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IFGNN: An Individual Fairness Awareness Model for Missing Sensitive Information Graphs
Graph neural networks (GNNs) provide an approach for analyzing complicated graph data for node, edge, and graph-level prediction tasks. However, due...
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Discovering Densest Subgraph over Heterogeneous Information Networks
Densest Subgraph Discovery (DSD) is a fundamental and challenging problem in the field of graph mining in recent years. The DSD aims to determine,...
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Influence Maximization Revisited
Influence Maximization (IM) has been extensively studied, which is to select a set of k seed users from a social network to maximize the expected...
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Maximum Fairness-Aware (k, r)-Core Identification in Large Graphs
Cohesive subgraph mining is a fundamental problem in attributed graph analysis. The k-core model has been widely used in many studies to measure the...
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Emerging Technologies for Edge Intelligent Computing Systems
Future next generation networks are expected to outline a wide class of ambitious challenges, mainly concerning the handling and fulfillment of...
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Offloading Methodologies for Air-Ground Edge Intelligent Computing Systems
Nowadays, a new domain for next Edge Intelligent computing systems, i.e., systems that combine edge computing with artificial intelligence (AI)...
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Predictive Maintenance Optimization Under Stochastic Production in Complex Systems
This paper focuses on predictive maintenance optimization under stochastic production in complex systems using prognostic Remaining Useful Life (RUL)...
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Comparing Power Flow Models in Tree Networks with Stochastic Load Demands
The process of charging electric vehicles (EVs) within an electricity network is a complex stochastic process. Various factors contribute to this...
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Minimizing the Non-value Task Times: A Pickup and Delivery Problem with Two-Dimensional Bin-Packing
The current crisis that struck the automotive industry created an urgency for improvement initiatives throughout the value chain. And, although it is...
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Robust Optimization for Operating Room Scheduling with Uncertain Surgical Durations: Impact of Risk-Aversion on Delay
We introduce a robust optimization model for scheduling operating rooms with uncertain surgical durations. The model addresses multiple operating...
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Multiple Heuristics with Reinforcement Learning to Solve the Safe Shortest Path Problem in a Warehouse
Intelligent vehicles, provided with an ability to move with some level of autonomy, recently became a hot spot in the mobility field. Still,...
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Automated City Segmentation for Pollution Threshold Attribution: The Example of New Cairo
Today the use of vehicles has greatly increased especially in cities where alternative transportation methods cannot really be relied on. Inevitably,...
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Efficient Motor Learning Through Action-Perception Cycles in Deep Kinematic Inference
How does the brain adapt to slow changes in the body’s kinematic chain? And how can it perform complex operations that need tool use? Here, we...
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Dynamical Perception-Action Loop Formation with Developmental Embodiment for Hierarchical Active Inference
To adapt an autonomous system to a newly given cognitive goal, we propose a method to dynamically combine multiple perception-action loops. Focusing...
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Contextual Qualitative Deterministic Models for Self-learning Embodied Agents
This work presents an approach for embodied agents that have to learn models from the least amount of prior knowledge, solely based on knowing which...
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Deep Learning Based Software Vulnerability Detection in Code Snippets and Tag Questions Using Convolutional Neural Networks
With the increase in the usage of the internet for gaining and providing information and knowledge, questionnaire forums are becoming popular means...
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Machine Learning Based Malware Identification and Classification in PDF: A Review Paper
Today’s modern antivirus software fails to provide protection against malicious PDF (Portable Document Format) files, which is considered a threat to...
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Comparative Analysis of Different Machine Learning Based Techniques for Crop Recommendation
Smart Agriculture is gradually becoming a blessing for mankind. It is very much efficient to mitigate food scarcity as well as minimize farmers’...
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QuMaDe: Quick Foreground Mask and Monocular Depth Data Generation
Segmentation of the desired object along with depth estimation is useful in various applications like robotics and autonomous navigation. Any deep...
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Sentiment Analysis: Indian Languages Perspective
Sentiment is a feeling or opinion on the basis of perception of a particular person, product or situation. Process of sentiment analysis (SA)...