This paper presents the development and implementation of an advanced plant health monitoring system. The primary objective is to create an integrated system capable of assessing and monitoring plant health by incorpo...
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Artificial intelligence is a field of computerscience dedicated to solving reasonable problems mostly associated with human intelligence such as pattern recognition and problem solving. This chapter proposes a projec...
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Illegal fishing is an unresolved and internationally pervasive problem that occurs both on the high seas and in areas within national jurisdiction. Existing technologies use anomaly detection algorithms that examine t...
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The quick rise in smart home technologies calls for the development of advanced energy forecasting models that can accurately predict consumption patterns while maintaining user privacy. Existing energy forecasting me...
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The growth of the Internet of Things (IoT) sector has ushered in an unprecedented era of connectedness, enabling a profusion of applications ranging from smart homes to industrial automation. Researchers predict that ...
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This study applies machine learning to determine rice crop production using sensor information from temperature, humidity, and water levels. This project looks forward to providing insights to maximize agricultural pr...
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Energy and environmental concerns have fostered the era of electric vehicles (EVs) to take over and be welcomed more than ever. Fuel-powered vehicles are still predominant;however, this trend appears to be changing so...
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Energy and environmental concerns have fostered the era of electric vehicles (EVs) to take over and be welcomed more than ever. Fuel-powered vehicles are still predominant;however, this trend appears to be changing sooner than we might expect. Countries in Europe, Asia, and many states in America have already made the decision to transition to a fully EV industry in the next few years. This looks promising;however, drivers still have concerns about the battery mileage of such vehicles and the anxiety that such driving experiences! Indeed, driving with the probability of having insufficient battery charge that may be involved in guaranteeing the delivery to the trip destination imposes a level of anxiety on the vehicle drivers. Therefore, for an alternative to traditional fuel-powered vehicles to be convincing, there needs to be sufficient coverage of charging stations to serve cities in the same way that fuel stations serve traditional vehicles. The current navigation models select routes based solely on distance and traffic metrics, without taking into account the coverage of fuel service stations that these routes may offer. This assumption is made under the belief that all routes are adequately covered. This might be true for fuel-powered vehicles, but not for EVs. Hence, in this work, we are presenting AFARM, a routing model that enables a smart navigation system specifically designed for EVs. This model routes the EVs via paths that are lined with charging stations that align with the EV’s current charge requirements. Different from the other models proposed in the literature, AFARM is autonomous in the sense that it determines navigation paths for each vehicle based on its make, model, and current battery status. Moreover, it employs Dijkstra’s algorithm to accommodate varying least-cost navigation preferences, ranging from shortest-distance routes to routes with the shortest trip time and routes with maximum residual battery capacities as well. According to t
In the contemporary digital landscape, ensuring the continuous functionality of computer networks is vital for business and critical infrastructure success. This research project utilizes cutting-edge technologies lik...
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Blockchain technology is a shared database of logs of all consumer transactions which are registered on all machines on a *** transactions in the system are carried out by consensus processes and to preserve confident...
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Blockchain technology is a shared database of logs of all consumer transactions which are registered on all machines on a *** transactions in the system are carried out by consensus processes and to preserve confidentiality all thefiles contained cannot be *** technology is the fundamental software behind digital currencies like Bitcoin,which is common in the *** computing is a method of using a network of external machines to store,monitor,and process information,rather than using the local computer or a local personal *** software is currently facing multiple problems including lack of data protection,data instability,and *** paper aims to give the highest security for multiple user environments in cloud for storing and accessing the data in *** users who are legitimate are only allowed for storing and accessing the data as like a secured block chain *** like the Blockchain which does not require a centralized system for transactions,the proposed system is also independent on centralized network *** decentralized system is developed in such a way to avoid *** system enables the fabricator to spend less or null resources to perform the validations for its direct operated *** ensures the product fabricator to avoid the circulation of its duplicate *** customer as an end-user is also ensured to have only the genuine products from the *** Fabricator(F),Merchant(M)and consumer(C)forms an interconnected triangular structure without allowing any counterfeiting agents in their secured cloud *** pro-posed approach provides the stability in the security system of the cloud using the chaining mechanism within different blocks at each *** takes roughly 4.7,6.2,and 7.5 ms,respectively,to register each node in the proposed system for 5,10,and 15 *** overall registration time for each scenario is 11.9,26.2,and 53.1 ms,despite the fact th
The traditional pipeline for non-rigid registration is to iteratively update the correspondence and alignment such that the transformed source surface aligns well with the target *** the pipeline,the correspondence co...
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The traditional pipeline for non-rigid registration is to iteratively update the correspondence and alignment such that the transformed source surface aligns well with the target *** the pipeline,the correspondence construction and iterative manner are key to the results,while existing strategies might result in local *** this paper,we adopt the widely used deformation graph-based representation,while replacing some key modules with neural learning-based ***,we design a neural network to predict the correspondence and its reliability confidence rather than the strategies like nearest neighbor search and pair ***,we adopt the GRU-based recurrent network for iterative refinement,which is more robust than the traditional *** model is trained in a self-supervised manner and thus can be used for arbitrary datasets without *** experiments demonstrate that our proposed method outperforms the state-of-the-art methods by a large margin.
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