深度学习:学习科学视阈下的最优整合

为超越认知心理学的局限,深度学习研究从狭义走向广义成为必然。复杂科学为广义深度学习研究提供了全新视角,学习科学为学习系统简化提供了合理依据,以此可重新审视深度学习的缘起、内涵、机制及过程。研究结合人工智能历史演变,指出深度学习缘起于认知心理学的重塑、课程与教学论的变革以及教育技术学的突破;基于对既有内涵的梳理,认为深度学习是学习科学视阈下对信息深度加工过程、教师深度引导过程、技术深度支持过程三者的最优整合;依托影响因素分析,点明深度学习的发生机制以知识内容为客观载体、以真实情境为客观条件、以心理机能为主观意识;从纵向优化和横向整合两个方面建立了深度学习的一般过程模型,其间三个“深度过程”和“三维机制”不断趋于最优整合,共同促进学习者深度学习。

基于共享SRM的最优供应链资源整合分析

在信息时代下,我国经济的发展形势也迎来了新的变化,而世界经济一体化和企业经济全球化,使得客户需求也产生了改变,企业与客户、供应商的关系越来越密切化和复杂化。很多企业需要与全球各地的对象展开合作,在拓展合作深度与范围的基础上也要应对其中的各种不确定因素,在这一背景下,供应商关系管理也就是SRM也成为了一项热议的话题。本文主要围绕共享SRM展开论述,探讨了基于共享云SRM的供应商关系管理及资源整合优化的有关策略。

利用“三网”融合,优化语文课堂教学

二十一世纪的今天,教育信息技术已经成为课堂教学不可缺少的一部分.教育信息技术 与语文课堂教学的整合,在提升语文课堂教学中占有一定分量的位置,增加了语文课堂 教学的主动性、形象性、实效性,使它成为文字教材的扩充,甚至提升,并可优化语文课 堂教学,使语文课堂教学更灵活化、自由化、高效化，以达到增强语文教学的整体效果.

基于深度学习的高阶思维培养模型研究

近年来高阶思维在基础教育改革中受到高度重视,而深度学习作为信息时代教学变革的必然选择,能够为学生高阶思维的培养提供支持。为此,文章首先明确了高阶思维的内涵,同时基于复杂系统理论将深度学习内涵界定为学习科学视域下的最优整合,并探讨了高阶思维和深度学习的关系。随后,文章结合对影响因素的梳理,分别提出了高阶思维的生成机制和深度学习的生成机制,并从宏观、中观、微观三个层面剖析了这两个生成机制的关系。最后,文章构建了基于深度学习的高阶思维培养模型,包括情境问题的创设、拓展方向的确立、最优整合的趋近、心理机能的升华等四个模块。此模型具有系统性、整体性特征,有助于在基础教育课程中促进学生的深度学习,从而更好地发展学生的高阶思维。

日常教学中提升中学英语写作

纵观小学至九年级英语教与学十年来,英语教学方式不断改良,学生对英语的感知也倍增。但对于农村、城镇中学生却对英语看似不陌生却很陌生的境地。特别是在写作方面,要求听、说、读、写各能力的兼溶,要求在实际教学中贯穿,要求整体思辩的思维,灵活应用所学的素材,实现由点到线到面的跨越。

