计及Spark和属性权重的售电套餐推荐方法

针对电力市场用户群庞大，交易过程中售电套餐选择困难的问题，在Spark环境下设计了一种售电套餐推荐方法，同时也解决了售电套餐推荐过程中在大数据环境下的可扩展性及实时性问题。首先，计算出每个套餐属性的权重值，从而计算得到售电套餐综合相似度。然后，计及用户和套餐两方面提出一种售电套餐推荐方法，实现售电套餐的精准推荐。实验表明，提出的推荐方法能够明显提高推荐的准确度，并且在分布式环境下具有良好的推荐效率和可扩展性。     

基于多尺度双线性卷积神经网络的多角度下车型精细识别

针对多角度下车辆出现一定的尺度变化和形变导致很难被准确识别的问题，提出基于多尺度双线性卷积神经网络（MS-B-CNN）的车型精细识别模型。首先，对双线性卷积神经网络（B-CNN）算法进行改进，提出MS-B-CNN算法对不同卷积层的特征进行了多尺度融合，以提高特征表达能力；此外，还采用基于中心损失函数与Softmax损失函数联合学习的策略，在Softmax损失函数基础上分别对训练集每个类别在特征空间维护一个类中心，在训练过程中新增加样本时，网络会约束样本的分类中心距离，以提高多角度情况下的车型识别的能力。实验结果显示，该车型识别模型在CompCars数据集上的正确率达到了93.63%，验证了模型在多角度情况下的准确性和鲁棒性。     

Constructing developable surfaces by wrapping cones and cylinders

We model developable surfaces by wrapping a planar figure around cones and cylinders. Complicated developables can be constructed by successive mappings using cones and cylinders of different sizes and shapes. We also propose an intuitive control mechanism, which allows a user to select an arbitrary point on the planar figure and move it to a new position. Numerical techniques are then used to find a cone or cylinder that produces the required mapping. Several examples demonstrate the effectiveness of our technique.     

An energy-saving nonlinear position control strategy for electro-hydraulic servo systems

The electro-hydraulic servo system (EHSS) demonstrates numerous advantages in size and performance compared to other actuation methods. Oftentimes, its utilization in industrial and machinery settings is limited by its inferior efficiency. In this paper, a nonlinear backstepping control algorithm with an energy-saving approach is proposed for position control in the EHSS. To achieve improved efficiency, two control valves including a proportional directional valve (PDV) and a proportional relief valve (PRV) are used to achieve the control objectives. To design the control algorithm, the state space model equations of the system are transformed to their normal form and the control law through the PDV is designed using a backstepping approach for position tracking. Then, another nonlinear set of laws is derived to achieve energy-saving through the PRV input. This control design method, based on the normal form representation, imposes internal dynamics on the closed-loop system. The stability of the internal dynamics is analyzed in special cases of operation. Experimental results verify that both tracking and energy-saving objectives are satisfied for the closed-loop system.     

Supply chain planning and scheduling integration using Lagrangian decomposition in a knowledge management environment

The integration of planning and scheduling decisions in rigorous mathematical models usually results in large scale problems. In order to tackle the problem complexity, decomposition techniques based on duality and information flows between a master and a set of subproblems are widely applied. In this sense, ontologies improve information sharing and communication in enterprises and can even represent holistic mathematical models facilitating the use of analytic tools and providing higher flexibility for model building. In this work, we exploit this ontologies’ capability to address the optimal integration of planning and scheduling using a Lagrangian decomposition approach. Scheduling/planning sub-problems are created for each facility/supply chain entity and their dual solution information is shared by means of the ontological framework. Two case studies based on a STN representation of supply chain planning and scheduling models are presented to emphasize the advantages and limitations of the proposed approach.     

Analysis of nitrogen oxide emissions from modern vehicles using hydrogen or other natural and synthetic fuels in combustion chamber

The paper presents a calculated analysis of the equilibrium emission of nitrogen oxides on the exhaust of carburetor and diesel internal combustion engines. The temperature of fuel oxidation is assumed to be 1,400 °C while the pressure for carburetor and diesel engines is assumed to be 60 atm and 80 atm respectively. The studies have been carried out for natural and synthetic fuels such as hydrogen, ethanol, methanol, petroleum, diesel fuel and methane at the excess air coefficient corresponding to the fuel oxidation temperature of 1,400 °C. In the paper, the method for calculating the equilibrium composition based on the equilibrium constant and mass conservation equations has been applied. It is shown that with an increase in pressure from 1 atm to 60 atm for carburetor engines and up to 80 atm for diesel engines, the reaction of nitrogen dioxide formation may shift towards an increase in NO₂. The formation of NO may be not affected by the increase in pressure by virtue of the fact that the reaction proceeds without changes in the amount. It has been determined that NO is the major atmospheric pollutant. However, it would be advisable to use more extensively the fuels characterized by the lowest output of nitrogen dioxide (methane and methanol), since nitrogen dioxide (NO₂) related to the 2nd hazard class is appeared to be the most dangerous to humans. It has been revealed that the reduction in oxidation temperature using hydrogen as a fuel for electrochemical current generators may allow reducing nitrogen oxide emissions by more than an order of magnitude as compared to the best results for ICE.     

Large variation in periphyton δ13C and δ15N values in the upper Great Lakes: Correlates and implications

Stable isotope ratios of carbon (δ¹³C) and nitrogen (δ¹⁵N) are frequently used to examine food web structure. Despite periphyton's importance to lake food webs, little is known about spatial variation of periphyton δ¹³C and δ¹⁵N values in the Great Lakes. We present periphyton δ¹³C and δ¹⁵N values from 28 sites the upper Great Lakes, including Lake Superior, the north shore of Lake Michigan, and Green Bay. We also examined variation in periphyton isotope values relative to several water quality parameters (TP, TN, TKN, NO₃⁻, K_d) as well as periphyton C:N. There was a large range in both periphyton δ¹³C (range = 13.5‰) and δ¹⁵N (range = 10.2‰) among sites. Periphyton in more eutrophic sites had more depleted δ¹³C and more enriched δ¹⁵N compared to more oligotrophic sites. Our finding of high variability in periphyton isotope values in the Upper Great Lakes has implications for stable isotope-based reconstructions of food web structure.