Secure Routing Packet Transmission

The Secure Routing Packet Transmission is the one which can be used to send or transmit the message or packets which contain some sensitive data in the network. Network is a medium which can consists of routers and network devices. In network there may be a chance of modifying the files by the attacker, but in our approach we age removing the attackers in other words we are removing the untrusted nodes. By generating the frequency to each and every nodes and by using the NDP protocol we can remove untrusted nodes and the shortest path is choosed based on frequency of all the nodes from source to destination, each time the frequency will be randomly generated so that same route will not select. The route will be selected based on shortest path. After successful transmission of file from source to destination, the file will be safely stored in destination folder

AN OVERVIEW OF TECHNOLOGY TRANSFER AS A REGULATORY ASPECT

Technology Transfer is fundamental and crucial to the drug development process for new drug products. The great decision is based on that factor in which the concept or process is advanced from research and development-oriented scheme to aimed towards the commercialization of the drug. The transfer could also be said to achieve success if the receiving section and the transferee can efficiently use the technology for profit. The achievement relies upon an understanding of the process or the capability to predict exactly the future prospects of a process. The main intention of this review article is to study the Regulatory aspects of technology transfer. This review article is mainly focused on the Consequence of technology transfer, the purpose for technology transfer in industries, barriers concerned with technology transfer, classification regarding technology transfer, facets of technology transfer, and steps among technology transferThis review was carried out by systematic searches of data integrity in relevant ICH, WHO, and US guidelines, published articles, reviews and abstracts in Google scholar, Pubmed, Science direct, Embase, Web of science of articles up to 2020

Support Vector Machine based Image Classification for Deaf and Mute People

A hand gesture recognition system provides a natural, innovative and modern way of nonverbal communication. It has a wide area of application in human computer interaction and sign language. The whole system consists of three components: hand detection, gesture recognition and human-computer interaction (HCI) based on recognition; in the existing technique, ANFIS(adaptive neuro-fuzzy interface system) to recognize gestures and makes it attainable to identify relatively complex gestures were used. But the complexity is high and performance is low. To achieve high accuracy and high performance with less complexity, a gray illumination technique is introduced in the proposed Hand gesture recognition. Here, live video is converted into frames and resize the frame, then apply gray illumination algorithm for color balancing in order to separate the skin separately. Then morphological feature extraction operation is carried out. After that support vector machine (SVM) train and testing process are carried out for gesture recognition. Finally, the character sound is played as audio output

Design and development of an instrument for non- destructive fabric weight measurement

In this study, an image processing approach for fabric weight measurement has been proposed and tested. The system involves digital capturing of image using a microscope and then its processing in simple steps using image processing software (MATLAB). The study is conducted using a range of woven fabric samples. The fabrics have been conventionally weighed using an electronic weighing balance, and digital images of the sample fabrics are obtained and processed. The process involves application of suitable filters to obtain weft count, warp count, EPI, PPI and yarn crimp. The values are then substituted in standard formula to obtain the fabric weight. The study shows that the results of the proposed method of image processing, based on fabric weight measurement, are well correlated with the results of conventional method of measurement

NATURAL PRODUCTS AS AN IMPORTANT LEADS FOR DISCOVERY OF NEW ANTITUBERCULAR AGENTS: A REVIEW

There is a very much need for a discovery of new molecules a potent molecule that can cure tuberculosis and prevent the recurrence. A multidisciplinary approach is required to procure a potent bioactive compound and this includes expertise in the fields of ethnobotany, ethnopharmacology and Phytochemistry. The present communication acts as a bioprospecting source for the drug discovery against tuberculosis, including several anti tubercular agents which is used by used by tribal people and prescribed by THPS which showed a good inhibition rate. Therefore, this review strives to describe the literature on the traditional plants/potent molecules those have been proved to have antimicrobial activity and to provide essential discussion and accelerate the research.Â

An Ensemble Learning Approach for Fast Disaster Response using Social Media Analytics

Natural disaster happens, as a result of natural hazards that cause financial, environmental or human losses. Natural disasters strike unexpectedly, affecting the lives of tens of thousands of people. During the flood, social media sites were also heavily used to disseminate information about flooded areas, rescue agencies, food and relief centres. This work proposes an ensemble learning strategy for combining and analysing social media data in order to close the gap and progress in catastrophic situation. To enable scalability and broad accessibility of the dynamic streaming of multimodal data namely text, image, audio and video, this work is designed around social media data. A fusion technique was employed at the decision level, based on a database of 15 characteristics for more than 300 disasters around the world (Trained with MNIST dataset 60000 training images and 10000 testing images).  This work allows the collected multimodal social media data to share a common semantic space, making individual variable prediction easier. Each  merged numerical vector(tensors) of text and audio  is sent into the K-CNN algorithm, which is an  unsupervised learning algorithm (K-CNN), and the  image and video data is given to a deep learning  based Progressive Neural Artificial Search (PNAS).  The trained data acts as a predictor for future  incidents, allowing for the estimation of total  deaths, total individuals impacted, and total  damage, as well as specific suggestions for food,  shelter and housing inspections. To make such a prediction, the trained model is presented a satellite image from before the accident as well as the geographic and demographic conditions, which is expected to result in a prediction accuracy of more than 85%

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

Genotypic Variability in Tomato for Total Carotenoids and Lycopene Content during Summer and Response to Post Harvest Temperature

Lycopene is the major carotenoid responsible for fruit colour in tomato (Lycopersicon esculentum Mill.). However, colour of the fruit is greatly affected by high temperature prevailing during fruit growth in the summer crop. To select a genotype suitable for summer conditions that can maintain colour better, a set of 52 tomato genotypes were evaluated for lycopene, total carotenoids and for TSS during summer in Bengaluru. Among the genotypes screened, IIHR 2892 recorded very high lycopene content (328.4mg/100g dry weight) and IIHR 2866 recorded very low lycopene content (25.2mg/100g dry weight). TSS values ranged from 2.6° Brix in cv. Vybhav to 7.0° Brix in IIHR 2866. In addition, study was carried out to determine the effect of postharvest temperature on biosynthesis of lycopene in five selected tomato cultivars (Arka Rakshak, Arka Samrat, Arka Ananya, Lakshmi and Abhinava). Tomatoes harvested at breaker stage were stored at 27° C, 35° C and 40° C for ripening. High temperature reduced lycopene content in tomato fruits. Lycopene synthesis in fruits was completely inhibited above 35°C. In this study, mean lycopene content in tomatoes stored at 27° C was 3-4 times higher than that in tomatoes stored at 40° C. This indicates that in tomatoes, temperature at which the fruits are stored after harvest, is a more important factor for colour development