Layered performance modelling and evaluation for cloud topic detection and tracking based big data applications

“Big Data” best characterized by its three features namely “Variety”, “Volume” and “Velocity” is revolutionizing nearly every aspect of our lives ranging from enterprises to consumers, from science to government. A fourth characteristic namely “value” is delivered via the use of smart data analytics over Big Data. One such Big Data Analytics application considered in this thesis is Topic Detection and Tracking (TDT). The characteristics of Big Data brings with it unprecedented challenges such as too large for traditional devices to process and store (volume), too fast for traditional methods to scale (velocity), and heterogeneous data (variety). In recent times, cloud computing has emerged as a practical and technical solution for processing big data. However, while deploying Big data analytics applications such as TDT in cloud (called cloud-based TDT), the challenge is to cost-effectively orchestrate and provision Cloud resources to meet performance Service Level Agreements (SLAs). Although there exist limited work on performance modeling of cloud-based TDT applications none of these methods can be directly applied to guarantee the performance SLA of cloud-based TDT applications. For instance, current literature lacks a systematic, reliable and accurate methodology to measure, predict and finally guarantee performances of TDT applications. Furthermore, existing performance models fail to consider the end-to-end complexity of TDT applications and focus only on the individual processing components (e.g. map reduce). To tackle this challenge, in this thesis, we develop a layered performance model of cloud-based TDT applications that take into account big data characteristics, the data and event flow across myriad cloud software and hardware resources and diverse SLA considerations. In particular, we propose and develop models to capture in detail with great accuracy, the factors having a pivotal role in performances of cloud-based TDT applications and identify ways in which these factors affect the performance and determine the dependencies between the factors. Further, we have developed models to predict the performance of cloud-based TDT applications under uncertainty conditions imposed by Big Data characteristics. The model developed in this thesis is aimed to be generic allowing its application to other cloud-based data analytics applications. We have demonstrated the feasibility, efficiency, validity and prediction accuracy of the proposed models via experimental evaluations using a real-world Flu detection use-case on Apache Hadoop Map Reduce, HDFS and Mahout Frameworks

City Data Fusion: Sensor Data Fusion in the Internet of Things

Internet of Things (IoT) has gained substantial attention recently and play a significant role in smart city application deployments. A number of such smart city applications depend on sensor fusion capabilities in the cloud from diverse data sources. We introduce the concept of IoT and present in detail ten different parameters that govern our sensor data fusion evaluation framework. We then evaluate the current state-of-the art in sensor data fusion against our sensor data fusion framework. Our main goal is to examine and survey different sensor data fusion research efforts based on our evaluation framework. The major open research issues related to sensor data fusion are also presented.Comment: Accepted to be published in International Journal of Distributed Systems and Technologies (IJDST), 201

One-step synthesis of Pt@three-dimensional graphene composite hydrogel: an efficient recyclable catalyst for reduction of 4-nitrophenol

A Pt@three-dimensional graphene (Pt@3DG) composite hydrogel with a unique porous nanostructure was prepared and used as an efficient, recyclable and robust catalyst for the reduction of 4-nitrophenol to 4-aminophenol under mild conditions. The influence of graphene architecture on catalytic activities was comparatively investigated by loading the same amount of Pt on reduced graphene oxide. Pt@3DG exhibits a very high catalytic activity owing to the three-dimensional macroporous framework with high specific surface area, numerous activation sites and efficient transport pathways. Moreover, catalyst separation can be easily achieved by simple filtration, and the catalyst can be reused for at least five runs, maintaining its high catalytic activity

Long Noncoding RNA HOTTIP Serves as an Independent Predictive Biomarker for the Prognosis of Patients with Clear Cell Renal Cell Carcinoma

Several studies have indicated that HOXA transcript at the distal tip (HOTTIP) play important roles in the tumorigenesis and development of various cancers. We aim to investigate the expression and prognostic value of HOTTIP in clear cell renal cell carcinoma (ccRCC). A systematic review of PubMed, Embase, Medline, and Web of Science databases was performed to select eligible literatures relevant to the correlation between HOTTIP expression and clinical outcome of different cancers. The association between the HOTTIP level and overall survival (OS), lymph node metastasis (LNM), or clinical stage was subsequently analyzed. Survival analyses were performed in a large cohort of more than 500 patients with ccRCC from The Cancer Genome Atlas (TCGA) using bioinformatic methods. Seventeen studies with a total of 1594 patients with thirteen kinds of carcinomas were included in this analysis. The result showed that high HOTTIP expression could predict worse outcome in cancer patients, with the pooled hazard ratio (HR) of 2.34 (95% confidence interval (CI) 1.96–2.79, p<0.0001). The result also showed that elevated HOTTIP expression was correlated with more LNM (OR=2.61, 95% CI 1.91-3.58, p<0.0001) and advanced clinical stage (OR=3.57, 95% CI 2.58-4.93, p<0.0001). We further validated that ccRCC patients with higher HOTTIP expression tend to have unsatisfactory outcomes both in the entire TCGA dataset and different clinical stratums, like age, grade, and stage. The tumor of those patients was associated with a larger size, easier to metastasis, advanced clinical stage, and a higher pathological grade. These findings suggested that increased HOTTIP expression might act as a novel prognostic marker for ccRCC patients

