A Skeleton-based Approach for Detection of Perceptually Salient Features on Polygonal Surfaces

The paper presents a skeleton‐based approach for robust detection of perceptually salient shape features. Given ashape approximated by a polygonal surface, its skeleton is extracted using a three‐dimensional Voronoi diagramtechnique proposed recently by Amenta et al. [ 3 ]. Shape creases, ridges and ravines, are detected as curvescorresponding to skeletal edges. Salient shape regions are extracted via skeleton decomposition into patches.The approach explores the singularity theory for ridge and ravine detection, combines several filtering methodsfor skeleton denoising and for selecting perceptually important ridges and ravines, and uses a topological analysisof the skeleton for detection of salient shape regions. ACM CSS: I.3.5 Computational Geometry and Object Modeling     

Chemical Reaction Engineering and Research and development of gas solid systems

A general procedure is proposed for innovative research and development of gas-solid reactor systems, with a brief explanation of the significance of each step in the procedureBased upon the contacting mode between gas and solid phases, as well as the ways of supplying thermal energy to the reacting regions, various types of gas-solid reactor systems are classified by using tables of so called “matrix” form, for thermal cracking and gasification of heavy oils, gasification of coal, gasification of solid waste, calcination of limestone, clinkering of cement and reduction of iron ore.The importance of fundamental concepts is emphasized for successful research and development by presenting several examples; namely, calcination of limestone, thermal cracking of heavy oils and gasification of solid waste materials.In connection with the direction in which fundamental research should be oriented, four primary ways of thinking are proposed, which can be applied to obtain innovative ideas for further research and development in this field.One example of the author's practical experience was selected to show the role of the fundamental research in the course of large scale development. Finally the author outlines the role of chemical reaction engineering to innovate the novel gas-solid reactor systems which may be inevitable for simultaneous solution of the three big E's; namely, Energy, Environment and Economy.     

Development of an epileptic seizure prediction algorithm using R–R intervals with self-attentive autoencoder

Epilepsy is a neurological disorder that may affect the autonomic nervous system (ANS) from 15 to 20 min before seizure onset, and disturbances of ANS affect R–R intervals (RRI) on an electrocardiogram (ECG). This study aims to develop a machine learning algorithm for predicting focal epileptic seizures by monitoring R–R interval (RRI) data in real time. The developed algorithm adopts a self-attentive autoencoder (SA-AE), which is a neural network for time-series data. The results of applying the developed seizure prediction algorithm to clinical data demonstrated that it functioned well in most patients; however, false positives (FPs) occurred in specific participants. In a future work, we will investigate the causes of FPs and optimize the developing seizure prediction algorithm to further improve performance using newly added clinical data.

     

Algorithms for Extracting Correct Critical Points and Constructing Topological Graphs from Discrete Geographical Elevation Data

Researchers in the fields of computer graphics and geographical information systems (GISs) have extensively studied the methods of extracting terrain features such as peaks, pits, passes, ridges, and ravines from discrete elevation data. The existing techniques, however, do not guarantee the topological integrity of the extracted features because of their heuristic operations, which results in spurious features. Furthermore, there have been no algorithms for constructing topological graphs such as the surface network and the Reeb graph from the extracted peaks, pits, and passes. This paper presents new algorithms for extracting features and constructing the topological graphs using the features. Our algorithms enable us to extract correct terrain features; i.e., our method extracts the critical points that satisfy the Euler formula, which represents the topological invariant of smooth surfaces. This paper also provides an algorithm that converts the surface network to the Reeb graph for representing contour changes with respect to the height. The discrete elevation data used in this paper is a set of sample points on a terrain surface. Examples are presented to show that the algorithms also appeal to our visual cognition.     

