Prediction of Passenger Flow at Sanya Airport Based on Combined Methods

It is crucial to correctly predict the passenger flow of an air route for the construction and development of an airport.Based on the passenger flow data of Sanya Airport from 2008 to 2016,this paper respectively adopted Holt-Winter Seasonal Model,ARMA and linear regression model to predict the passenger flow of Sanya Airport from 2017 to 2018.In order to reduce the prediction error and improve the prediction accuracy at meanwhile,the combinatorial weighted method is adopted to predict the data in a combined manner.Upon verification,this method has been proved to be an effective approach to predict the airport passenger flow.

Teaching Reform of Ideological and Political Education in the Course of Electromagnetic Field and Electromagnetic Wave

To strengthen moral education, improve the quality of talent cultivation, our school carries out “the aggregation action of the ideological and political education in all the courses” to comprehensively improve the quality of personnel training. It strongly encourages the reform of education and teaching of “ideological and political education in the courses” throughout the school, and requires all course teachers to raise their awareness of teaching and educating to explore and build a big ideological education system of the whole staff and all the courses. Taking the teaching of the course “electromagnetic field and electromagnetic wave” as an example, this paper analyzes the necessity and feasibility of carrying out the political education in the courses when professional teachers in colleges teach students’ specialty knowledge and train their specialty quality. Simultaneously, some concrete measures were given and the reform of the course teaching and practice were carried out to make the political education run through the course learning.

An On-chip Interconnection QoS Verification Platform of Processor of Large Data for Architectural Modeling Analysis

This paper presents introduction for a QoS verification of on-chip interconnection based on the new progress of the industry, which combined with an AMD processor chip design for big data. Some verification experience in architectural modeling and simulation of on-chip interconnection is also introduced in this paper.

Multi-step Reinforcement Learning Algorithm of Mobile Robot Path Planning Based on Virtual Potential Field

A algorithm of dynamic multi-step reinforcement learning based on virtual potential field path planning is proposed in this paper. Firstly, it is constructed the virtual potential field according to the known information. And then in view of Q learning algorithm of the QekT algorithm, a multi-step reinforcement learning algorithm is proposed in this paper. It can update current Q value used of future dynamic k steps according to the current environment status. At the same time, the convergence is analyzed. Finally the simulation experiments are done. It shows that the proposed algorithm and convergence and so on are more efficiency than similar algorithms.

Word Segmentation for Chinese Judicial Documents

Word segmentation is an integral step in many knowledge discovery applications. However, existing word segmentation methods have problems when applying to Chinese judicial documents:(1) existing methods rely on large-scale labeled data which is typically unavailable in judicial documents, and (2) judicial document has its own language features and writing formats. In this paper, a word segmentation method is proposed for Chinese judicial documents. The proposed method consists of two steps:(1) automatically generating some labeled data as legal dictionaries, and (2) applying a hybrid multilayer neural networks to do word segmentation incorporating legal dictionaries. Experiments are conducted on a dataset of Chinese judicial documents showing that the proposed model can achieve better results than the existing methods.

A Biomechanical Study of Young Women in High Heels with Fatigue and External Interference

From the perspective of biomechanics, gait inquiry under the influence of fatigue on young women wearing high heels and wear flat shoes with a difference. Explore the intervention of external interference conditions mechanism young women wearing high heels to keep the body in balance, and when you wear flat shoes with a difference.

Sentence-Level Paraphrasing for Machine Translation System Combination

In this paper, we propose to enhance machine translation system combination (MTSC) with a sentence-level paraphrasing model trained by a neural network. This work extends the number of candidates in MTSC by paraphrasing the whole original MT translation sentences. First we train a neural paraphrasing model of Encoder-Decoder, and leverage the model to paraphrase the MT system outputs to generate synonymous candidates in the semantic space. Then we merge all of them into a single improved translation by a state-of-the-art system combination approach (MEMT) adding some new paraphrasing features. Our experimental results show a significant improvement of 0.28 BLEU points on the WMT2011 test data and 0.41 BLEU points without considering the out-of-vocabulary (OOV) words for the sentence-level paraphrasing model.

Oracle Bone Inscriptions Big Knowledge Management and Service Platform

Oracle bone inscriptions (OBI) has important historical and cultural values. The traditional OBI research methods are at a choke point, and the research method using computer science and information technology has opened up the way of OBI information processing. However, it faces some problems, such as large but not centralized knowledge system, long learning cycle, learning difficulties, being difficult to obtain resources, inconsistent format, low retrieval accuracy, and low knowledge sharing and reuse. To solve these problems, it designs an OBI big data research resource management and intelligent knowledge service platform. Its goal is to make full use of OBI big data characteristics and use the knowledge engineering technology to build an OBI knowledge ecosystem. The experiment results show that the platform proposed provides effective one-stop knowledge management and knowledge service.

