Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.     

Characterization,Mechanism and Control Measures of V Segregation in Continuous Casting Billet of C-Mn Steel

Metallurgical and Materials Transactions B - To eliminate V segregation, which significantly deteriorates the homogeneity of continuous casting steel billets, V segregation in the C-Mn steel billet...     

Microstructure and Mechanical Properties of Mg–RE–TM Cast Alloys Containing Long Period Stacking Ordered Phases: A Review

Casting magnesium alloys hold the greatest share of magnesium application products due to their short processing period, low cost and near net shape forming. Compared with conventional commercial magnesium alloys or other Mg–RE-based alloys, the novel Mg–RE–TM cast alloys with long period stacking ordered(LPSO) phases usually possess a higher strength and are promising candidates for aluminum alloy applications. Up to now, two ways: alloying design and casting process control(including subsequent heat treatments), have been predominantly employed to further improve the mechanical properties of these alloys. Alloying with other elements or ceramic particles could alter the solidifi cation pattern of alloys, change the morphology of LPSO phases and refi ne the microstructures. Diff erent casting techniques(conventional casting, rapidly solidifi cation, directional solidifi cation, etc.) introduce various microstructure characteristics, such as dendritic structure, nanocrystalline, metastable phase, anisotropy. Further heat treatments could activate the transformation of various LPSO structures and precipitation of diverse precipitates. All these evolutions exert great impacts on the mechanical properties of the LPSO-containing alloys. However, the underlying mechanisms still remain a subject of debate. Therefore, this review mainly provides the state of the art of the casting magnesium alloys research and the accompanying challenges and summarizes some topics that merit future investigation for developing high-performance Mg–RE–TM cast alloys.     

载气热提取法测定熔敷金属中扩散氢收集条件的探究

探究了GB/T 3965—2012《熔敷金属中扩散氢测定方法》中载气热提取法收集条件对测定扩散氢含量的影响,并与水银法进行了对比。研究结果表明,样本炉温设定为400℃,A型试块的内部温度大约在51 min时稳定在358℃左右,B型试块内部温度大约在27 min时稳定在391℃左右;载气热提取法电信号曲线收集结束点的电信号及斜率均接近0时获得的结果与水银法具有较好的一致性。     

Factors Affecting Web Disclosure Adoption in the Nonprofit Sector

ABSTRACT

Nonprofit organizations (NPOs) are strategically using their own personal website to present themselves to the public and share information. Despite the potential benefits of enhanced public confidence and trust, reduced operating costs, improved donor decision making, and increased donations, many nonprofit organizations have resisted the adoption of web disclosure. Informed by the literature on information systems (IS) adoption and technological innovation, this study examines the primary factors that influence the adoption and resistance of web disclosure. Our sample consisted of 176 survey responses from an initial group of 3,323 U.S. NPOs. The statistical results indicate that attitude toward disclosure, compatibility of disclosure with current practices, and financial readiness have a positive influence on web disclosure adoption. The findings have implications for research and practice.     

Poly(L-lysine)-poly(ethylene glycol) layers with different structure and their influence on silica suspension stability

The effects of the structure of di- and triblock copolymers of poly(L-lysine) – LYS with poly(ethylene glycol) – PEG as well as the length of nonionic fragment in the LYS-PEG macromolecule on the copolymer chains conformation in the adsorption layer formed on the colloidal silica (SiO2) surface were examined. Spectrophotometry and turbidimetry were applied for the determination of copolymer adsorbed amounts and stability coefficients of silica aqueous suspensions. The electrokinetic parameters such as solid surface charge density and zeta potential were also estimated. The adsorption of LYS-PEG was proved to be the highest at pH 10 whereas the lowest adsorption on the solid surface was found for the triblock copolymer with long fragments of LYS at the same pH value.     

