Covert communication is considered a promising technology for hiding transmission processes and activities from malicious eavesdropping. With the development of detection technology, the traditional point-to-point cov...
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Smartphones offer a wide range of applications globally, and usability is a key factor in their quality. Human-computer Interaction (HCI) continuously evolves to enhance usability by improving user interface (UI) comp...
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The general increase in data size and data sharing motivates the adoption of Big Data strategies in several scientific disciplines. However, while several options are available, no particular guidelines exist for sele...
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We study temporal analogues of the Unrestricted Vertex Separator problem from the static world. An (s, z)-temporal separator is a set of vertices whose removal disconnects vertex s from vertex z for every time step in...
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Soil salinity is a serious land degradation issue in *** is a major threat to agriculture *** irrigation water is applied to leach down the salts from the root zone of the plants in the form of a Leaching fraction(LF)...
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Soil salinity is a serious land degradation issue in *** is a major threat to agriculture *** irrigation water is applied to leach down the salts from the root zone of the plants in the form of a Leaching fraction(LF)of irrigation *** the leaching process to be effective,the LF of irriga-tion water needs to be adjusted according to the environmental conditions and soil salinity level in the form of Evapotranspiration(ET)*** relationship between environmental conditions and ET rate is hard to be defined by a linear relationship and data-driven Machine learning(ML)based decisions are required to determine the calibrated Evapotranspiration(ETc)***-assisted ETc is pro-posed to adjust the LF according to the ETc and soil salinity level.A regression model is proposed to determine the ETc rate according to the prevailing tempera-ture,humidity,and sunshine,which would be used to determine the smart LF according to the ETc and soil salinity *** proposed model is trained and tested against the Blaney Criddle method of Reference evapotranspiration(ETo)*** validation of the model from the test dataset reveals the accu-racy of the ML model in terms of Root mean squared errors(RMSE)are 0.41,Mean absolute errors(MAE)are 0.34,and Mean squared errors(MSE)are 0.28 mm *** applications of the proposed solution in a real-time environ-ment show that the LF by the proposed solution is more effective in reducing the soil salinity as compared to the traditional process of leaching.
Smart metering systems (SMS) are popular in industrial and residential areas but can risk privacy by revealing user behaviors. Homomorphic encryption (HE) is a technique that protects data privacy by enabling calculat...
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As the application of smart contracts in blockchain technology becomes increasingly widespread, their security issues have emerged as a focal point of both research and practice. Although symbolic execution technology...
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False news spreads quickly due to the extensive distribution of incorrect or misleading information across digital channels, which is a global problem. This bias undermines the credibility of information, promotes the...
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This paper investigates the impact of feature encoding techniques on the explainability of XAI (Explainable Artificial Intelligence) algorithms. Using a malware classification dataset, we trained an XGBoost model and ...
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In recent years,a gain in popularity and significance of science understanding has been observed due to the high paced progress in computer vision techniques and *** primary focus of computer vision based scene unders...
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In recent years,a gain in popularity and significance of science understanding has been observed due to the high paced progress in computer vision techniques and *** primary focus of computer vision based scene understanding is to label each and every pixel in an image as the category of the object it belongs *** it is required to combine segmentation and detection in a single *** many successful computer vision methods has been developed to aid scene understanding for a variety of real world *** understanding systems typically involves detection and segmentation of different natural and manmade things.A lot of research has been performed in recent years,mostly with a focus on things(a well-defined objects that has shape,orientations and size)with a less focus on stuff classes(amorphous regions that are unclear and lack a shape,size or other characteristics Stuff region describes many aspects of scene,like type,situation,environment of scene *** hence can be very helpful in scene *** methods for scene understanding still have to cover a challenging path to cope up with the challenges of computational time,accuracy and robustness for varying level of scene complexity.A robust scene understanding method has to effectively deal with imbalanced distribution of classes,overlapping objects,fuzzy object boundaries and poorly localized *** proposed method presents Panoptic Segmentation on Cityscapes ***-V2 is used as a backbone for feature extraction that is pre-trained on ***-V2 with state-of-art encoder-decoder architecture of DeepLabV3+with some customization and optimization is employed Atrous convolution along with Spatial Pyramid Pooling are also utilized in the proposed method to make it more accurate and *** promising and encouraging results have been achieved that indicates the potential of the proposed method for robust scene understanding in a fast and
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