COMS: Customer Oriented Migration Service

Virtual machine live migration has been studied for more than a decade, and this technique has been implemented in various commercial hypervisors. However, currently in the cloud environment, virtual machine migration is initiated by system administrators. Cloud customers have no say on this: They can not initiate a migration, and they do not even know whether or not their virtual machines have been migrated. In this paper, we propose the COMS framework, which is short for Customer Oriented Migration Service . COMS gives more control to cloud customers so that migration becomes a service option and customers are more aware of the migration process. We have implemented a suite of modules in our COMS framework. Our evaluation results show that these modules could either bring performance benefit to cloud customers, or mitigate security threats in the cloud environment

Rapid thermally processed hierarchical titania-based hollow fibres with tunable physicochemical and photocatalytic properties

A series of photocatalytic TiO2–carbon composite hollow fibres (HFs) was prepared in this study by a wet-dry phase inversion spinning method followed by a rapid thermal processing (RTP). The RTP method consists of two stages: (1) calcination at 800 °C for 15 min encased in a quartz tube followed by (2) a short open heating exposure at 800 °C for 0 to 7.5 min in air. The innovative two-stage RTP method led to a time saving of more than 90%. Results revealed that the pyrolysis conditions during the second stage of HF fabrication were essential to the final physical and chemical properties of resultant TiO2-carbon HFs, such as TiO2 crystallinity and carbon content, mechanical, textural and electronic properties, as well as photocatalytic reactivity. The best results show that HFs pyrolysed for a short duration (< 2 min) in the second stage produced a high microporous surface area of 217.8 m2·g−1, a good mechanical strength of 11 MPa and a TiO2 anatase-to-rutile (A/R) ratio of 1.534 on the HF surface. The HFs also achieved a 68% degradation of acid orange 7 dye with a kapp of 0.0147 min−1 based on a Langmuir-Hinshelwood model during the photocatalysis under UV light. Thus, this work provides a new synthesis protocol with significant time and cost savings to produce high-quality HFs for wastewater treatment

Fault diagnosis method using support vector machine with improved complex system genetic algorithm

The idea of dimensional raising and linearization in support vector machine (SVM) provides a new solution for the diagnosis problem of reciprocating compressor in which the spatial distribution of fault data is complex. The selection of parameters in SVM has significant influence on the diagnosis performance. The excellent global searching ability of genetic algorithm (GA) makes itself suitable to optimize the parameters of SVM. However, GA needs many generations and longer training time which results in the low efficiency of diagnosis. To address this issue, a new fault diagnosis method ICSGA-SVM is proposed in this paper. ICSGA-SVM adopts the improved complex system genetic algorithm (ICSGA) to optimize the parameter in SVM. The complex system genetic algorithm (CSGA) applies the features of self-adaption and self-organization in complex system theory to the redesign of GA. According to the characteristics of the data set in reciprocating compressor, an adaptive mutation operator is created to replace the original mutation operator in CSGA. Besides, the gene floating operator in CSGA is removed in ICSGA to further improve the efficiency of the algorithm on-chip run. The simulation results on the fault data of reciprocating compressor indicate that our algorithm reduce the training time by 20.7 % when increasing diagnosis accuracy compared with the diagnosis method of SVM with GA (GA-SVM)

The Application of Driver Models in the Safety Assessment of Autonomous Vehicles: A Survey

Driver models play a vital role in developing and verifying autonomous vehicles (AVs). Previously, they are mainly applied in traffic flow simulation to model realistic driver behavior. With the development of AVs, driver models attract much attention again due to their potential contributions to AV certification. The simulation-based testing method is considered an effective measure to accelerate AV testing due to its safe and efficient characteristics. Nonetheless, realistic driver models are prerequisites for valid simulation results. Additionally, an AV is assumed to be at least as safe as a careful and competent driver. Therefore, driver models are inevitable for AV safety assessment. However, no comparison or discussion of driver models is available regarding their utility to AVs in the last five years despite their necessities in the release of AVs. This motivates us to present a comprehensive survey of driver models in the paper and compare their applicability. Requirements for driver models in terms of their application to AV safety assessment are discussed. A summary of driver models for simulation-based testing and AV certification is provided. Evaluation metrics are defined to compare their strength and weakness. Finally, an architecture for a careful and competent driver model is proposed. Challenges and future work are elaborated. This study gives related researchers especially regulators an overview and helps them to define appropriate driver models for AVs