Enhancing Auction Systems with Blockchain Technology

This research paper examines the use of blockchain technology in auction systems. Traditional auction systems face issues related to trust, transparency, and security. Blockchain offers a decentralized and immutable solution that can enhance the efficiency, security, and transparency of auctions. The paper provides an overview of blockchain technology and identifies the challenges in traditional auctions that blockchain can address. It explores existing blockchain-based auction systems and evaluates their effectiveness in mitigating issues such as bid manipulation and fraud. The impact of blockchain on auction participants is also discussed, including benefits like increased trust and reduced transaction costs, as well as challenges related to adoption and scalability. The paper considers both theoretical and practical aspects, analyzing case studies and implementation challenges. It concludes by summarizing the key findings and suggesting future research directions to advance the application of blockchain in auction systems. The auction contract allows users to place bids and determine the highest bidder within a specified time period. The contract also provides functionality for canceling the auction and finalizing it by transferring the funds to the appropriate recipients

High-resolution aerial monitoring using DL for identifying abnormal activity based on visual patterns in drone videos

Unmanned aerial vehicles (UAVs) and sophisticated deep learning (DL) models have made the application of artificial intelligence (AI) more popular. This has resulted in an increase in the number of attempts to improve high-resolution aerial monitoring using DL for identifying abnormal activity based on visual patterns in drone videos. The study introduces a one-class support vector machine (OC-SVM) oddity locator for low-altitude, limited-scope UAVs used for ethereal video surveillance. The primary goal is to improve UAV-based observation capabilities by identifying areas or things of interest without prior knowledge, hence improving tasks like queue control, vehicle following, and hazardous product identification. The framework makes use of OC-SVM because of its quick and lightweight setup, making it suitable for continuous operation on low-computational UAVs. It empowers the identification of several peculiarities necessary for low-elevation reconnaissance by using textural characteristics to recognise both large-scale and tiny structures. Examine the UAV mosaicking and change location (UMCD) dataset to demonstrate the effectiveness of the framework, which achieves excellent accuracy and outperforms traditional methods by about one fifth in a variety of metrics. The suggested model compares with current methods, demonstrating superior accuracy and performance in recognition of peculiarities. Evaluation metrics include F1-score, review, exactness, and accuracy. The model demonstrates that it always encounters an oddity with a review compromise of up to seven on ten, achieving complete accuracy

AN OVERVIEW ON CARBON NANOTUBES

ABSTRACT: In different fields like semiconductors, field emission, conductive plastics, energy storage, conductive adhesives and connectors, molecular electronics, thermal materials carbon nanotubes are applicable. Carbon nanotubes are generally produced by three main techniques: arc discharge, laser ablation, chemical vapour deposition. In arc discharge, a vapour is created by an arc discharge between two carbon electrodes with or without catalyst. Nanotubes self-assemble from the resulting carbon vapour. In the laser ablation technique, a high-power laser beam impinges on a volume of carbon -containing feedstock gas (methane or carbon monoxide). At the moment, laser ablation produces a small amount of clean nanotubes, whereas arc discharge methods generally produce large quantities of impure material. In general, chemical vapour deposition (CVD) results in Multi Walled Nanotubes or poor quality Single Walled Nanotubes. The SWNTs produced with CVD have a large diameter range, which can be poorly controlled. But on the other hand, this method is very easy to scale up, what favours commercial production

Optimization of Nanoscience Parameters for Extracting Phenolic Compounds from Ficus religiosa by Three-Phase Partitioning (TPP) Method

Background: Phenolic compounds are generally found in different parts of various herbs and plants such as leaves, barks, seeds, fruits, etc. These compounds show numerous bioactive properties, including antioxidant characteristics. Phenolic compounds obtained from beneficial herbs and dietary plants include flavonoids and tannins. In recent times, nanoscience has proved to be extensively helpful in extracting bioactive components. Additionally, nanomaterials have made a considerable contribution to the development of methodical techniques to retain superiority in processing foods and medicines. Objective: Of late, the process of extraction of nano-bioactive composites from natural resources has gained significant interest as these composites are used in manufacturing a wide range of products such as foods, paints, and pharmaceuticals. Therefore, there is a requirement to separate natural products to identify new nano-bioactive compounds that have the potential to improve the developed techniques. Methods: This research focuses on optimizing the experimental parameters to extract the phenolic compounds from Ficus religiosa (banyan leaves) by the three-phase partitioning (TPP) method. TPP is an advanced method that is widely used for the extraction, concentration, and purification of various nano-based bioactive compounds and enzymes. Results: During the investigation, various experimental parameters have been studied to obtain the maximum concentration of phenolic compounds from the dried powder of the Ficus religiosa leaves. The optimised results were found to be as follows: 30% of ammonium sulphate, solute to the solvent in the ratio of 1:20 (v/v), and slurry to t-butanol in the ratio of 1:1. Conclusion: The experimental results showed that the TPP method is very efficient as it needs minimum time to complete the extraction compared to the conventional solvent-based stirred batch extraction method. </jats:sec

Aqueous Two-Phase Separation (ATPS) Methods for Oleic acid extraction from Neem leaves

Abstract The aqueous two-phase separation system (ATPS) signifies an environmentally responsible approach for the extraction of bioactive compounds from a plants basis, as it is a liquid-liquid fractionation technique centred on the inconsistency of two aqueous solutions. In this investigation, various experimental parameters are optimized as the speed of agitation (200, 300 400 and 500 rpm) and solvent ratio (1:1, 2:3 and 3:2) with 20 % (w/w) of Ammonium Sulphate (AMS) salt composition and 30 % (w/w) of Polyethelyene Glycol (PEG). The obtained extract contains alkaloids, flavonoids, tannins, glycosides, acids and total phenolic compounds (TPC). The extracted Oleic acid by the ATPS method was measured with gallic acid equivalent (GAE) of TPC extracted from neem leaves powder. The determined concentration of oleic acid in the practice of TPC is 8.033 mg of GAE/g from the optimized experimental parameter. The optimized results can be cast off for a commercial process on an industrialized scale. Also, the mathematical modelling investigation was done to intent the critical impeller speed (Njs) with the Zwittering model. The identified model calculates the essential speed of agitation (rpm) for maximum extraction yield.</jats:p