Bipartite Flat-Graph Network for Nested Named Entity Recognition

In this paper, we propose a novel bipartite flat-graph network (BiFlaG) for nested named entity recognition (NER), which contains two subgraph modules: a flat NER module for outermost entities and a graph module for all the entities located in inner layers. Bidirectional LSTM (BiLSTM) and graph convolutional network (GCN) are adopted to jointly learn flat entities and their inner dependencies. Different from previous models, which only consider the unidirectional delivery of information from innermost layers to outer ones (or outside-to-inside), our model effectively captures the bidirectional interaction between them. We first use the entities recognized by the flat NER module to construct an entity graph, which is fed to the next graph module. The richer representation learned from graph module carries the dependencies of inner entities and can be exploited to improve outermost entity predictions. Experimental results on three standard nested NER datasets demonstrate that our BiFlaG outperforms previous state-of-the-art models.Comment: Accepted by ACL202

Natural Selection, Irrationality and Monopolistic Competition

This paper builds an evolutionary model of an industry where firms produce differentiated products. Firms have different average cost functions and different demand functions. Firms are assumed to be totally irrational in the sense that firms enter the industry regardless of the existence of profits; firms' outputs are randomly determined rather than generated from profit maximization problems; and firms exit the industry if their wealth is negative. It shows that without purposive profit maximization assumption, monopolistic competition still evolves in the long run. The only long run survivors are those that possess the most efficient technology, face the most favorable market conditions and produce at their profit maximizing outputs. This paper modifies and supports the classic argument for the derivation of monopolistic competition.Evolution, Natural Selection, Irrationality, Monopolistic Competition, Survival of the Fittest, Market Rationality

What\u27s Happening with Potential Ratings?

Several years ago, we would hear everywhere that the performance ratings are dead. Companies then revamped their performance management systems and many went back to ratings they eliminated. Is the same happening with potential ratings? Is the 9-box Performance Potential Grid dead? What are the benefits of doing that? Findings show that across a wide range of tasks, industries and organizations, a small proportion of the workforce tends to drive a large proportion of organizational results. In other words, the top 1% accounts for 10% of organizational output; the top 5% accounts for 25% of organizational output; and the top 20% accounts for 80% of organizational output and organizational outperformance. Synthesis of ‘star’ research, findings, and amongst other outperformance evidence indicates that simply adding a star performer to a team can boost the effectiveness of the team members by 5-15%. Therefore, it is necessary to understand how to identify and assess HIPO in order to help develop them and help your organization achieve performance maximization in this dynamic globalized economy

On the Survival of Overconfident Traders in a Competitive Securities Market

Recent research has proposed several ways in which overconfident traders can persist in competition with rational traders. This paper offers an additional reason: overconfident traders do better than purely rational traders at exploiting mispricing caused by liquidity or noise traders. We examine both the static profitability of overconfident versus rational trading strategies, and the dynamic evolution of a population of overconfident, rational and noise traders. Replication of overconfident and rational types is assumed to be increasing in the recent profitability of their strategies. The main result is that the long-run steady-state equilibrium always involves overconfident traders as a substantial positive fraction of the population.Survivorship, Natural Selection, Overconfident Traders, Noise traders

Learning text representation using recurrent convolutional neural network with highway layers

Recently, the rapid development of word embedding and neural networks has brought new inspiration to various NLP and IR tasks. In this paper, we describe a staged hybrid model combining Recurrent Convolutional Neural Networks (RCNN) with highway layers. The highway network module is incorporated in the middle takes the output of the bi-directional Recurrent Neural Network (Bi-RNN) module in the first stage and provides the Convolutional Neural Network (CNN) module in the last stage with the input. The experiment shows that our model outperforms common neural network models (CNN, RNN, Bi-RNN) on a sentiment analysis task. Besides, the analysis of how sequence length influences the RCNN with highway layers shows that our model could learn good representation for the long text.Comment: Neu-IR '16 SIGIR Workshop on Neural Information Retrieva

Studies on the growth of BaTaO₂N single crystals by flux method for photocatalytic H₂ evolution （フラックス法による水素発生用光触媒BaTaO₂N結晶育成の研究）

信州大学(Shinshu university)博士（工学）この博士論文は、次の学術雑誌論文を一部に使用しています。 / ACS APPLIED ENERGY MATERIALS 3(11):10669-10675 (2020); doi:10.1021/acsaem.0c01739. © 2020 American Chemical Society. / CRYSTAL GROWTH & DESIGN 20(1):255-261 (2020); doi:10.1021/acs.cgd.9b01118. © 2019 American Chemical Society.ThesisLUO, YING. Studies on the growth of BaTaO2N single crystals by flux method for photocatalytic H2 evolution （フラックス法による水素発生用光触媒BaTaO2N結晶育成の研究）. 信州大学, 2021, 博士論文. 博士（工学）, 甲第762号, 令和03年03月20日授与.doctoral thesi

The Predicament of Moral Education and the Analysis on Its Realization

In the era of diversified social life, the moral education in our country is facing with some predicaments: the lag of traditional morality and the conflict of social modernization; the lack of family ethics education; the trust crisis caused by overdraft of social trust; the value orientation of human being under the social division of labor under the development of science and technology. In the new period, it is of great practical significance to explore the effective path of moral education. Moral education should be oriented by the correct value. In the practice of moral education, we should fully understand that moral education is not a saint education, and moral education should go for public education. Moral education should be based on fairness, be oriented by people, affirmative to rationality of self-interest. We should enhance the effectiveness of moral education and establish a moral education system with Chinese characteristics so as to provide a powerful spiritual driver for the economic and social construction in our country