Generally, it is possible to increase agricultural output while decreasing the time required for human oversight by automating routine tasks. In this work, the Internet of things (IoT) played a vital role in designing a platform to monitor a farm wirelessly, reducing human involvement, allowing remote observing, and remote control of the design using a public IP address based cross-platform, Apache, MySQL, PHP and Perl (XAMPP) Apache package. A cloud is appealing when a wireless sensor network generates a lot of data. Cloud-based wireless communication systems are being tested to monitor and manage a set of sensors and actuators to estimate paddy (rice) water requirements in a particular location. The proposed design shows robust interaction between two microcontrollers to deal with different sensors and simultaneously act as a WiFi unit. The row data obtained from the sensors is uploaded to the cloud through specific Hypertext Preprocessor (PHP) files to store and fetch the data from the database. Through the programming method, the system focuses on tracking the paddy growing value and the amount of water available in the soil, which should be around (10 Kpa) for an optimum paddy environment. The results emphasized that 80% of water is retained when a maximal 10 Kpa of soil moisture is achieved.
Currency counterfeiting is a significant offense that has an impact on a nation's finances. Due to the enormous progress in printing technology, it is now quite simple to create fake currency that resembles real currency in both appearance and texture, making it nearly difficult to manually tell them apart. The suggested approach will be helpful in identifying fake currency in financial systems. Because of the rise of fake currency in the market, numerous false note detecting techniques are available globally to address this issue, however the most of them rely on expensive technology. In this paper, we'll introduce a revolutionary way for separating fake banknotes from real ones using the support vector machine (SVM) approach. To categorize bank notes as authentic or counterfeit utilizing the data retrieved from the photos of the bank notes, SVM performs better overall and is more effective, particularly when it comes to pattern categorization. Finally, the results of our experiment will demonstrate that the suggested algorithm does really yield extremely good performance.
A vital feature of modern web search engine is the ability to display relevant and reputable pages near the top of the list of query results. A well-used search engine nowadays is Google search engine, it is the world's most popular search engine, rely on PageRank technology to determine a website's ranking. We put our attention on important benefactions to improving the quality of rankings via the value which is called damping factor, commonly the original suggestion d=0.85 by Brin and Page is the most common choice. In this paper, we suggest a new value which plays an important role to rank web sites accurately, our work focuses on damping factor value which improves the efficiency of PageRank value for each website. Our results show that the suggested value can get greater performance. Finally, we will show satisfactory result without link spam and dangling node applying PageRank algorithm on graphs with over 5000 links.
<span lang="EN-US">The centrality of an edge in a graph is proposed to be the degree of sensitivity of a graph distance function to the weight of the edge under consideration. Many centrality metrics are available in network analysis and are effectively used in the investigation of social network properties. Node position is one of them. In this paper, we propose a novel importance of nodes showing how to locate the most essential nodes in a network and to construct a centrality measure for each node in the network, sort the nodes by centralities, and focus on the top ranked nodes, which are the most relevant in terms of this centrality measure. Our research aims to explain how to identify the most important nodes in networks. A centrality metric should be established for each node in the network, and then the nodes based on their centralities, focusing on the top-ranked nodes, which in light of this importance, might be regarded as the most pertinent measure.</span>
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