A risk-based methodology for the optimal placement of hazardous gas detectors

Hazardous gas detection systems play an important role in preventing catastrophic gas-related accidents in process industries. Even though effective detection technology currently exists for hazardous gas releases and a majority of process installations have a large number of sensitive detectors in place, the actual operating performance of gas detection systems still does not meet the expected requirements. In this paper, a riskbased methodology is proposed to optimize the placement of hazardous gas detectors. The methodology includes three main steps, namely, the establishment of representative leak scenarios, computational fluid dynamics(CFD)-based gas dispersion modeling, and the establishment of an optimized solution. Based on the combination of gas leak probability and joint distribution probability of wind velocity and wind direction, a quantitative filtering approach is presented to select representative leak scenarios from all potential scenarios. The commercial code ANSYS-FLUENT is used to estimate the consequence of hazardous gas dispersions under various leak and environmental conditions. A stochastic mixed-integer linear programming formulation with the objective of minimizing the total leak risk across all representative leak scenarios is proposed, and the greedy dropping heuristic algorithm(GDHA) is used to solve the optimization model. Finally, a practical application of the methodology is performed to validate its effectiveness for the optimal design of a gas detector system in a high-sulfur natural gas purification plant in Chongqing, China. The results show that an appropriate number of gas detectors with optimal cost-effectiveness can be obtained, and the total leak risk across all potential scenarios can be substantially reduced. This methodology provides an effective approach to guide the optimal placement of pointtype gas detection systems involved with either single or mixed gas releases.

Strategic mining options optimization:Open pit mining, underground mining or both

Near-surface deposits that extend to considerable depths are often amenable to both open pit mining and/or underground mining. This paper investigates the strategy of mining options for an orebody using a Mixed Integer Linear Programming(MILP) optimization framework. The MILP formulation maximizes the Net Present Value(NPV) of the reserve when extracted with(i) open pit mining,(ii) underground mining, and(iii) concurrent open pit and underground mining. Comparatively, implementing open pit mining generates a higher NPV than underground mining. However considering the investment required for these mining options, underground mining generates a better return on investment than open pit mining. Also, in the concurrent open pit and underground mining scenario, the optimizer prefers extracting blocks using open pit mining. Although the underground mine could access ore sooner, the mining cost differential for open pit mining is more than compensated for by the discounting benefits associated with earlier underground mining.

Integration of a Gas Fired Steam Power Plant with a Total Site Utility Using a New Cogeneration Targeting Procedure

A steam power plant can work as a dual purpose plant for simultaneous production of steam and elec-trical power. In this paper we seek the optimum integration of a steam power plant as a source and a site utility sys-tem as a sink of steam and power. Estimation for the cogeneration potential prior to the design of a central utility system for site utility systems is vital to the targets for site fuel demand as well as heat and power production. In this regard, a new cogeneration targeting procedure is proposed for integration of a steam power plant and a site utility consisting of a process plant. The new methodology seeks the optimal integration based on a new cogenera-tion targeting scheme. In addition, a modified site utility grand composite curve(SUGCC) diagram is proposed and compared to the original SUGCC. A gas fired steam power plant and a process site utility is considered in a case study. The applicability of the developed procedure is tested against other design methods(STAR? and Thermoflex software) through a case study. The proposed method gives comparable results, and the targeting method is used for optimal integration of steam levels. Identifying optimal conditions of steam levels for integration is important in the design of utility systems, as the selection of steam levels in a steam power plant and site utility for integration greatly influences the potential for cogeneration and energy recovery. The integration of steam levels of the steam power plant and the site utility system in the case study demonstrates the usefulness of the method for reducing the overall energy consumption for the site.

Integrating artificial neural networks and geostatistics for optimum 3D geological block modeling in mineral reserve estimation:A case study

In this research, a method called ANNMG is presented to integrate Artificial Neural Networks and Geostatistics for optimum mineral reserve evaluation. The word ANNMG simply means Artificial Neural Network Model integrated with Geostatiscs, In this procedure, the Artificial Neural Network was trained, tested and validated using assay values obtained from exploratory drillholes. Next, the validated model was used to generalize mineral grades at known and unknown sampled locations inside the drilling region respectively. Finally, the reproduced and generalized assay values were combined and fed to geostatistics in order to develop a geological 3D block model. The regression analysis revealed that the predicted sample grades were in close proximity to the actual sample grades, The generalized grades from the ANNMG show that this process could be used to complement exploration activities thereby reducing drilling requirement. It could also be an effective mineral reserve evaluation method that could oroduce optimum block model for mine design.

