Media Research Center

About: Media Research Center is a based out in . It is known for research contribution in the topics: Collaborative learning & Educational technology. The organization has 491 authors who have published 950 publications receiving 28581 citations. The organization is also known as: MRC.

Neural correlates of externalized auditory motion perception under reverberation

Abstract: Using functional magnetic resonance imaging, we investigated neural substrates of realistic auditory motion perception. "Realistic" here means experiencing the sound as located outside the head instead of originating inside the head. In order to examine neural effects of moving sounds and neural effects of externalized sounds separately, we included two experimental factors in our design: whether auditory stimuli were externalized or not (externalizability factor) and whether auditory stimuli were moving or not (motion factor). Externalized sounds activated planum temporale (PT) more than non-externalized sounds. Moving sounds activated posterior middle temporal gyrus (pMTG) more than stationary sounds. An interaction effect was found in the right PT. Our results indicate that the PT and pMTG are involved in realistic auditory motion perception. The fidelity of auditory space presentation may be evaluated by observing neural activity change in the PT and pMTG.

Current research on enzyme polymorphism

Abstract: Overall incidence of variation: Enzyme polymorphism is a well documented phenomenon in human populations. Estimates derived from electrophoretic studies indicate that approximately one third of all human enzymes exhibit genetic polymorphism where “polymorphism” is defined as the occurrence of heterozygotes with a frequency greater than 2%. Taken as a whole the data indicate that the average heterozygosity per locus is about 0.06 and this implies that any single individual in any human population is likely to be heterozygous at about 6% of the loci encoding enzyme proteins, for alleles which give rise to electrophoretically distinct isozyme forms (Harris & Hopkinson, 1976). The complexity of the isozyme patterns varies according to the subunit structure of the enzyme proteins and on average monomeric enzymes exhibit a higher incidence of genetic polymorphism than multimeric enzymes (Harris, Hopkinson & Edwards, 1977).

Viewing angle enlarged in-line holographic 3D display system using multi-sideband filtering method

Abstract: We propose an omnidirectional viewing zone based in-line holographic 3D display system using center-symmetric multi-sideband filtering method for viewing angle enlargement. Optical analysis and experiments are executed to confirm the feasibility of the proposed system.

Binary Mth band filters for image size conversion

Abstract: Images and video sequences often have to be scaled to a different size. We present binary interpolation filters obtained from the Mth band eigenfilters via the lifting steps for the sampling rate alteration. The binary filters are implemented with only the shift and add operations, providing an efficient way to perform image size conversion. Scaled images using the proposed filters show superb image quality.

A Decentralized AI Data Management System In Federated Learning

Abstract: Federated Learning is a distributed machine learning approach which enables model training without sharing private locally produced data. It has been actively researched for several years as a means to utilize big data while protecting personal information. However, the server must decide which clients to participate in and what results to be used for aggregation each round. Besides, since the server needs to maintain the connection with the client directly, device overload and the processing delay may cause due to changes in the system environment such as network condition. In this paper, we propose a data management system that efficiently addresses the problem of general Federated Learning by improvements of the data management process on the connection between the Federated Learning server and the client. Additionally, it is shown that the proposed system can perform tasks independently and scales for increasing number of devices participating in the Federated Learning tasks.