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.     

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.     

A Hemispherical Image Sensor Array Fabricated with Organic Photomemory Transistors

Hemispherical image sensors simplify lens designs, reduce optical aberrations, and improve image resolution for compact wide-field-of-view cameras. To achieve hemispherical image sensors, organic materials are promising candidates due to the following advantages: tunability of optoelectronic/spectral response and low-temperature low-cost processes. Here, a photolithographic process is developed to prepare a hemispherical image sensor array using organic thin film photomemory transistors with a density of 308 pixels per square centimeter. This design includes only one photomemory transistor as a single active pixel, in contrast to the conventional pixel architecture, consisting of select/readout/reset transistors and a photodiode. The organic photomemory transistor, comprising light-sensitive organic semiconductor and charge-trapping dielectric, is able to achieve a linear photoresponse (light intensity range, from 1 to 50 W m⁻²), along with a responsivity as high as 1.6 A W⁻¹ (wavelength = 465 nm) for a dark current of 0.24 A m⁻² (drain voltage = −1.5 V). These observed values represent the best responsivity for similar dark currents among all the reported hemispherical image sensor arrays to date. A transfer method was further developed that does not damage organic materials for hemispherical organic photomemory transistor arrays. These developed techniques are scalable and are amenable for other high-resolution 3D organic semiconductor devices.     

Design of a memory‐based prefilter supplementing a robust PID control system

For systems with uncertainties, lots of PID parameter tuning methods have been proposed from the view point of the robust stability theory. However, the control performance becomes conservative using robust PID controllers. In this paper, a new two‐degree‐of‐freedom (2DOF) controller, which can improve the tracking properties, is proposed for nonlinear systems. According to the proposed method, the prefilter is designed as the PD compensator whose control parameters are tuned by the idea of a memory‐based modeling (MBM) method. Since the MBM method is a type of local modeling methods for nonlinear systems, PD parameters can be tuned adequately in an online manner corresponding to nonlinear properties. Finally, the effectiveness of the newly proposed control scheme is numerically evaluated on a simulation example. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Efficient blind dereverberation and echo cancellation based on independent component analysis for actual acoustic signals

This letter presents a new algorithm for blind dereverberation and echo cancellation based on independent component analysis (ICA) for actual acoustic signals. We focus on frequency domain ICA (FD-ICA) because its computational cost and speed of learning convergence are sufficiently reasonable for practical applications such as hands-free speech recognition. In applying conventional FD-ICA as a preprocessing of automatic speech recognition in noisy environments, one of the most critical problems is how to cope with reverberations. To extract a clean signal from the reverberant observation, we model the separation process in the short-time Fourier transform domain and apply the multiple input/output inverse-filtering theorem (MINT) to the FD-ICA separation model. A naive implementation of this method is computationally expensive, because its time complexity is the second order of reverberation time. Therefore, the main issue in dereverberation is to reduce the high computational cost of ICA. In this letter, we reduce the computational complexity to the linear order of the reverberation time by using two techniques: (1) a separation model based on the independence of delayed observed signals with MINT and (2) spatial sphering for preprocessing. Experiments show that the computational cost grows in proportion to the linear order of the reverberation time and that our method improves the word correctness of automatic speech recognition by 10 to 20 points in a RT??= 670 ms reverberant environment.     

Multi-modal Information Integration for Interactive Multi-agent Systems

This paper proposes a multi-agent system that carries out cooperative work. To achieve this, we use Fuzzy Associative Memory Organizing Unit Systems (FAMOUS) and Conceptual Fuzzy Sets (CFS). By using these proposed methods, each agent robot can decide its own behaviour to suit the situation in its environment. We apply this system to an Intelligent Transportation System (ITS) and do simulations.