58 research outputs found
Review of Secure Distributed Range-Free Hop-Based Localization Algorithms in the Wireless Sensor Networks
No full textSynthesis Of Gum Tragacanth-Cl-Poly (Acrylic Acid) Superabsorbent Hydrogels with Salt, pH and Electrical Responsive Properties
No full textThe Gum tragacanth-acrylic acid-based hydrogels were prepared using KPS-ascorbic acid as an initiator and glutaraldehyde as crosslinker via free radical graft copolymerization technique. Synthesized polymers were characterized with FTIR, SEM and thermal techniques in order to authenticate the grafting of poly (AA) on to Gum tragacanth. The candidate’s hydrogel was also evaluated for salt resistant distension studies by means of biological electrolytic system using AC/DC supply. Moreover, the re-swelling ability of the candidate polymer was also studied using different pH media for its utilization in the site specific drug delivery. The results of the study suggested that the candidate polymer shows good salt resistant behavior alongwith pulsatile (swelling/de-swelling) nature. From the results of present study it was concluded that the polymer can be utilized for targeted drug delivery system as carrier.</jats:p
PHARMACEUTICAL WORLD OF PERMEATION ENHANCERS
Get PDFThe drugs with poor solubility results in delayed absorption which consequently affects the bioavailability. There are many drugs which are having good therapeutic value but not used commercially because of this reason. The permeation enhancers are therefore being utilized to counter this problem. There are many such synthetic and natural materials which have the ability to enhance the drug permeation rate. The essential oils, alcohols, terpenes, azoles and many other chemical derivatives have the capability to be used for permeation enhancer. The present review work suggested the role of permeation enhancer in the pharmaceutical world
HFRAS : design of a high-density feature representation model for effective augmentation of satellite images
Get PDFEfficiently extracting features from satellite images is crucial for classification and post-processing activities. Many feature representation models have been created for this purpose. However, most of them either increase computational complexity or decrease classification efficiency. The proposed model in this paper initially collects a set of available satellite images and represents them via a hybrid of long short-term memory (LSTM) and gated recurrent unit (GRU) features. These features are processed via an iterative genetic algorithm, identifying optimal augmentation methods for the extracted feature sets. To analyse the efficiency of this optimization process, we model an iterative fitness function that assists in incrementally improving the classification process. The fitness function uses an accuracy & precision-based feedback mechanism, which helps in tuning the hyperparameters of the proposed LSTM & GRU feature extraction process. The suggested model used 100 k images, 60% allocated for training and 20% each designated for validation and testing purposes. The proposed model can increase classification precision by 16.1% and accuracy by 17.1% compared to conventional augmentation strategies. The model also showcased incremental accuracy enhancements for an increasing number of training image sets.© The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.fi=vertaisarvioitu|en=peerReviewed
CP-NR Distributed Range Free Localization Algorithm in WSN
Get PDFAdvancements in wireless communication technology have empowered the researchers to develop large scale wireless networks with huge number of sensor nodes. In these networks localization is very active field of research. Localization is a way to determine the physical position of sensor nodes which is useful in many aspects such as to find the origin of events, routing and network coverage. Locating nodes with GPS systems is expensive, power consuming and not applicable to indoor environments. Localization in three dimensional space and accuracy of the estimated location are two factors of major concern. In this paper, a new three dimensional Distributed range-free algorithm which is known as CP-NR is proposed. This algorithm has high localization accuracy and resolved the problem of existing NR algorithm. CP-NR (Coplanar and Projected Node Reproduction) algorithm makes use of co-planarity and projection of point on plane concepts to reduce the localization error. Results have shown that CP-NR algorithm is superior to NR algorithm and comparison is done for the localization accuracy with respect to variations in range, anchor density and node density
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