Revisting SQL Query Recommender System Using Hierarchical Classification

For analytical purposes, lots of data are gathered which are gathered and explored in data warehouses. Even to handle such a large data is a tough task for expert people. For non-expert users or for users who are not familiar with the database schema, handling such a voluminous data is more difficult task. The aim of this paper is to facilitate this class of users by recommending them SQL queries that they may use. By following the users past behavior and comparing them with other users, these SQL recommendations are selected. Initially, users may not know from where they can start their exploration. Secondly, users may overlook queries which help them to retrieve important data. Using hierarchical classification, the queries are recorded and compared which is then re-ranked according to relevance. Using users querying behavior, the relevant queries are retrieved. To issue a series of SQL queries, users use a query interface which aim to analyze the data and mine it for interesting information. DOI: 10.17762/ijritcc2321-8169.150614

Query Recommender System Using Hierarchical Classification

In data warehouses, lots of data are gathered which are navigated and explored for analytical purposes. Even for expert people, to handle such a large data is a tough task. Handling such a voluminous data is more difficult task for non-expert users or for users who are not familiar with the database schema. The aim of this paper is to help this class of users by recommending them SQL queries that they might use. These SQL recommendations are selected by tracking the users past behavior and comparing them with other users. At first time, users may not know where to start their exploration. Secondly, users may overlook queries which help to retrieve important information. The queries are recorded and compared using hierarchical classification which is then re-ranked according to relevance. The relevant queries are retrieved using users querying behavior. Users use a query interface to issue a series of SQL queries that aim to analyze the data and mine it for interesting information. DOI: 10.17762/ijritcc2321-8169.15067

A Deep Learning based Model for Fruit Grading using DenseNet

Detecting the rotten fruits become significant in the agricultural industry. Usually, the classification of fresh and rotten fruits is carried by humans is not effectual for the fruit farmers. Human beings will become tired after doing the same task multiple times, but machines do not. Thus, this paper proposes an approach to reduce human efforts, reduce the cost and time for production by identifying the defects in the fruits in the agricultural industry. If we do not detect those defects, those defected fruits may contaminate good fruits. Hence, we proposed a model to avoid the spread of rottenness. The proposed model classifies the fresh fruits and rotten fruits from the input fruit images. For this work, we have used three types of fruits, such as apple, banana, and oranges. A Convolutional Neural Network (CNN) is used for extracting the features from input fruit images, and Softmax is used to classify the images into fresh and rotten fruits. The performance of the proposed model is evaluated on a dataset that is downloaded from Kaggle and produces an accuracy of 97.82%. The results showed that the proposed CNN model can effectively classify the fresh fruits and rotten fruits

Data Sharing using BFID Encryption for Privacy Preseration of Data in Cloud

The most important functionality in cloud storage is data sharing. With the advent of cloud computing [1], data owners are motivated to outsource their complex data management systems from local sites to the commercial public cloud for great flexibility and economic savings. But for protecting data privacy and integrity, sensitive data have to be encrypted before outsourcing, which causes the need of traditional data utilization based on plaintext keyword search. Thus, enabling an encrypted cloud data search service is of paramount importance.Typically cloud computing is a combination of computing recourses accessible via internet. Historically the client or organizations store data in data centers with firewall and various security techniques used to protect data against intrudes to access the data. Since the data was contained to data centers in limits of organisation, the control over the data was more and well defined procedures could be used for accessing its own data. Howeverin cloud computing, since the data is stored anywhere across the world, the client organizations have less control over the stored data.Identity-Based Encryption (IBE) which is used to simplifies the public key and certificate management at Public Key Infrastructure (PKI) is an important alternative to public key encryption. Identity-based encryption (IBE) is an important aspect of ID-based cryptography. As such it is a type of public-key encryption in which the public key of a user is provides unique information about the identity of the user (e.g. a user's Identification). This can use the text-value of the name or domain name as a key or the physical IP address it translates to

Bio-Efficacy of Aureofungin-sol in Control of Downy and Powdery Mildews in Grape

Bio-efficacy of Aureofungin-sol, an antifungal antibiotic, for control of downy mildew and powdery mildew of grape was evaluated during October 2008 - April 2009 fruiting season in vineyards at three locations in Maharashtra. Four to nine sprays of Aureofungin-sol, @ 0.108, 0.163 and 0.217 g/l, starting from 12-16 days to 46-75 days after fruit pruning gave good control of downy mildew on leaves and bunches, and increased harvestable yield over the Control. Similarly, four sprays of Aureofungin-sol @ 0.108 g/l at 11 to 20 days' interval at 65 days after pruning provided complete control of powdery mildew on leaves and bunches. No residue of Aureofungin-sol was found in harvest samples above the limit of detection (0.1 mg/kg)

Exploring the therapeutic mechanisms of Cassia glauca in diabetes mellitus through network pharmacology, molecular docking and molecular dynamics

