Intelligent Data Monitoring and Controlling System for Health Related Social Networks

Depression is a worldwide wellbeing concern in view of healthcare. Now a days, social media became popular to allow the affected people to share their experience in the form of posts. These kinds of experiences are stored in the database and extracted and analyzed to give the precautions to the other people or to recall the drugs from the side effects, and other service improvements in their treatment regarding to a particular disease. In such cases depression-related social websites are helpful to monitor or get knowledge in various kinds of drugs, side effects and to share the user experiences. In this paper, we proposed a social media website to allow the users to share the experiences of a particular disease i.e. depression and their experience over on it. We used a weighted network model to represent the activities in the social networks. The proposed work has three steps. The first one is to monitor the user activity and followed by network clustering and the module analysis. The persons who likes a particular post comes under a group and those who contrasted belongs to other group. The stop word technique we have implemented in this work is helpful to avoid the misleading communication over the posts and for the efficient user interaction. The statistical analysis of this kind of user interactions are helpful in health networks to gain much knowledge about a specific disease. This approach will enable all the gatherings to take a part and for the future healthcare improvements to the patients suffering from a disease

Studies on the effect of post harvest treatments on shelf life and quality of mango [Mangifera indica l.] cv. Amrapali

he physicochemical characteristics and shelf life of mango[Mangifera indica L.] fruits treated with calci- um chloride (CaCl2-1%, 2%), calcium nitrate (Ca(NO3)2-1%, 2%), potassium nitrate (KNO3-1%, 2%) and carboxyl methyl cellulose (CMC - 0.5, 1%) were studied. Untreated fruits served as the control. All tested treatments indicated a significant delay in the change of weight loss (16.84%), ripening (51.66%), decaying percentage (46.66) and retained firmness (3.23 kg/cm2) of fruits and biochemical qualities viz., total soluble solids(22.33Brix), sugar accumulation (18.17%) and tritratable acidity on 16th day in mango fruits compared to control. The significant (5%) impact of treatment is found on the least decay percentage in the order of fruits treated with calcium nitrate (2%) followed by 1% Ca(NO3)2, 2% CaCl2 and 1% CaCl2. Hence, it could be concluded that post harvest chemical treatment with calcium nitrate, calcium chloride (1%, 2%) has the potential to control spoilage, prolong the storage life and preserve valuable attributes of post harvest quality of mango, presumably because of its effect on inhibition of ripening and senescence processes by lowering the respiration rate

Efficient Query Processing For Integrity and Privacy Validation In WSN

To reserve secrecy, we body a guide for each sensor placid data element via pseudo-random hash function and Bloom filters and converts top-k queries into top assortment queries. To game reserve honor, we advise a data barrier algorithm to dividing wall each data item into an interlude and award the partition data with the data. The emotionally involved information warrants that the sink can attest the veracity of query results. We strictly ascertain that our order is safe as houses under IND-CKA security model. Our untried results on real-life data show that our style is true and real for huge network sizes

FORMULATION AND EVALUATION OF RAMIPRIL MOUTH DISSOLVING FILMS

Objective: The present investigation was aimed at preparation and evaluation of mouth dissolving films (MDFs) of Ramipril to enhance patient convenience, compliance and to improve bioavailability. Methods: MDFs with 0.5% w/w Ramipril were prepared by a solvent casting method using a wet film applicator. The effects of film formers, wetting/solubilizing, saliva stimulating agents and film modifiers on the physicomechanical and in vitro Ramipril release from MDFs were evaluated. Results: The MDFs prepared were transparent, smooth and showed no re-crystallization upon storage. MDFs casted with hydroxypropyl methylcellulose (HPMC) E3 as film former and polyethylene glycol (PEG-400) as plasticizer showed superior Ramipril release rates and good physicomechanical properties when compared to MDFs with E5 and E15 as film formers. HPMC E3 MDFs with polyvinyl pyrrolidone K30 (PVP K30) and sodium lauryl sulphate (SLS) gave superior drug release properties than MDFs without PVP K30 and SLS. The HPMC E3 MDFs with citric acid (CA) as saliva stimulating and xylitol as soothing agent gave significantly superior in vitro drug release than the MDFs without CA and xylitol. Release kinetics data reveals diffusion as a drug release mechanism. Conclusion: From the obtained results, it can be concluded that the administration of Ramipril as MDF may provide a quick onset of action with enhanced oral bioavailability and therapeutic efficacy

