Laser-based geometrical modeling of large-scale architectural structures using co-operative multiple robots

For the construction of 3-D shape models of large-scale architectural structures using laser range finders, a number of range images are taken from different viewpoints around the targets. Next, the obtained images are normally aligned by post-processing procedures, such as the ICP algorithm. However, to obtain convergent results in the ICP algorithm and align these range images to their proper positions, the initial position of each range image needs to be manually aligned to roughly the correct position. This paper proposes a new measurement and modeling system using a group of multiple robots and an on-board laser range finder. Each measurement position is identified by a highly precise positioning technique called the Co-operative Positioning System (CPS), which utilizes the characteristics of the multiple-robot system. Therefore, the proposed system can construct 3-D shapes of large-scale architectural structures without any post-processing procedure or manual intervention. In addition, it is possible to register range images even if the number of measurements is few and there are only a few range images, for example, due to range images containing insufficient feature shapes or overlapping regions. Measurement experiments in unknown and large indoor/outdoor environments including a large hall, a building, an urban district, and a cultural heritage have been successfully carried out using the newly developed measurement system consisting of three mobile robots named CPS-V. Path generation experiments of the mobile robots based on the partially measured 3-D model are also presented.     

Optical design and roll‐to‐roll fabrication process of microstructure film for wide viewing LCDs

We have developed a new microstructure film for wide viewing liquid crystal displays (LCDs). By attaching it to the surface of a conventional LCD, the viewing angle characteristics of LCD has drastically improved without causing a blur of the frontal image and a decrease in the contrast ratio under bright ambient light conditions. This film can be applied to various LC modes including twisted nematic and multidomain vertical alignment by changing its internal micrometer‐size 3D structure. Further, this film can be mass‐produced efficiently by self alignment roll‐to‐roll process.     

Global mapping of greenhouse gases retrieved from GOSAT Level 2 products by using a kriging method

Because a synoptic overview facilitates understanding of the temporal and spatial changes in the global distribution of greenhouse gases, we developed a statistical spatial estimation method using kriging. Level 3 (L3) data products for the Greenhouse Gases Observing Satellite (GOSAT) Thermal And Near infrared Sensor for Carbon Observation (TANSO) Fourier Transform Spectrometer (FTS) Short Wave Infrared (SWIR) were generated from column-averaged, dry-air mole fractions of carbon dioxide (XCO₂) and methane (XCH₄) TANSO-FTS SWIR Level 2 (L2) products using this method. Although there have been some reports on the use of kriging for analysing GOSAT products, the kriging method used in this research was specifically adapted to the statistical characteristics of GOSAT L2 products. In the context of using data for atmospheric research, spatially interpolated data (GOSAT L3 products) cannot be more accurate than model-simulated global distributions of gas concentrations (GOSAT Level 4B (L4B) products), which are generated using an atmospheric tracer transport model. However, the L3 product takes much less time to generate than the L4B. It would take about a year to produce the L4B after generation of an L2 product. The great advantage of the L3 product is that it gives a comprehensive and reasonable monthly global distribution of gas concentrations with little delay. The L3 product using the kriging method can be generated on a monthly basis by estimating global semi-variogram curves from the L2 products for each month and interpolating spatially within a region with a radius of 1000 km from existing L2 data locations. The main purpose of this paper is to describe the methodology and characteristics of kriging used to generate the GOSAT L3 product, not for strictly scientific use of the estimated values, but for a reasonable global map of gas concentrations derived statistically from the sparsely observed L2 products within a short time frame. The characteristics of this method are compared to XCO₂ products simulated with an atmospheric tracer transport model. The results show that the method proposed in this study is of practical use for generating L3 products from L2 products.     

Pedestrian trajectory prediction using BiRNN encoder–decoder framework*

Autonomous mobile robots navigating through human crowds are required to foresee the future trajectories of surrounding pedestrians and accordingly plan safe paths to avoid any possible collision. This paper presents a novel approach for pedestrian trajectory prediction. In particular, we developed a new method based on an encoder–decoder framework using bidirectional recurrent neural networks (BiRNN). The difficulty of incorporating social interactions into the model has been addressed thanks to the special structure of BiRNN enhanced by the attention mechanism, a proximity-independent model of the relative importance of each pedestrian. The main difference between our and the previous approaches is that BiRNN allows us to employs information on the future state of the pedestrians. We tested the performance of our method on several public datasets. The proposed model outperforms the current state-of-the-art approaches on most of these datasets. Furthermore, we analyze the resulting predicted trajectories and the learned attention scores to prove the advantages of BiRRNs on recognizing social interactions.     

