem-EX are the latest vector and scalar processors. Those processors have much higher peak performances than their previous-generation processors. However, their memory bandwidth improvement cannot catch up with the performance improvement of processors. This is the so-called memory wall problem. In our paper, we discuss optimization techniques for implementation of the SOR method based on architectural characteristics of these modern processors, and evaluate their effects on the sustained performances of these processors for BCM.     

A pilot survey of 39 Victorian WWTP effluents using a high speed luminescent umu test in conjunction with a novel GC-MS-database technique for automatic identification of micropollutants

In 2007, samples of treated effluent were collected at point of discharge to the environment from 39 wastewater treatment plants (WWTPs) located across Victoria, Australia grouped by treatment type. Sample genotoxicity was assessed with a high-throughput luminescent umu test method using Salmonella typhimurium TL210 strain, with and without addition of a commercially available metabolic activation system. Samples were also screened using a gas chromatographic-mass spectrometric mass-structure database recognition method. A genotoxic response was observed in half of the samples tested without metabolic activation system (相似文献   

Linking sanitation and wastewater treatment: from evaluation on the basis of effluent pollutant concentrations to evaluation on the basis of pollutant removal efficiencies

The evaluation of centralised wastewater treatment plants (WWTPs) in planning and management is sometimes based solely on effluent pollutant concentrations or pollutant loads. For sanitation purposes, the effluent pollutant concentrations/loads of WWTPs are important; of course, but from the point of view of wastewater treatment, the pollutant removal performance should also be evaluated. Focussing on low- and middle-income countries, especially those in tropical regions, published kinetics studies on biological WWTPs (such as oxidation ditches and aerated lagoons) are summarised in this paper. In most studies, effluent pollutant concentrations/loads are described as first-order linear functions of influent pollutant concentrations/loads. Therefore, pollutant removal efficiencies can be expressed as first-order linear functions of the reciprocal of influent pollutant concentrations/loads with negative coefficients. This implies that pollutant removal efficiencies increase with influent pollutant concentration/load increases. Based on pollutant removal efficiency functions, biological or ecological WWTPs when operating with small influent pollutant concentrations/loads should change their management to increase influent pollutant concentrations/loads in order to increase pollutant removal efficiencies. It may, however, be possible for technological development in wastewater treatment to overcome this problem.     

High rate nitrogen removal by the CANON process at ambient temperature

Completely autotrophic nitrogen removal over nitrite (CANON) is a cost-effective nitrogen removal process. Implementation of the CANON process relies on the cooperation of ammonium-oxidizing and Anammox bacteria, as well as the inhibition of nitrite-oxidizing bacteria. Strict limitations on dissolved oxygen (DO) concentration in the reactor, and the addition of sufficient inorganic carbon in the influent, were adopted as the main operational strategies. The reactor was fed with synthetic inorganic wastewater composed mainly of NH(4)(+)-N, and operated for 106 days. Stable nitrogen removal rates (NRR) of around 1.4 kg N m(-3) d(-1) were obtained at ambient temperature. Morphological characteristics and analysis of bacterial community confirmed the formation of functional outer aerobic and inner anaerobic granular sludge, providing evidence of stable nitrogen removal.     

Construction of a brain–machine hybrid system to evaluate adaptability of an insect

Insects perform adaptive behavior according to changing environmental conditions using comparatively small brains. Because adaptability is generated through the relationship among brain, body and environment, it is necessary to examine how a brain works under these conditions. In this study, to understand neural processing involved in adaptive behavior, we constructed a brain–machine hybrid system using motor signals related to the steering behavior of the male silkworm moth for controlling a two-wheeled mobile robot. We developed this hybrid system according to the following steps. (1) We selected steering signals corresponding to walking direction that were activated during neck swinging induced by optic flow and pheromone stimuli. (2) To control a robot by neural activity, we implemented a spike-behavior conversion rule such that frequency of the left and right neck motor neurons’ spikes was linearly converted into rotation of the wheels. (3) For electrophysiological multi-unit recordings on a robot, we developed small amplifiers. Using this hybrid system, we could observe the programmed behavioral pattern and orientation toward a pheromone source. Moreover, we compared the orientation behavior of moths and that of the hybrid system at different pheromone stimulus frequencies. From these experiments, we concluded that we could reconstruct silkworm moth behavior on the hybrid system.