REST API技术及在移动通信网络管理中的应用

介绍了目前最炙手可热的REST架构风格，该风格顺应Web2.0的兴起，完美的匹配了云计算时代来临的可扩展要求，在各种应用场景中都得到了充分的表现。根据其技术特点，分析了该风格的API在移动通信网络管理中的应用，从网管系统内部、网管系统之间以及网管系统与上层APP应用之间等多方面对是否适用于REST风格以及如何在合适的位置使用REST API进行了分析。     

Coil‐Type Asymmetric Supercapacitor Electrical Cables

Cable‐shaped supercapacitors (SCs) have recently aroused significant attention due to their attractive properties such as small size, lightweight, and bendability. Current cable‐shaped SCs have symmetric device configuration. However, if an asymmetric design is used in cable‐shaped supercapacitors, they would become more attractive due to broader cell operation voltages, which results in higher energy densities. Here, a novel coil‐type asymmetric supercapacitor electrical cable (CASEC) is reported with enhanced cell operation voltage and extraordinary mechanical‐electrochemical stability. The CASECs show excellent charge–discharge profiles, extraordinary rate capability (95.4%), high energy density (0.85 mWh cm⁻³), remarkable flexibility and bendability, and superior bending cycle stability (≈93.0% after 4000 cycles at different bending states). In addition, the CASECs not only exhibit the capability to store energy but also to transmit electricity simultaneously and independently. The integrated electrical conduction and storage capability of CASECS offer many potential applications in solar energy storage and electronic gadgets.     

Augmented context-based recommendation service framework using knowledge over the Linked Open Data cloud

This research proposes ACARDS (Augmented-Context bAsed RecommenDation Service) framework that is able to utilize knowledge over the Linked Open Data (LOD) cloud to recommend context-based services to users. To improve the level of user satisfaction with the result of the recommendation, the ACARDS framework implements a novel recommendation algorithm that can utilize the knowledge over the LOD cloud. In addition, the noble algorithm is able to use new concepts like the enriched tags and the augmented tags that originate from the hashtags on the SNSs materials. These tags are utilized to recommend the most appropriate services in the user’s context, which can change dynamically. Last but not least, the ACARDS framework implements the context-based reshaping algorithm on the augmented tag cloud. In the reshaping process, the ACARDS framework can recommend the highly receptive services in the users’ context and their preferences. To evaluate the performance of the ACARDS framework, we conduct four kinds of experiments using the Instagram materials and the LOD cloud. As a result, we proved that the ACARDS framework contributes to increasing the query efficiency by reducing the search space and improving the user satisfaction on the recommended services.     

Quality and Emulsion Stability of Milk from Ettawah Crossed Bred Goat During Frozen Storage

Goat milk has specific chemical composition and physical properties. The purpose of this study was to investigate the change of milk quality and emulsion stability during 60 d frozen storage. Milk sample was taken from three Ettawah Crossedbred goats that were divided into three groups. Samples were frozen and stored for 0, 30 and 60 days. At the end of each storage periode, milk sample was thawed in the refrigerator and analyzed for total number of bacteria, chemical (acidity, pH, free fatty acids), physical (alcohol test, clot on boiling test) quality, and emulsion stability. The microbiological and chemical data were analyzed statistically using one way ANOVA, whereas physical quality and emulsion stabilty were expressed qualitatively. There were no change in the total bacteria, acidity, pH and free fatty acid (FFA) of milk during storage, whereas the assessment by 70% alcohol showed positive since 0 d. Emulsions stability changed after 30 d of storage. While, the clot on boiling (COB) test of milk was positive at 60 d of storage. Recommendation is frozen storage of goat milk should not longer than 30 d.     

