Search results for "Machine"

An Efficient and Secure Energy Trading Approach with Machine Learning Technique and Consortium Blockchain

2022

In this paper, a secure energy trading mechanism based on blockchain technology is proposed. The proposed model deals with energy trading problems such as insecure energy trading and inefficient charging mechanisms for electric vehicles (EVs) in a vehicular energy network (VEN). EVs face two major problems: finding an optimal charging station and calculating the exact amount of energy required to reach the selected charging station. Moreover, in traditional trading approaches, centralized parties are involved in energy trading, which leads to various issues such as increased computational cost, increased computational delay, data tempering and a single point of failure. Furthermore, EVs fac…

Network Threat Detection Using Machine/Deep Learning in SDN-Based Platforms: A Comprehensive Analysis of State-of-the-Art Solutions, Discussion, Chal…

2022

A revolution in network technology has been ushered in by software defined networking (SDN), which makes it possible to control the network from a central location and provides an overview of the network’s security. Despite this, SDN has a single point of failure that increases the risk of potential threats. Network intrusion detection systems (NIDS) prevent intrusions into a network and preserve the network’s integrity, availability, and confidentiality. Much work has been done on NIDS but there are still improvements needed in reducing false alarms and increasing threat detection accuracy. Recently advanced approaches such as deep learning (DL) and machine learning (ML) have been implemen…

From 12 to 1 ECG lead: multiple cardiac condition detection mixing a hybrid machine learning approach with a one-versus-rest classification strategy

2022

Abstract Objective. Detecting different cardiac diseases using a single or reduced number of leads is still challenging. This work aims to provide and validate an automated method able to classify ECG recordings. Performance using complete 12-lead systems, reduced lead sets, and single-lead ECGs is evaluated and compared. Approach. Seven different databases with 12-lead ECGs were provided during the PhysioNet/Computing in Cardiology Challenge 2021, where 88 253 annotated samples associated with none, one, or several cardiac conditions among 26 different classes were released for training, whereas 42 896 hidden samples were used for testing. After signal preprocessing, 81 features per ECG-le…

Development of an ultrasound-based muscle texture analysis as a potential imaging biomarker for frailty phenotype

2018

Las herramientas habituales para evaluar la fragilidad muestran, entre otras características, una baja sensibilidad y un bajo valor predictivo positivo. Es por eso que, en este estudio prospectivo-retrospectivo, nos preguntamos si es posible identificar y desarrollar biomarcadores cuantitativos a partir de imágenes de ultrasonido muscular, para la identificación de sujetos con riesgo de fragilidad. Para ello utlilizamos el análisis de textura de ecointensidad con ayuda del aprendizaje automático (machine learning, en inglés) como enfoque experimental para responder a esta pregunta. El proyecto se desarrolló en consulta externa, donde se realizó la ecografía muscular. Al final de la adquisic…

Assessing incentives to increase digital payment acceptance and usage: A machine learning approach.

2022

An important step to achieve greater financial inclusion is to increase the acceptance and usage of digital payments. Although consumer adoption of digital payments has improved dramatically globally, the acceptance and usage of digital payments for micro, small, and medium-sized retailers (MSMRs) remain challenging. Using random forest estimation, we identify 14 key predictors out of 190 variables with the largest predictive power for MSMR adoption and usage of digital payments. Using conditional inference trees, we study the importance of sequencing and interactions of various factors such as public policy initiatives, technological advancements, and private sector incentives. We find tha…

Technics Amélioration for geo-localization in wsn via smart computing and real time application

2022

New technologies exploiting digital information acquisition by radio frequency techniques are now commonly used in various practical fields. They are most often used to measure a variety of physical variables such as temperature, humidity, speed, etc. and are gathered under the name of Wireless Sensor Networks “WSN”. For this variant of applications, the accurate location of connected sensor nodes remains an important issue for researchers and industrial applications. Indeed, existing localization algorithms can be classified into two categories known as « range-based » and « range-free ». Range-based localization systems are characterized by major drawbacks. The first one is the cost of th…

Gender analysis and attention to gender: An experimental framework

Gender aspects are gaining more and more attention for policy makers, practitioners and faculties. They also have a great importance for funding purposes, since many calls for proposals by national and international agencies require a gender plan and/or an analysis of the gender aspect, especially referring to the extent to which a candidate research project affects differently men and women. In this context, we want to understand whether there exists a relationship between the gender diversity of corporate boards of directors and the way a business articulates gender aspects on their corporate communications and activities on the Internet. To achieve this goal, we created a set of meaningf…

On the Suitability of Neural Networks as Building Blocks for the Design of Efficient Learned Indexes

2022

With the aim of obtaining time/space improvements in classic Data Structures, an emerging trend is to combine Machine Learning techniques with the ones proper of Data Structures. This new area goes under the name of Learned Data Structures. The motivation for its study is a perceived change of paradigm in Computer Architectures that would favour the use of Graphics Processing Units and Tensor Processing Units over conventional Central Processing Units. In turn, that would favour the use of Neural Networks as building blocks of Classic Data Structures. Indeed, Learned Bloom Filters, which are one of the main pillars of Learned Data Structures, make extensive use of Neural Networks to improve…

Machine learning and ontology in eCoaching for personalized activity level monitoring and recommendation generation.

2022

AbstractLeading a sedentary lifestyle may cause numerous health problems. Therefore, passive lifestyle changes should be given priority to avoid severe long-term damage. Automatic health coaching system may help people manage a healthy lifestyle with continuous health state monitoring and personalized recommendation generation with machine learning (ML). This study proposes a semantic ontology model to annotate the ML-prediction outcomes and personal preferences to conceptualize personalized recommendation generation with a hybrid approach. We use a transfer learning approach to improve ML model training and its performance, and an incremental learning approach to handle daily growing data …

Color and multispectral image processing for the detection of inflammatory lesions of the stomach

2019

The work presented in this manuscript is part of the ANR project EMMIE. This project aims to develop an innovative multimodal system for the detection of inflammatory lesions in the stomach. To this purpose, a prototype has been developed to be able to acquire NBI endoscopic images and multispectral images during human's antrum exploration. The prototype is made of a standard endoscope and multispectral images.The prototype can acquire two types of data: NBI images and spectra. These two modalities are processed independently. Common image processing features are used to recognize four kind of diseases: active gastritis, chronic gastritis, metaplasia and atrophy. In addition, visual based f…