A reference architecture for big data systems

Over dozens of years, applying new IT technologies into organizations has always been a big concern for business. Big data certainly is a new concept exciting business. To be able to access more data and empower to analysis big data requires new big data platforms. However, there still remains limited reference architecture for big data systems. In this paper, based on existing reference architecture of big data systems, we propose new high level abstract reference architecture and related reference architecture notations, that better express the overall architecture. The new reference architecture is verified using one existing case and an additional new use case

A Novel Structure of Rolling Piston Type Rotary Compressor

This paper presents a new design of rolling piston type rotary compressor and the analysis of the performance of the novel compressor is conducted. The concept of the novel compressor is to utilize the interior space of the roller as inner working volume. The vane is connected and fixed to the outer cylinder and the inner cylinder, and the split bush is located between the roller and the vane to help revolution of the roller. Therefore, the novel compressor has two working volumes. One is outer volume trapped within the outer cylinder, the vane, and the roller and the other is inner volume trapped within the inner cylinder, the vane, and the roller. In the same frame size, the cooling capacity of the novel compressor is increased by average 34.77% over that of the traditional rolling piston type rotary compressor. This is because the mass flow rate of the refrigerant into the compressor increases due to the increase of the total working volume. However, the input power is also increased by average 23.4% over that of the traditional rolling piston type rotary compressor. It is because the indicated work increases due to inner compression work. As a result, the energy efficiency ratio (EER) of the novel compressor is increased by 9.42% over that of the traditional rolling piston type compressor

Numerical Investigation on Effects of Sub-cooling Methods on Performance of Multi-split Variable Refrigerant Flow Systems with Bypass and Vapor Injection Techniques

The pipeline connected between outdoor units and indoor units is lengthened in the VRF systems because the VRF systems are generally used in light commercial buildings. Therefore, a sub-cooler is installed in the VRF systems to avoid flash gas caused by pressure drop and heat transfer in the liquid pipeline. Usually, the liquid refrigerant in the pipeline can be cooled by bypass and refrigerant injection techniques with an internal heat exchanger (IHX) and electric expansion valve (EEV). In this study, the performance of the VRF systems using bypass and refrigerant injection cycles are compared by numerical method. The simulation for multi-split VRF is developed with considering application of vapor injection and bypass cycle and validated with experimental data. The bypass and refrigerant injection have improvement potential for cooling capacity by 3.11% and 15.5%, respectively due to increasing enthalpy difference in evaporators. The vapor injection technique has more improvement potential of performance than bypass technique. Subcooling degree at inlet of EEV is above 10°C degree in two systems, which can avoid flash gas generation

Predictive Maintenance in Industry 4.0

In the context of Industry 4.0, the manufacturing-related processes have shifted from conventional processes within one organization to collaborative processes cross different organizations, for example, product design processes, manufacturing processes, and maintenance processes across different factories and enterprises. The development and application of the Internet of things, i.e. smart devices and sensors increases the availability and collection of diverse data. With new technologies, such as advanced data analytics and cloud computing provide new opportunities for flexible collaborations as well as effective optimizing manufacturing-related processes, e.g. predictive maintenance. Predictive maintenance provides a detailed examination of the detection, location and diagnosis of faults in related machinery using various analyses. RAMI4.0 is a framework for thinking about the various efforts that constitute Industry 4.0. It spans the entire product life cycle & value stream axis, hierarchical structure axis and functional classification axis. The Industrial Data Space (now International Data Space) is a virtual data space using standards and common governance models to facilitate the secure exchange and easy linkage of data in business ecosystems. It thereby provides a basis for creating and using smart services and innovative business processes, while at the same time ensuring digital sovereignty of data owners. This paper looks at how to support predictive maintenance in the context of Industry 4.0. Especially, applying RAMI4.0 architecture supports the predictive maintenance using the FIWARE framework, which leads to deal with data exchanging among different organizations with different security requirements as well as modularizing of related functions

Predictive Maintenance in Industry 4.0

In the context of Industry 4.0, the manufacturing-related processes have shifted from conventional processes within one organization to collaborative processes cross different organizations, for example, product design processes, manufacturing processes, and maintenance processes across different factories and enterprises. The development and application of the Internet of things, i.e. smart devices and sensors increases the availability and collection of diverse data. With new technologies, such as advanced data analytics and cloud computing provide new opportunities for flexible collaborations as well as effective optimizing manufacturing-related processes, e.g. predictive maintenance. Predictive maintenance provides a detailed examination of the detection, location and diagnosis of faults in related machinery using various analyses. RAMI4.0 is a framework for thinking about the various efforts that constitute Industry 4.0. It spans the entire product life cycle & value stream axis, hierarchical structure axis and functional classification axis. The Industrial Data Space (now International Data Space) is a virtual data space using standards and common governance models to facilitate the secure exchange and easy linkage of data in business ecosystems. It thereby provides a basis for creating and using smart services and innovative business processes, while at the same time ensuring digital sovereignty of data owners. This paper looks at how to support predictive maintenance in the context of Industry 4.0. Especially, applying RAMI4.0 architecture supports the predictive maintenance using the FIWARE framework, which leads to deal with data exchanging among different organizations with different security requirements as well as modularizing of related functions

