Thematic and Country-Specific Characteristics of Research on the Great East Japan Earthquake: An Analysis Using Data Science Methods

The Great East Japan Earthquake of 2011 had profound impacts in various ways because it was a complex disaster. In addition to the earthquake itself, the tsunami and nuclear accident were even more severe for human lives, health, economy, and the environment. Researchers around the world responded to the disaster. The study topics spanned from natural sciences to social sciences. In this study, we analyzed over 20, 000 academic records concerning the Great East Japan Earthquake from a data science perspective. As a result of text mining, the characteristics of many research fields were elucidated. By collecting the studies in terms of country and research subject, we found characteristics of countries that conducted studies on the disaster. We found that countries in the same Asian region as Japan and countries prone to frequent earthquakes and tsunamis have a high research interest. With the possibility of such a catastrophe in the future in mind, we should prepare ourselves by learning from previous studies to take better countermeasures next time

Handheld Augmented Reality: Effect of registration jitter on cursor-based pointing techniques

International audienceHandheld Augmented Reality relies on the registration of digital content on physical objects. Yet, the accuracy of this registration depends on environmental conditions. It is therefore important to study the impact of registration jitter on interaction and in particular on pointing at augmented objects where precision may be required. We present an experiment that compares the effect of registration jitter on the following two pointing techniques: (1) screen-centered crosshair pointing; and (2) relative pointing with a cursor bound to the physical object's frame of reference and controlled by indirect relative touch strokes on the screen. The experiment considered both tablet and smartphone form factors. Results indicate that relative pointing in the frame of the physical object is less error prone and is less subject to registration jitter than screencentered crosshair pointing

A benchmark suite with virtualized reality models for supporting tracking evaluation and data set generation

TrakMark 2012, The 3rd International Workshop on Benchmark Test Schemes for AR/MR Geometric Registration and Tracking Method , November 11th 2012, Tsukuba, JapanWe describe a benchmark suite with virtualized reality models for augmented reality and mixed reality. Benchmark datasets created with virtualized reality models do not include any measurement errors. On the other hand, supports for benchmarking processes and for creating datasets are desired by creators and users. The benchmark suite is for supporting tracking evaluation and data set generation. In this paper, we describe a design of the benchmark suite, and show experimental results of benchmarking our tracking method and creating datasets with the benchmark suite

Relations spatiales en Réalité Augmentée sur dispositifs mobiles

National audienceLes dispositifs mobiles étant de plus en plus puissants et intégrant de nombreux capteurs, il est maintenant possible de superposer des images numériques a la vue du monde physique retournée par la caméra. Le terme Réalité Augmentée est désormais couramment utilisé et cette technique est employée dans de nombreux domaines. Dans ce contexte, cet article étudie les relations spatiales mises en jeu lors de l'interaction avec cet environnement mixte composé de la vue du monde physique augmentée d'éléments numériques et affiché sur l'écran du dispositif mobile. Nous nous intéressons en particulier a deux relations spatiales : l'une entre l'objet physique et le dispositif mobile et l'autre entre le dispositif mobile et l'utilisateur. Nous présentons des exemples d'application de Réalité Augmentée sur dispositifs mobiles qui exploitent ces relations spatiales pour l'interaction

Tumorigenesis of Epstein–Barr Virus-Positive Epithelial Cell Lines Derived from Gastric Tissues in the SCID Mouse

AbstractTo study the tumorigenesis of Epstein–Barr virus (EBV)-positive epithelial cell lines GT38 and GT39 derived from human gastric tissues, we inoculated these cells under the skin of severe combined immunodeficient (SCID) mice. The development of tumors was observed in each of the mice about 2 months after the inoculation. The tumors were diagnosed with undifferentiated carcinoma by hematoxylin/eosin staining. EBV-encoded small RNA1 was detected in the paraffin-embedded tumor sections. The tumor cells had human chromosome. The circular, but not linear, EBV DNA was detected in the tumors. The molecular sizes of EBV DNA termini were the same as that of the inoculated GT38 or GT39 cells. The expressions of EBV nuclear antigen 2 and latent membrane protein 1 reduced in the tumors. Transcripts of BamHI C and W promoters in latency III were detected in the tumors and the cultured cells in vitro. The tumor cells were passaged from one SCID mouse to other SCID mice and to cultures in vitro. This is the first evidence that the EBV-positive epithelial cell lines produced tumors in the SCID mouse

Molecular investigation of the Aum Shinrikyo anthrax release in Kameido, Japan

In 1993, the Aum Shinrikyo cult aerosolized Bacillus anthracis spores over Kameido, Japan. Spore samples were obtained from the release site, cultured, and characterized by molecular genetic typing. The isolates were consistent with strain Sterne 34F2, which is used in Japan for animal prophylaxis against anthrax

Techniques de Pointage à Distance : Cibles Numériques et Cibles Physique

National audienceAu sein d'un environnement ubiquitaire, l'ordinateur devient évanescent : nos objets quotidiens sont augmentés d'électronique, les environnements deviennent perceptifs déconfinant l'interaction homme-machine de l'ancien ordinateur "boîte grise" à des espaces pervasifs. Désormais, l'utilisateur évolue dans un monde physico-numérique ou espace interactif mixte. Au sein de cet espace interactif, un besoin est alors d'interagir à distance que ce soit pour manipuler des objets numériques sur un écran distant ou des objets physiques. Cet article est dédié aux techniques de pointage à distance pour désigner un objet numérique ou physique. Nous décrivons six techniques de pointage pour interagir dans un environnement ubiquitaire, la première pour pointer à distance sur des cibles numériques, les cinq autres pour pointer sur des objets physiques avec et sans un dispositif mobile

Non-learning Stereo-aided Depth Completion under Mis-projection via Selective Stereo Matching

We propose a non-learning depth completion method for a sparse depth map captured using a light detection and ranging (LiDAR) sensor guided by a pair of stereo images. Generally, conventional stereo-aided depth completion methods have two limiations. (i) They assume the given sparse depth map is accurately aligned to the input image, whereas the alignment is difficult to achieve in practice. (ii) They have limited accuracy in the long range because the depth is estimated by pixel disparity. To solve the abovementioned limitations, we propose selective stereo matching (SSM) that searches the most appropriate depth value for each image pixel from its neighborly projected LiDAR points based on an energy minimization framework. This depth selection approach can handle any type of mis-projection. Moreover, SSM has an advantage in terms of long-range depth accuracy because it directly uses the LiDAR measurement rather than the depth acquired from the stereo. SSM is a discrete process; thus, we apply variational smoothing with binary anisotropic diffusion tensor (B-ADT) to generate a continuous depth map while preserving depth discontinuity across object boundaries. Experimentally, compared with the previous state-of-the-art stereo-aided depth completion, the proposed method reduced the mean absolute error (MAE) of the depth estimation to 0.65 times and demonstrated approximately twice more accurate estimation in the long range. Moreover, under various LiDAR-camera calibration errors, the proposed method reduced the depth estimation MAE to 0.34-0.93 times from previous depth completion methods.Comment: 15 pages, 13 figure