Dynamic moduli for short fiber-CR composites

The dynamic moduli, E′ and E″, and tan δ for nylon–CR and PET–CR composites with unidirectional short fibers were studied as a function of temperature by using a Rheovibron. The temperature dependence of tan δ showed two dispersion peaks for nylon–CR composite. The peak at ?28°C corresponded to the main dispersion of CR and the peak at 100°C to the α-dispersion of nylon 6. For a PET-CR composite, in addition to the individual dispersion of CR and PET, a small and broad peak was observed at about 90°C. The angular dependence of E′ indicated that the short fibers assumed good orientation. The storage modulus for the composites was given by the parallel model as E′ = V_f′E_f + V_mE′_m., where E′_c, E′_f and E′_m were the storage modulus for the composite, fiber, and matrix and V_f and V_m were the volume fraction of fiber and matrix, respectively. In the transverse direction of fiber, the peak values of tan δ at ?28°C were given by the following equation; tan δ_c = tan δ_m ? δV_f, where tan δ_c and tan δ_m are the loss tangent for the composite and matrix, respectively, and α is coefficient depending on fiber type. The results indicated that a region with strong interaction was formed between fibers and CR matrix.     

k-NN classification of handwritten characters via accelerated GAT correlation

This paper addresses the problem of reinforcing the ability of the k-NN classification of handwritten characters via distortion-tolerant template matching techniques with a limited quantity of data. We compare three kinds of matching techniques: the conventional simple correlation, the tangent distance, and the global affine transformation (GAT) correlation. Although the k-NN classification method is straightforward and powerful, it consumes a lot of time. Therefore, to reduce the computational cost of matching in k-NN classification, we propose accelerating the GAT correlation method by reformulating its computational model and adopting efficient lookup tables. Recognition experiments performed on the IPTP CDROM1B handwritten numerical database show that the matching techniques of the simple correlation, the tangent distance, and the accelerated GAT correlation achieved recognition rates of 97.07%, 97.50%, and 98.70%, respectively. The computation time ratios of the tangent distance and the accelerated GAT correlation to the simple correlation are 26.3 and 36.5 to 1.0, respectively.     

Anodic Dissolution of Uranium Mononitride in Lithium Chloride-Potassium Chloride Eutectic Melt

Uranium-plutonium nitride is a candidate fuel for fast reactors, but its major drawback is ¹⁴C formation from natural nitrogen. One would probably have to use highly ¹⁵N-enriched nitrogen. A pyrochemical process with molten-salt electroreflning has been proposed as a means to increase the nuclear proliferation resistance of the fuel cycle. Molten-salt electroreflning could also be applied to nitride fuels to make possible the recycling of ¹⁵N. The anodic dissolution behavior of UN in LiCI-KCI melt was studied to provide the basis for a feasibility study of electroreflning of irradiated nitride fuels.     

Formation of phase structure and crystallization behavior in blends containing polystyrene–polyethylene block copolymers

The microphase separation structure in the molten state and the structure formation in crystallization from such ordered melt were investigated for the blends of polystyrene–polyethylene block copolymers (SE) with polystyrene homopolymer (PS) and polyethylene homopolymer (PE) and for the blends consisting of two kinds of SE with different copolymer compositions from each other, using synchrotron small-angle X-ray scattering techniques (SAXS). The copolymer compositions of SE block copolymers employed were 0.34, 0.58 and 0.73 wt. fraction of PE, and their melt morphologies were cylindrical, lamellar and lamellar, respectively. Macrophase separation or the morphology change in the melt occurred depending on the molecular weight and the blend composition, as reported so far. In crystallization from such macrophase-separated and microphase-separated melts, the melt morphology was completely kept for all the blends. Crystallization behavior was also investigated for the blends. The crystallization within the spherical and cylindrical domains surrounded by glassy PS was not observed for SE/PS blends. In the crystallization from the macrophase-separated melt, two exothermal peaks were observed in the DSC measurements, while a single peak was observed for other blends. For the blends with PS, the degree of crystallinity was depressed and the apparent activation energy of crystallization was high, compared to those for the corresponding neat SE. For SE/PE and SE/SE blends, those were changed depending on the blend composition.     

