Misusability Measure Based Sanitization of Big Data for Privacy Preserving MapReduce Programming

Leakage and misuse of sensitive data is a challenging problem to enterprises. It has become more serious problem with the advent of cloud and big data. The rationale behind this is the increase in outsourcing of data to public cloud and publishing data for wider visibility. Therefore Privacy Preserving Data Publishing (PPDP), Privacy Preserving Data Mining (PPDM) and Privacy Preserving Distributed Data Mining (PPDM) are crucial in the contemporary era. PPDP and PPDM can protect privacy at data and process levels respectively. Therefore, with big data privacy to data became indispensable due to the fact that data is stored and processed in semi-trusted environment. In this paper we proposed a comprehensive methodology for effective sanitization of data based on misusability measure for preserving privacy to get rid of data leakage and misuse. We followed a hybrid approach that caters to the needs of privacy preserving MapReduce programming. We proposed an algorithm known as Misusability Measure-Based Privacy serving Algorithm (MMPP) which considers level of misusability prior to choosing and application of appropriate sanitization on big data. Our empirical study with Amazon EC2 and EMR revealed that the proposed methodology is useful in realizing privacy preserving Map Reduce programming

Business intelligence analytics using sentiment analysis-a survey

Sentiment analysis (SA) is the study and analysis of sentiments, appraisals and impressions by people about entities, person, happening, topics and services. SA uses text analysis techniques and natural language processing methods to locate and extract information from big data. As most of the people are networked themselves through social websites, they use to express their sentiments through these websites.These sentiments are proved fruitful to an individual, business, government for making decisions. The impressions posted on different available sources are being used by organization to know the market mood about the services they are providing. Analyzing huge moods expressed with different features, style have raised challenge for users. This paper focuses on understanding the fundamentals of sentiment analysis, the techniques used for sentiment extraction and analysis. These techniques are then compared for accuracy, advantages and limitations. Based on the accuracy for expexted approach, we may use the suitable technique

Business recommendation based on collaborative filtering and feature engineering – aproposed approach

Business decisions for any service or product depend on sentiments by people. We get these sentiments or rating on social websites like twitter, kaggle.  The mood of people towards any event, service and product are expressed in these sentiments or rating. The text of sentiment contains different linguistic features of sentence. A sentiment sentence also contains other features which are playing a vital role in deciding the polarity of sentiments. If features selection is proper one can extract better sentiments for decision making. A directed preprocessing will feed filtered input to any machine learning approach. Feature based collaborative filtering can be used for better sentiment analysis. Better use of parts of speech (POS) followed by guided preprocessing and evaluation will minimize error for sentiment polarity and hence the better recommendation to the user for business analytics can be attained

Data Mining in Biodata Analysis

For finding interesting patterns in large databases has lot of development in recent years.. Data mining is used in many fields like medicine, securing the data etc. Whereas bio data means the data regarding the biology, medical science, DNA technology and Bioinformatics in-depth analysis. Bio Informatics is the science which can perform managing, finding data, integrating, interrupting information from biological data, genomic, and metadata. Even additional knowledge and complexness can lead to the integration among genes. This paper is all about joining these two fields, the data regarding biology us ing data mining and gives the details of future developments in biodata analysis

Comparative evaluation of organic zinc supplementation as proteinate with inorganic zinc in buffalo heifers on health and immunity

Graded Murrah buffalo heifers (18) were randomly allotted to 3 dietary groups varying in source and level of Zn supplementation in concentrate mixture to study the effect of organic (O) Zn (Zn proteinate; Zn-prot) supplementation (80 or 140 ppm) compared to inorganic Zn (I) (ZnSO4) (140 ppm) on serum biochemical parameters, antioxidant status and ovarian folliculogenesis. Mineral and biochemical constituents in serum and antioxidant enzyme activities in haemolysate were measured on 90th d of experiment. Antibody titres (log2) against Brucella abortus S19 and chicken RBC antigens was measured in serum at 7, 14, 21 and 28th d post sensitization (humoral immunity) and cell mediated immunity was assessed (120 d) by in-vivo delayed type hypersensitivity (DTH) against phytohemagglutinin-P (PHA-P). After 60 days of feeding, ovarian folliculogenesis study was made daily with ultrasound scanner in all the animals for next 60 days. Highest Zn concentration in serum without affecting the retention of other minerals (Cu, Mn and Fe) was observed with 140 ppm Zn supplementation as Zn-prot and mineral concentrations was comparable between 80 ppm Zn as Zn-prot and 140 ppm Zn as ZnSO4. Alkaline phosphatase, total protein, globulin, and glucose concentrations in serum increased with organic Zn supplementation. Organic Zn lowered lipid peroxidation (140O80O>140I) activities. Antibody titres against B. abortus and chicken RBC and in vivo DTH response improved with organic Zn supplementation. Similarly, irrespective of the dose, organic Zn supplementation significantly increased the number of large follicle with greater follicular size in ovary. The study indicated that 140 ppm Zn supplementation as Zn-prot resulted in better antioxidant status, immune response and folliculogenesis in ovaries than inorganic source and the Zn supplementation could be reduced from 140 to 80 ppm as Zn-prot without any adverse effect in buffalo heifers

