An Exploratory Practice of Integration of Industry and Education in High-level Programming Language Course in the Background of New Engineering

This paper analyzes some problems of the current teaching situation in the course High-level Programming Language,such as the lagging content of the course compared with technology development,the emphasis on theory rather than on practice,the low enthusiasm of students for learning,and the weak practical ability of students.In response to the needs of enterprises for talents under the background of New Engineering,especially the cultivation of students’adaptability and practical abilities towards future industries to improve students’knowledge and problemsolving abilities to keep up with the modern technology,this paper proposes the ways and methods to reform and explore the teaching content and teaching methods by integrating industry and education,assisting teaching according to industrial demands,and lowering technology barriers of new technology.The practical effect is evaluated through a survey in class and the follow-up questionnaire after class,and the results show that the effect of the practice is effective.

UAV Online Path Planning Algorithm in a Low Altitude Dangerous Environment

UAV online path-planning in a low altitude dangerous environment with dense obstacles, static threats (STs) and dynamic threats (DTs), is a complicated, dynamic, uncertain and real-time problem. We propose a novel method to solve the problem to get a feasible and safe path. Firstly STs are modeled based on intuitionistic fuzzy set (IFS) to express the uncertainties in STs. The methods for ST assessment and synthesizing are presented. A reachability set (RS) estimator of DT is developed based on rapidly-exploring random tree (RRT) to predict the threat of DT. Secondly a subgoal selector is proposed and integrated into the planning system to decrease the cost of planning, accelerate the path searching and reduce threats on a path. Receding horizon (RH) is introduced to solve the online path planning problem in a dynamic and partially unknown environment. A local path planner is constructed by improving dynamic domain rapidly-exploring random tree (DDRRT) to deal with complex obstacles. RRT∗ is embedded into the planner to optimize paths. The results of Monte Carlo simulation comparing the traditional methods prove that our algorithm behaves well on online path planning with high successful penetration probability. © 2014 Chinese Association of Automation.

Learning Effectiveness Oriented Hybrid Teaching Mode

In the course of program comprehension and analysis,we have carried out an effectiveness oriented hybrid teaching mode,and carried out the reform of student-centered teaching methods.The teaching content puts forward specific solution cases from the perspective of industrial practice.Latest literatures from top conferences are analyzed and disused in class,so as to track the state art of research and practice.Practical project is assigned to improve students’practice and innovation ability.Teaching,learning and practice are closely integrated.In each link,students are guided to carry out autonomous and inquiry learning to improve their learning effectiveness.Good learning results have been achieved.

An Empirical Study of Code Clone Clustering Based on Clone Evolution

There are lots of code clones appearing in software,which are similar code fragments with each other. In the past decades,researchers have proposed some state-of-the-art methods to detect clones. The code clones have showing some relationship with the evolution of software. In order to explore relationships between clones and their evolution,we propose a framework to cluster clones with a Fuzzy C-means clustering method.Firstly,we detect all the clones using Ni Cad,and build the clone genealogies for multiple versions software.Secondly,we extract some metrics to describe the clones and their evolution. Finally,we cluster all clone's vectors,which are generated with the different metrics for different proposes. Experimental results on six open source software packages have shown the relationships among the clone life,the number of change times,the clone pattern and et al. can help developers to understand clones.

A New Model of Scenario Comprehension and Practical Progressive Teaching

Taking Digital Logic Design,a professional foundation course for undergraduates in the School of Computer Science of Harbin Institute of Technology,as an example,we propose a new teaching model of scenario comprehension and practical progressive teaching in response to the many difficult problems faced in undergraduate teaching,such as the change of the teaching target to first-year university students with zero foundation and low starting point,and the compression of class time,while the quality of the course and the quality of student training have to be improved simultaneously.With the help of MOOC to implement blended teaching,effective means such as lowering the threshold,raising interest,building foundation and progressive improvement are adopted to help freshmen challenge themselves and move to a higher starting point.This paper is a useful exploration of the current new model of high-quality teaching in hardware courses for junior undergraduates.