Value Source of Integrated Refining/Chemical Plant

Based on an integrated refining/chemical plant processing 15 Mt/a of crude and manufacturing 1.0 Mt/a of ethylene under the guideline of＂engaging in refining, olefins and aromatics by whatever appropriate means＂ to maximize the overall value of the integrated refining/chemical plant, it is necessary to concentrate on working on the flow diagram and the solution for mutual supply of materials between the refinery and ethylene plant. After analyzing the feedstock slate, the composition and properties of products, it is proposed to optimize the integrated refming/chemical plant in order to reduce investment and operating cost to realize maximization of the value of the integrated plant.

Optimized vehicle scheduling and filling model based on effective space and integrated solving algorithm

We established an integrated and optimized model of vehicle scheduling problem and vehicle filling problem for solving an extremely complex delivery mode-multi-type vehicles, non-full loads, pickup and delivery in logistics and delivery system. The integrated and optimized model is based on our previous research result-effective space method. An integrated algorithm suitable for the integrated and optimized model was proposed and corresponding computer programs were designed to solve practical problems. The results indicates the programs can work out optimized delivery routes and concrete loading projects. The model and algorithm have many virtues and are valuable in practice.

Open cut resource optimisation as applied to coal

Pit optimisation is the earliest and most established application of its kind in the minerals industry, but this has been primarily driven by metal, not coal. Coal has the same financial drivers for resource optimisation as does the metalliferous industry, yet pit optimisation is not common practice. Why？ The following discussion presents the basics of pit optimisation as they relate to coal and illustrates how a technology developed for massive deposits is not suitable for thin, multi-seam deposits where mine planning is often driven more by product quality than by value drivers such as Net Present Value. An alternative methodology is presented that takes advantage of the data structure of bedded deposits to optimise resource recovery in terms of a production schedule that meets constraints on coal quality.

Detection of gross errors using mixed integer optimization approach in process industry

A novel mixed integer linear programming (NMILP) model for detection of gross errors is presented in this paper. Yamamura et al.(1988) designed a model for detection of gross errors and data reconciliation based on Akaike information cri- terion (AIC). But much computational cost is needed due to its combinational nature. A mixed integer linear programming (MILP) approach was performed to reduce the computational cost and enhance the robustness. But it loses the super performance of maximum likelihood estimation. To reduce the computational cost and have the merit of maximum likelihood estimation, the simultaneous data reconciliation method in an MILP framework is decomposed and replaced by an NMILP subproblem and a quadratic programming (QP) or a least squares estimation (LSE) subproblem. Simulation result of an industrial case shows the high efficiency of the method.

Analysis on the Optimization Approaches of Contemporary Piano Education System from the Perspective of Music Knowledge Integration

In this paper, we conduct analysis on the optimization approaches of contemporary piano education system from the perspective of music knowledge integration. In the process of the piano teaching, teacher and school the training of musicianship as the key point of teaching. This is because the skill can through student plays to display directly, appraises the student performance technique quality an important criterion. However, the student has the excellent adept technique merely also by far insufficient, but also needs the high artistic aesthetic ability, not only need be able to appreciate the piano performance, but must be able to reveal the artistic aesthetic feature in the process of piano performance. Piano education as one of the ways of music education, and other subjects, there is the subject of the universal education as its educational ideas, educational ideas and teaching methods, a direct impact on the generation after generation of the comprehensive quality of education. Under this basis, we propose the new idea on the issues that will be beneficial.

Integration Interval Determination and Decision Threshold Optimization for Improved TRPC-UWB Communication Systems

Integration interval and decision threshold issues were investigated for improved transmitted reference pulse cluster （iTRPC-） ultra-wideband （UWB） systems. Our analysis shows that the bit error rate （BER） performance of iTRPC-UWB systems can be significantly improved via integration interval determination （IID） and decision threshold optimization. For this purpose, two modifications can be made at the autocorrelation receiver as follows. Firstly, the liD processing is performed for autocorrelation operation to capture multi-path energy as much as possible. Secondly, adaptive decision threshold （ADT） instead of zero decision threshold （ZDT）, is used as estimated optimal decision threshold for symbol detection. Performance of iTRPCUWB systems using liD and ADT was evaluated in realistic IEEE 802.15.4a UWB channel models and the simulation results demonstrated our theoretical analysis.

