Query Formulation and Recommendation for Relational Databases Using User Sessions and Collaborative Filtering

Structured Query Language (SQL) has a uniform structure over different programming languages. The queries fired on Database Management System (DBMS) contain textual information along with selected segments of data parsed by data base management system to fire it as a structured query. Currently DBA needs to execute complex queries on large databases. Many times user or DBA fires similar queries on database server to get useful information. The queries which are similar to each other can then be categorized into two types a) the tuples retrieved by SQL queries are similar b) the fragment of the queries are similar. System gives recommendation to those similar queries so that it saves the time of DBA to construct it again and again. Query suggestions given to DBA or users are known as Query Recommendation. To develop a Query Recommendation system many authors suggested the use of Query Log. Query suggestions are divided into two areas mainly Collaborative Recommendations and Single Log Recommendations. This system is designed by single or collaborative log using parameter known as mixing factor. In this paper we analyzed Sql query Recommendation concepts and their uses. There are basically two types of similarity measure for Query Recommendation considered in [1] such as 1) Fragment Based 2) Tuple Based. Here in this research paper we are motivated towards generating recommendations for nested SQL queries. We adopt hierarchical classification on query log to create classes of similar queries and further to generate recommendations for SQL Query we proceed with finding matching class from which the recommendations can be modeled. DOI: 10.17762/ijritcc2321-8169.15070

Mining of Frequent Item with BSW Chunking

Apriori is an algorithm for finding the frequent patterns in transactional databases is considered as one of the most important data mining problems. Apriori algorithm is a masterpiece algorithm of association rule mining. This algorithm somehow has constraint and thus, giving the opportunity to do this research. Increased availability of the Multicore processors is forcing us to re-design algorithms and applications so as to accomplishment the computational power from multiple cores finding frequent item sets is more expensive in terms of computing resources utilization and CPU power. Thus superiority of parallel apriori algorithms effect on parallelizing the process of frequent item set find. The parallel frequent item sets mining algorithms gives the direction to solve the issue of distributing the candidates among processors. Efficient algorithm to discover frequent patterns is important in data mining research Lots of algorithms for mining association rules and their mutations are proposed on basis of Apriori algorithm, but traditional algorithms are not efficient. The objective of the Apriori Algorithm is to find associations between different sets of data. It is occasionally referred to as "Market Basket Analysis". Every several set of data has a number of items and is called a transaction. The achievement of Apriori is sets of rules that tell us how often items are contained in sets of data. In order to find more valuable rules, our basic aim is to implement apriori algorithm using multithreading approach which can utilization our system hardware power to improved algorithm is reasonable and effective, can extract more value information

Survey of Diesease Prediction on Plants with the Helps of IOT

overall climate change is a diversity in the long-term weather patterns that indicates the regions of the world. The term "weather" refers to the short-term (daily) changes in temperature, wind, and precipitation of a region.With the up-gradation in data mining and its applications, data mining is extensively used to make smarter decisions in farming.Agricultural forecasting is the science that employ knowledge in weather data relating to atmospheric environment observed by instruments on the ground and by remote sensing. Most of the data need to be processed for generating various decisions such as cropping and scheduling of irrigation.Various meteorological data like- temperature, humidity, leaf wetness duration (LWD) plays the vital roles in the growth of microorganism responsible for disease.Effective forecasting of such diseases on the basis of climate data can help the farmers to take timely actions to restrain the diseases. This can also justify the use of pesticides, which are one of the source behind land pollution. This paper illustrate the study which is useful for farmers in order to make decision if there is change occur in environment. In this study we are going to implement application which give the notification to farmers, if there is change in environment so based on that changes which disease should be affected to plant such type of notification will be generated on farmers mobile.Weather based forecasting system can be treated as a part of the Agricultural Decision Support System (ADSS) which is Knowledge Based System (KBS). IoT device that collects data regarding physical parameters, using a sophisticated microcontroller platform, from various types of sensors, through different modes of communication and then uploads the data to the Internet

