5 research outputs found
Fortune of smart-phones by A model recommendation
No full textIn recent market, there are several cell phones available, Smart phones differ based on their Operating system. Here we are going to do a comparison between two Operating systems i.e., “IOS and ANDROID”. The comparison starts including the basic features of smart phones. The features are varying from each other. Some of them are categorical and some are numerical. According to these data, classify the smart phones using machine learning classification model. After the classification we are going to analyse which operating system-based Smartphone will be taken for further classification. A “Recommendation system”, will be designed which recommend a better smart phone to the customer. In market a lot of smart phones are available, which are of different companies but with same cost. From classification model we will find which set is more affordable with good combination of features. Further Recommendation model will help us to find which model will be the best model according to the customer requirement and budget. On the basis of customer requirement that is what are the features and price of the phone our model is going to predict which model will be more suitable and gives the solution in a form of recommendation. It will give us the exact phone, which is having all the features and also pocket friendly
FORECASTING THE TIME DELAY IN DELIVERY OF PHARMACEUTICAL PRODUCTS
No full textSupply chain management system is a centralized system which controls and plans the activities involved from production to delivery of a product. Disruption in treatment and loss of life occurs due to delay in delivery of pharmaceutical products. The objective is to do a model using Machine learning algorithms to determine: Classification to predict which product will be delayed and Regression shows how much time it will be delayed exactly. This study will use publicly available supply chain data which helps to identify primary aspect of predicting whether HIV drugs are delivered in time or not. It will then use these factors to predict how long delays are likely to be, thus allowing HIV/Supply Chain program managers to know details of the products which are going to be delayed and quantify the exact delay. and how much it will be delayed. so that they can take mitigating action to save lives and avoid additional supply chain costs. We will use Machine learning prediction model to predict which product will be delayed and regression model shows how much time it will be delayed exactly
Pravi in nepravi oziralni stavki v slovenščini
No full text The author explores the various types of relative clauses in Slovene, focusing on a construction that has traditionally been assumed to be a special type of relative clause in which there seems to be a mismatch between the number feature of the clitic pronoun and that of the relative head, e.g., Najboljši iskalec si, [RC kar smo jih imeli.]1 best-Nom.sg.masc. seeker-Nom.sg.masc. BE-2nd. sg.pres. that BE-1st.pl.pres. 3rd.pl.acc.pron have-L-participle ‘You are the best seeker that we have had (them).’ The paper illustrates how contemporary generative syntax can handle the problem of this feature mismatch, giving two possible solutions.Avtorica raziskuje raznovrstne oziralne stavke v slovenšcini s posebnim ozirom na strukturo, ki se tradicionalno obravnava kot izjemna glede na to, da je v njej neskladje med številom v naslonskem zaimku in številom v odnosnici, npr. Najboljši iskalec si, [RC kar smo jih imeli.] Razprava kaže, kako sodobna generativna skladnja lahko reši ta problem, in sicer z dvema možnima rešitvama
Pravi in nepravi oziralni stavki v slovenščini
No full textAvtorica raziskuje raznovrstne oziralne stavke v slovenšcini s posebnim ozirom na strukturo, ki se tradicionalno obravnava kot izjemna glede na to, da je v njej neskladje med številom v naslonskem
zaimku in številom v odnosnici, npr. Najboljši iskalec si, [RC kar smo jih imeli.] Razprava kaže, kako sodobna generativna skladnja lahko reši ta problem, in sicer z dvema možnima rešitvama.
The author explores the various types of relative clauses in Slovene, focusing on a construction
that has traditionally been assumed to be a special type of relative clause in which there seems to be a mismatch between the number feature of the clitic pronoun and that of the relative head, e.g., Najboljši iskalec si, [RC kar smo jih imeli.]1 best-Nom.sg.masc. seeker-Nom.sg.masc. BE-2nd.
sg.pres. that BE-1st.pl.pres. 3rd.pl.acc.pron have-L-participle ‘You are the best seeker that we have
had (them).’ The paper illustrates how contemporary generative syntax can handle the problem of this feature mismatch, giving two possible solutions
Nitric oxide prevents a pathogen-permissive granulocytic inflammation during tuberculosis
No full textFull author list omitted for brevity. For the full list of authors, see article.Nitric oxide contributes to protection from tuberculosis. It is generally assumed that this protection is due to direct inhibition of Mycobacterium tuberculosis growth, which prevents subsequent pathological inflammation. In contrast, we report that nitric oxide primarily protects mice by repressing an interleukin-1- and 12/15-lipoxygenase-dependent neutrophil recruitment cascade that promotes bacterial replication. Using M. tuberculosis mutants as indicators of the pathogen's environment, we inferred that granulocytic inflammation generates a nutrient-replete niche that supports M. tuberculosis growth. Parallel clinical studies indicate that a similar inflammatory pathway promotes tuberculosis in patients. The human 12/15-lipoxygenase orthologue, ALOX12, is expressed in cavitary tuberculosis lesions; the abundance of its products correlates with the number of airway neutrophils and bacterial burden and a genetic polymorphism that increases ALOX12 expression is associated with tuberculosis risk. These data suggest that M. tuberculosis exploits neutrophilic inflammation to preferentially replicate at sites of tissue damage that promote contagion
