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c-Axis-textured BiCuSeO thin films were grown directly on amorphous glass substrates by pulsed laser deposition. The resistivity (∼27.1 mΩ cm) of the films at room temperature was found to be much lower than those reported for polycrystalline bulk samples with the same nominal composition, and a three dimensional variable-range-hopping conduction process was suggested to govern the electrical transport properties of the films below room temperature. Moreover, detailed microstructural analysis revealed the existence of amorphous grain boundaries throughout the films, which would lead to a significant decrease of thermal conductivity. Thus, the thermoelectric performance of the present BiCuSeO thin films is expected to be greatly enhanced as compared to that of bulk samples with the same nominal composition, demonstrating the potential application in the thermoelectric thin film devices.

Nanoscale Fe3O4-Sn@CNFs was prepared by loading Fe3O4 and Sn nanoparticles onto CNFs synthesized via electrostatic spinning and subsequent thermal treatment by solvothermal reaction, and were used as anode materials for lithium-ion batteries. The prepared anode delivers an excellent reversible specific capacity of 1120 mAh·g−1 at a current density of 100 mA·g−1 at the 50th cycle. The recovery rate of the specific capacity (99%) proves the better cycle stability. Fe3O4 nanoparticles are uniformly dispersed on the surface of nanofibers with high density, effectively increasing the electrochemical reaction sites, and improving the electrochemical performance of the active material. The rate and cycling performance of the fabricated electrodes were significantly improved because of Sn and Fe3O4 loading on CNFs with high electrical conductivity and elasticity.

Microsoft's Kinect was applied as a senser for optimizing the spray path and dose.The average distance was calculated to adjust and optimize the distance of sprayers.The LWA density equation was proposed to control the spray intensity. Microsoft's Kinect system can capture the colour and depth information of a scene in real time. However, to date, there have been no known reports on the application of the Kinect system in the area of precision spray control. To obtain a relatively good spray effect, the present study integrates the advantages of colour and depth information using Microsoft's Kinect system and proposes equations for calculating the average distance between the Kinect system and a fruit tree, as well as the leaf wall area (LWA) density, to address the difficulty in estimating the dose of sprayed pesticides. First, to adjust and control the spray intensity of sprayers and the dose of sprayed pesticides, the present study proposes an equation for calculating the LWA average distance of fruit trees. The experimental results showed that the average distance was largest between the Kinect system and the bottom part or trunk of a fruit tree. A comparison with the measured distances showed that the distances calculated based on the data acquired by the Kinect system were accurate. Second, to better control the dose of sprayed pesticides, the present study proposes the concept of LWA density. Finally, the results of the experiment on peach trees, apricot trees and grapevines demonstrated that the intelligent orchard pesticide precision spray model established based on the average distance and the LWA density can improve the efficiency in spraying pesticides, reduce waste and environmental pollution, and achieve automated and precision orchard production.

We reported the epitaxial growth of c-axis-oriented Bi1−xBaxCuSeO (0 ≤ x ≤ 10%) thin films and investigated the effect of Ba doping on the structure, valence state of elements, and thermoelectric properties of the films. X-ray photoelectron spectroscopy analysis reveal that Bi3+ is partially reduced to the lower valence state after Ba doping, while Cu and Se ions still exist as + 1 and − 2 valence state, respectively. As the Ba doping content increases, both resistivity and Seebeck coefficient decrease because of the increased hole carrier concentration. A large power factor, as high as 1.24 mWm−1 K−2 at 673 K, has been achieved in the 7.5% Ba-doped BiCuSeO thin film, which is 1.5 times higher than those reported for the corresponding bulk samples. Considering that the nanoscale-thick Ba-doped films should have a very low thermal conductivity, high ZT can be expected in the films. Electronic supplementary material The online version of this article (10.1186/s11671-018-2752-6) contains supplementary material, which is available to authorized users.

Figure S1. The linear dependency of Hall voltage on the external magnetic field. Figure S2. The voltage difference (ΔV) vs. temperature difference (ΔT) plot for the Seebeck coefficient measured at 340 K of the Bi0.975Ba0.025CuSeO thin film. (DOCX 90 kb)

This paper describes an approach to the use of genetic programming (GP) to multi-class object recognition problems. Rather than using the standard tree structures to represent evolved classifier programs which only produce a single output value that must be further translated into a set of class labels, this approach uses a linear structure to represent evolved programs, which use multiple target registers each for a single class. The simple error rate fitness function is refined and a new fitness function is introduced to approximate the true feature space of an object recognition problem. This approach is examined and compared with the tree based GP on three data sets providing object recognition problems of increasing difficulty. The results show that this approach outperforms the standard tree based GP approach on all the tasks investigated here and that the programs evolved by this approach are easier to interpret. The investigation into the extra target registers and program length results in heuristic guidelines for initially setting system parameters.

Welding is a complex process including of physics, conducting heat, metallurgy, mechanics. There are some cracks, air holes and residual stress in the parts after welding, which will reduce welding strength and welding quality. Though there are many methods to relif residual stress, it is a difficult problem about how to improve it. In the article, it uses the software ANSYS to simulate muti-welding seam process of flat, knows temperature field and residual stress field in the parts after welding, so we can know some parameters such as area of hammerhead, peening temperature, peening force, and the peening frequency and control them to redcue residual stress, then optimize welding parameters, improve welding quality of the parts.

This paper describes an approach to the use of neural networks for improving the scientific paper classification performance. On the basis of the initial classification results obtained from the content-based naive Bayes method, this approach uses neural networks to model the citation link structures of the scientific papers for refining the class labels of the documents. The approach is examined and compared with the naive Bayes method on a standard paper classification data set with increasing training set sizes. The results suggest that using citation link structures, neural networks can significantly improve the system performance over the content-based naive Bayes method for all the training set sizes

This paper describes an approach to the use of citation links to improve the scientific paper classification performance. In this approach, we develop two refinement functions, a linear label refinement (LLR) and a probabilistic label refinement (PLR), to model the citation link structures of the scientific papers for refining the class labels of the documents obtained by the content-based Naive Bayes classification method. The approach with the two new refinement models is examined and compared with the content-based Naive Bayes method on a standard paper classification data set with increasing training set sizes. The results suggest that both refinement models can significantly improve the system performance over the content-based method for all the training set sizes and that PLR is better than LLR when the training examples are sufficient.

This paper describes an approach to the refinement of a fitness function and the optimisation of training data in genetic programming for object detection particularly object localisation problems. The approach is examined and compared with an existing fitness function on three object detection problems of increasing difficulty. The results suggest that the new fitness function outperforms the old one by producing far fewer false alarms and spending much less training time and that some particular types of training examples contain most of the useful information for object detection.

The composite thin-film IR image detector consists of pyroelectric, LCD and electronic information processing technique. It can reproduce thermal image directly under the condition of uncooled, room temperature. The pyroelectric film signal charge amplifier and LCDs are its mainly components. It is respectively composed of PVDF (or PVDF- TGS, PVDF-PZT) film, TFT and LC film. The device properties parameter are relatively high level, D* approximately 108cmHz1/2w-1, NEP approximately 10-9 W and NETD approximately 10-1 K. The four units is a IR signal detector and to make a foundation for 32 X 32 units and above of multiunits plane array. It is a novel, convenient thermal detecting device and possesses a quite prospects of development and application.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.