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IoMT Applications Perspectives: From Opportunities and Security Challenges to Cyber-Risk Management
The Internet of Things (IoT) paradigm is gaining popularity since it promotes the development of several smart and innovative applications....
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Implementation of the C4.5 Algorithm in the Internet of Things Applications
The Internet of Things changes how people perform their daily activities. With data mining techniques, the Internet of Things assists users to...
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Multivariate Procedure for Modeling and Prediction of Temperature in Punjab, Pakistan
Climate study often relies upon global climate models (GCM) to project future scenarios of change in climate behavior. This study aims to refine GCM...
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A New Proposed Model for the Influence of Climate Change on the Tension Anticipation in Hospital Emergencies
Various threats of different nature have emerged over the past decades such as COVID-19, terrorism, industrial, and environmental disasters. They...
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Intrusion Detection Systems Using Machine Learning
Intrusion detection systems (IDS) have developed and evolved over time to form an important component in network security. The aim of an intrusion...
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AutomaTutor: An Educational Mobile App for Teaching Automata Theory
Automata theory is one of the core theories in computer science because it allows scientists and practitioners to understand the complexity of...
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Considerations and Challenges
As with any new technology, continuous biometric authentication systems have a variety of considerations and challenges that must be addressed before...
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Introduction
This chapter introduces the research topic of face de-identification covered in this book. First, it describes the background that motivates the need...
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Differential Private Identification Protection for Face Images
In this chapter, we focus on providing theory guarantee to improve fundamental face de-identification. We propose IdentityDP, a face anonymization...
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Executive Summary
Recent advancements in machine learning, particularly in natural language processing, have been marked by the emergence of large models pretrained on...
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Beyond Words: A Comparative Analysis of LLM Embeddings for Effective Clustering
The document clustering process involves the grou** of similar unlabeled textual documents. This task relies on the use of document embedding...
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Data Quality in NLP: Metrics and a Comprehensive Taxonomy
Data quality is a crucial factor for the success of natural language processing (NLP) models. However, there is a lack of a standard taxonomy for...
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GloNets: Globally Connected Neural Networks
Deep learning architectures suffer from depth-related performance degradation, limiting the effective depth of neural networks. Approaches like...
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Example-Based Explanations of Random Forest Predictions
A random forest prediction can be computed by the scalar product of the labels of the training examples and a set of weights that are determined by...
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An Interpretable Human-in-the-Loop Process to Improve Medical Image Classification
Medical imaging classification improves patient prognoses by providing information on disease assessment, staging, and treatment response. The high...
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Node Classification in Random Trees
We propose a method for the classification of objects that are structured as random trees. Our aim is to model a distribution over the node label...
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Variational Perspective on Fair Edge Prediction
Algorithmic fairness has been of great interest in the machine learning community and more recently in the graph context. In this paper, we address...
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\(\lambda \) -DBSCAN: Augmenting DBSCAN with Prior Knowledge
State-of-the-art density based cluster algorithms offer remarkable speed and robustness. However, they do not allow the user to make local changes...
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Efficient Lookahead Decision Trees
Conventionally, decision trees are learned using a greedy approach, beginning at the root and moving toward the leaves. At each internal node, the...
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Unsupervised Representation Learning for Smart Transportation
In the automotive industry, sensors collect data that contain valuable driving information. The collected datasets are in multivariate time series...