Performance Comparison of CRUD Operations in IoT based Big Data Computing

Nowadays, due to the development of mobile devices, the kinds of data that are generated are becoming diverse, and the amount is becoming huge. The vast amount of data generated in this way is called big data. Big data must be processed in a different way than existing data processing methods. Representative methods of big data processing are RDBMS (Relational Database System) and NoSQL method. We compare NoSQL and RDBMS, which are representative database systems. In this paper, we use MySQL query and MongoDB query to compare RDBMS and NoSQL. We gradually compare the performance of CRUD operations in MySQL and MongoDB by increasing the amount of data. MongoDB sets index and compares it again.  Through result of these operations is to choose a database system that fits the situation.  This makes it possible to design and analyse big data more efficiently.

Detecting Variability in Massive Astronomical Time-series Data. II. Variable Candidates in the Northern Sky Variability Survey

We present variability analysis of data from the Northern Sky Variability Survey (NSVS). Using the clustering method, which defines variable candidates as outliers from large clusters, we cluster 16,189,040 light curves having data points at more than 15 epochs as variable and non-variable candidates in 638 NSVS fields. Variable candidates are selected depending on how strongly they are separated from the largest cluster and how rarely they are grouped together in eight-dimensional space spanned by variability indices. All NSVS light curves are also cross-correlated with IRAS , AKARI, Two Micron All Sky Survey, Sloan Digital Sky Survey (SDSS), and GALEX objects, as well as known objects in the SIMBAD database. The variability analysis and cross-correlation results are provided in a public online database, which can be used to select interesting objects for further investigation. Adopting conservative selection criteria for variable candidates, we find about 1.8 million light curves as possible variable candidates in the NSVS data, corresponding to about 10% of our entire NSVS sample. Multi-wavelength colors help us find specific types of variability among the variable candidates. Moreover, we also use morphological classification from other surveys such as SDSS to suppress spurious cases caused by blending objects or extended sources due to the low angular resolution of the NSVS.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98631/1/1538-3881_143_3_65.pd

The EPOCH Project: I. Periodic variable stars in the EROS-2 LMC database

The EPOCH (EROS-2 periodic variable star classification using machine learning) project aims to detect periodic variable stars in the EROS-2 light curve database. In this paper, we present the first result of the classification of periodic variable stars in the EROS-2 LMC database. To classify these variables, we first built a training set by compiling known variables in the Large Magellanic Cloud area from the OGLE and MACHO surveys. We crossmatched these variables with the EROS-2 sources and extracted 22 variability features from 28 392 light curves of the corresponding EROS-2 sources. We then used the random forest method to classify the EROS-2 sources in the training set. We designed the model to separate not only $\delta$ Scuti stars, RR Lyraes, Cepheids, eclipsing binaries, and long-period variables, the superclasses, but also their subclasses, such as RRab, RRc, RRd, and RRe for RR Lyraes, and similarly for the other variable types. The model trained using only the superclasses shows 99% recall and precision, while the model trained on all subclasses shows 87% recall and precision. We applied the trained model to the entire EROS-2 LMC database, which contains about 29 million sources, and found 117 234 periodic variable candidates. Out of these 117 234 periodic variables, 55 285 have not been discovered by either OGLE or MACHO variability studies. This set comprises 1 906 $\delta$ Scuti stars, 6 607 RR Lyraes, 638 Cepheids, 178 Type II Cepheids, 34 562 eclipsing binaries, and 11 394 long-period variables. A catalog of these EROS-2 LMC periodic variable stars will be available online at http://stardb.yonsei.ac.kr and at the CDS website (http://vizier.u-strasbg.fr/viz-bin/VizieR).Comment: 18 pages, 20 figures, suggseted language-editing by the A&A editorial office is applie

SREBP and MDT-15 protect C. elegans from glucose-induced accelerated aging by preventing accumulation of saturated fat

Glucose-rich diets shorten the life spans of various organisms. However, the metabolic processes involved in this phenomenon remain unknown. Here, we show that sterol regulatory element-binding protein (SREBP) and mediator-15 (MDT-15) prevent the life-shortening effects of a glucose-rich diet by regulating fat-converting processes in Caenorhabditis elegans. Up-regulation of the SREBP/MDT-15 transcription factor complex was necessary and sufficient for alleviating the life-shortening effect of a glucose-rich diet. Glucose feeding induced key enzymes that convert saturated fatty acids (SFAs) to unsaturated fatty acids (UFAs), which are regulated by SREBP and MDT-15. Furthermore, SREBP/MDT-15 reduced the levels of SFAs and moderated glucose toxicity on life span. Our study may help to develop strategies against elevated blood glucose and free fatty acids, which cause glucolipotoxicity in diabetic patients.112217Ysciescopu

Mediastinal lymphoma in a young Turkish Angora cat

An 8-month old intact male Turkish Angora cat was referred to the Veterinary Medical Teaching Hospital (VMTH), Seoul National University, for an evaluation of anorexia and severe dyspnea. The thoracic radiographs revealed significant pleural effusion. A cytology evaluation of the pleural fluid strongly suggested a lymphoma containing variable sized lymphocytes with frequent mitotic figures and prominent nucleoli. The feline leukemia virus and feline immunodeficiency virus tests were negative. The cat was euthanized at his owner's request and a necropsy was performed. A mass was detected on the mediastinum and lung lobes. A histopathology evaluation confirmed the mass to be a lymphoma. Immunohistochemistry revealed the mass to be CD3 positive. In conclusion, the cat was diagnosed as a T-cell mediastinal lymphoma

Critical heat flux enhancement in flow boiling of Al 2O 3 and SiC nanofluids under low pressure and low flow conditions

Critical heat flux (CHF) is the thermal limit of a phenomenon in which a phase change occurs during heating (such as bubbles forming on a metal surface used to heat water), which suddenly decreases the heat transfer efficiency, thus causing localized overheating of the heating surface. The enhancement of CHF can increase the safety margins and allow operation at higher heat fluxes; thus, it can increase the economy. A very interesting characteristic of nanofluids is their ability to significantly enhance the CHF. Nanofluids are nanotechnology-based colloidal dispersions engineered through the stable suspension of nanoparticles. All experiments were performed in round tubes with an inner diameter of 0.01041 m and a length of 0.5 m under low pressure and low flow (LPLF) conditions at a fixed inlet temperature using water, 0.01 vol.% Al2O3/water nanofluid, and SiC/water nanofluid. It was found that the CHF of the nanofluids was enhanced and the CHF of the SiC/water nanofluid was more enhanced than that of the Al2O3/water nanofluid.close6