编路 习路 教路——四年级上册第六单元教材解析与教学建议

统编教材四年级上册第六单元采用"人文主题"和"语文要素"双线组织课文和相关的练习。教学时,教师要读懂"编路"——编写本单元的语文要素的体现,梳理"习路"——如何围绕编路层层递进设置的课后的思考题,构建"教路"——以学生为主体,顺学情而引导,促进学生达成学习的目标。这样",胸中有丘壑"才能"笔下有华章"。

BUILDING A MODERATELY PROSPEROUS SOCIETY IN ALL RESPECTS——Poverty Reduction: Xi Jinping’s Statements and Chinese Path

After the founding of the People’s Republic of China, the Chinese people have been struggling against poverty amid national development under the leadership of the Communist Party of China(CPC). Since reform and opening up, in particular, China has planned for and organized development-oriented poverty reduction practices on a broad scale with remarkable achievements and blazed a new path of development-oriented poverty reduction with Chinese characteristics. This path is both an essential component of Chinese socialism and a result of the CPC’s ideological improvement on poverty reduction. Since the 18 th CPC National Congress in 2012, the whole Party, country, and society have been called upon to fight the battle against poverty on a full-scale under the guidance of General Secretary Xi Jinping’s important statements on poverty reduction, unveiling a new stage for China’s development-oriented poverty reduction in the new era. China’s unprecedented poverty reduction achievements have enriched the path of poverty reduction with Chinese characteristics. Xi Jinping’s insightful and coherent statements on poverty reduction represent the latest results of Marxist anti-poverty theories and comprise an essential part of Xi Jinping Thought on Socialism with Chinese Characteristics for the New Era. His guidelines are the basis for the brilliant achievements of China’s poverty reduction endeavors, and will contribute Chinese experience and wisdom to global poverty governance.

Particle swarm optimization for train schedule of Y-type train routing in urban rail transit

The train schedule usually includes train stop schedule,routing scheme and formation scheme.It is the basis of subway transportation.Combining the practical experience of transport organizations and the principle of the best match between transport capacity and passenger flow demand,taking the minimum value of passenger travel costs and corporation operating costs as the goal,considering the constraints of the maximum rail capacity,the minimum departure frequency and the maximum available electric multiple unit,an optimization model for city subway Y-type operation mode is constructed to determine the operation section of mainline as well as branch line and the train frequency of the Y-type operation mode.The particle swarm optimization(PSO)algorithm based on classification learning is used to solve the model,and the effectiveness of the model and algorithm is verified by a practical case.The results show that the length of branch line in Y-type operation affects the cost of waiting time of passengers significantly.

Short-time prediction for traffic flow based on wavelet de-noising and LSTM model

Aiming at the problem that some existing traffic flow prediction models are only for a single road segment and the model input data are not pre-processed,a heuristic threshold algorithm is used to de-noise the original traffic flow data after wavelet decomposition.The correlation coefficients of road traffic flow data are calculated and the data compression matrix of road traffic flow is constructed.Data de-noising minimizes the interference of data to the model,while the correlation analysis of road network data realizes the prediction at the road network level.Utilizing the advantages of long short term memory(LSTM)network in time series data processing,the compression matrix is input into the constructed LSTM model for short-term traffic flow prediction.The LSTM-1 and LSTM-2 models were respectively trained by de-noising processed data and original data.Through simulation experiments,different prediction times were set,and the prediction results of the prediction model proposed in this paper were compared with those of other methods.It is found that the accuracy of the LSTM-2 model proposed in this paper increases by 10.278%on average compared with other prediction methods,and the prediction accuracy reaches 95.58%,which proves that the short-term traffic flow prediction method proposed in this paper is efficient.

Teaching Business English Course： Incorporating Portfolio Assessment-based Blended Learning and MOOC

Recent years have witnessed the growth of the popularity of open online learning platforms in China’s colleges and universities. This not only promotes the change of teaching concept and the reform of teaching methodology, but also provides a broad new opportunity for the teaching resource integration between universities in China and the prestigious universities in the world. However, with MOOC’s booming and spreading, educators and teachers have also found its limitations during the course of teaching and learning. This paper focuses on the design and the application of the integration of blended learning model and MOOC in Business English Course by selective use of the Open Course Ware of MIT Management School. With the advanced e-portfolio assessment as the standard for students’ achievement, it aims to reveal that the proposed model can trigger students’ study interest and cultivate their autonomous study, corporate learning as well as creative thinking ability.