A self‐scalable load injection service

Load testing of applications is an important and costly activity for software provider companies. Classical solutions are very difficult to set up statically, and their cost is prohibitive in terms of both human and hardware resources. Virtualized cloud computing platforms provide new opportunities for stressing an application's scalability, by providing a large range of flexible and less expensive (pay‐per‐use model) computation units. On the basis of these advantages, load testing solutions could be provided on demand in the cloud. This paper describes a Benchmark‐as‐a‐Service solution that automatically scales the load injection platform and facilitates its setup according to load profiles. Our approach is based on: (i) virtualization of the benchmarking platform to create self‐scaling injectors; (ii) online calibration to characterize the injector's capacity and impact on the benched application; and (iii) a provisioning solution to appropriately scale the load injection platform ahead of time. We also report experiments on a benchmark illustrating the benefits of this system in terms of cost and resource reductions. Copyright © 2013 John Wiley & Sons, Ltd.     

Development of New Product: Rambutan Pulpy Juice

This study aimed to know the effect of adding pulp in rambutan fruit juice on the characteristics of rambutan juice during storage. Research using the CRD, the treatment were kind of pulp (mandarin and rambutan) and pulp concentration (5%, 7.5%, and 10%). The results showed that the addition of pulp significantly affect the characteristics of rambutan juice (pH, vitamin C, total acid) during storage. Pulpy juice with the most prefered was addition of rambutan pulp as much as 7.5% (w/v) and the addition of citrus pulp as much as 7.5% (w/v) with the score of 3-4 (moderate like - like).     

Effect of stoichiometry and Cu-substitution on the phase structure and hydrogen storage properties of Ml-Mg-Ni-based alloys

To improve the electrochemical properties of rare-earth–Mg–Ni-based hydrogen storage alloys, the effects of stoichiometry and Cu-substitution on the phase structure and thermodynamic properties of the ...     

Changes in the physical properties of honey powder during storage

Honey powders produced by spray drying with the addition of Arabic gum and sodium caseinate were characterised in terms of the influence of storage time on the following physical properties: particle size, moisture content, water activity, bulk density, flowability and hygroscopicity. The storage affected those properties; after 12 weeks of storage, particle size decreased (except Arabic gum powder treated as a control sample), moisture content and water activity increased, hygroscopicity decreased. Changes in bulk density, particle size and moisture content caused the rise of Hausner ratio value; however, the powders were still characterised by a very good flow properties and low cohesiveness. The colour of reconstituted powders was also affected by storage; in most of samples, the darkening, reduction in redness and yellowness were observed. Colour parameters were the most stable in powders obtained with the addition of 2% w/w of sodium caseinate.     

Iron mediated cathodic electrosynthesis of hausmannite nanoparticles

A novel synthetic route has been proposed to prepare hausmannite nanoparticles. The synthetic route comprises an iron mediated constant current cathodic electrodeposition of manganite and heat treatment of the latter to obtain hausmannite. The obtained nanostructures have been characterized using X-ray Diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectrometry (EDX) and Fourier transform Infrared Spectrometry (FTIR). The role of iron in the formation of manganite precursor has been studied by cyclic voltammetry (CV) and differential thermal analysis (DTA). A formation mechanism based on iron mediated formation of Mn³⁺ and subsequent cathodic reduction of the disproportionated products has been proposed accordingly. The prepared nanoparticles exhibited specific capacitance of 143 F g⁻¹ in 0.5 M Na₂SO₄ solution. The retained specific capacity was 87% after 2000 cycles.     

基于云概率密度分布估计的大坝监测数据分析

大坝运行监测易受自然环境和监测条件影响，存在时间和空间上的变异性，监测数据具有不确定性。以云理论的随机性和不确定性分析方法为基础，并与空间数据辐射思想相结合，建立了云滴概率密度分布估计模型，然后导出云概率密度分布函数，依据样本监测数据推求母体空间数据的分布特征，并设计了基于逆向云算法云变换的计算程序。分析陆浑水库1979~1999年测压管监测数据和位移变形数据的云概率密度分布特征和云数字特征，得出了20 a来大坝的数据分布特征和运行状态。监测数据分析结果表明，云概率密度分布估计不仅能有效合理地分析大坝的运行状态，而且能够依据云数字特征来判断监测状态和监测环境的异常变化。 