Event Recognition Based on Deep Learning in Chinese Texts.

Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features using methods based on rules is difficult; methods based on shallow neural networks converge too quickly to a local minimum, resulting in low recognition precision. To address these problems, we propose the Chinese emergency event recognition model based on deep learning (CEERM). Firstly, we use a word segmentation system to segment sentences. According to event elements labeled in the CEC 2.0 corpus, we classify words into five categories: trigger words, participants, objects, time and location. Each word is vectorized according to the following six feature layers: part of speech, dependency grammar, length, location, distance between trigger word and core word and trigger word frequency. We obtain deep semantic features of words by training a feature vector set using a deep belief network (DBN), then analyze those features in order to identify trigger words by means of a back propagation neural network. Extensive testing shows that the CEERM achieves excellent recognition performance, with a maximum F-measure value of 85.17%. Moreover, we propose the dynamic-supervised DBN, which adds supervised fine-tuning to a restricted Boltzmann machine layer by monitoring its training performance. Test analysis reveals that the new DBN improves recognition performance and effectively controls the training time. Although the F-measure increases to 88.11%, the training time increases by only 25.35%

Maximin and Bayesian robust experimental design for measurement set selection in modelling biochemical regulatory systems

Experimental design is important in system identification, especially when the models are complex and the measurement data are sparse and noisy, as often occurs in modelling of biochemical regulatory networks. The quality of conventional optimal experimental design largely depends on the accuracy of model parameter estimation, which is often either unavailable or poorly estimated at the stage of design. Robust experimental design (RED) algorithms have thus been proposed when model parametric uncertainties need to be addressed during the design process. In this paper, two robust design strategies are investigated and the comparative study has been made on signal pathway models. The first method is a maximin experimental design approach which is a worst-case design strategy, and the second method is the Bayesian experimental design that 'takes an average' of the parametric uncertainty effects. The limitations of the maximin design which describes the structural uncertainty using a local Taylor representation are quantitatively evaluated. To better quantitatively assess the differences between the maximin and the Bayesian REDs, a concept of effective design parameters is proposed, from which the advantages of the Bayesian design is demonstrated especially in the case of large model uncertainties

Status of end-of-life electronic product remanufacturing in China

Remanufacturing is an industrial process of returning used or worn-out products to an “as-new” functional state with an equal warranty to newly manufactured equivalents. In recent years, remanufacturing has become an emerging research area, a direction toward which China's economic development is tending as well. As the world's fastest-growing solid waste stream, the handling of end-of-life (EOL) electronic products has drawn global concern, and China is no exception. Although it is currently at a preliminary development stage, the remanufacturing of EOL electronic products is rapidly developing, supported by relevant policies. There is a critical need for properly structured management systems, especially when it comes to regulations and standards applicable to EOL electronic products—both at the stage of remanufacturing processes and end products. The status of EOL electronic product remanufacturing in China is reviewed from three perspectives: (1) policies, regulations, and standards; (2) research; and (3) industry. The scope for remanufactured electronic products hereby analyzed mainly covers the following products: cartridge; copier; and information technology (IT) servers. For these, there is an urgent development need of methods and/or tools enabling a standardized remanufacturability assessment. Consumers’ willingness to buy remanufactured products could also be promoted through the improvement and dissemination of knowledge and know-hows related to remanufacturing. The rapid advances in technology and products, and the falling prices of electronic products, could result in an adverse impact on remanufacturing