wastewater treatment technology in the cyclic nature of the process that takes a long time. but man tries to rush to their needs with experience and understanding of the natural processes of interaction, and using technology to build their industrial development is authorized. sewage treatment reed have been born from the vision of man's increasing need to water daily decreases the natural reso...

Background: RNA plays key role in many aspects of biological processes and its tertiary structure is critical for its biological function. RNA secondary structure represents various significant portions of RNA tertiary structure. Since the biological function of RNA is concluded indirectly from its primary structure, it would be important to analyze the relations between the RNA sequences and t...

Convolutional neural networks (CNNs) have recently emerged as a popular building block for natural language processing (NLP). Despite their success, most existing CNN models employed in NLP are not expressive enough, in the sense that all input sentences share the same learned (and static) set of filters. Motivated by this problem, we propose an adaptive convolutional filter generation framewor...

Subjective opinions generalize probability distributions by including degrees of uncertainty which reflect lack of confidence in the probabilities. This paper describes a method for computing the joint subjective opinion of two variables which can be generalized to a method for computing joint subjective opinions over multiple variables in a subjective Bayesian network. We show how the joint op...

â  the prediction of maximum temperatures as one of the most important climatic parameters due to climate change, global warming and the recent drought will provide definitely more opportunity for planning and the provision of necessary arrangements for the planners. maximum temperatures are much important in management of natural and water resources, agriculture, development of pests and disea...

Entity recognition is an important part of natural language processing, but nowadays most entity recognition systems are restricted to a limited set of entity classes (e.g., person, location, organization or miscellaneous). Therefore, fine-grained entity type classification becomes a hot issue to further study. This paper proposed a neural network model based on topic information for fine-grain...

Natural language inference (NLI) is a central problem in language understanding. End-to-end artificial neural networks have reached state-of-the-art performance in NLI field recently. In this paper, we propose Characterlevel Intra Attention Network (CIAN) for the NLI task. In our model, we use the character-level convolutional network to replace the standard word embedding layer, and we use the...

Word embeddings based on neural networks are widely used in Natural Language Processing. However, despite their success in capturing semantic information from massive corpora, word embeddings still conflate different meanings of a word into a single vectorial representation and do not benefit from information available in lexical resources. We address this issue by proposing a new model that jo...