首先论述了大学的本质属性,接着论及大学的根本性质和天然内涵,及其所决定的大学核心职能、第一天职,最后提出并简要分析了大学坚守初心、回归本真、促进内涵式发展应处理好的七种关系.

"以学生为中心"的教学理念的落地落实,核心在于因材施教,关键是区分教学对象的差异性,通过差异性引领因材施教."自动控制原理"是一门大类技术基础课程,面向全校十余个专业开设,学情状况复杂;根据学生的学科差异、专业差异和个体差异,分类制定课程标准,按需定制教学案例,精准开展因材施教.特别是基于自建的MOOC课程、微课视频、知识导图等大量数字化教学资源,开展线上线下混合式教学实践,努力提升学生学习体验,不断提高教学质量.

本文结合“微机原理与接口技术”课程教学体系和教学内容改革,针对不同专业对象、不同教学时数的需求,探讨既可用传统汇编语言又可用C语言开展教学的教材建设.教材的内容组织上,以培养应用计算机接口技术、从硬件与软件的结合上分析、设计微机应用系统的计算思维能力为切入点,淡化背景机,强化总线接口层面硬软件教学,突出各种CPU与外设接口原理、方法上的通用性.

针对计算机硬件技术基础教学中的“中断机制”章节,说明如何培养学生的计算思维能力.首先从机理层面分析中断的检测、响应、处理过程,指出多中断源管理存在的两种情况:同时性与嵌套性,并提出优先级的一致性原则,分析查询式中断优先级判决方法中有可能存在的错误嵌套的现象及产生的原因,给出改进方法,并将此方法用于中断控制器8259A内部结构的讲解,结合逻辑建模的方法,提出ISR实现嵌套管理的观点.

The practical teaching is a very important process for students to develop their innovation abilities.This paper is written under the trend of practical teaching reform in computer hardware curriculums.According to our experience on teaching and training talents as well as focusing on developing students′ innovation abilities,this paper puts forward opinions and suggestions on exploring the reform in computer hardware curriculums,including the practical teaching system,implementation method and laboratory construction.

Research-Oriented Teaching which has become the current trend of high education reform,is proved to be an effective mode to cultivate innovation capability and computational thinking.In the paper,a whole teaching scheme conducted by the problem-based learning is proposed to comply with the characteristic of the course Basis of Computer Hardware Technology.This scheme has been applied in teaching in the following issues: content,teaching modes and methods,practice teaching and the way of examinations.Suggestions are put forward from the explorations,and practice has proved that the scheme was effective in our reform.

In this paper, we explicitly explore how to manipulate single qubits by one-rotation controls under various manipulation conditions. It is revealed that one can construct control Hamiltonian and adjust the control to manipulate quantum states. Furthermore, we comprehensively discuss how to optimize control magnitude in terms of a new kind of weighted time-energy performance. A comparison has been made among the optimal performances under different manipulation conditions. Three concrete examples indicate the feasibility and efficiency of this approach on optimal control of two-level quantum systems.

In this paper, optimization scheduling control problem of aluminum industrial production process were divided in four main production stages: ore proportioning, production of alumina, aluminum electrolysis and aluminum fabrication. Each production stage is abstracted for production scheduling agent by the agent technology, and built as the supply chain alliance of virtual enterprise. Through connecting the agents to mesh structure, this paper establishes system structure of the aluminum industrial production intelligent scheduling platform and develops to realize the scheduling system preliminarily.

This paper presents an approach to solve the Vehicle Scheduling Problem(VSP). Taking into the actual connectivity of paths connected to the nodes, we establish a multi-objective mathematical model based on the path length and customer waiting time. A algorithm combining the A* algorithm for path searching with the Particle Swarm Optimization(PSO) for global exploration together, is applied to the multi-objective vehicle scheduling model. Some practical problems has been solved with good results by this approach.

The model for the energy consumption problem of the aluminum industrial production is established in this paper, and the energy consumption situation out of one ton of aluminum production is calculated. The threshold cluster analysis algorithm is a method of saving energy of the producing process. However, the choice of its distance threshold is somewhat random, so further work has been done to improve the algorithm's performance, that is calculating the distance threshold with a function of the maximum distance and the minimum distance between all of the energy consumption data. Through simulation experiments and comparative analysis, the fact that the improved algorithm performs better is shown. A better reasonable input can be found faster, and the energy saving of the aluminum industrial production is much more effective.