Inner surface modification of poly(dimethylsiloxane) microchannel with chitin for electrophoretic analysis of proteins

Microchip electrophoresis in a poly(dimethylsiloxane) microfluidic device is one of the versatile separation techniques in a micro total analysis system, while an unstable electroosmotic flow depending on an inner surface of a microchannel and a nonspecific adsorption of biogenic compounds onto the inner surface are often problematic in microchip electrophoresis. To overcome these drawbacks, a chitin-coated poly(dimethylsiloxane) microchannel was newly developed by a relatively simple experimental procedure based on vacuum drying. The obtained chitin-coating showed high durability during 10-times experiments with a stable electroosmotic flow. It was also confirmed that the chitin-coated poly(dimethylsiloxane) microchannel provided the pH-dependent electroosmotic flow related to the dissociations of amino and silanol groups of chitin and poly(dimethylsiloxane), respectively. The nonspecific adsorption of fluorescently labeled proteins onto the inner surface of the channel was well suppressed by the coating, resulting in the sharp and symmetric peak without tailing in the microchip electrophoretic analysis of proteins. The separation of the proteins was also demonstrated in the chitin-coated microchannel, so that the resolution and reproducibility of the migration time were improved as compared to those in the untreated microchannel.     

Domain decomposition method for unstructured meshes in an OpenMP computing environment

In this paper, an efficient unstructured mesh calculation method in an OpenMP parallel computation using multi-core processor is proposed. This is a new domain decomposition method with two characteristics. The first characteristic is to define the size of the sub-block in the computation domain by the size of the cache memory in each core. The second one is to reduce idle time by distributing a defined sub-block for each core appropriately. Using the proposed method, a computation on compressible flow around a plane was able to achieve speed-up more than about 20% in comparison with a conventional method.     

Surface characterization of MgO:Al,N films with meta‐stable de‐excitation spectroscopy and x‐ray photoelectron spectroscopy

Abstract— It is shown that meta‐stable de‐excitation spectroscopy (MDS) is one of the most useful characterization methods to analyze the interaction between the discharge gas and the surface of the material and is applied to MgO:Al,N films. From the results of the measurement and analysis of helium MDS and the in‐situ discharge experiment, it is confirmed that the limited composition films of MgO:Al,N have potentially a larger secondary‐electron‐emission coefficient (γ) compared with that of MgO. The improvement in γ is caused by the electron‐occupied tailing state at around the top of the valence band which is generated by the introduction of Al,N to MgO films. Also, the O1s spectra measured by x‐ray photoelectron spectroscopy (XPS) shows that the stable surfaces are formed with the introduction of Al,N to MgO films.     

Performance evaluation of evolutionary multiobjective optimization algorithms for multiobjective fuzzy genetics-based machine learning

Recently, evolutionary multiobjective optimization (EMO) algorithms have been utilized for the design of accurate and interpretable fuzzy rule-based systems. This research area is often referred to as multiobjective genetic fuzzy systems (MoGFS), where EMO algorithms are used to search for non-dominated fuzzy rule-based systems with respect to their accuracy and interpretability. In this paper, we examine the ability of EMO algorithms to efficiently search for Pareto optimal or near Pareto optimal fuzzy rule-based systems for classification problems. We use NSGA-II (elitist non-dominated sorting genetic algorithm), its variants, and MOEA/D (multiobjective evolutionary algorithm based on decomposition) in our multiobjective fuzzy genetics-based machine learning (MoFGBML) algorithm. Classification performance of obtained fuzzy rule-based systems by each EMO algorithm is evaluated for training data and test data under various settings of the available computation load and the granularity of fuzzy partitions. Experimental results in this paper suggest that reported classification performance of MoGFS in the literature can be further improved using more computation load, more efficient EMO algorithms, and/or more antecedent fuzzy sets from finer fuzzy partitions.     

Suspended bimaterial microchannel resonators for thermal sensing of local heat generation in liquid

Suspended bimaterial microchannel resonator devices have been fabricated to measure the thermal behaviors of small biological molecules and individual cells in liquid. A resonant microbridge structure embeds this microfluidic channel in its interior. The fabrication process is based on the creation of buried channels in silicon-on-insulator wafers. For the bimaterial bridge structure layers of SiO₂ and SiN_x were used. This bimaterial resonant bridge with internal microfluidic channel could be employed as a very sensitive calorimeter, since the tensile stress generated by bimaterial effect in the heated bridge, produces a shift of resonant frequency. A laser beam was used to heat the center of the bridge resonator with the microchannel filled by water and the corresponding resonant frequency variations were evaluated. The measured sensitivity for the local heat at the center of the bridge is 8.6 ppm/μW in atmospheric condition.