Multimodal sensing and active continuous closed‐loop feedback for achieving reliable manipulation in the outdoor physical world

The use of field robots can greatly decrease the amount of time, effort, and associated risk compared to if human workers were to carryout certain tasks such as disaster response. However, transportability and reliability remain two main issues for most current robot systems. To address the issue of transportability, we have developed a lightweight modularizable platform named AeroArm. To address the issue of reliability, we utilize a multimodal sensing approach, combining the use of multiple sensors and sensor types, and the use of different detection algorithms, as well as active continuous closed‐loop feedback to accurately estimate the state of the robot with respect to the environment. We used Challenge 2 of the 2017 Mohammed Bin Zayed International Robotics Competition as an example outdoor manipulation task, demonstrating the capabilities of our robot system and approach in achieving reliable performance in the fields, and ranked fifth place internationally in the competition.     

A quantitative analysis of a trace amount of hydrogen in high temperature heat-treated carbons

A technique to determine a trace amount of hydrogen in carbon materials heat-treated above 1000 °C was developed. Three types of carbons prepared from poly(furfulyl alcohol), poly(vinyl chloride) and mesophase carbon microbeads were heat-treated at various temperatures ranging from 1000 to 1800 °C. Then they were gasified by O₂ in a fixed bed flow reactor, and the H₂O gases formed during the gasification processes were carefully monitored with a Karl Fischer moisture analyzer. As a result, this method makes it possible to determine the hydrogen contents in the carbons down to three places of decimals as a weight percent and can detect even a trace amount of hydrogen as low as 0.002 wt.%. A possible chemical structure of carbon edge sites was also discussed based on the experimentally determined hydrogen contents.     

The homotopy model: a generalized model for smooth surface generation from cross sectional data

A generalized model, called the homotopy model, is presented to reconstruct surfaces from cross-sectional data of objects using a homotopy to generate surfaces connecting consecutive contours. The homotopy model consists of continuous toroidal graph representation and homotopic generation of surfaces from the representation. It is shown that the homotopy model includes triangulation as a special case and generates smooth parametric surfaces from contour-line definitions using homotopy. The model can be applied to contours represented by parametric curves as well as linear line segments. First, a heuristic method that finds the optimal path on the toroidal graph is presented. Then the toroidal graph is expanded to a continuous version. Finally, homotopy is used for reconstructing parametric surfaces from the toroidal graph representation. A loft surface is also a special case of homotopy, a straight-line homotopy. Homotopy that corresponds to the cardinal spline surface is also introduced. Three-dimensional surface reconstruction of human auditory surface reconstruction of human auditory ossicles illustrates the advantages of the homotopy model over the others.     

Evidence for Altered Phosphoinositide Signaling-Associated Molecules in the Postmortem Prefrontal Cortex of Patients with Schizophrenia

Phosphoinositides (PIs) play important roles in the structure and function of the brain. Associations between PIs and the pathophysiology of schizophrenia have been studied. However, the significance of the PI metabolic pathway in the pathology of schizophrenia is unknown. We examined the expression of PI signaling-associated proteins in the postmortem brain of schizophrenia patients. Protein expression levels of phosphatidylinositol 4-phosphate 5-kinase type-1 gamma (PIP5K1C), phosphatidylinositol 4-kinase alpha (PIK4CA, also known as PIK4A), phosphatase and tensin homolog deleted from chromosome 10 (PTEN), protein kinase B (Akt), and glycogen synthase kinase 3β (GSK3β) were measured using enzyme-linked immunosorbent assays and multiplex fluorescent bead-based immunoassays of the prefrontal cortex (PFC) of postmortem samples from 23 schizophrenia patients and 47 normal controls. We also examined the association between PIK4CA expression and its genetic variants in the same brain samples. PIK4CA expression was lower, whereas Akt expression was higher, in the PFC of schizophrenia patients than in that of controls; PIP5K1C, PTEN, and GSK3β expression was not different. No single-nucleotide polymorphism significantly affected protein expression. We identified molecules involved in the pathology of schizophrenia via this lipid metabolic pathway. These results suggest that PIK4CA is involved in the mechanism underlying the pathogenesis of schizophrenia and is a potential novel therapeutic target.