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.

Photosensitization of nanostructured TiO2 with CdSe quantum dots: effects of microstructure and electron transport in TiO2 substrates

Abstract: Four sample types of nanostructured titanium dioxide (TiO 2 ) electrodes were studied, variously prepared with TiO 2 nanocrystalline particles of different sizes (15 and 27 nm in diameter) and with the addition of polyethylene glycol (PEG) binders having two different molecular weights (MW) (20,000 and 500,000). CdSe nanoparticles (CdSe quantum dots: CdSe QDs) were adsorbed on to each of the four types of TiO 2 electrode using a chemical deposition technique. Photoacoustic (PA) and photoelectrochemical (PEC) current spectra were measured, together with the incident photon to current conversion efficiency (IPCE). The photosensitization by the CdSe QDs was confirmed. It was found that the PEC current and IPCE are strongly dependent on the TiO 2 nanoparticle size and the MW of PEG in the TiO 2 /water paste. The correlation of the PEC and IPCE with the microstructure and the electron diffusion coefficient for each of TiO 2 nanostructured electrode type are discussed, providing information which could lead to the optimization of dye-sensitized solar cells (DSSC).

SnortView: visualization system of snort logs

Abstract: False detection is a major issue in deploying and maintaining Network-based Intrusion Detection Systems (NIDS). Traditionally, it is recommended to customize its signature database (DB) to reduce false detections. However, it requires quite deep knowledge and skills to appropriately customize the signature DB. Inappropriate customization causes the increase of false negatives as well as false positives. In this paper, we propose a visualization system of a NIDS log, named SnortView, which supports administrators in analyzing NIDS alerts much faster and much more easily. Instead of customizing the signature DB, we propose to utilize visualization to recognize not only each alert but also false detections. The system is based on a 2-D time diagram and alerts are shown as icons with different styles and colors. In addition, the system introduces some visualization techniques such as overlayed statistical information, source-destination matrix, and so on. The system was used to detect real attacks while recognizing some false detections.

Symbol emergence in robotics: a survey

Abstract: Humans can learn a language through physical interaction with their environment and semiotic communication with other people. It is very important to obtain a computational understanding of how humans can form symbol systems and obtain semiotic skills through their autonomous mental development. Recently, many studies have been conducted regarding the construction of robotic systems and machine learning methods that can learn a language through embodied multimodal interaction with their environment and other systems. Understanding human?-social interactions and developing a robot that can smoothly communicate with human users in the long term require an understanding of the dynamics of symbol systems. The embodied cognition and social interaction of participants gradually alter a symbol system in a constructive manner. In this paper, we introduce a field of research called symbol emergence in robotics (SER). SER represents a constructive approach towards a symbol emergence system. The symbol emergence sys...

High-Performance Drug Discovery: Computational Screening by Combining Docking and Molecular Dynamics Simulations

Abstract: Virtual compound screening using molecular docking is widely used in the discovery of new lead compounds for drug design. However, this method is not completely reliable and therefore unsatisfactory. In this study, we used massive molecular dynamics simulations of protein-ligand conformations obtained by molecular docking in order to improve the enrichment performance of molecular docking. Our screening approach employed the molecular mechanics/Poisson-Boltzmann and surface area method to estimate the binding free energies. For the top-ranking 1,000 compounds obtained by docking to a target protein, approximately 6,000 molecular dynamics simulations were performed using multiple docking poses in about a week. As a result, the enrichment performance of the top 100 compounds by our approach was improved by 1.6–4.0 times that of the enrichment performance of molecular dockings. This result indicates that the application of molecular dynamics simulations to virtual screening for lead discovery is both effective and practical. However, further optimization of the computational protocols is required for screening various target proteins.