Power Generation Expansion Planning Using an Interior Point with Cutting Plane （IP/CP） Method

The generation expansion planning is one of complex mixed-integer optimization problems, which involves a large number of continuous or discrete decision variables and constraints. In this paper, an interior point with cutting plane （IP/CP） method is proposed to solve the mixed-integer optimization problem of the electrical power generation expansion planning. The IP/CP method could improve the overall efficiency of the solution and reduce the computational time. Proposed method is combined with the Bender＇s decomposition technique in order to decompose the generation expansion problem into a master investment problem and a slave operational problem. The numerical example is presented to compare with the effectiveness of the proposed algorithm.

Parameters and Trajectory Overall Optimization Design of the Combined Cycle Engine Reusable Launch Vehicle

Reusable launch vehicle is an important way to realize fast,cheap and reliable space transportation.A combined cycle engine system provides a more efficient and flexible form of power.The investigation on the research status of the combined cycle engine technology,including basic principle,research programs and classification of structure is firstly discussed in this paper.Then the bilevel hierarchical and integrated parameters/trajectory overall optimization technologies are applied to improve the efficiency and effectiveness of overall vehicle design.Simulations are implemented to compare and analyze the effectiveness and adaptability of the two algorithms,in order to provide the technical reserves and beneficial references for further research on combined cycle engine reusable launch vehicles.

Integration of Theory of Constraints Thinking Process and Lean Production for Troubleshooting on a Contractor

The thinking process of TOC （Theory of Constraints） was an important consolidated tool to the systematization of the companies＇ necessities because of its competitive advantage. The lean thinking proposed by Taiichi Ohno and developed by Toyota Company has been tested and found effective in several production processes. This paper aims to propose a method of problem solving through the integration of the principles of lean thinking and the TPTOC （Thinking Process of the Theory of Constraints）. The method was implemented on a civil contractor, using the research methodology and the action research. We concluded that, after the research, the core problem regarding the company is the technical failure of the administrative staff, which causes delay in the construction works and financial loss. We also concluded that the obstacles that could prevent the achievement of objectives are related to lack of a vision from senior management regarding financial return when investing in employee training. The goal was accomplished with the integration of two philosophies, TPTOC and lean. And only the tools proposed by Fl^vio Augusto Picchi were not enough for executing the action, so new lean actions were verbalized.

Optimization and integration of LED array for uniform illumination distribution

A design method for light-emitting diode （LED） array is proposed to achieve a good uniform illumination distribution on target plane. By using random walk algorithm, the basic LED array modules are optimized ftrstly. The optimized basic arrays can generate uniform illumination distribution on their target plane. The optimized basic LED array mod- ules can be integrated into a large LED array module with more than tens of LEDs. In the large array, we can select a sub-array with K LEDs （K〉7）, which can produce the good uniform illumination distribution. By this way, we design two LED arrays which consist of 21 and 25 LEDs, respectively. The 21-LED array and 25-LED array can generate uniform illumination distributions with the uniformities of 95% and 90%, respectively.

Primary studies on integration optimization of differential steering of electric vehicle with motorized wheels based on quality engineering

The model of the differential steering system(DSS) of electric vehicle with motorized wheels and the three-degree-of-freedom dynamic model of vehicle are built.Based on these models,the concepts and quantitative expressions of steering road feel,steering portability and steering stability are proposed.Through integrating the Monte Carlo descriptive sampling,elitist non-dominated sorting genetic algorithm(NSGA-II) and Taguchi robust design method,the system parameters are optimized with steering road feel and steering portability as optimization targets,and steering stability and steering portability as constraints.The simulation results show that the system optimized based on quality engineering can improve the steering road feel,guarantee steering stability and steering portability and thus provide a theoretical basis for the design and optimization of the electric vehicle with motorized wheels system.