Cassia glauca is reported as anti-diabetic medicinal plant and is also used as an ethnomedicine. However, its mode of action as an anti-diabetic agent has not been clearly elucidated. Hence, the present study investigated the probable mechanism of action of C. glauca to manage diabetes mellitus via network pharmacology and molecular docking and simulations studies. The reported bioactives from C. glauca were retrieved from an open-source database, i.e. ChEBI, and their targets were predicted using SwissTargetPrediction. The proteins involved in the pathogenesis of diabetes were identified from the therapeutic target database. The targets involved in diabetes were enriched in STRING, and the pathways involved in diabetes were identified concerning the KEGG. Cytoscape was used to construct the network among bioactives, proteins, and probably regulated pathways, which were analyzed based on edge count. Similarly, molecular docking was performed using the Glide module of the Schrodinger suite against majorly targeted proteins with their respective ligands. Additionally, the drug-likeness score and ADMET profile of the individual bioactives were predicted using MolSoft and admetSAR2.0 respectively. The stability of these complexes were further studied via molecular dynamics simulations and binding energy calculations. Twenty-three bio-actives were retrieved from the ChEBI database in which cassiarin B was predicted to modulate the highest number of proteins involved in diabetes mellitus. Similarly, GO analysis identified the PI3K-Akt signaling pathway to be primarily regulated by modulating the highest number of gene. Likewise, aldose reductase (AKR1B1) was majorly targeted via the bioactives of C. glauca. Similarly, docking study revealed methyl-3,5-di-O-caffeoylquinate (docking score −9.209) to possess the highest binding affinity with AKR1B1. Additionally, drug-likeness prediction identified cassiaoccidentalin B to possess the highest drug-likeness score, i.e. 0.84. The molecular dynamics simulations and the MMGBSA indicate high stability and greater binding energy for the methyl-3,5-di-O-caffeoylquinate (ΔGbind = −40.33 ± 6.69 kcal mol−1) with AKR1B1, thus complementing results from other experiments. The study identified cassiarin B, cassiaoccidentalin B, and cinnamtannin A2 as lead hits for the anti-diabetic activity of C. glauca. Further, the PI3K-Akt and AKR1B1 were traced as majorly modulated pathway and target, respectively

Lifestyle management of hypertension: International Society of Hypertension position paper endorsed by the World Hypertension League and European Society of Hypertension

Hypertension, defined as persistently elevated systolic blood pressure (SBP) >140 mmHg and/or diastolic blood pressure (DBP) at least 90 mmHg (International Society of Hypertension guidelines), affects over 1.5 billion people worldwide. Hypertension is associated with increased risk of cardiovascular disease (CVD) events (e.g. coronary heart disease, heart failure and stroke) and death. An international panel of experts convened by the International Society of Hypertension College of Experts compiled lifestyle management recommendations as first-line strategy to prevent and control hypertension in adulthood. We also recommend that lifestyle changes be continued even when blood pressure-lowering medications are prescribed. Specific recommendations based on literature evidence are summarized with advice to start these measures early in life, including maintaining a healthy body weight, increased levels of different types of physical activity, healthy eating and drinking, avoidance and cessation of smoking and alcohol use, management of stress and sleep levels. We also discuss the relevance of specific approaches including consumption of sodium, potassium, sugar, fibre, coffee, tea, intermittent fasting as well as integrated strategies to implement these recommendations using, for example, behaviour change-related technologies and digital tools

Structure-Function Studies of DNA Binding Domain of Response Regulator KdpE Reveals Equal Affinity Interactions at DNA Half-Sites

Expression of KdpFABC, a K+ pump that restores osmotic balance, is controlled by binding of the response regulator KdpE to a specific DNA sequence (kdpFABCBS) via the winged helix-turn-helix type DNA binding domain (KdpEDBD). Exploration of E. coli KdpEDBD and kdpFABCBS interaction resulted in the identification of two conserved, AT-rich 6 bp direct repeats that form half-sites. Despite binding to these half-sites, KdpEDBD was incapable of promoting gene expression in vivo. Structure-function studies guided by our 2.5 Å X-ray structure of KdpEDBD revealed the importance of residues R193 and R200 in the α-8 DNA recognition helix and T215 in the wing region for DNA binding. Mutation of these residues renders KdpE incapable of inducing expression of the kdpFABC operon. Detailed biophysical analysis of interactions using analytical ultracentrifugation revealed a 2∶1 stoichiometry of protein to DNA with dissociation constants of 200±100 and 350±100 nM at half-sites. Inactivation of one half-site does not influence binding at the other, indicating that KdpEDBD binds independently to the half-sites with approximately equal affinity and no discernable cooperativity. To our knowledge, these data are the first to describe in quantitative terms the binding at half-sites under equilibrium conditions for a member of the ubiquitous OmpR/PhoB family of proteins