DEVELOPMENT AND VALIDATION OF HPTLC METHOD FOR ESTIMATION OF VOGLIBOSE IN PHARMACEUTICAL DOSAGE FORMS

Objective: This paper describes a new, simple, precise, accurate and specific HPTLC method for estimation of voglibose as a bulk drug and in tablet dosage forms.Methods: Chromatographic separation of the drug was performed on aluminum plates pre-coated with silica gel 60 F254 as the stationary phase and a mobile phase comprising of toluene: ethyl acetate: methanol: 30% ammonia 5:4:1.5:0.2 (v/v/v/v). Densitometric quantification of voglibose was carried out at 292 nm. Voglibose was detected satisfactorily with a Rf value 0.26.Results: The accuracy and reliability of the method was assessed by evaluation of linearity (0.2-1.2 µg/spot), precision (intra-day RSD 0.6-0.9% and inter-day RSD 0.20-0.25%), accuracy (97.32-102.46%) and specificity according to ICH guidelines. Conclusion: The proposed HPTLC method is less expensive, simpler, rapid and more flexible than the reported RP-HPLC method for routine analysis of voglibose in bulk and tablet dosage forms.Â

Study of anti-nociceptive potential of physostigmine and its combination with morphine in albino rats

Background: The cholinergic drugs are having antinociceptive potential but are under investigation because of their serious side effects. It is difficult to accept them as an analgesic. This study is undertaken in the experimental animal models for the evaluation of the antinociceptive potential of Physostigmine and its combination with Morphine at their sub-analgesic doses. The objective of the study was to evaluate the antinociceptive effect of Physostigmine and its combination with subanalgesic dose of morphine and comparing their effect with analgesic dose of Morphine.Methods: Antinociceptive effect of Physostigmine in three graded doses (50, 100 & 200 µg/kg) and combination of Physostigmine at low dose (50 µg/kg) with sub-analgesic dose of Morphine (0.1 mg/kg) and Morphine in analgesic dose (1 mg/kg) was evaluated by using tail flick method in albino rats.Results: Comparison of maximal possible effect in percentage (MPE in %) between groups at 90 minutes in control, Morphine, Physostigmine in 50, 100, 200 µg/ kg doses and combination group respectively, demonstrated significant difference (p < 0.001) when compared by one way ANOVA test. There was no much increase in the tail flick latency in Physostigmine 50 µg/kg (SC) treatment at 90 min (3.08±0.15) in comparison to control (NS) treatment group. Combination treatment of low doses of both Physostigmine 50 µg/kg + Morphine 0.1 mg/kg increased the tail flick latency 90 min (7.08±0.15) in-comparison to control (NS) treatment group (3.33±0.11).Conclusions: Physostigmine is more potent antinociceptive than Morphine and Physostigmine potentiated the antinociceptive activity of low dose of standard drug Morphine

eNavigate: A Survey On Effective and Efficient User Website Navigation

Web Structure Improvement has attracted much attention now days. The large websites such as E-commerce, universities etc. have lots of pages visited by users daily. The users needed to be navigated effectively and efficiently throughout the website. Each user has its own set of target pages where the stay time is larger than that of other pages. While making website structure improvements the web master must consider the set of target pages of the users. The users’ web log must be maintained at the server side which further has to be divided into session and mini sessions. These mini sessions provides the inputs to extract the target pages of a specific user. The improvement in website must be done under some circumstances. The newly added links must satisfy some criteria such as how many number of links can be added. Previous literature provides some meaningful considerations about static and dynamic websites. The effective website structure improvements along with the set of target pages can be efficiently designed with static and informative websites while it’s difficult to consider the target pages in dynamic one. The structure optimization can be done with minimization or maximization strategies. Here in this survey paper we studied some previously published journals to get better knowledge about the web structure improvements for effective user navigation

Characterization of eDNA from the Clinical Strain Acinetobacter baumannii AIIMS 7 and Its Role in Biofilm Formation

