Answer Sequence Learning with Neural Networks for Answer Selection in Community Question Answering

In this paper, the answer selection problem in community question answering (CQA) is regarded as an answer sequence labeling task, and a novel approach is proposed based on the recurrent architecture for this problem. Our approach applies convolution neural networks (CNNs) to learning the joint representation of question-answer pair firstly, and then uses the joint representation as input of the long short-term memory (LSTM) to learn the answer sequence of a question for labeling the matching quality of each answer. Experiments conducted on the SemEval 2015 CQA dataset shows the effectiveness of our approach.Comment: 6 page

Learning Segmentation Masks with the Independence Prior

An instance with a bad mask might make a composite image that uses it look fake. This encourages us to learn segmentation by generating realistic composite images. To achieve this, we propose a novel framework that exploits a new proposed prior called the independence prior based on Generative Adversarial Networks (GANs). The generator produces an image with multiple category-specific instance providers, a layout module and a composition module. Firstly, each provider independently outputs a category-specific instance image with a soft mask. Then the provided instances' poses are corrected by the layout module. Lastly, the composition module combines these instances into a final image. Training with adversarial loss and penalty for mask area, each provider learns a mask that is as small as possible but enough to cover a complete category-specific instance. Weakly supervised semantic segmentation methods widely use grouping cues modeling the association between image parts, which are either artificially designed or learned with costly segmentation labels or only modeled on local pairs. Unlike them, our method automatically models the dependence between any parts and learns instance segmentation. We apply our framework in two cases: (1) Foreground segmentation on category-specific images with box-level annotation. (2) Unsupervised learning of instance appearances and masks with only one image of homogeneous object cluster (HOC). We get appealing results in both tasks, which shows the independence prior is useful for instance segmentation and it is possible to unsupervisedly learn instance masks with only one image.Comment: 7+5 pages, 13 figures, Accepted to AAAI 201

Damping multi-model adaptive switching controller design for electronic air suspension system

This paper presents the design and verification of a damping multi-model adaptive switching controller for electronic air suspension (EAS) system. In order to improve the convergence rate of identification algorithm of conventional adaptive controller, multiple local linear full-car vehicle models of EAS system with fixed parameters are established according to the actual damping control process of EAS for different vehicle driving conditions and an adaptive model whose initial value of parameters can be re-assigned is introduced to enhance the system control precision. The model switching control strategy based on minimum error is used to select the best matching model online and the optimum damping force is regulated by adaptive control algorithm, thus constituting the damping multi-model adaptive control for EAS. Simulation results show that the control method proposed in this paper can improve the damping regulating performance of EAS effectively in wide range driving conditions, especially for the case of sudden change in driving conditions

The Analysis of Electricity Deployment Under the Government Involvement in Holidays

As the power load is less on holidays compared with the annual electricity load, we built a model to analyze the feasibility of the use of electricity for enterprises on holidays. This paper paid attention to the electric deployment under the government involvement. We set up a discounted electricity price, the industrial enterprises may restart production of the preferential tariff during holidays. It analyzed all of the situations that the power enterprises would like to do with the change of the public subsidies and encouragement of the government. It is helpful to deploy electricity and provide a reference for government to make a decision

A “University-Community-Student” multi-profit model of service learning basing on mentoring program

There is a topic, that how to combine the function of social service with the task of developing manpower, being more and more concerned throughout higher education in mainland china. By means of consistent exploring, a team from Chinese Youth University for Political Sciences established a multi-profit model of service learning, which base on mentoring program. This model focus on inviting particular field where direct social service and education happens organically: institutions for higher education engage in community changes, which shown as promoting social inclusion, by grouping students and professors into practice; and students, by performance in one-to-one mentoring and cooperate-learning, subsequently comprehend the knowledge, achieve self-reflection and obtain in-depth recognition of society. This article indicated a finding that the migrant children, for who students mobilized, have affirmative impact especially in integrating into urban life. And the better qualitative relationship acquired between mentors and children, the more contribution would be on arising protective factors at the same time. Teachers and community workers, joining with students in the process of learning, facilitate further understanding on the problem of migrant population under circumstance of urbanization. And they experience together the inherent and external transform of migrant children. Nowadays, migrate population issue being emphasized on a social inclusion’s view while urbanization growing in intensity. We suggest that universities and colleges should utilize their advantage in human resource to promote wellbeing of migrant children. The mentoring based “university, community and student” multi-profit model of service learning, in a widespread field, should be introduced to a harmonious society

Bis[μ-1,2-diphenyl-N,N′-bis­(di-2-pyridyl­methyl­eneamino)ethane-1,2-diimine]disilver(I) bis­(hexa­fluorido­phosphate) acetonitrile disolvate

In the centrosymmetric dinuclear title compound, [Ag2(C36H26N8)2](PF6)2·2C2H3N, the Ag+ ion is bound to four N atoms from two 1,2-diphenyl-N,N′-bis­(di-2-pyridyl­methyl­eneamino)ethane-1,2-diimine ligands in a distorted tetra­hedral geometry. The ligand adopts a twist conformation, coordinating two metal centers by three pyridyl N atoms and one imine N atom and spanning two Ag+ ions, resulting in the formation of a helical dimeric structure