Angular Minkowski p-distance is a dissimilarity measure that is obtained by replacing Euclidean distance in the definition of cosine dissimilarity with other Minkowski p-distances. Cosine dissimilarity is frequently u...
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Weather Forecasting is the application of AI to predict the state of the atmosphere for a given location. Earlier, weather forecasting methods usually relied on observed patterns of events. Our ancestors predicted the...
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Weather Forecasting is the application of AI to predict the state of the atmosphere for a given location. Earlier, weather forecasting methods usually relied on observed patterns of events. Our ancestors predicted the next day weather based on the happenings of the previous day evening. However, those intuitive methods and predictions are not reliable. This paper depicts the design and implementation of an application for weather forecasting and visualization using Augmented Reality (AR), which can forecast climatic conditions, namely, such as rain, snow, sun, wind, and hail. This work deals with various real-world weather types and how they could be simulated using a mobile augmented reality system. Users can move freely inside the real world without limitations, experiencing the developed augmented objects. A visual change of the augmented reality weather conditions can be used as a supplement to train the simulations for search and rescue teams during catastrophic disasters.
The traditional polysomnography (PSG) examination for Obstructive Sleep Apnea (OSA) diagnosis needs to measure several signals, such as EEG, ECG, EMG, EOG and the oxygen level in blood, of a patient who may have to we...
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The community has begun paying more attention to source OSCTI Cyber Threat Intelligence to stay informed about the rapidly changing cyber threat landscape. Numerous reports from the OSCTI frequently provide Informatio...
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Operando X-ray micro-computed tomography(µCT)provides an opportunity to observe the evolution of Li structures inside pouch *** is an essential step to quantitatively analyzingµCT datasets but is challenging...
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Operando X-ray micro-computed tomography(µCT)provides an opportunity to observe the evolution of Li structures inside pouch *** is an essential step to quantitatively analyzingµCT datasets but is challenging to achieve on operando Li-metal battery datasets due to the low X-ray attenuation of the Li metal and the sheer size of the ***,we report a computational approach,batteryNET,to train an Iterative Residual U-Net-based network to detect Li *** resulting semantic segmentation shows singular Li-related component changes,addressing diverse morphologies in the *** addition,visualizations of the dead Li are provided,including calculations about the volume and effective thickness of electrodes,deposited Li,and redeposited *** also report discoveries about the spatial relationships between these *** approach focuses on a method for analyzing battery performance,which brings insight that significantly benefits future Li-metal battery design and a semantic segmentation transferrable to other datasets.
There are a lot more IoT gadgets and data being made because IoT apps are becoming more common in our daily lives. IoT devices don't have a lot of resources, which makes it harder to handle and store IoT data. Tra...
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Detecting suspicious activities in public places with higher people gathering and interaction has turned out to be an act with growing interest due to the increasing number of crime scenes and causalities happening in...
Detecting suspicious activities in public places with higher people gathering and interaction has turned out to be an act with growing interest due to the increasing number of crime scenes and causalities happening in these days. Surveying and tracking of human activities are increasingly difficult owing to the random nature of human movements and actions. The reliability is greatly affected due to this randomness. Also a human operator cannot continuously monitor multiple screens efficiently in a consequent manner so an automated surveillance system deployment becomes a necessity. Currently, tracking individuals may be done remotely, and the analysis of the recorded images can be automated using object detection models, with the help of high resolution cameras and the development of machine learning techniques. This proposed system aims in identifying threats that are probable to occur in a public gathering or space which may be an explosion, accident or possession of armoury, etc. This proposed model takes advantage of the information from the image data to learn complex patterns and develop pattern recognition technique to identify the anomalies using high resolution camera and alert the monitoring authority in order to take the necessary actions. This proposed work compares various object detection techniques of machine learning algorithms and suggests the best model based on its performance metrics.
The advent of sixth-generation (6G) technology is poised to revolutionize connectivity, particularly by enhancing the integration of Internet of Medical Things (IoMT) devices. This advancement offers ultra-fast data t...
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This paper presents a resilient distributed algorithm for solving a system of linear algebraic equations over a multi-agent network in the presence of Byzantine agents capable of arbitrarily introducing untrustworthy ...
This paper presents a resilient distributed algorithm for solving a system of linear algebraic equations over a multi-agent network in the presence of Byzantine agents capable of arbitrarily introducing untrustworthy information in communication. It is shown that the algorithm causes all non-Byzantine agents' states to converge to the same least squares solution exponentially fast, provided appropriate levels of graph redundancy and objective redundancy are established. An explicit convergence rate is also provided.
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