河北省能源消耗强度变动及因素分解

根据2005-2010年能源消费数据及相关经济数据,分析了河北省能源消耗强度的时空变化特征;运用Laspeyres指数及其分解模型将河北省能源消耗强度的影响因素分解为结构因素和效率因素。结果表明:研究期内河北省能源消耗强度稳步下降,但空间差异较大;研究期能源消耗强度降低主要贡献因素是第二产业能源利用效率的提高;相对于效率份额,结构份额对能源消耗强度的影响很小,研究期内产业结构变动对能源消耗强度降低的总体影响是负面的。     

基础教育师资职前实训与职中研修的协同模式探讨——基于“国培计划·顶岗置换”项目的实践思考

"国培计划"中的"顶岗置换"项目是高校师范生实习与农村中小学教师脱产研修有机结合的一种新模式,是基础教育师资职前实训和职中研修协同促进模式的有效尝试。本文基于对师范生实践教学保障不足、农村中小学教师培训面临的困难等问题分析,总结了"国培计划·顶岗置换"双向协同促进机制的状况,提出了发挥区域统筹、县域主导、经费分担和双重双向担责等进一步优化完善基础教育师资职前培养和职中研修协同机制的对策建议。     

对“对口升学”考试的思考

文章简要介绍了对口升学的概况,探讨了对口招生中高校层次不平衡、中职学校过分重视对口升学以及技能考试模式存有的致命漏洞,并针对这些问题提出了相应的建议。     

Tension in In a Station of a Metro to Explore the Energy in Language

Pound’s poem In a Station of a Metro is a masterpiece of imagism. Pound once talked about the energy in language, and American scholar Allen Tate told us that the meaning of poetry is its tension. Base...     

基于Adhoc能量均衡的AODV协议改进

针对Adhoc网络中移动节点能量受限的问题,考虑节点剩余能量和节点能量消耗速率两方面因素,对AODV协议,在选路机制,hello机制几个方面作了改进,改进后的路由协议能够有效均衡负载,保护低能量节点,延长网络生存时间。     

A study on forecasting electricity production and consumption in smart cities and factories

The electrical power sector must undergo a thorough metamorphosis to achieve the ambitious targets in greenhouse gas reduction set forth in the Paris Agreement of 2015. Reducing uncertainty about demand and, in case of renewable electricity generation, supply is important for the determination of spot electricity prices. In this work we propose and evaluate a context-based technique to anticipate the electricity production and consumption in buildings. We focus on a household with photovoltaics and energy storage system. We analyze the efficiency of Markov chains, stride predictors and also their combination into a hybrid predictor in modelling the evolution of electricity production and consumption. All these methods anticipate electric power based on previous values. The main goal is to determine the best method and its optimal configuration which can be integrated into a (possibly hardware-based) intelligent energy management system. The role of such a system is to adjust and synchronize through prediction the electricity consumption and production in order to increase self-consumption, reducing thus the pressure over the power grid. The experiments performed on datasets collected from a real system show that the best evaluated predictor is the Markov chain configured with an electric power history of 100 values, a context of one electric power value and the interval size of 1.     

Continuous walking and time- and intensity-matched interval walking: Cardiometabolic demand and post-exercise enjoyment in insufficiently active,healthy adults

ABSTRACT

We compared cardiometabolic demand and post-exercise enjoyment between continuous walking (CW) and time- and intensity-matched interval walking (IW) in insufficiently active adults. Sixteen individuals (13 females and three males, age 25.3 ± 11.1 years) completed one CW and one IW session lasting 30 min in a randomised-counterbalanced design. For CW, participants walked at a mean intensity of 65–70% predicted maximum heart rate (HR_max). For IW, participants alternated between 3 min at 80% HR_max and 2 min at 50% HR_max. Expired gas was measured throughout each protocol. Participants rated post-exercise enjoyment following each protocol. Mean HR and V˙O₂ showed small positive differences in IW vs. CW (2, 95%CL 0, 4 beat.min^?1; d = 0.23, 95%CL 0.06, 0.41 and 1.4, 95%CL 1.2 ml.kg^?1.min^?1, d = 0.36, 95%CL 0.05, 0.65, respectively). There was a medium positive difference in overall kcal expenditure in IW vs. CW (25, 95%CL 7 kcal, d = 0.58, 95%CL 0.33, 0.82). Post-exercise enjoyment was moderately greater following IW vs. CW (9.1, 95%CL 1.4, 16.8 AU, d = 0.62, 95%CL 0.06, 0.90), with 75% of participants reporting IW as more enjoyable. Interval walking elicits meaningfully greater energy expenditure and is more enjoyable than CW in insufficiently active, healthy adults.     

Machine learning based system for managing energy efficiency of public sector as an approach towards smart cities

Energy efficiency of public sector is an important issue in the context of smart cities due to the fact that buildings are the largest energy consumers, especially public buildings such as educational, health, government and other public institutions that have a large usage frequency. However, recent developments of machine learning within Big Data environment have not been exploited enough in this domain. This paper aims to answer the question of how to incorporate Big Data platform and machine learning into an intelligent system for managing energy efficiency of public sector as a substantial part of the smart city concept. Deep neural networks, Rpart regression tree and Random forest with variable reduction procedures were used to create prediction models of specific energy consumption of Croatian public sector buildings. The most accurate model was produced by Random forest method, and a comparison of important predictors extracted by all three methods has been conducted. The models could be implemented in the suggested intelligent system named MERIDA which integrates Big Data collection and predictive models of energy consumption for each energy source in public buildings, and enables their synergy into a managing platform for improving energy efficiency of the public sector within Big Data environment. The paper also discusses technological requirements for developing such a platform that could be used by public administration to plan reconstruction measures of public buildings, to reduce energy consumption and cost, as well as to connect such smart public buildings as part of smart cities. Such digital transformation of energy management can increase energy efficiency of public administration, its higher quality of service and healthier environment.     

现代金融企业产权制度变革及对我国的启示

经济学从零交易费用的理想世界走向正交易费用的现实世界，获得了现实经济问题的新的解释力；有效的制度必须是一种提供信息、传递信息并且保证质量的制度，而且它能够使实现社会目标所需要信息量减少到最少并使信息成本降至最低。从现代金融企业产权制度的历史变迁，我们不难发现其发展规律，这对解决我国金融企业产权制度存在的问题是大有裨益。     

童庆炳教授课堂教学艺术之解读

本文主要从民主教学、讲授特点、课堂教学语体等三个方面对童庆炳教授课堂教学艺术进行解读.