Prevalence, virulence genes and Antimicrobial Resistance of Shiga-toxigenic E.coli in diarrhoea patients from Kitale, Kenya

Introduction: Shiga toxin-producing Escherichia coli (STEC) are among the most important causes of food-borne diseases. They cause illnesses ranging from mild diarrhea to more severe conditions that may progress to hemorrhagic colitis (HC) and hemolytic uremic syndrome (HUS). The burden of STEC in patients with diarrheal illness in Kitale county referral hospital, Trans-Nzoia County had not been established.Objectives: To determine the prevalence of STEC, its associated virulence genes and antimicrobial resistance among patients seeking treatment for diarrhoeal illness at Kitale County Referral Hospital.Methods: Stool samples from patients seeking treatment for diarrheal illness and had consented to participate in the study were collected and cultured for enteric bacteria. Suspect E.coli isolates were further identified using conventional biochemical methods. Conventional multiplex PCR targeting Shiga toxins (stx1, stx2, hlyA and attaching and effacing mechanisms (eaeA) were used to detect STEC virulence markers responsible for the Pathogenicity of STEC infection among other E.coli pathotypes.Results: A total of 295 participants were enrolled; median age 120 months (IQR: 36-312). 39 %( 115) were children aged <5yearsof whom 54% (160) were females. The prevalence of pathogenic E.coli was 19%56/295 and STEC was the most prevalent among E.coli pathotypes at5.4%16/295. The Stx2 gene and the Stx1/Stx2/hlyAcombination were the most prevalent in the STEC strains. The virulence genes (Stx1, Stx2, eaeA* and HlyA*)were observed in 13, 19, 9 and 14 in STEC isolates respectively.The most common gene was Stx2 and combinations of (Stx1+Stx2+hlyA)genes. Antimicrobial resistance to commonly prescribed antibiotics: chloramphenicol, ampicillin 10μg, erythromycin15μg, gentamicin10μg, ciprofloxacin 5μg, tetracycline 30μg, Trimethoprim/Sulfamethoxazole 25 μg, Cefotaxime 30 μg, furazolidine (8μg) and nalidixic acid 30 μg. were observed for all E.coli isolates except one (1.8%; 95% CI=0.1-9.6%). No isolates among STEC showed resistance to Furazolidine drug. However, Trimethoprim / Sulphurmethoxazole) was the drug which exhibited the highest resistance at (94%, 95% CI 70 to 99%).Conclusion and recommendation: Prevalence of STEC was 5.4%, (Stx1/Stx2/hlyA) virulence genes combination was the most common. High resistance to commonly prescribed antibiotics were observed in E.coli isolates and may be an existing problem that needs to be further research investigation.Keywords: Shiga-Toxigenic Escherichia coli (STEC), antimicrobial resistance, Kitale County referral hospitalAfr J Health Sci. 2017; 30(2):105-11

A measurement of the tau mass and the first CPT test with tau leptons

We measure the mass of the tau lepton to be 1775.1+-1.6(stat)+-1.0(syst.) MeV using tau pairs from Z0 decays. To test CPT invariance we compare the masses of the positively and negatively charged tau leptons. The relative mass difference is found to be smaller than 3.0 10^-3 at the 90% confidence level.Comment: 10 pages, 4 figures, Submitted to Phys. Letts.

First Measurement of Z/gamma* Production in Compton Scattering of Quasi-real Photons

We report the first observation of Z/gamma* production in Compton scattering of quasi-real photons. This is a subprocess of the reaction e+e- to e+e-Z/gamma*, where one of the final state electrons is undetected. Approximately 55 pb-1 of data collected in the year 1997 at an e+e- centre-of-mass energy of 183 GeV with the OPAL detector at LEP have been analysed. The Z/gamma* from Compton scattering has been detected in the hadronic decay channel. Within well defined kinematic bounds, we measure the product of cross-section and Z/gamma* branching ratio to hadrons to be (0.9+-0.3+-0.1) pb for events with a hadronic mass larger than 60 GeV, dominated by (e)eZ production. In the hadronic mass region between 5 GeV and 60 GeV, dominated by (e)egamma* production, this product is found to be (4.1+-1.6+-0.6) pb. Our results agree with the predictions of two Monte Carlo event generators, grc4f and PYTHIA.Comment: 18 pages, LaTeX, 5 eps figures included, submitted to Physics Letters