Event-triggered variable horizon Supervisory Predictive control of hybrid power plants

The supervision of a hybrid power plant, including solar panels, a gas microturbine and a storage unit operating under varying solar power profiles is considered. The Economic Supervisory Predictive controller assigns the power references to the controlled subsystems of the hybrid cell using a financial criterion. A prediction of the renewable sources power is embedded into the supervisor. Results deteriorate when the solar power is unsteady, owing to the inaccuracy of the predictions for a long-range horizon of 10 s. The receding horizon is switched between an upper and a lower value according to the amplitude of the solar power trend. Theoretical results show the relevance of horizon switching, according to a tradeoff between performance and prediction accuracy. Experimental results, obtained in a Hardware In the Loop (HIL) framework, show the relevance of the variable horizon approach. Power amplifiers allow us to simulate virtual components, such as a gas microturbine, and to blend their powers with that of real devices (storage unit, real solar panels). In this case, fuel savings, reaching 15%, obtained under unsteady operating conditions lead to a better overall performance of the hybrid cell. The overall savings obtained in the experiments amount to 12%.     

Utilizing sensor data to model students’ creativity in a digital environment

While creativity is essential for developing students’ broad expertise in Science, Technology, Engineering, and Math (STEM) fields, many students struggle with various aspects of being creative. Digital technologies have the unique opportunity to support the creative process by (1) recognizing elements of students’ creativity, such as when creativity is lacking (modeling step), and (2) providing tailored scaffolding based on that information (intervention step). However, to date little work exists on either of these aspects. Here, we focus on the modeling step. Specifically, we explore the utility of various sensing devices, including an eye tracker, a skin conductance bracelet, and an EEG sensor, for modeling creativity during an educational activity, namely geometry proof generation. We found reliable differences in sensor features characterizing low vs. high creativity students. We then applied machine learning to build classifiers that achieved good accuracy in distinguishing these two student groups, providing evidence that sensor features are valuable for modeling creativity.     

Sanitary legislation governing Food Services in Brazil

The Technical Regulation of Good Practices for Brazilian Food Services (Regulamento Técnico de Boas Práticas para Serviços de Alimentação do Brasil) can be complemented by sanitary surveillance agencies at the state, district and municipal levels by tailoring it to location-specific requirements. The purpose of the present study was to survey sanitary legislation governing Brazilian Food Services. During the period from November 2011 to November 2012, a survey was conducted with the sanitary surveillance agencies from the various states, capitals and the Federal District. A previously prepared and tested tool was used for data collection, comprising 10 questions. Only 10 (19.2%) of the sanitary codes had been established prior to RDC Resolution n° 216/2004 and were not complementary. Of the legislation cited as complementary, only the states of Santa Catarina, Rio Grande do Sul and São Paulo and the capital of the state of São Paulo truly presented additional and location-specific aspects. No legislation that was specific to hospital kitchens was found. The majority of participating coordination, including the Evaluation List for Good Practices in Food Services, was also verified; however, it had not been published. In conclusion, a gap in sanitary surveillance services exists, which was caused by the lack of location-specific food service regulations.     

Artificial bee colony based algorithm for maximum power point tracking (MPPT) for PV systems operating under partial shaded conditions

Artificial bee colony (ABC) algorithm has several characteristics that make it more attractive than other bio-inspired methods. Particularly, it is simple, it uses fewer control parameters and its convergence is independent of the initial conditions. In this paper, a novel artificial bee colony based maximum power point tracking algorithm (MPPT) is proposed. The developed algorithm, does not allow only overcoming the common drawback of the conventional MPPT methods, but it gives a simple and a robust MPPT scheme. A co-simulation methodology, combining Matlab/Simulink™ and Cadence/Pspice™, is used to verify the effectiveness of the proposed method and compare its performance, under dynamic weather conditions, with that of the Particle Swarm Optimization (PSO) based MPPT algorithm. Moreover, a laboratory setup has been realized and used to experimentally validate the proposed ABC-based MPPT algorithm. Simulation and experimental results have shown the satisfactory performance of the proposed approach.     

Understanding value creation in closed loop supply chains – Past findings and future directions

The topic of value creation through the recovery of returned products in closed loop supply chains is scattered across various bodies of literature. We undertake a systematic literature review of 144 articles in relevant green, reverse and closed loop supply chain literature to synchronize existing knowledge on value creation. Value manifestations of four types of value, namely economic, environmental, information and customer value, are identified. Value adding concepts from the forward- and reverse supply chain may leverage the process of value creation. They are classified into six subclasses, namely partnerships and collaboration, product design characteristics, service concepts, IT solutions, supply chain processes and organizational characteristics. We present a conceptual framework on a strategic level. In this way companies can create competitive advantages by closing the loop. The results of the literature analysis suggest avenues for future research on the operational and strategic level.     

移动通信系统中功率控制研究

在阐述功率控制在移动通信系统中的发展过程的基础上，着重研究了WCDMA系统的功率控制，最后对功率控制未来的研究方向做了简要的分析。     

2.4GHz动态CMOS分频器的设计

对现阶段的主流高速CMOS分频器进行分析和比较,在此基础上设计一种采用TSPC(truesingle phase clock)和E-TSPC(extended TSPC)技术的前置双模分频器电路.该分频器大大提高了工作频率,采用0.6μm CMOS工艺参数进行仿真的结果表明,在5V电源电压下,最高频率达到3GHz,功耗仅为8mW.     

基于服务器端会话追踪的Web查询服务的研究

在探讨了Web查询服务的典型模型后,论文阐述了服务器端会话追踪机制的实现方式,设计了基于服务器端会话追踪的Web查询服务的典型解决方案。该设计方案可以较为安全地保存和维护客户的上下文信息,可靠地跟踪用户查询所处的状态,有效地实现有状态的Web查询服务。     

以一种新的距离度量作为反馈的相关跟踪方法

基于相关的模板匹配方法在图像跟踪中得到了广泛的应用,但是这种方法的主要缺点是对图像噪声非常敏感,而且由这种方法得出的相关曲面比较平坦。为了有效抑制噪声和局部遮挡对图像的影响,提出用鲁棒统计中的一个值代替相关值作为距离度量。它不是计算两幅图像的对应像素差值,而是计算两幅图像中差别不大的对应像素对的个数。实验证明这样得到的曲面相对　　收稿日期:2003 08 31;　修订日期:2003 10 28作者简介:张桂林(1944 ),男,天津人,教授,博士生导师,主要研究方向为自动识别、人体生物统计特征识别、图像处理算法与系统性能评估等。　　　　　　　要尖锐得多。当上述的距离度量应用于跟踪过程中时,模板的合理更新对跟踪非常重要。基于上述的距离度量方法,提出了一种新的模板更新策略。利用两幅图像中近似像素在整修匹配模板像素中所占的比例大小决定加权系数。这种加权策略可以自适应地根据图像序列的变化选择更新相关模板,同时在一定程度上减小模板漂移的危险。     

用DSP实现多目标实时跟踪

介绍了在 TMS3 2 0 C62 0 3上实现 4个目标的快速跟踪技术。为了提高实时性和精确度 ,采用线性汇编优化实现。1个 3 2 0× 160主窗口的 DSP平均处理时间为 2 m s,3个 60× 60副窗口的 DSP平均处理时间各为 0 .4ms,实现了复杂背景下低对比度目标的快速跟踪。实验结果证明跟踪效果良好 ,解决了以前窗口开不大、跟踪速度慢的问题