Methods of analysis modified size exchange chromatography method for analysis of heavy oil residues

A modified size exchange chromatography method is used to obtain molecular weight distributions, average molecular weight, and other characteristics of heavy oil residues: coal asphalt, petroleum asphalt, vacuum residue oil, and ethylene residue oil. This method can be applied for developing and studying processes involved in hydrogenation of heavy oil residues, road asphalt production, and coal liquefaction.     

Design and development of an innovative individualized adaptive and intelligent e-learning system for teaching–learning of probability unit: Details of UZWEBMAT

In this study, an innovative adaptive and intelligent web based e-learning system, UZWEBMAT (Turkish abbreviation of Adaptive and INtelligent WEB based MAThematics teaching–learning system) was designed, developed and implemented. This e-learning system was intended for learning and teaching secondary school level permutation-combination-binomial expansion and probability subjects. Content which was prepared according to Turkish curriculum for secondary school mathematics course was transformed into learning objects in three different ways in accordance with VAK (Visual–Auditory–Kinesthetic) learning styles. Primary/secondary/tertiary learning styles of learners registering the system are determined and each learner receives the content appropriate for his/her dominant learning style. Also, they can be directed to contents of other styles according to their performances thanks to an expert system. Learning objects constituting the content were prepared according to constructivist approach. An active role for the learner was the purpose. Tips and intelligent solution supports within the learning objects were presented with expert system support to the learners. With this structure, UZWEBMAT bears the characteristics of intelligent tutoring system as well as an adaptive e-learning environment. All the movements of learners studying with UZWEBMAT are recorded and the necessary information is reported to both learners and teachers in a visualized way.     

Robust orientation control of multi‐DOF cell based on uncertainty and disturbance estimation

Multiple degrees‐of‐freedom (multi‐DOF) cell orientation control is a vital important technique involved in single cell surgery applications. Currently, few studies have been performed toward automation of multi‐DOF cell orientation control using robotically controlled optical tweezers. In this paper, a robust control framework is developed to perform multi‐DOF cell rotational control with consideration of model uncertainties and external disturbances. Both simulation and experimental studies are presented to illustrate the performance of the proposed control strategy. The main contributions of this work lie in that this is the first time to develop a unified framework to achieve multi‐DOF cell orientation control without the need for accurate dynamic model parameters and/or any knowledge about uncertainty characteristic, which greatly enhances the robustness of the overall system.     

Machine learning based optimized live virtual machine migration over WAN links

Live virtual machine migration is one of the most promising features of data center virtualization technology. Numerous strategies have been proposed for live migration of virtual machines on local area networks. These strategies work perfectly in their respective domains with negligible downtime. However, these techniques are not suitable to handle live migration over wide area networks and results in significant downtime. In this paper we have proposed a Machine Learning based Downtime Optimization (MLDO) approach which is an adaptive live migration approach based on predictive mechanisms that reduces downtime during live migration over wide area networks for standard workloads. The main contribution of our work is to employ machine learning methods to reduce downtime. Machine learning methods are also used to introduce automated learning into the predictive model and adaptive threshold levels. We compare our proposed approach with existing strategies in terms of downtime observed during the migration process and have observed improvements in downtime of up to 15 %.     

Strained fermented milks – A review of existing legislative provisions,survey of nutritional labelling of commercial products in selected markets and terminology of products in some selected countries

A survey of the information contained in the labels of 109 commercial concentrated fermented milks from the Eastern Mediterranean, Australasia, the United Kingdom, Ireland, the United States of America and Canada plus Skyr (from Iceland), Ymer (from Denmark) and Chakka (from India) was carried out in late 2012 and early 2013. There were substantial differences in composition. The carbohydrate, fat and protein contents ranged between 1–12, 0–20 and 3.3–11 g/100 g, respectively. Considering the compositional data of the product and existing legislative provisions, a typical strained product should have a protein content of ≥8 g/100 and ~5 g/100 g of carbohydrates, and it would be appropriate to name such products as ‘strained yoghurt’, ‘Greek strained yoghurt’ and/or ‘Labneh’. A higher content of carbohydrate would suggest that the product was made using the product formulation method (i.e. without straining the fermentate), or the milk base had been fortified with skimmed milk before straining the fermentate to enhance the yield of the product, and such products should be known, for example, as ‘Greek‐style yoghurt’. It was also observed in some of the samples that the nomenclature of the starter cultures did not conform to recommendations of the International Union of Microbiological Societies (IUMS). Manufacturers could address such issues to minimise consumer confusion.     

A comprehensive review on theoretical framework‐based electric vehicle consumer adoption research

Green vehicles, such as electric vehicles (EVs), are getting noteworthy popularity among consumers worldwide. The purpose of this paper is to establish EVs as a feasible long‐term solution for the future of technology in the vehicle industry, which can decrease the current dependency on fossil fuels and also decrease greenhouse gas (GHG) emissions. As a part of long‐term benefits, the adoption of EVs gives environmentally friendly innovation to society. Despite positive environmental implications, the total number of EVs in usage is still inadequate. One of the major causes of this insubstantial adoption of EVs is largely dependent on the perceptions of consumers regarding EVs. However, this particular research study offers an inclusive outline on the existing hurdles for consumer adoption of EVs as well as a framework of the theoretical standpoints that were developed for the adoption behaviour, in addition to considering consumer intentions in the direction of EVs. In this particular study, the researcher found that the literature regarding EV adoption tried to address only the diffusion method of EVs. Whereas this study highlights consumer innovations, which provides a wide insight on consumer emotions to overlook the major aspect in consumer EVs' adoption research. The theme of this particular literature can be implemented in order to better understand the consumers' emotions and behaviour towards the adoption of EVs. The scholars further stated that there is a possible cause for more recent developments within the technological adoption part that can assist to be a standard for upcoming developments. For the last few years, knowledge regarding the problems surrounding the adoption and diffusion of EVs has gained less attention. This study expands this line of research by focusing on making a chance for developing the theoretical frameworks in terms of adding emotions in a psychological perspective where consumer behaviour and ethics are considered. Copyright © 2016 John Wiley & Sons, Ltd.     

工艺参数设置和厚度对电子束熔融加工Ti-6Al-4V合金微观结构的影响

研究了试件尺寸和工艺参数(电子束强度,扫描速度,焦点偏移量和扫描长度)对电子束熔融(EBM)加工Ti-6Al-4V合金微观结构的影响。结果表明,可以观察到EBM加工的Ti-6Al-4V合金的微观结构由原始β相的柱状晶粒组成。在柱状晶粒内部观察到典型的(α+β)结构,即魏氏体α片和在细小的α晶粒的界面上形成的杆状β相。还发现沿原始β柱状晶粒的晶界形成的α层晶界。随着试件厚度、电子束能量密度和扫描长度的增加,先前的β柱状晶粒的直径增大,并且生长的方向与加工方向一致。同时,柱状晶粒直径随着试件高度的增加而减小。随着试件厚度和电子束能量密度的增加,α片会变得更粗大。