Use of Blackboard Collaborate at Qassim University： Evaluating Teachers＇ Perceptions

Learning has come a long way from the conventional blackboard that marked the earlier decades to the new age Blackboard Collaborate which enables learners to work and learn in a collaborative online environment. Virtual classrooms, especially with learners sharing in academic workload on portals such as Google Docs, have arrived as a natural development of the ICT （In Circuit Tester） wave. In addition to offering ample scope for peer interaction, Blackboard Collaborate gives learners the electronic environment they are most familiar with and keeps them updated with the latest educational tools. However, for it to succeed, the perception of the teachers is a factor that needs close scrutiny before this tool can be incorporated into the system. The aim of this paper is to investigate the perceptions of teachers at Qassim University, KSA （Kingdom of Saudi Arabia） towards the inclusion of Blackboard Collaborate into the teaching-learning environment, and its efficacy as a learning tool in the university＇s EFL （English as a Foreign Language） situation.

Generalized Nonlinear Irreducible Auto-Correlation and Its Applications in Nonlinear Prediction Models Identification

There is still an obstacle to prevent neural network from wider and more effective applications, i.e., the lack of effective theories of models identification. Based on information theory and its generalization, this paper introduces a universal method to achieve nonlinear models identification. Two key quantities, which are called nonlinear irreducible auto-correlation (NIAC) and generalized nonlinear irreducible auto-correlation (GNIAC), are defined and discussed. NIAC and GNIAC correspond with intrinstic irreducible auto-(dependency) (IAD) and generalized irreducible auto-(dependency) (GIAD) of time series respectively. By investigating the evolving trend of NIAC and GNIAC, the optimal auto-regressive order of nonlinear auto-regressive models could be determined naturally. Subsequently, an efficient algorithm computing NIAC and GNIAC is discussed. Experiments on simulating data sets and typical nonlinear prediction models indicate remarkable correlation between optimal auto-regressive order and the highest order that NIAC-GNIAC have a remarkable non-zero value, therefore demonstrate the validity of the proposal in this paper.

Network traffic flow evolution with battery electric vehicles and conventional gasoline vehicles

In order to investigate the effect of the use of battery electric vehicles on traffic dynamics,the valid paths of electric battery vehicles are defined and a check-based method is proposed to obtain them.Then,assuming that travelers only focus on their past travel experience,a day-to-day traffic assignment model is established based on reinforcement learning and bounded rationality.In the proposed model,the Bush-Mosteller model,a reinforcement learning model,is modified to calculate path choice probability according to bounded rationality.The modified model updates the path choice probability only if the gap between expected travel time and perceived travel time is beyond the cognitive threshold.Numerical experiments validate the effectiveness of the model and show that traffic flows can converge to the equilibrium in any case of cognitive thresholds and penetration rates of battery electric vehicles.The cognitive threshold has a positive influence on the variation of traffic flows while it has a negative influence on the differences between traffic flows.The adaptation of battery electric vehicles leads to the poor performance of the traffic system.

Numerical study and acceleration of LBM-RANS simulation of turbulent flow

The coupled models of LBM （Lattice Boltzmann Method） and RANS （Reynolds-Averaged Navier-Stokes） are more practical for the transient simulation of mixing processes at large spatial and temporal scales such as crude oil mixing in large-diameter storage tanks. To keep the efficiency of parallel computation of LBM, the RANS model should also be explicitly solved; whereas to keep the numerical stability the implicit method should be better for PANS model. This article explores the numerical stability of explicit methods in 2D cases on one hand, and on the other hand how to accelerate the computation of the coupled model of LBM and an implicitly solved RANS model in 3D cases. To ensure the numerical stability and meanwhile avoid the use of empirical artificial lim- itations on turbulent quantities in 2D cases, we investigated the impacts of collision models in LBM （LBGK, MRT） and the numerical schemes for convection terms （WENO, TVD） and production terms （FDM, NEQM） in an explic- itly solved standard k-e model. The combination of MRT and TVD or MRT and NEQM can be screened out for the 2D simulation of backward-facing step flow even at Re = 107. This scheme combination, however, may still not guarantee the numerical stability in 3D cases and hence much finer grids are required, which is not suitable for the simulation of industrial-scale processes.Then we proposed a new method to accelerate the coupled model of LBM with RANS （implicitly solved）. When implemented on multiple GPUs, this new method can achieve 13.5-fold accelera- tion relative to the original coupled model and 40-fold acceleration compared to the traditional CFD simulation based on Finite Volume （FV） method accelerated by multiple CPUs. This study provides the basis for the transient flow simulation of larger spatial and temporal scales in industrial applications with LBM-RANS methods.