A Graded and Individualized Teaching and Learning method

Taking the programming course as an example,a comprehensive solution for individualized and precise teaching has been proposed.Firstly,graded teaching strategy is performed.The students are divided into three groups according to their base of learning and the degree of acceptance of knowledge.Designed teaching resources are provided for the teaching mode of low starting points and high landing points.Secondly,a process evaluation method combining online and offline has been proposed.An“evaluation-feedback-improvement”mechanism based on the analysis of students’learning data has been adopted.The practice in Harbin Institute of Technology has shown that the proposed method can not only help students achieve individualized learning goals,but also help teachers achieve precise teaching.

DeST 3.0:A new-generation building performance simulation platform

Buildings contribute to almost 30%of total energy consumption worldwide.Developing building energy modeling programs is of great significance for lifecycle building performance assessment and optimization.Advances in novel building technologies,the requirements of high-performance computation,and the demands for multi-objective models have brought new challenges for building energy modeling software and platforms.To meet the increasing simulation demands,DeST 3.0,a new-generation building performance simulation platform,was developed and released.The structure of DeST 3.0 incorporates four simulation engines,including building analysis and simulation(BAS)engine,HVAC system engine,combined plant simulation(CPS)engine,and energy system(ES)engine,connected by air loop and water loop balancing iterations.DeST 3.0 offers numerous new simulation features,such as advanced simulation modules for building envelopes,occupant behavior and energy systems,cross-platform and compatible simulation kernel,FMI/FMU-based co-simulation functionalities,and high-performance parallel simulation architecture.DeST 3.0 has been thoroughly evaluated and validated using code verification,inter-program comparison,and case-study calibration.DeST 3.0 has been applied in various aspects throughout the building lifecycle,supporting building design,operation,retrofit analysis,code appliance,technology adaptability evaluation as well as research and education.The new generation building simulation platform DeST 3.0 provides an efficient tool and comprehensive simulation platform for lifecycle building performance analysis and optimization.

Detection of semantically similar code

The traditional similar code detection approaches are limited in detecting semantically similar codes, impeding their applications in practice. In this paper, we have improved the traditional metrics-based approach as well as the graph- based approach and presented a metrics-based and graph- based combined approach. First, source codes are represented as augmented system dependence graphs. Then, metrics- based candidate similar code extraction is performed to filter out most of the dissimilar code pairs so as to lower the computational complexity. After that, code normalization is performed on the candidate similar codes to remove code variations so as to detect similar code at the semantic level. Finally, program matching is performed on the normalized control dependence trees to output semantically similar codes. Experiment results show that our approach can detect similar codes with code variations, and it can be applied to large software.

Endocuticle is involved in caste differentiation of the lower termite

Caste differentiation in termites is one of the most conspicuous examples of facultative polyphenism in animals.It is clear that specific cuticular formation occurs in hard exocuticles during caste differentiation.However,the developmental pattern of the soft endocuticle in the differentiation pathways of castes is unknown.To reveal whether the endocuticle is involved in caste differentiation,we compared the exocuticle and endocuticle thickness of individuals in 2 pathways(nymph line and worker line)of caste differentiation in the termite Reticulitermes aculabialis.The endocuticle protein genes were identified by transcriptome analysis and the expression patterns of these genes were confirmed in caste differentiation.We found that the endocuticle structure showed dynamic changes in 2 pathways,and the first difference in endocuticle structure occurred after larvae differentiation bifurcated into workers and nymphs.The thinning of the endocuticle was a significant event from nymphs developing into alates with the thickest exocuticle and thinnest endocuticle.The thickest endocuticle layers were found in the heads of the workers and the ultrastructure of the endocuticle in the heads was more complex than that in the thorax–abdomens.Six endocuticle protein genes were identified and annotated as endocuticle structural glycoproteins SgAbd-2,SgAbd-9,and Abd-5.The expression levels of endocuticle protein genes changed dramatically during caste development and the expression levels in neotenic reproductives(secondary reproductives)were significantly higher than those in alates(primary reproductives).These results reveal the roles of endocuticles in caste differentiation and adaptation to the environment.