Burkholderia pseudomallei in soil and natural water bodies in rural Sri Lanka: A hidden threat to public health

Burkholderia pseudomallei is the causative agent of the potentially fatal infection, melioidosis. This study provides the first evidence for the presence of B. pseudomallei in soil and water in Sri Lanka. Targeted sampling of soil and natural water sources was done between November 2019 and October 2020 over eight field visits encompassing the neighborhood of 28 culture and/or antibody-positive melioidosis patients in northwestern, western and southern Sri Lanka. A total of eight environmental isolates of B. pseudomallei (BPs-env1 to BPs-env8) were cultured from 116 soil and 117 natural water samples collected from 72 locations. The presence of B. pseudomallei in soil and natural water in these areas poses a risk of melioidosis for populations cultivating crops in such soils and using untreated water from these sources for drinking, bathing, and other domestic purposes. Identifying sites positive for B. pseudomallei may help to mitigate risk by raising public awareness of contaminated environmental sources and allowing soil and water remediation

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Bridging conventional and molecular genetics of sorghum insect resistance

Sustainable production of sorghum, Sorghum bicolor (L.) Moench, depends on effective control of insect pests as they continue to compete with humans for the sorghum crop. Insect pests are a major constraint in sorghum production, and nearly 150 insect species are serious pests of this crop worldwide and cause more than 9% loss annually. Annual losses due to insect pests in sorghum have been estimated to be $1,089 million in the semiarid tropics (ICRISAT Annual report 1991. International Crop Research Institute for Semi-arid Tropics. Patancheru, Andhra Pradesh, India, 1992), but differing in magnitude on a regional basis. Key insect pests in the USA include the greenbug, Schizaphis graminum (Rondani); sorghum midge, Stenodiplosis sorghicola (Coquillett); and various caterpillars in the Southern areas. For example, damage by greenbug to sorghum is estimated to cost US producers$248 million annually. The major insect pests of sorghum on a global basis are the greenbug, sorghum midge, sorghum shoot fly (Atherigona soccata Rond.), stem borers (Chilo partellus Swin. and Busseola fusca Fuller), and armyworms (Mythimna separata Walk and Spodoptera frugiperda J.E. Smith). Recent advances in sorghum genetics, genomics, and breeding have led to development of some cutting-edge molecular technologies that are complementary to genetic improvement of this crop for insect pest management. Genome sequencing and genome mapping have accelerated the pace of gene discovery in sorghum..

Combined searches for the production of supersymmetric top quark partners in proton-proton collisions at root s=13 TeV

A combination of searches for top squark pair production using proton-proton collision data at a center-of-mass energy of 13 TeV at the CERN LHC, corresponding to an integrated luminosity of 137 fb(-1) collected by the CMS experiment, is presented. Signatures with at least 2 jets and large missing transverse momentum are categorized into events with 0, 1, or 2 leptons. New results for regions of parameter space where the kinematical properties of top squark pair production and top quark pair production are very similar are presented. Depending on themodel, the combined result excludes a top squarkmass up to 1325 GeV for amassless neutralino, and a neutralinomass up to 700 GeV for a top squarkmass of 1150 GeV. Top squarks with masses from 145 to 295 GeV, for neutralino masses from 0 to 100 GeV, with a mass difference between the top squark and the neutralino in a window of 30 GeV around the mass of the top quark, are excluded for the first time with CMS data. The results of theses searches are also interpreted in an alternative signal model of dark matter production via a spin-0 mediator in association with a top quark pair. Upper limits are set on the cross section for mediator particle masses of up to 420 GeV