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Phase change materials (PCMs) are attracting significant attentions in research and application, categorized into mainly three types, that is, organic (O), inorganic (IO) and eutectic (E). This section introduces the experimental and numerical investigations conducted in recent decades, mainly focused on the properties enhancement of PCMs and the performance improvement of its application in latent heat storage (LHS) units, as well as the evaluation and optimization of LHS units. It was concluded that lots of contribution have been made to PCMs and LHS units analysis. However, there is still some weakness in research, such as the lackness of detailed and systematic research on properties, the nonuniform standard on testing method as well as the contradictory conclusions. The most evaluation of LHS units is based on energy, instead of exergy, entropy and entransy. There is another issue that most of the research is based on numerical analysis, while less experimental research is conducted, especially in the case of LHS unit.

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In engineering, the highest operating head of the pumping station is usually controlled to be slightly lower than the lowest saddle bottom head of the axial-flow pump. However, in the practical operation, it is found that the highest operating head of the pumping station is obviously lower than the saddle bottom head of the pump device, which leads to the reduction of the operating range of the pumping station. To investigate the difference of lowest saddle bottom head between axial flow pump and axial flow pump device and apply it correctly, the energy performance tests of the TJ04-ZL-06 hydraulic model and its corresponding pump device were carried out to obtain the external curves, and numerical simulation was carried out to analyze and compare the internal flow field and pressure distribution. The results show that when the flow rate decreases, the first saddle-shaped region of the axial-flow pump and the saddle-shaped region of the pump device are caused by the decrease of the lift coefficient due to the increase of the attack angle between flow and blade. When the flow rate is less than 0.32Qd, the influence range of backflow in the inlet pipe is large, which leads to the high-pressure zone near the wall of the inlet pressure measurement section during the pump performance test, and hence the second saddle-shaped region of the axial-flow pump is essentially a measurement illusion. It is suggested that the inlet pressure measurement section should be set at least 4Dp away from the inlet flange of the impeller when testing the performance of the axial-flow pump under the condition of small flow rate, and the first saddle bottom head of the axial-flow pump or the saddle bottom head of the corresponding pump device can be considered as the control value of the highest head of the pumping station.

Tracking serves as a means to prepare data for pose estimation and action recognition. The CONDENSATION algorithm is a conditional density propagation method for motion tracking. This algorithm combines factored sampling with learned dynamic models to propagate an entire probability distributes for object position and shape over time. It can accomplish highly robust tracking of object motion. However, it usually requires a large number of samples to ensure a fair maximum likelihood estimation of the current state. In this paper, we use the mutation and crossover operators of the genetic algorithm to find appropriate samples. With this approach, we are able to improve robustness, accuracy and flexibility in CONDENSATION for visual tracking.

Aiming at the complex and diverse agricultural information resources, the article proposes a kind of intelligent and scientific agricultural economic analysis method and tool combining the various information technologies, which can improve the level of modern agricultural information management. A universal and compatible counties agricultural economic intelligent decision-making system based on GIS and knowledge is constructed to characterize and analyze agricultural economic spatial and temporal distribution of counties, which introduces multiple agricultural economic analyzing models combining the quantitative analysis of agricultural economic monitoring subsystem with the qualitative analysis of knowledge subsystem. The system utilizes C#.NET as development platform, and the secondary development technology of GIS that helps in the design of the agricultural economic intelligent decision support system, which provides efficient decision support for agricultural economic management sectors.