To the prolbems in the alumina ore-burden process,such as the uncertain factors,the heavy calculations,the difficulty of obtaining an optimal scheme,and the energy waste caused by the irrational structure of production,with the minimum of energy consumption as the objective function,consider the production experience,an optimal scheduling model of unified ore-burden in sintering and Bayer process is presented.Comsidering the existence of nonlinearity,multiple constraints and multi-objective,a hybrid particle algorithm with mutation parameter is proposed to get the optimum solution.Based on the scheduling method,the optimal scheduling software in the alumina ore-burden process is desingned and exploited.The computation results show that the optimal scheduling software can offer the best alumina ore-burden scheduling scheme,the minimum energy consumption can be obtained efficiently,and the distinct effect of application is obtained.

首先从自动化专业的专业定位与学科内涵、业务培养目标与培养要求出发,分析了该专业毕业生应有的知识、能力、素质结构,进而分析了该专业教学应有的课程体系和系列课程设置。然后着重结合本校的人才培养实践和教学经验,从学科发展和教育教学规律出发,紧密围绕创新能力培养,对自动化专业课程体系中电子信息类课程特别是其硬件类课程的教学改革问题进行了探讨,提出了思考和见解。

This paper presents an approach based on hybrid particle swarm optimization to solve weapon-target assignment (WTA) problem. The mathematical model of WTA problem is explained in detail. Then the idea of basic particle swarm optimization (PSO) is introduced. A hybrid PSO algorithm (HPSO) is structured by introducing the mutation operator and changing the inertia weight with the generation. The results of simulation indicate that this approach is effective to solve WTA problem.

In this paper, a multi-agent particle swarm optimization (MPSO) based on multi-agent system (MAS) and PSO was proposed for hybrid flow-shop scheduling problem (HFSP), and a random cycle topological structure is presented related to MPSO. In MAS, every particle represents an agent, and it can cooperate and compete with the agent around and do self-learning. Using these agent interactions and the evolution mechanism of PSO, MPSO can find the global optimum more accurately. The result of simulation proved that this algorithm has a higher searching efficiency and better optimal searching performance.

Traditional research on production scheduling in aluminum industry, aimed to certain production process, simply pursued the output as the highest aim, scheduled based on experience, so that the result of scheduling cannot reach the global optimization, and cannot realize production scheduling and resource allocation with the aim of optimal energy consumption, resulting in the waste of energy. Taken the minimal sum of energy consumption in production, transport and stock as objective function and integrated with enterprise’s experiences in production, the article establishes a model of virtual enterprise’s task scheduling in aluminum industry and a hybrid distributed particle swarm optimization (PSO) algorithm is proposed to solve the problem. Finally, simulation experiment is carried out using industrial data and the result shows the optimized scheduling method has obvious optimal effect on reducing scheduling time, optimizing allocation of resources and so on, and thus the energy saving and consumption reducing purpose are obtained.

The basic energy consumption situation in 1 ton of aluminum production, is addressed in this paper for the current aluminum industry from mining to the aluminum processing. For a lot of energy data, and multi-dimensional character of the data, the threshold cluster analysis algorithm is proposed in this paper, and the classification of the energy consumption data of the aluminum industrial production is completed by using C++. After contrasting and analyzing the class hearts, and a comprehensive consideration of two factors of the smallest total energy consumption data and the maximum data number, an aimed class is found, and such class heart is used as an input to save the aluminum industrial production. Further more the feasibility and the effectiveness of the algorithm are verified.

This paper presents an approach based on constructing control Hamiltonians to steer qubit states. When three tunable control Hamiltonians are available, we can adjust the controls to transform two-level quantum systems from an arbitrary initial pure state to another arbitrary target pure state along the unique geodesic curve on Block sphere. In terms of a kind of time-energy performance J = ∫0tf [λ + (1 - λ)E(u(t))]dt, we discuss how to design control magnitude to minimize this performance. An example indicates the feasibility and efficiency of this approach on optimal control of two-level quantum systems.

The basic energy consumption situation in 1 ton of aluminum production is addressed in this paper for the current aluminum industry from mining to the aluminum processing. In order to save energy of the aluminum industrial production, the K-means algorithm and threshold cluster analysis algorithm from the pattern recognition are proposed, and the classification of the energy consumption data of the aluminum industrial production is completed by using C++. The two algorithms are compared in terms of minimum total energy consumption and the actual production requirements. A class is found with more data number and smaller total energy consumption data, and such class heart is used as an input to save the aluminum industrial production. Further-more the feasibility and the effectiveness of the algorithms are verified.

The basic energy situation in 1 ton of aluminum production,for the current aluminum industry from mining to electrolytic aluminum,is extracted in this paper.And a correlation analysis of the association rule mining algorithm is proposed,then the algorithm is implemented by using C language,the association rule mining of a lot of energy consumption data of the aluminum industry is completed,the most closely related variables are found,by controlling these variables to guide the energy-saving of the aluminum industrial production process.Further more the feasibility and the effectiveness of the algorithm are verified.