Corrosion resistance of nanostructured magnesium hydroxide coating on magnesium alloy AZ31: influence of EDTA

A hexagonal nanosheet Mg(OH)_2 coating was prepared through a one-step hydrothermal method using LiOH solution as mineralizer and then modified by ethylenediaminetetraacetic acid(EDTA) to minimize the rapid corrosion of AZ31 Mg alloy.The performance of the coating was evaluated using electrochemical technique,hydrogen evolution measurements, nanoscratch test,Fourier-transform infrared spectroscopy(FTIR), X-ray diffraction(XRD) patterns and field-emission scanning electron microscopy(FESEM).The results suggested that the corrosion rate of bare AZ31 Mg alloys was significantly reduced by one and two orders of magnitude through the protection from Mg(OH)_2 coating and modification with EDTA(i.e., EDTA-Mg(OH)_2 coating), respectively.FESEM micrographs indicated that the modification in EDTA elicits to the formation of an EDTA-Mg(OH)_2 composite with a thickness as twice as that of as-prepared Mg(OH)_2 coating.Nanoscratch tests revealed strong adhesion between the composite or Mg(OH)_2 coating and the substrate.The study of formation and corrosion mechanisms of the coatings manifested that Mg(OH)_2 was first formed near the intermetallic compound AlMn particles and gradually covered the entire surface, wherein the AlMn particles played an important role in the coating growth process.And it also proved that EDTA accelerated the formation of Mg(OH)_2.     

The 3-dimensional morphology of dendrite during equiaxed solidification of an Al-5 wt.% Cu alloy

In a sample quenched during equiaxed solidification of an Al-5 wt.% Cu alloy, the multi-scales 3-dimensional morphology of equiaxed dendrite was observed. The slim primary stem and secondary branches constitute the frame of dendrite, and rows of dense tertiary branches further divide the 3-dimensional space. In the divided space, the quartic branches grow further. The dendritic branches,which are perpendicular to each other, can change their growth directions and coalesce into a whole. In the tertiary branches and quartic branches, the formation of double branch structures is induced by competitive growth. The branch that wins in the competitive growth will produce a cabbage-like structure by wrapping the failed branches. In addition, the side branch can also wrap the original parent branch to produce cabbage-like structures. Depending on the historical growth direction, the dendritic arms can form vein-like and spicate structures, and the shapes of single dendritic arm may be the cylinder, plate and trapezoid platform. According to the compositions and etching morphology, the single dendritic arm in the final solidification structures should coalesce from a fine porous structure. The porous structures at different length-scales are principally induced by the preferential growth. Based on 3-dimensional morphology of equiaxed dendrite, a new research object for the investigation of microsegregation was suggested.     

Regional-scale rice-yield estimation using stacked auto-encoder with climatic and MODIS data: a case study of South Korea

In South Korea, rice is the most important grain crop that it is crucial to develop yield estimation model for supporting sustainable agriculture and national food security. The main objectives of this paper are (1) to propose a Deep Learning (DL) algorithm, the Stacked Sparse Auto-encoder (SSAE), for rice-yield estimation using climatic and Moderate Resolution Imaging Spectroradiometer (MODIS) data; (2) to choose scenarios showing the best combined performance in terms of length of crop season (before and after harvest) and aggregation periods (7, 10, 15, and 30 days) of climatic data; and (3) to analyse the results in both the temporal and spatial perspectives. In this procedure, the SSAE model was built around the study objectives and compared with the artificial neural network (ANN) model for evaluation of its performance. According to the results, the combined 15-day-aggregated climatic data (between June and August) and MODIS data were selected as the optimal feature set for rice-yield estimation in the study area, Jeolla-do; the SSAE model outperformed ANN, showing root mean square error (RMSE) and RMSE% of 33.09 kg(10a)^?1 (5.21 kg(10a)^?1lower than ANN) and 6.89% (1.14% lower than ANN). Throughout the experiments, the rice-yield-estimation potentiality of a DL algorithm, namely the SSAE, was substantiated.