Studies on Garden Path Phenomenon in English

Garden path phenomenon is a term that originated from psycholinguistic field. As a special temporary or local ambiguity in language processing, it has been widely explored and studied from aspects of semantics, syntax, pragmatics as well as psycholinguistics and cognitive linguistics over the years, since it was first put forward by Bever in the 1970s. The research of garden path phenomenon is of considerable significance both theoretically and practically. This paper is designed to explore the garden path phenomenon in English through literature and examples. Some basic concepts and main triggering factors of garden path phenomenon are analyzed. This paper explores the triggering factors of garden path phenomenon from the aspects of syntax, semantics, and pragmatics. The major finding is that garden path phenomenon can help learners understand the operation of human language processing mechanism and improve their abilities to deal with garden path sentences, which is of great benefits to learn and understand English language.

Log integration on large scale for global networking monitoring

Supposing that the overall situation is dug out from the distributed monitoring nodes, there should be two critical obstacles, heterogenous schema and instance, to integrating heterogeneous data from different monitoring sensors. To tackle the challenge of heterogenous schema, an instance-based approach for schema mapping, named instance-based machine-learning （IML） approach was described. And to solve the problem of heterogenous instance, a novel approach, called statistic-based clustering （SBC） approach, which utilized clustering and statistics technologies to match large scale sources holistically, was also proposed. These two algorithms utilized the machine-leaning and clustering technology to improve the accuracy. Experimental analysis shows that the IML approach is more precise than SBC approach, reaching at least precision of 81% and recall rate of 82%. Simulation studies further show that SBC can tackle large scale sources holisticalty with 85% recall rate when there are 38 data sources.

Reading with Strategies： A Study of Young EFL Learners＇ Use of Online Reading Strategies

To assist young learners to cultivate efficient learning strategies in the early ages, students in the current study were guided to read three authentic online storybooks and then write their own digital stories with tablet PCs. The study aims to investigate Taiwan Residents elementary school students＇ use of online reading strategies, and their relationship with students＇ performance on reading proficiency tests. The target population consisted of upper-grade learners （n = 83）. The instruments were a M-SORS （modified survey of reading strategy） questionnaire and a reading proficiency test. Major findings were as follows： （l） Students used online reading strategies at medium level; （2） problem solving strategies were proven to significantly correlate with students＇ performance on reading comprehension test; and （3） there was a significant difference between higher and lower reading proficiency learners＇ use of online reading strategies. Pedagogical implications of the findings and suggestion for future research are discussed.

Local Path Planning Method of the Self-propelled Model Based on Reinforcement Learning in Complex Conditions

Conducting hydrodynamic and physical motion simulation tests using a large-scale self-propelled model under actual wave conditions is an important means for researching environmental adaptability of ships. During the navigation test of the self-propelled model, the complex environment including various port facilities, navigation facilities, and the ships nearby must be considered carefully, because in this dense environment the impact of sea waves and winds on the model is particularly significant. In order to improve the security of the self-propelled model, this paper introduces the Q learning based on reinforcement learning combined with chaotic ideas for the model＇s collision avoidance, in order to improve the reliability of the local path planning. Simulation and sea test results show that this algorithm is a better solution for collision avoidance of the self navigation model under the interference of sea winds and waves with good adaptability.

Moving Further Closer

In 2013,Chinese President Xi Jinping proposed the building of the Silk Road Economic Belt and the 21st-Century Maritime Silk Road in hopes of connecting Asian,European and African countries more closely and promoting mutual y beneficial cooperation.

The Road From Talk to Action

Beijing and Tokyo must reconcile their differences The rift between China and Japan shows signs of healing,as evidenced by the brief meeting between Chinese President Xi Jinping and Japanese Prime Minister Shinzo Abe on the sidelines of the 2016 APEC forum in Lima,Peru,on November 20. This was their fourth face-to- face encounter, following meetings at the Beijing APEC forum in China in 2014. the Bandung anniversary in Indonesia in 201 S. and the Hangzhou G20 Summit in China this September.