混合动态系统SPN的可达性分析

根据混合动态系统SPN(StochasticPetriNets)模型的运行规则,给出了几种典型结构(串行结构、并行结构、冲突结构)中变迁的可激发以及可激发成功概率的计算方法,在此基础上,计算出托肯沿几种基本路径(简单串行路径、简单并行路径、简单Fork/Join路径)从起始库所到达终止库所的可达概率,同时从宏观状态的角度构建了该SPN模型的状态可达树,通过可达树可以判断状态间的可达性并计算可达概率。     

关于“四色方柱”的初步构思与理论探讨

本文探讨了“四色方柱”的着色及其叠列方法。     

基于伪ID码的树型防碰撞算法

树型防碰撞算法在标签数目过多的情况下,由于树的深度过深导致标签识别效率低.为此,提出一种基于伪ID码的树型防碰撞算法.阅读器利用标签数量预测算法,检测出识别范围内未识别标签的大致数量并发给其标签.标签根据数量随机生成一个数字,作为自己的伪ID码.阅读器依次查询伪ID码,若发生碰撞,则利用碰撞跟踪树算法进行识别,在识别标签的过程中通过伪ID码降低查询树的深度,提高标签的识别效率.理论分析和仿真结果表明,与CTT算法和QT算法相比,该算法吞吐率分别提高了15%和74%,并且能够有效加快标签的识别速度,减少时隙总数.     

Explaining variation in front gardens between suburbs of Hobart, Tasmania, Australia

This paper determines the relationships between the dependent variables, presence of trees in front garden and front garden type, and socio-economic, environmental and demographic variables, at the suburb scale in Hobart, Tasmania, Australia. Garden type, largely following a pre-existing classification, and the presence/absence of trees, were recorded from 50 randomly located front gardens in each of 31 suburbs. The suburbs were classified into four groups on the basis of their spectrum of garden types and the percentage frequency of trees. Group one consisted of coastal suburbs of relatively high socio-economic status. Group 2 consisted of suburbs of moderate socio-economic status. Group 3 consisted of the poorest suburbs. The fourth group was composed of suburbs of high socio-economic status, located close to the centre of the city in hilly terrain. All except the rarest garden type occurred in all four groups of suburbs. Multiple regression and general linear models were used to predict tree presence, and the prevalence of particular garden types at the suburb level. Household income was the best predictor of the percentage frequency of trees in front gardens. The variables that appeared in models for garden types were: the percentage of the population with tertiary education (four instances); percentage of population older than 65 years (4); household income (3); percentage of households renting dwellings (3); altitude (3), rainfall (3); unemployment rate (2); percentage of population born in Australia (2); percentage of medium-sized gardens (2); suburb age (1); percentage of workforce in professional and managerial occupations (1). The 12 garden types that could be modelled responded individualistically to these independent variables.     

Self-regulating supply–demand systems

Supply–demand systems in Smart City sectors such as energy, transportation, telecommunication, are subject of unprecedented technological transformations by the Internet of Things. Usually, supply–demand systems involve actors that produce and consume resources, e.g. energy, and they are regulated such that supply meets demand, or demand meets available supply. Mismatches of supply and demand may increase operational costs, can cause catastrophic damage in infrastructure, for instance power blackouts, and may even lead to social unrest and security threats. Long-term, operationally offline and top-down regulatory decision-making by governmental officers, policy makers or system operators may turn out to be ineffective for matching supply–demand under new dynamics and opportunities that Internet of Things technologies bring to supply–demand systems, for instance, interactive cyber–physical systems and software agents running locally in physical assets to monitor and apply automated control actions in real-time. e.g. power flow redistributions by smart transformers to improve the Smart Grid reliability. Existing work on online regulatory mechanisms of matching supply–demand either focuses on game-theoretic solutions with assumptions that cannot be easily met in real-world systems or assume centralized management entities and local access to global information. This paper contributes a generic decentralized self-regulatory framework, which, in contrast to related work, is shaped around standardized control system concepts and Internet of Things technologies for an easier adoption and applicability. The framework involves a decentralized combinatorial optimization mechanism that matches supply–demand under different regulatory scenarios. An evaluation methodology, integrated within this framework, is introduced that allows the systematic assessment of optimality and system constraints, resulting in more informative and meaningful comparisons of self-regulatory settings. Evidence using real-world datasets of energy supply–demand systems confirms the effectiveness and applicability of the self-regulatory framework. It is shown that a higher informational diversity in the options, from which agents make local selections, results in a higher system-wide performance. Several strategies with which agents make selections come along with measurable performance trade-offs creating a vast potential for online adjustments incentivized by utilities, system operators and policy makers.     

凝固模拟热物性参数数据库系统的研究与开发

针对凝固模拟中热物性参数数据量大、种类多,数据查找困难、更新不便的问题,研究开发了一套热物性参数数据库系统.系统包括参数录入、数据更新、数据查询和液固相线温度计算模块,实现了对参数数据的集中有效管理.