University of Electro-Communications

About: University of Electro-Communications is a education organization based out in Tokyo, Japan. It is known for research contribution in the topics: Laser & Robot. The organization has 8041 authors who have published 16950 publications receiving 235832 citations. The organization is also known as: UEC & Denki-Tsūshin Daigaku.

Collaborative Learning of Communication Routes in Edge-Enabled Multi-Access Vehicular Environment

Abstract: Some Internet-of-Things (IoT) applications have a strict requirement on the end-to-end delay where edge computing can be used to provide a short delay for end-users by conducing efficient caching and computing at the edge nodes. However, a fast and efficient communication route creation in multi-access vehicular environment is an underexplored research problem. In this paper, we propose a collaborative learning-based routing scheme for multi-access vehicular edge computing environment. The proposed scheme employs a reinforcement learning algorithm based on end-edge-cloud collaboration to find routes in a proactive manner with a low communication overhead. The routes are also preemptively changed based on the learned information. By integrating the “proactive” and “preemptive” approach, the proposed scheme can achieve a better forwarding of packets as compared with existing alternatives. We conduct extensive and realistic computer simulations to show the performance advantage of the proposed scheme over existing baselines.

Three‐dimensional ionospheric tomography using observation data of GPS ground receivers and ionosonde by neural network

Abstract: [1] In this paper we present a new method based on a Residual Minimization Training Neural Network (RMTNN) to reconstruct the three-dimensional electron density distribution of the local ionosphere with high spatial resolution (about 50 km × 50 km in east/west and 30 km in altitude) using GPS and ionosonde observation data. In this method we reconstruct an approximate three-dimensional electron density distribution as a computer tomographic image by making use of the excellent capability of a multilayer neural network to approximate an arbitrary function. For this application the network training is carried out by minimizing the squared residuals of an integral equation. We combine several additional techniques with the new method, i.e., input space discretization, use of ionosonde observation data to improve the vertical resolution, automatic estimation of the biases of the satellite and the ground receivers by using the parameter estimation method, and estimation of plasmasphere contributions to the total electron content on the basis of an assumption of diffusive equilibrium with constant scale height. Numerical experiments for the actual positions of the GPS satellites and the ground receivers are used to validate the reliability of the method. We also applied the method to the analysis of real observation data and compared the results with ionosonde observations which were not used for the network training.

Direct Correlation between Ultrafast Injection and Photoanode Performance in Quantum Dot Sensitized Solar Cells

Abstract: The performance of quantum dot (QD) sensitized solar cells depends mainly on both electron injection from the QDs to the oxide matrix and recombination rates. Here we show a direct correlation between ultrafast carrier dynamics and photoanode (and complete solar cell) performance. TiO2 nanoparticulate electrodes sensitized with colloidal CdSe QDs are prepared by either direct or linker-assisted adsorption (using cysteine, p-mercaptobenzoic acid, and mercaptopropionic acid). These electrodes are examined by ultrafast carrier dynamics, photopotential, and incident photon-to-current efficiency measurements to unravel factors controlling the efficiency in a closed solar cell. Subpicosecond time-resolved measurements are carried out by means of a lens-free heterodyne transient grating technique. In general, faster electron injection is observed for QDs directly adsorbed on TiO2, which correlates with a better cell performance. Otherwise, increasingly faster electron injection is obtained as QD size decreases, ...

Electromagnetic Phenomena Associated with Earthquakes

Abstract: Electromagnetic phenomena are recently found to take place prior to an earhquake, and they are regarded as the most promising candidate for short-term earthquake prediction. This report reviews the recent findings on seismo electromagnetic phenomena, including ULF emissions, seismo-atmospheric and -ionospheric perturebations, Earth's surface temperature anomaly, in-situ observational results etc.

Depth profile of diffuse reflectance near-infrared spectroscopy for measurement of water content in skin.

Abstract: Background/purpose: The penetration depth of light in diffuse reflectance near-infrared spectroscopy for measuring water content in skin is assessed both from theoretical and experimental points of view. Methods: The Monte Carlo simulation was implemented to investigate the dependencies of the light penetration depth on a source–detector distance. To compare with the simulation results, an in vivo experiment for water contents of skin was performed introducing two different optical fiber probes. Results: It is found that the minimum separation between a source and detector fibers influences largely the measurement depth. The larger separation leads to a deeper measurement depth at a particular wavelength. The measurement depth is also influenced fairly by the absorption coefficient of the tissue. The larger absorption coefficient results in a shallower measurement depth. Conclusion: The correlations between the water contents measured by the optical and capacitance techniques were discussed. The dependencies of the light penetration depth on the source-detector geometry and wavelength are presented.