A VIBRANT STRUCTURE FOR IDENTIFYING MALICIOUS NODES IN UNWIRED NETS

In the present occasions, recent has highlighted the important thing contribution of attribution within systems where utilization of difficult to depend on data could cause disastrous failures. Attribution is going to be monitored for every packet, however essential challenges will arise because of fixed storage, energy additionally to bandwidth limits of sensor nodes consequently, you should produce a light-weight attribution solution by means of low overhead. You need to deal with security needs for instance privacy, reliability additionally to originality of attribution and our goal is always to devise an attribution encoding additionally to deciphering means by which assures protection additionally to performance needs. Inside our work we advise a completely new lightweight method of strongly convey attribution for sensor data. The recommended method is dependent upon in-packet Blossom filters to correct attribution. Blossom filters make well-organized utilization of bandwidth, additionally to yield small error rates used

Myxoid degeneration of leiomyoma-a masquerader

Uterine leiomyomas are one of the most common benign lesions in the uterus. The lesion can vary in size from a few millimetres to centimetres, location, its presentation and degeneration. They are easy to diagnose clinically with the help of available imaging techniques. Myxoid degeneration is an uncommon degeneration and has to be kept as a differential diagnosis as it mimics uterine sarcoma. Histopathology and Immunohistochemical analysis help in confirming the diagnosis. Here is a patient in reproductive age group who presented with rapidly growing abdominal mass in a span of 1 year with a prior surgical history of myomectomy. Pre-operative imaging was inconclusive for benign etiology and possibility of uterine leiomyosarcoma could not be ruled out. She was hence counselled for a laparotomy with a frozen section to prevent extensive surgery. Myxoid degeneration is not a common degeneration of leiomyoma with a reported incidence of 10% while the incidence of uterine leiomyosarcoma is less than 1% in reproductive age group. Even though rare, myxoid degeneration should be considered as a differential diagnosis of rapidly growing uterine mass with inconclusive pre-operative imaging

CONTRIBUTE, DETACH AND AUTONOMOUS ACCESS TO CIPHER TEXT IN CLOUD DATABASE

In some approaches to repository functions have been adopted, while the approach to building trust in the message as a taboo of interests is being developed to be carefully dealt with. Having a pulse to swallow an embarrassing information usage ensures the withdrawal and implements the appropriate procedure in the encrypted message. Introducing the information, you need to distract yourself must confirm your trust, as well as an easy approach to the message. The car builds on popular encryption programs as well as unique ways to tune the encrypted data in hard to believe information into the shower. Secure confidential information acts as a basic job of creating a hacker to distract and discern irresponsibility, in addition to the gain measurement options, loss of unencrypted messages pointing to deformation Temporary and offer many options they detect the best way for tape information functions. The solid information prediction function does not retain anything legally right before the information has been previously benefited; it does not need any suggestion for the distraction function of the command

ACUMULATIVE BUG ORIGINATED SYSTEM TO A DEVELOPER

Mining of understanding has switched right into a competent approach to manage software data.  By leveraging means of data mining, mining manner of software repositories can expose interesting data within software repositories and resolve actual software problems. Within our work we manage impracticality of information reduction for bug triage that's decrease in bug data in order to save work price of developers and get better the traditional to create easy the whole process of bug triage. A lengthy move of managing of software bugs is bug triage, which assign a precise developer to repair a totally new bug.  To influence obvious of costly price of manual bug triage, existing work has forecasted an analog means of bug triage, involving the techniques of text classification can be expected developers for bug reports. Data decrease in aid of bug triage aims to place up somewhat-scale furthermore to expert quantity of bug data by way of elimination of bug reports furthermore to words which are redundant otherwise non-informative

Deep Learning Frameworks for Cardiovascular Arrhythmia Classification

Arrhythmia classification is a prominent research problem due to the computational complexities of learning the morphology of various ECG patterns and its wide prevalence in the medical field, particularly during the COVID-19 pandemic. In this article, we used Empirical Mode Decomposition and Discrete Wavelet Transform for preprocessing and then the modified signal is classified using various classifiers such as Decision Tree, Logistic Regression, Gaussian Naïve Bayes, Random Forest, Linear  SVM, Polynomial SVM, RBF SVM, Sigmoid SVM and Convolutional Neural Networks. The proposed method classify the data into five classes N (Normal), S (Supraventricular premature) beat, (V) Premature ventricular contraction, F (Fusion of ventricular and normal), and Q, (Unclassifiable Beat) using softmax regressor at the end of the network. The proposed approach performs well in terms of classification accuracy when tested using ECG signals acquired from the MIT-BIH database. In comparison to existing classifiers, the Accuracy, Precision, Recall, and F1 score values of the proposed technique are 98.5%, 96.9%, 94.3%, and 91.32%, respectively.  &nbsp