Release of extracellular DNA (eDNA) was observed during in vitro growth of a clinical strain of Acinetobacter baumannii. Membrane vesicles (MV) of varying diameter (20–200 nm) containing DNA were found to be released by transmission electron microscopy (TEM) and atomic force microscopy (AFM). An assessment of the characteristics of the eDNA with respect to size, digestion pattern by DNase I/restriction enzymes, and PCR-sequencing, indicates a high similarity with genomic DNA. Role of eDNA in static biofilm formed on polystyrene surface was evaluated by biofilm augmentation assay using eDNA available in different preparations, for example, whole cell lysate, cell-free supernatant, MV suspension, and purified eDNA. Biofilm augmentation was seen up to 224.64%, whereas biofilm inhibition was 59.41% after DNase I treatment: confirming that eDNA facilitates biofilm formation in A. baumannii. This is the first paper elucidating the characteristics and role of eDNA in A. baumannii biofilm, which may provide new insights into its pathogenesis

Effectiveness of low dose physostigmine for dose reduction of morphine in pain management

Background: This is an interventional study, undertaken in the experimental animal models for the evaluation of the antinociceptive potential of Physostigmine and its combination with Morphine at their sub-analgesic doses. The objective of the study was to evaluate the antinociceptive potential of Physostigmine alone and in combination with morphine.Methods: Antinociceptive effect of Physostigmine in three graded doses (50, 100 and 200 μg/kg) and combination of Physostigmine at low dose (50 μg/kg) with sub-analgesic dose of Morphine (0.1 mg/kg) and Morphine in analgesic dose (1 mg/kg) was evaluated by using Hot Water Bath method in albino rats.Results: Comparison of maximal possible effect in percentage (MPE in %) between groups at 90 minutes in control, Morphine, Physostigmine in 50, 100, 200 μg/ kg doses and combination group respectively, demonstrated significant difference (p <0.001) when compared by one way ANOVA test. There was no much increase in maximal possible effect in the tail withdrawal latency in Physostigmine 50 μg/kg (SC) treatment at 90 min (5.50±0.88) in comparison to control (NS) treatment group. Combination treatment of low doses of both Physostigmine 50 μg/kg + Morphine 0.1 mg/kg increased in maximal possible effect the tail withdrawal latency 90 min (53.87±1.38) in-comparison to control (NS) treatment group (6.17±0.92).Conclusions: Physostigmine is more potent antinociceptive than Morphine and Physostigmine potentiated the antinociceptive activity of low dose of standard drug Morphine

An MFS Transporter-Like ORF from MDR Acinetobacter baumannii AIIMS 7 Is Associated with Adherence and Biofilm Formation on Biotic/Abiotic Surface

A major facilitator superfamily (MFS) transporter-like open reading frame (ORF) of 453 bp was identified in a pathogenic strain Acinetobacter baumannii AIIMS 7, and its association with adherence and biofilm formation was investigated. Reverse transcription PCR (RT-PCR) showed differential expression in surface-attached biofilm cells than nonadherent cells. In vitro translation showed synthesis of a ~17 kDa protein, further confirmed by cloning and heterologous expression in E. coli DH5α. Up to 2.1-, 3.1-, and 4.1- fold biofilm augmentation was observed on abiotic (polystyrene) and biotic (S. cerevisiae/HeLa) surface, respectively. Scanning electron microscopy (SEM) and gfp-tagged fluorescence microscopy revealed increased adherence to abiotic (glass) and biotic (S. cerevisiae) surface. Extracellular DNA(eDNA) was found significantly during active growth; due to probable involvement of the protein in DNA export, strong sequence homology with MFS transporter proteins, and presence of transmembrane helices. In summary, our findings show that the putative MFS transporter-like ORF (pmt) is associated with adherence, biofilm formation, and probable eDNA release in A. baumannii AIIMS 7

Flipping the odds of drug development success through human genomics

Drug development depends on accurately identifying molecular targets that both play a causal role in a disease and are amenable to pharmacological action by small molecule drugs or bio-therapeutics, such as monoclonal antibodies. Errors in drug target specification contribute to the extremely high rates of drug development failure. Integrating knowledge of genes that encode druggable targets with those that influence susceptibility to common disease has the potential to radically improve the probability of drug development success