Forming of aluminium alloy at temperatures just below melting point

In order to improve the mechanical properties of products, a forming process of a solid material at a temperature just below the melting point is proposed. The material is deformed at the semi-solid temperature due to the heat generation caused by plastic deformation. The tensile strength, elongation, hardness and toughness of the aluminium alloy (Al–7%Si–0.3%Mg) billet extruded at temperatures between 500 and 550 °C are compared with those of the billet extruded in the hot forming (450 °C) and the semi-solid (560 °C) temperatures. The billet temperature during forming is evaluated by the finite element simulation. The tensile strength and hardness of the billet extruded at 550 °C just below the solidus temperature are higher than those for a billet at 450 °C, and they are almost the same as those for a billet deformed at 560 °C in the semi-solid region. The elongation and toughness of the extruded billet at 550 °C are lower than those for a billet at 450 °C. The forming load at 550 °C is almost half of that at 450 °C. Cracking on the surface of the extruded billet occurs at a high punch speed. The calculated temperature when the solid billet is extruded in the semi-solid state agrees well with the experimental one at which the tensile and hardness are improved.     

What kind of floor am I standing on? Floor surface identification by a small humanoid robot through full-body motions

This study addresses a floor identification method for small humanoid robots that work in such daily environments as homes. The fundamental difficulty lays in a method to understand the physical properties of floors. To achieve floor identification with small humanoid robots, we used inertial sensors that can be easily installed on such robots, and dynamically selected a full-body motion that physically senses floors to achieve accurate floor identification. We collected a training data-set over 10 different kinds of common floors in home environments. We achieved 85.7% precision with our proposed method. We also demonstrate that our robot could appropriately change its locomotion behaviours depending on the floor identification results.     

Cost-Efficient Traffic Aggregation Employing Cross-Layer Shared Protection

Shared protection/restoration is a promising solution for reducing protection resources and is supported at each layer of the current multi-layer networks. Software-defined networking is expected to reduce equipment cost as well as operational cost by orchestrating these shared protection functionalities. However, although protection resource sharing improves link utilization, it sometimes increases the required equipment. Meanwhile, traffic re-aggregation at each layer is an important technique for low volume traffic to utilize the underlying link capacity more efficiently, but re-aggregation also makes it difficult to share protection resources with traffic at lower layers. In this paper, we present multi-layer network design strategy and method that reduce equipment cost by means of both traffic re-aggregation at each layer and protection resource sharing among multiple service traffic at different layers. The strategy first prioritizes traffic re-aggregation at each layer, and then maximally delegates shared protection to lower layers as long as it does not increase the required capacity at the lower layer. Evaluation results from the example three-layer networks confirm that the proposed method can effectively reduce equipment cost compared to the conventional design method. Cost reduction is achieved by leveraging shared protection functions at multiple layers.     

Ergonomics solution for crossing collisions based on field assessment of visual environment at urban intersections in Japan

This paper aims to assess quantitatively the actual visual environment of uncontrolled urban downtown intersections in Japan in relation to frequently occurring crossing collisions and to discuss the safety countermeasures for them. In Field Study 1 dealing with direct visibility, our ultra-wide-angle photograph analysis revealed that most of the right/left-ward visible range at 11 intersections were insufficient to check safety, and the quality of direct visibility was closely associated with causing crossing collisions. The countermeasures to reduce a blind area were determined to be a top priority. In Field Study 2 dealing with indirect visibility, more than half of the 25 traffic convex mirrors had marked shortcomings for preventive safety, and ergonomics guidelines ensuring indirect visibility were proposed for installing traffic convex mirrors. Low-cost/low-technology-oriented countermeasures are highly recommended to obtain clear/sufficient images of crucial information satisfying drivers' requirements on traffic convex mirrors in accordance with those ergonomics guidelines was highly recommended. Crossing collisions could be prevented by improvement of poor direct and indirect visibility.     

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.

     

Ultra-fast microwave aided synthesis of gold nanocages and structural maneuver studies

Gold nanocages (AuNcgs) are well-studied,hollow,metallic nanostructures that have fascinated researchers in the fields of nanotechnology,materials science,photoelectronics,biotechnology,and medical science for the last decade.However,the time-consuming synthesis of AuNcgs has limited their widespread use in materials science and nano-biotechnology.A novel,ultra-fast,simple,and highly convenient method for the production of AuNcgs using microwave heating is demonstrated herein.This quick method of AuNcg synthesis requires mild laboratory conditions for large-scale production of AuNcgs.The microwave heating technique offers the advantage of precise mechanical control over the temperature and heating power,even for the shortest reaction period (i.e.,seconds).Microwave-synthesized AuNcgs were compared with conventionally synthesized AuNcgs.Structural maneuver studies employing the conventionally produced AuNcgs revealed the formation of screw dislocations and a shift in the lattice plane.Detailed characterization of the microwave-generated AuNcgs was performed using high resolution transmission electron microscopy (HRTEM),scanning electron microscopy (SEM),X-ray powder diffraction (XRD),and spectroscopic techniques.