Hiroko Nakamura Miyamura

Two-tone pseudo coloring: compact visualization for one-dimensional data

A new pseudo coloring technique for large scale one-dimensional datasets is proposed. For visualization of a large scale dataset, user interaction is indispensable for selecting focus areas in the dataset. However, excessive switching of the visualized image makes it difficult for the user to recognize overview/ detail and detail/ detail relationships. The goal of this research is to develop techniques for visualizing details as precisely as possible in overview display. In this paper, visualization of a one-dimensional but very large dataset is considered. The proposed method is based on pseudo coloring, however, each scalar value corresponds to two discrete colors. By painting with two colors at each value, users can read out the value precisely. This method has many advantages: it requires little image space for visualization; both the overview and details of the dataset are visible in one image without distortion; and implementation is very simple. Several application examples, such as meteorological observation data and train convenience evaluation data, show the effectiveness of the method.

Remote visualization system based on particle based volume rendering

In this paper, we propose a novel remote visualization system based on particle-based volume rendering (PBVR),1 which enables interactive analyses of extreme scale volume data located on remote computing systems. The re- mote PBVR system consists of Server, which generates particles for rendering, and Client, which processes volume rendering, and the particle data size becomes significantly smaller than the original volume data. Depending on network bandwidth, the level of detail of images is flexibly controlled to attain high frame rates. Server is highly parallelized on various parallel platforms with hybrid programing model. The mapping process is accelerated by two orders of magnitudes compared with a single CPU. The structured and unstructured volume data with ~108 cells is processed within a few seconds. Compared with commodity Client/Server visualization tools, the total processing cost is dramatically reduced by using proposed system.

Remote radiation imaging system using a compact gamma-ray imager mounted on a multicopter drone

ABSTRACT A remote radiation imaging system comprising a lightweight Compton camera and a multicopter drone was developed to remotely and quickly measure radioactive contamination inside the buildings of the Fukushima Daiichi Nuclear Power Station (FDNPS). The drone system is used for measuring detailed radiation distributions in narrow areas, which have been difficult to gauge with conventional aircraft monitoring using helicopters. A measurement of radiation distributions in outdoor environments in the coastal areas of Fukushima, Japan, was performed. The drone system with the Compton camera succeeded in remote observations of dense hotspots from the sky over a contaminated area near the FDNPS. The time required for image reconstruction is approximately 550 s in the case of a 9-m flight altitude for the hotspots with a surface dose rate of several tens of µSv/h. This drone system will be used inside the buildings of the FDNPS for remote measurement of radioactive contamination.

The Proposal of the EEG Characteristics Extraction Method in Weighted Principal Frequency Components Using the RGA

An EEG has frequency components which can describe most of the significant features. These combinations are often unique like individual human beings and yet they have underlying basic features. These frequency components are contained the important and/or not so important components, and then each importance of these frequency components are different. The real-coded genetic algorithm (: RGA) is used for selecting and being weighted the principal characteristic frequency components. We attempt to construct mental change appearance model (: MCAM) of only one measurement point. In order to show the effectiveness of the proposed method, computer simulations are carried out by using real data

Algebraic design of multi-dimensional transfer function using transfer function synthesizer

In this paper, we propose a novel transfer function (TF) design interface for multi-variate volume rendering. To design higher dimensional TFs in an general and flexible manner, a transfer function synthesizer (TFS) is developed. On the TFS, multi-dimensional TFs are generated by algebraic synthesis of one-dimensional TFs, which are designed based on the conventional GUIs or algebraic expressions. The TFS enables not only multi-variate volume rendering, but also general visualization techniques, such as surface visualization and image composition, within the framework of volume rendering. The TFS is implemented on the remote visualization system PBVR, and applied to various multi-variate scalar volume data generated from nuclear applications.Graphical abstract

Multivariate volume rendering using transfer function synthesizer implemented in remote visualization system PBVR

In this paper, we propose a novel transfer function design technique for multivariate volume rendering. This technique generates a multidimensional transfer function by logical synthesis of variables and transfer functions. This technique enables analysts to extract correlation of variables and to combine multivariate surface and volume shapes. And this technique is implemented in Remote Visualization System PBVR optimized to several supercomputers. An experiment for the multi-phase fuel melting simulation result in the nuclear energy field shows the powerful ability of this technique enough by extracting complex behavior of molten materials.

