Sfoglia per Soggetto "Machine learning models"
Items 1-15 di 15
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Applying unsupervised and supervised machine learning methodologies in social media textual traffic data
(2019)Traffic increasingly shapes the trajectory of city growth and impacts on the climate change in modern cities. Traffic patterns’ monitoring can provide with innovative practices in understanding city traffic dynamics, ... -
CAS-HtBase: a new database for the study of HTs at the pre-silicon stage of ASICs
(2022)Hardware Trojan (HT) consists a chip-level viruses which aim to leak encrypted information or degrade the performance of the infected device. They are a modification to the original design of a circuit and consist of two ... -
A comparative assessment of machine learning algorithms for events detection
(2019)Nowadays, one can observe massive amount of data production by numerous devices interacting with their environment and end users. [1] Such data can be the subject of advanced processing usually through machine learning ... -
Deep Bidirectional and Unidirectional LSTM Neural Networks in Traffic Flow Forecasting from Environmental Factors
(2021)The application of deep learning techniques in several forecasting problems has been increased the last years, in many scientific fields. In this research, a deep learning structure is proposed, composed mainly of double ... -
Distributed Fuzzy Cognitive Maps for Feature Selection in Big Data Classification
(2022)The features of a dataset play an important role in the construction of a machine learning model. Because big datasets often have a large number of features, they may contain features that are less relevant to the machine ... -
An explainable machine learning model for material backorder prediction in inventory management
(2021)Global competition among businesses imposes a more effective and low-cost supply chain allowing firms to provide products at a desired quality, quantity, and time, with lower production costs. The latter include holding ... -
IPLS: A Framework for Decentralized Federated Learning
(2021)The proliferation of resourceful mobile devices that store rich, multidimensional and privacy-sensitive user data motivate federated learning, a paradigm that enables mobile devices to produce a machine-learning model ... -
A Lipschitz - Shapley Explainable Defense Methodology Against Adversarial Attacks
(2021)Every learning algorithm, has a specific bias. This may be due to the choice of its hyperparameters, to the characteristics of its classification methodology, or even to the representation approach of the considered ... -
MACHINE LEARNING to DEVELOP A MODEL THAT PREDICTS EARLY IMPENDING SEPSIS in NEUROSURGICAL PATIENTS
(2022)Sepsis is currently defined as a "life-threatening organ dysfunction caused by a dysregulated host response to infection". The early detection and prediction of sepsis is a challenging task, with significant potential gains ... -
A new W-SVM kernel combining PSO-neural network transformed vector and Bayesian optimized SVM in GDP forecasting
(2020)Considering that in the literature there is a very limited number of studies proposing new SVM kernels especially in regression problems, the scope of this research is to investigate the development of a novel Support ... -
Prediction of Injuries in CrossFit Training: A Machine Learning Perspective
(2022)CrossFit has gained recognition and interest among physically active populations being one of the most popular and rapidly growing exercise regimens worldwide. Due to the intense and repetitive nature of CrossFit, concerns ... -
Proactive, uncertainty-driven queries management at the edge
(2021)Research community has already revealed the challenges of data processing when performed at the Cloud that may affect the performance of any desired application. The main challenge is the increased latency observed when ... -
The role of compute nodes in privacy-aware decentralized AI
(2022)Mobile devices generate and store voluminous data valuable for training machine learning (ML) models. Decentralized ML model training approaches eliminate the need for sharing such privacy-sensitive data with centralized ... -
Using machine learning to predict mortality and morbidity after Traumatic Brain Injury
(2022)A very interesting and important application of machine learning relates to healthcare. There are several studies that illustrate that machines can assist clinicians to make treatment decisions and forecast disease outcomes. ... -
Vessel's trim optimization using IoT data and machine learning models
(2022)The shipping industry is an important source of greenhouse gas emissions, such as carbon dioxide, methane and nitrogen oxides. In the past few years, environmental and policy reasons dictate the immense reduction of ...