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Yuan cosmos is a virtual world linked and created by scientific and technological means, which is mapped and interacted with the real world, and a digital living space with a new social system. With the increasing popularity of data acquisition and production equipment, people are increasingly convenient to produce multimedia data such as images, graphics, audio, video, animation, and three-dimensional models. In addition to the rapid development of digital technology itself, the biological information technology related to digital technology also greatly promotes the emergence of the metauniverse. This paper aims to study the application of multimedia digital technology to the ecological scene design of metauniverse space, introduces the related concepts of metauniverse and multimedia digital technology, expounds the related methods of multimedia digital technology and neural network related algorithms, and then takes the three-dimensional simulation of the auditory system in the interactive multisensory simulation system of the constituent elements of metauniverse as an example. The mel-frequency cepstrum coefficient (MFCC) is used to simulate the auditory characteristics of the auditory periphery (cochlea) as the perceptual end of the model. A variety of bionic mechanisms are used in the model, such as designing the connection mode of neurons, learning state and release effect, and the regeneration mechanism of neurons. For the verification of the performance of the model, the speech sample database, including English words and phrases, is recorded and the speech content information recognized by the model by means of speech recognition is experimented. The experimental results show that, in terms of phrase accuracy, the DN-1 model improves 2.59% and the DN-2 model improves 2.77% compared with MFCC feature on the basis of mixed features. When only DBN features are used, the performance improvement rate of the developmental network model is small.

Abstract-In this paper we present the design and evaluation of our biomedical literature searching approaches using the TREC 2004 ad hoc retrieval task in the Genomics track. The main approach taken in our system is to expand queries by exploiting the three widely used strategies -local analysis, global analysis, and ontology-based term re-weighting across various search engines. The experimental results show that (1) ontology-based term re-weighting provides the best results among the three query expansion strategies, (2) expanding the initial query with more precise ontology-based term enhances LSI based local analysis substantially, and (3) including context to term re-weighting and LSI further improves the precision. Experimental results also show that the ontology-based term re-weighting with LUCENE or LEMUR search engines increases the average precision by up to 20.3% or 12.1%, respectively, compared to that of the baseline runs. In addition, the LSI-based local analysis increases the average precision by 9.2% with LEMUR search engine. We believe the principles of the term re-weighting strategy and LSI-based local analysis may be extended and utilized in other bio-medical domains.

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