Tunable structure and intensive upconversion photoluminescence for Ho3+-Yb3+ codoped bismuth titanate composite synthesized by sol-gel-combustion (SGC) method

Ho³⁺ and Yb³⁺ codoped bismuth titanate (BTO) composite powders with infrared to visible upconversion luminescence (UCL) function were prepared by SGC method. The effects of Ho³⁺ and Yb³⁺ doping content on the structure and property were investigated for BTO: xHo, 0.2 Yb (x = 0, 0.02, 0.04, 0.06, 0.08, 0.1) and BTO: 0.02Ho, yYb (y = 0.1, 0.2, 0.3, 0.5, 0.7, 0.9) samples. All the samples include three bismuth titanate phases (Bi₄Ti₃O₁₂, Bi₂Ti₂O₇, and Bi₂₀TiO₃₂), and the phase proportion can be tuned by changing Ho³⁺ and Yb³⁺ doping content. These powders are well crystalized with honeycomb-like microscopic structure, and with good absorption for 233 nm, 310 nm and 975 nm wavelength. The band gap can be tuned from 3.53 eV to 4.03 eV when increasing Yb³⁺ content from y = 0 to y = 0.9. A strong 530–580 nm green emission band and a relative weak 630–690 nm red one corresponding to Ho³⁺: ⁵S₂ → ⁵I₈ and ⁵F₅ → ⁵I₈ transitions appear in the UCL spectra for all the BTO: Ho, Yb samples when pumped at 980 nm. The emission intensities can well be tuned with various Ho³⁺ and Yb³⁺ content. The optimal UCL was obtained in BTO: 0.02Ho, 0.5 Yb for all the prepared samples. The energy transfer mechanism is analyzed by building a two-photon energy transfer model, which is proved by the relationship between emission intensities and pumping power measurement. The concentration quenching of Ho³⁺ is caused by cross relaxation of CR₁ and CR₂ (Ho: ⁵F₄, ⁵S₂ + ⁵I₈ → ⁵I₄ + ⁵I₇) and by CR₃ (Ho: ⁵F₄, ⁵S₂ + Yb: ²F_7/2 → Ho: ⁵I₆ + Yb: ²F_5/2) for Yb³⁺ quenching. The mean luminescence lifetime (τ_m) from Ho: ⁵S₂ decreases monotonously with the increase of Ho³⁺ and Yb³⁺ content.     

Searching and learning english translation long text information based on heterogeneous multiprocessors and data mining

Cooperation with the entire language information retrieval aims to develop intelligent models that use non-compliant and English. It has been constructed to construct the translation model extraction of similar Source Language Sentences Extraction (SLSE). The SLSE, by creating a new pipeline of SLSE through the establishment of the network described above, the first bilingual dictionary of the model of training data, including the Deep Neural Network (DNN) that has been proposed, because it is often in such, it is building because it plays a very important role in the model, SLSE is evaluated by people to ensure the richness of the content that has been used as training data. If the English applicable, not built from 60 gigabytes of text. Since the processing time for it when not highly structured data mining is large, it is troublesome to collect data on this scale. To shorten the processing time, data mining is implemented as a whole.     

Studies on the treatment of brilliant green solution by combination microwave induced oxidation with CoFe2O4

In this work the synergistic effects of microwave (MW) irradiation induced oxidation processes and CoFe₂O₄ were studied for the degradation of brilliant green (BG) from aqueous solutions. Under the optimum condition, the ratio of solid to liquid was 1:167 (0.3 g CoFe₂O₄ mixed with 50 mL of 20 mg L⁻¹ BG solution), MW power 600 W, and the time of the irradiation 2 min. And the decolorization rate could reach up to 100%. Further investigation showed that BG was degraded by MW-induced oxidation combined with CoFe₂O₄ surface adsorption. The CoFe₂O₄ could increase the efficiencies of MW degradation and be used repeatedly. The experimental results indicated that the method of MW degradation BG in the presence of CoFe₂O₄ could reduce reaction time and increase product yield.     

A security and authentication layer for SCADA/DCS applications

Mid 2010, a sophisticated malicious computer worm called Stuxnet targeted major ICS systems around the world causing severe damages to Siemens automation products. Stuxnet proved its ability to infect air-gapped-segregated critical computers control system. After this attack, the whole ICS industry security was thrust into spotlight. Automation suppliers have already started to re-think their business approach to cyber security. The OPC foundation have made also significant changes and improvements on its new design OPC-UA to increase security of automation applications but, what is still missing and seems to be not resolved any time soon is having security in depth for industrial automation applications. In this paper, we propose a simple but strong security control solution to be implemented as a logic level security on SCADA and DCS systems. The method presented in this work enforces message integrity to build trusts between DCS system components, but it should not be viewed as the main nor the only protection layer implemented on an industrial automation system. The proposed solution can be viewed as a low-level security procedure to avoid malicious attacks such as Stuxnet.     