The EEG feature extraction method of listening to music using the genetic algorithms and the latency structure model

It is known that an electroencephalogram (EEG) is characterized by the unique and personal features of an individual. The EEG frequency components are contained the significant and immaterial information, and then each importance of these frequency components is different. These combinations are often unique like individual human beings and yet they have underlying basic characteristics. We think that these combinations and/or the importance of the frequency components show the personal features. Therefore we propose the two techniques for estimating the personal features. A simple genetic algorithm is used for specifying these frequency combinations. Other technique, a real-coded genetic algorithm is used for estimating the importance of EEG frequency components. Then a latency structure model based on the personal features is used for extracted the feature vector of the EEG. Furthermore, the visualization map is used for evaluating the extracted feature vector of the EEG. In order to show the effectiveness of the proposed methods, the performance of the proposed method is evaluated using real EEG data.

Hierarchical image gathering technique for browsing surveillance camera images

We propose an image gathering and display method for efficient browsing of surveillance camera images. The proposed method requires large cost to inspect lengthy image sequences taken by a surveillance camera. The proposed method involves generating a still image by gathering the moving parts from image sequences captured by a fixed camera. The gathered images are generated for several intervals of time and are displayed hierarchically. A user can easily browse the scene by observing the images with moving parts. Since detection and recognition of the target objects are performed by a human operator, efficient and reliable browsing can be established.

Abstract: Remote Visualization for Large-Scale Simulation Using Particle-Based Volume Rendering

With the recent development of supercomputers, it is required to efficiently visualize the results of extremely large-scale numerical simulations with a few hundreds to several tens of thousands of parallel processes. Conventional offline-processing visualization approaches are facing difficulties such as transferring large-scale data and reassembly of extensive amount of computational result files, which are inevitable for sort-first or sort-last visualization methods [1]. On the other hand interactive visualization on a supercomputer is still limited. We propose a remote visualization system which has three features. First, our visualization system can avoid the reassembly of the result files. This system can generate rendering primitives on the same number of parallel processes of the numerical simulation. Second, this system enables users to interactively manipulate camera position and time progress. Third, this system is appropriate to overview entire physical values of computational space (volume data) by volume rendering.

R&D of Validity Evaluation System for Seismic Simulation of Entire Nuclear Plant

Our goal is to evaluate validity of numerical simulation results in the nuclear field in order to estimate real behavior of nuclear plants and thus to contribute their security and safety. Recently, it becomes possible to execute a full-scale numerical simulation under a real condition, such as a seismic behavior of entire nuclear plant. To estimate real behavior accurately by such simulations, it is indispensable to evaluate validity of simulation results because numerical simulations include various uncertainties such as “uncertainty due to randomness” and “uncertainty due to lack of knowledge”. As one of approaches to evaluate validity of simulation results, we introduce “the degree of certainty” of simulations to real behavior. Here, to get a more accurate degree of certainty, we try to confirm the degree of influence about unevenness of uncertainty and to reduce uncertainty due to lack of knowledge. For this, we research and develop a validity evaluation system composed of three tools. One is a tool able to introduce the degree of certainty from various uncertainties to put together various uncertainties. Another is a tool able to analyze the sensitivity of each uncertainty to whole uncertainty. Moreover, we research a tool able to analyze factors of various uncertainties. We have applied them to our seismic simulation system which enables to execute the assembly structure analysis of an entire nuclear plant and confirmed that their functions are applicable to the simulation.© 2012 ASME