Search results for "Machine"
showing 10 items of 2592 documents
Hydraulic power and control system
2020
Abstract In recent years, there has been worldwide interest in the improvement of the mobility of people with lower-limb amputation. Despite significant developments in new technologies during the last decade, commercial below-knee and above-knee prostheses are still energetically passive devices. However, many locomotive functions, like walking up stairs and slopes, need significant power in the knee and ankle joints. The additional power for doing previously mentioned activities needs to be achieved by means of external energy sources, which should be integral prosthetic components. In this chapter the design and development of the hydraulic power and control system are described.
Three-dimentional tracking of human eye
2003
The study of human movements is the object of numerous searches, among them, the study of the face movements and more particularly the eye kinetics estimate represents an important part. A study realized by artificial vision is presented here. It allows to characterize eye movements in normal shooting condition (mobility of the subject, background lighting). Our approach allows to obtain in a simple way the localization of the iris and the characterization of their movement in the three dimensional shape. The absolute 3D movement of eyeballs and their relative movement with regard to the head are obtained, even if this one are moving.
HEALTH MONITORING, FAULT DETECTION AND DIAGNOSIS IN INDUSTRIAL ROTATING MACHINERY BY ADVANCED VIBRATION ANALYSIS
Greenfield FDI attractiveness index: a machine learning approach
2022
Purpose This study aims to propose a comprehensive greenfield foreign direct investment (FDI) attractiveness index using exploratory factor analysis and automated machine learning (AML). We offer offer a robust empirical measurement of location-choice factors identified in the FDI literature through a novel method and provide a tool for assessing the countries' investment potential. Design/methodology/approach Based on five conceptual key sub-domains of FDI, We collected quantitative indicators in several databases with annual data ranging from 2006 to 2019. This study first run a factor analysis to identify the most important features. It then uses AML to assess the relative importance of…
DEVELOPMENT AND IMPLEMENTATION OF MACHINE LEARNING METHODS FOR THE IIF IMAGES ANALYSIS
2021
Behaviour of a speargun with a novel muzzle
2013
The paper presents the results of a numerical and experimental investigation performed on a barrel of a speargun equipped with two kinds of muzzle. In particular, a standard muzzle for speargun (having an elastic propulsion) has been compared with an innovative one called ‘roller’. This new muzzle is equipped with two rollers and special bands. The rubber bands, fixed at the lower side of the barrel, run through the rollers and are engaged in suitable seats of the shaft. These bands are, therefore, longer than the traditional ones and, consequently, with equal force applied by the diver, the roller speargun has a longer range. Thanks to the particular geometry of the new muzzle, one of the …
Remote Sensing Image Classification with Large Scale Gaussian Processes
2017
Current remote sensing image classification problems have to deal with an unprecedented amount of heterogeneous and complex data sources. Upcoming missions will soon provide large data streams that will make land cover/use classification difficult. Machine learning classifiers can help at this, and many methods are currently available. A popular kernel classifier is the Gaussian process classifier (GPC), since it approaches the classification problem with a solid probabilistic treatment, thus yielding confidence intervals for the predictions as well as very competitive results to state-of-the-art neural networks and support vector machines. However, its computational cost is prohibitive for…
Unlocking the potential of deep learning for marine ecology: overview, applications, and outlook
2022
The deep learning revolution is touching all scientific disciplines and corners of our lives as a means of harnessing the power of big data. Marine ecology is no exception. These new methods provide analysis of data from sensors, cameras, and acoustic recorders, even in real time, in ways that are reproducible and rapid. Off-the-shelf algorithms can find, count, and classify species from digital images or video and detect cryptic patterns in noisy data. Using these opportunities requires collaboration across ecological and data science disciplines, which can be challenging to initiate. To facilitate these collaborations and promote the use of deep learning towards ecosystem-based management…
Automatic image-based identification and biomass estimation of invertebrates
2020
1. Understanding how biological communities respond to environmental changes is a key challenge in ecology and ecosystem management. The apparent decline of insect populations necessitates more biomonitoring but the time-consuming sorting and expert-based identification of taxa pose strong limitations on how many insect samples can be processed. In turn, this affects the scale of efforts to map and monitor invertebrate diversity altogether. Given recent advances in computer vision, we propose to enhance the standard human expert-based identification approach involving manual sorting and identification with an automatic image-based technology. 2. We describe a robot-enabled image-based ident…
USE-Net: Incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets
2019
Prostate cancer is the most common malignant tumors in men but prostate Magnetic Resonance Imaging (MRI) analysis remains challenging. Besides whole prostate gland segmentation, the capability to differentiate between the blurry boundary of the Central Gland (CG) and Peripheral Zone (PZ) can lead to differential diagnosis, since tumor's frequency and severity differ in these regions. To tackle the prostate zonal segmentation task, we propose a novel Convolutional Neural Network (CNN), called USE-Net, which incorporates Squeeze-and-Excitation (SE) blocks into U-Net. Especially, the SE blocks are added after every Encoder (Enc USE-Net) or Encoder-Decoder block (Enc-Dec USE-Net). This study ev…