Thermal Sensitivity of Birefringence in Polarization-Maintaining Hollow-Core Photonic Bandgap Fibers

Polarization-maintaining (PM) fiber is the core sensitive component of a fiber optic gyroscope (FOG); its birefringence temperature stability is crucial for maintaining accuracy. Here, we systematically investigated the structural thermal deformation and the resulting birefringence variation in typical PM hollow-core photonic bandgap fibers (HC-PBGFs) for FOG according to varying fiber structure parameters. To verify the application potential of PM HC-PBGFs in FOG, we compared the thermal sensitivity of birefringence (TSB) with that of the commonly used Panda PM fiber, which was tested to 5.07 × 10−5/100 °C. For rhombic-core fibers, the TSB was determined by the structure of the cladding and could be tuned as low as low as 10−7/100 °C, two orders of magnitude smaller than that of the panda PM fibers. For hexagonal-core fibers, the birefringence variation depended mainly on the drift of the surface modes (SMs) caused by the deformation of the core. A slight drift in SMs could cause a dramatic birefringence variation in hexagonal-core fiber, and the TSB could be as high as 10−4/100 °C, much higher than that of panda PM fiber. This study lays the foundation for the development of high birefringence temperature-stable HC-PBGFs and their applications in FOG

Thermal Sensitivity of Birefringence in Polarization-Maintaining Hollow-Core Photonic Bandgap Fibers

Polarization-maintaining (PM) fiber is the core sensitive component of a fiber optic gyroscope (FOG); its birefringence temperature stability is crucial for maintaining accuracy. Here, we systematically investigated the structural thermal deformation and the resulting birefringence variation in typical PM hollow-core photonic bandgap fibers (HC-PBGFs) for FOG according to varying fiber structure parameters. To verify the application potential of PM HC-PBGFs in FOG, we compared the thermal sensitivity of birefringence (TSB) with that of the commonly used Panda PM fiber, which was tested to 5.07 &times; 10&minus;5/100 &deg;C. For rhombic-core fibers, the TSB was determined by the structure of the cladding and could be tuned as low as low as 10&minus;7/100 &deg;C, two orders of magnitude smaller than that of the panda PM fibers. For hexagonal-core fibers, the birefringence variation depended mainly on the drift of the surface modes (SMs) caused by the deformation of the core. A slight drift in SMs could cause a dramatic birefringence variation in hexagonal-core fiber, and the TSB could be as high as 10&minus;4/100 &deg;C, much higher than that of panda PM fiber. This study lays the foundation for the development of high birefringence temperature-stable HC-PBGFs and their applications in FOG

Human Lysozyme Synergistically Enhances Bactericidal Dynamics and Lowers the Resistant Mutant Prevention Concentration for Metronidazole to Helicobacter pylori by Increasing Cell Permeability

Metronidazole (MNZ) is an effective agent that has been employed to eradicate Helicobacter pylori (H. pylori). The emergence of broad MNZ resistance in H. pylori has affected the efficacy of this therapeutic agent. The concentration of MNZ, especially the mutant prevention concentration (MPC), plays an important role in selecting or enriching resistant mutants and regulating therapeutic effects. A strategy to reduce the MPC that can not only effectively treat H. pylori but also prevent resistance mutations is needed. H. pylori is highly resistant to lysozyme. Lysozyme possesses a hydrolytic bacterial cell wall peptidoglycan and a cationic dependent mode. These effects can increase the permeability of bacterial cells and promote antibiotic absorption into bacterial cells. In this study, human lysozyme (hLYS) was used to probe its effects on the integrity of the H. pylori outer and inner membranes using as fluorescent probe hydrophobic 1-N-phenyl-naphthylamine (NPN) and the release of aspartate aminotransferase. Further studies using a propidium iodide staining method assessed whether hLYS could increase cell permeability and promote cell absorption. Finally, we determined the effects of hLYS on the bactericidal dynamics and MPC of MNZ in H. pylori. Our findings indicate that hLYS could dramatically increase cell permeability, reduce the MPC of MNZ for H. pylori, and enhance its bactericidal dynamic activity, demonstrating that hLYS could reduce the probability of MNZ inducing resistance mutations