Research on the Localization of High-Quality Teaching Resources

The emergence of the MOOC leads to the revolution of education.All people can be taught by excellent teachers.But the interest of most of the MOOC learners only last less than two weeks.The main reasons may be the courses too difficult to study and without the restraint mechanism.This paper tries to solve the problem that learners cannot last in a MOOC.We put forward that it is feasible to bring the MOOC of elite courses to general university classroom after the localization of high quality teaching resources.We imported Information and Entropy of MIT to the curriculum of Heilongjiang Institute of Technology.First,we combine with own school characteristics in Information and Entropy.Second,we brought part of Information and Entropy in our class and edit of the original video in some part.Third,we have a test in the end of the course.At last all of students of class finished the instructional video and got good grades in test.The method of bringing the MOOC of elite courses to the curriculum of general university outperforms that of traditional teaching meth.

Topic Model Based Text Similarity Measure for Chinese Judgment Document

In the recent informatization of Chinese courts, the huge amount of law cases and judgment documents, which were digital stored,has provided a good foundation for the research of judicial big data and machine learning. In this situation, some ideas about Chinese courts can reach automation or get better result through the research of machine learning, such as similar documents recommendation, workload evaluation based on similarity of judgement documents and prediction of possible relevant statutes. In trying to achieve all above mentioned, and also in face of the characteristics of Chinese judgement document, we propose a topic model based approach to measure the text similarity of Chinese judgement document, which is based on TF-IDF, Latent Dirichlet Allocation (LDA), Labeled Latent Dirichlet Allocation (LLDA) and other treatments. Combining with the characteristics of Chinese judgment document,we focus on the specific steps of approach, the preprocessing of corpus, the parameters choices of training and the evaluation of similarity measure result. Besides, implementing the approach for prediction of possible statutes and regarding the prediction accuracy as the evaluation metric, we designed experiments to demonstrate the reasonability of decisions in the process of design and the high performance of our approach on text similarity measure. The experiments also show the restriction of our approach which need to be focused in future work.

Towards Realizing Sign Language-to-Speech Conversion by Combining Deep Learning and Statistical Parametric Speech Synthesis

This paper realizes a sign language-to-speech conversion system to solve the communication problem between healthy people and speech disorders. 30 kinds of different static sign languages are firstly recognized by combining the support vector machine (SVM) with a restricted Boltzmann machine (RBM) based regulation and a feedback fine-tuning of the deep model. The text of sign language is then obtained from the recognition results. A context-dependent label is generated from the recognized text of sign language by a text analyzer. Meanwhile,a hiddenMarkov model (HMM) basedMandarin-Tibetan bilingual speech synthesis system is developed by using speaker adaptive training.The Mandarin speech or Tibetan speech is then naturally synthesized by using context-dependent label generated from the recognized sign language. Tests show that the static sign language recognition rate of the designed system achieves 93.6%. Subjective evaluation demonstrates that synthesized speech can get 4.0 of the mean opinion score (MOS).

Method of Consistency Judgment for App Software’s User Comments

With the popularity of mobile intelligent terminal, user comments of App software is viewed as one of the research interests of social computing. Faced with the massive App software, most users usually view the other users’ comments and marks to selecting the desired App software. Due to the freedom and randomness of the network comments, the inconsistence between the user’s comment and mark makes it difficult to choose App software. This paper presents a method by analyzing the relationships among user’s comment information, the user’s mark and App software information. Firstly, the consistency between user’s comment information and App software information is judged. Then, through analyzing the grammar relationships among the feature-words, adverbs and the feature-sentiment-words in App software’s feature-sentimentword- pairs, the user’s emotional tendency about App software is quantified quantified combining with the dictionary and the network sentiment words. After calculating the user’s comprehensive score of App software, the consistency of App software’s user comment is judged by comparing this score and the user’s mark. Finally, the experimental results show that the method is effective.

An Algorithm for Hybrid Nodes Barrier Coverage Based on Voronoi in Wireless Sensor Networks

In order to make up for the deficiencies and insufficiencies that In order to make up for the deficiencies and insufficiencies that wireless sensor network is constituted absolutely by static or dynamic sensor nodes. So a deployment mechanism for hybrid nodes barrier coverage (HNBC)is proposed in wireless sensor network, which collaboratively consists of static and dynamic sensor nodes. We introduced the Voronoi diagram to divide the whole deployment area. According to the principle of least square method, and the static nodes are used to construct the reference barrier line (RBL). And we implemented effectively barrier coverage by monitoring whether there is a coverage hole in the deployment area, and then to determine whether dynamic nodes need limited mobility to redeploy the monitoring area. The simulation results show that the proposed algorithm improved the coverage quality, and completed the barrier coverage with less node moving distance and lower energy consumption, and achieved the expected coverage requirements

SAR Image Quality Assessment System Based on Human Visual Perception for Aircraft Electromagnetic Countermeasures

In electronic confrontation, Synthetic Aperture Radar (SAR) is vulnerable to different types of electronic jamming. The research on SAR jamming image quality assessment can provide the prerequisite for SAR jamming and anti-jamming technology, which is an urgent problem that researchers need to solve. Traditional SAR image quality assessment metrics analyze statistical error between the reference image and the jamming image only in the pixel domain; therefore, they cannot reflect the visual perceptual property of SAR jamming images effectively. In this demo, we develop a SAR image quality assessment system based on human visual perception for the application of aircraft electromagnetic countermeasures simulation platform.The internet of things and cloud computing techniques of big data are applied to our system. In the demonstration, we will present the assessment result interface of the SAR image quality assessment system.