Multi-step ahead time series forecasting is essential in Internet of Things (IoT) applications in smart cities and smart homes to make accurate future predictions and precise decision-making. Thus, this study introduc...
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he MITRE ATT&CK framework categorizes threat actor behaviors into a sequence of techniques called the attack lifecycle. Based on this, Our work introduces a dual-labeled dataset that is accurately labeled with dis...
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Autonomous take-off and landing capabilities are crucial in UAV vision-based missions, ensuring adaptive navigation, especially in challenging environments where realtime identification and interaction with a variety ...
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ISBN:
(数字)9798331513283
ISBN:
(纸本)9798331513290
Autonomous take-off and landing capabilities are crucial in UAV vision-based missions, ensuring adaptive navigation, especially in challenging environments where realtime identification and interaction with a variety of landing platforms are required. In this context, this paper presents a servo-visual controller that uses pattern detection and color segmentation techniques to identify take-off/landing platforms and estimate their current orientation. The proposed system was subjected to experimental validation with four platforms positioned in different orientations, heights, and positions, demonstrating its versatility in various conditions. Our study addresses the Flying Robots Trial League challenge, which emulates mapping and inspection tasks in offshore platforms.
Intrusion detection systems continuously watch the activity on a network or computer, looking for attack and intrusion evidences. However, host-based intrusion detectors are particularly vulnerable, as they can be dis...
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Intrusion detection systems continuously watch the activity on a network or computer, looking for attack and intrusion evidences. However, host-based intrusion detectors are particularly vulnerable, as they can be disabled or tampered by successful intruders. This work proposes and implements an architecture model aimed to protect host-based intrusion detectors, through the application of the virtual machine concept. Virtual machine environments are becoming an interesting alternative for several computing systems due to their advantages in terms of cost and portability. The architecture proposed here makes use of the execution spaces separation provided by a virtual machine monitor, in order to separate the intrusion detection system from the system under monitoring. As a consequence, the intrusion detector becomes invisible and inaccessible to intruders. The prototype implementation and the tests performed show the viability of this solution. (c) 2006 Elsevier B.V. All rights reserved.
The recent proliferation of hyper-realistic deepfake videos has drawn attention to the threat of audio and visual forgeries. Most previous studies on detecting artificial intelligence-generated fake videos only utiliz...
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Background Rare diseases can be difficult to diagnose due to limited patient data and broad genetic diversity. Despite the advances in variant prioritization tools, many rare disease cases remain undiagnosed. While la...
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Background Rare diseases can be difficult to diagnose due to limited patient data and broad genetic diversity. Despite the advances in variant prioritization tools, many rare disease cases remain undiagnosed. While large language models (LLMs) have performed well in medical exams, their accuracy in diagnosing rare genetic diseases has not yet been evaluated. Methods To identify causal genes for genetic diseases, we benchmarked various LLMs for gene prioritization. We employed multi-agent and Human Phenotype Ontology (HPO) classification approaches to identify patient case groups based on phenotypes categorizing them into different levels of solvability. To address LLM limitations in ranking large gene sets, we used a divide-and-conquer strategy to break down the ranking task into smaller subsets. Mini-batching inputs and limiting the number of generated tokens improved efficiency. Results In its vanilla form, GPT-4 consistently outperformed the other LLMs with an accuracy around 30%. Multi-agent and HPO classification approaches aided us in distinguishing between confidently-solved and challenging cases. In addition, we observed bias towards well-studied genes and input order sensitivity which are drawbacks of LLMs in disease-causal gene prioritization. Our divide-and-conquer strategy enhanced accuracy by overcoming positional and gene frequency biases in literature. This framework, based on benchmarking insights and novel techniques, significantly optimizes the overall process when identifying disease-causal genes for genetic diseases when compared to our baseline evaluation, and thereby better enables the development of targeted diagnostic and therapeutic interventions. Conclusions Using HPO classification and our novel multi-agent techniques, and our LLM divide-and-conquer strategy (1) highlighted the importance of accounting for differences in patient case solvability and (2) yielded improved performance in identifying causal genes for rare diseases when compare
Motivation: Bulk RNA-Seq is a widely used method for studying gene expression across a variety of contexts. The significance of RNA-Seq studies has grown with the advent of high-throughput sequencing technologies. Com...
Research efforts in Quality of Service (QoS) management have usually addressed the problem under the network infrastructure perspective whereas a business-oriented perspective, named Service Quality Management (SQM), ...
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Two different non_Newtonian models for blood flow are considered,first a simple power law model displaying shear thinning viscosity,and second a generalized Maxwell model displaying both shear thinning viscosity and o...
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Two different non_Newtonian models for blood flow are considered,first a simple power law model displaying shear thinning viscosity,and second a generalized Maxwell model displaying both shear thinning viscosity and oscillating flow viscous_*** models are used along with a Newtonian model to study sinusoidal flow of blood in rigid and elastic straight arteries in the presence of magnetic *** elasticity of blood does not appear to influence its flow behavior under physiological conditions in the large arteries,purely viscous shear thinning model should be quite realistic for simulating blood flow under these *** using the power law model with high shear rate for sinusoidal flow simulation in elastic arteries,the mean and amplitude of the flow rate were found to be lower for a power law fluid compared to Newtonian fluid for the same pressure *** governing equations have been solved by Crank_Niclson *** results are interpreted in the context of blood in the elastic arteries keeping the magnetic effects in *** physiological flow simulation in the aorta,an increase in mean wall shear stress,but a reduction in peak wall shear stress were observed for power law model compared to a Newtonian fluid model for matched flow rate wave *** flow in the presence of transverse magnetic field in an elastic artery is investigated and the influence of factors such as morphology and surface irregularity is evaluated.
A finite element solution for the Navier-Stokes equations for steady flow under the porosity effects through a double branched two-dimensional section of a three-dimensional model of a canine aorta was obtained. The n...
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A finite element solution for the Navier-Stokes equations for steady flow under the porosity effects through a double branched two-dimensional section of a three-dimensional model of a canine aorta was obtained. The numerical solution involves transforming a physical coordinates to a curvilinear boundary fitted coordinate *** steady flow,branch flow and shear stress under the porous effects were discussed in detail. The shear stress at the wall was calculated for Reynolds number of 1 000 with branch to main aortic flow rate ratio as a parameter. The results are compared with earlier works involving experimental data and it has been observed that our results are very close to the exact *** work is in fact an improvement of the work of Sharma et al. (2001) in the sense that computational technique is economic and (Reynolds) number is large.
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