Analysis on the spatial ecological distribution model of landscape plant community

Because the spatial pattern of plant communities in garden landscapes usually exhibits highly non-random distribution characteristics, the accuracy of the analysis results is not high. For this purpose, a spatial ecological distribution model of landscape landform plant communities is designed. Based on the remote sensing images of landscape plant communities, the study area was obtained. The grassland communities in this area were classified and calculated by geostatistics, and the semi variogram values of typical samples of different vegetation types were obtained. According to the calculation results, the spatial terrain factors of landscape plant community are extracted, and the annual NDVI value is taken as the ecological vitality index of landscape green vegetation, the NDVI level is divided, the spatial ecological distribution model of landscape plant community is constructed, and the evaluation index system is generated, so as to complete the spatial ecological distribution model analysis of landscape plant community. The results show that the method of this study accurately analyzes the area of coniferous and broad-leaved mixed forest, mountain meadow, road, construction land, water area land and slope grade, which is slightly different from the actual value, indicating that the method has certain reliability.     

Paradigm and performance analysis of distributed frequent itemset mining algorithms based on Mapreduce

FrequentItemsetMining (FIM) is one of the most important data mining tasks and is the foundation of many data mining tasks. In Big Data era, centralized FIM algorithms cannot meet the needs of FIM for big data in terms of time and space, so Distributed Frequent Itemset Mining (DFIM) algorithms have been designed to meet the above challenges. In this paper, LocalGlobal and RedistributionMining which are two main paradigms of DFIM algorithm are discussed; Two algorithms of these paradigms on MapReduce named LG and RM are proposed while MapReduce is a popular distributed computing model, and also the related work is discussed. The experimental results show that the RM algorithm has better performance in terms of computation and scalability of sites, and can be used as the basis for designing the DFIM algorithm based on MapReduce. This paper also discusses the main ideas of improving the DFIM algorithms based on MapReduce.     

Government ecological governance management based on heterogeneous multi-processors and dynamic image sampling

With the advent of the governance economy era, traditional government governance models face enormous challenges. Governance management is the source of power to enter the era of the knowledge economy. This is a profound change that governments have needed to implement innovative government governance models, methods of social organization, and management. Governments in many countries are now adopting the construction of e-government as a strategy and response to demonstrate their priority development competitive advantage over the international competition and the challenges of the knowledge economy that spreads around the world. Therefore, the establishment of a new model of government governance has great theoretical and practical significance for impulse and government management innovation. The Dynamic Image Classification Algorithm (DICA) system is introduced in the implementation of the image processing technology and global disaster detection proposed here, and of this dynamic image classification algorithm (DICA) of the government, sector to extract more effectively. DICA is the most important task, or it is a strong shadow, proper access to the characteristics of the disaster area, and a false impact on the impact of the disaster, overcoming false alarms. It creates patches of post-disaster aerial image data from pre-tailoring and pre-adjustment training and satellite imagery. DICA training, all patches to government-managed data modified without delay or image data extraction. Two types of proposed systems are high-speed operation and accuracy (96.6%) and detection of earth disasters.     

基于手机移动传感网络的矿震群智定位方法

为提高矿震监测系统定位精度,减少监测盲区,降低监测成本,基于分布式的思想,提出一种基于手机移动传感网络的矿震定位方法。首先以矿区附近工人及家属等使用的智能手机建立手机移动传感网络,其次对模拟震源点网格化,构建基于标准差的目标函数,提出改进的萤火虫寻优策略,并使用拐点回溯法以及手机移动传感网络排除离散点策略(EDPS)降低定位误差,最后通过矿震模拟实验进行验证。实验结果表明:在手机移动传感网络无到时误差理想情况下,所有模拟震源点都能够准确收敛至震源位置,定位误差小于1 m。但手机相较于检波器到时误差较高,且定位误差与到时误差具有相关性,当手机到时误差为?1.0～1.0 s时,传统算法定位误差为216 m,无法实现高精度定位。通过研究目标函数值与定位误差间的关系,提出并使用拐点回溯法以及EDPS两种优化方法,算法绝对定位误差降低至73 m,当到时误差为?0.2～0.2 s时,绝对定位误差降低至17 m,定位精度提高76.1%。基于手机移动传感网络的矿震群智定位方法,为矿震监测提供了一种新方法,未来可考虑与井下微震系统联合,在节省监测成本、提高定位精度方面具有重要意义。      

Preparation and Characterization of K_n|Ga(H_2O)MW_(11)O_(39)|·xH_2O

In this paper the heteropoly complexes K_n[Ga(H_20)MW_(11)O_39)]·xH_20 [M=Cu(Ⅱ), Co(Ⅱ), Cr(Ⅲ),Fe(Ⅲ), Mn(Ⅳ)] have been prepared in this laboratory firstly. The products were characterized by chemicalanalysis, ionexchange, IR, UV and X-ray powder diffraction.     

硫酸铁改性活性炭催化微波降解甲基对硫磷

在硫酸铁改性活性炭存在下，微波照射能使溶液中的甲基对硫磷迅速降解。对25、100mg／L的甲基对硫磷溶液，改性活性炭0．4g／L，微波照射3．0min，降解率达77．18％。适当提高改性活性炭加入量，同样照射时间即可达96．90％。而采用未改性活性炭甲基对硫磷降解率为93．20％。结果表明，微波照射下改性活性炭的催化活性明显高于未改性活性炭。另外，采用紫外．可见光谱和离子色谱技术探讨了微波照射时间、甲基对硫磷初始浓度和酸度、活性炭用量、改性液硫酸铁浓度和酸度对改性活性炭催化微波降解甲基对硫磷的影响。