Search results for "Artificial Intelligence"

Argumentative reasoning and taxonomic analysis for the identification of medical errors

2015

Telemedicine consists of the use of information and communication technologies (ICTs) in the practice of medicine. The massive digitalisation of the society is changing the behaviour of ordinary people even in medical sectors. The impact of digitisation is also having impacts on teleexpertise, where a medical professional can remotely ask some advices through the use of ICTs to provide treatment to a patient in critical conditions in remote environment. However, sometimes the outcome of such advice obtained remotely can lead to medical errors. In these situations, it is important to determine whether the causes of the errors could have been avoidable or not for the purposes of establishing …

Religious and spiritual motifs in the art of the patients of Nikkilä Hospital

2021

This article focuses on religiousness and spirituality in the art works of psychiatric patients of Nikkilä Hospital, Finland. The pictures analysed here belong to a collection held at the Helsinki City Museum and they were made during the twentieth century. The theoretical frame of the study is a cultural study of mental health. The collection is approached as presenting a specific kind of imagery which has connections not only to the personal history and diagnoses of the patients; their cultural context and hospital environment is also taken into account. The religiousness and spirituality of the Nikkilä collection are also compared with outsider art and examples of art history internation…

Modeling the insect mushroom bodies: application to a delayed match-to-sample task.

2013

Despite their small brains, insects show advanced capabilities in learning and task solving. Flies, honeybees and ants are becoming a reference point in neuroscience and a main source of inspiration for autonomous robot design issues and control algorithms. In particular, honeybees demonstrate to be able to autonomously abstract complex associations and apply them in tasks involving different sensory modalities within the insect brain. Mushroom Bodies (MBs) are worthy of primary attention for understanding memory and learning functions in insects. In fact, even if their main role regards olfactory conditioning, they are involved in many behavioral achievements and learning capabilities, as …

Evolutionary Algorithms and Metaheuristics : Applications in Engineering Design and Optimization

2018

Demand Sharing Inaccuracies in Supply Chains: A Simulation Study

2018

We investigate two main sources of information inaccuracies (i.e., errors and delays) in demand information sharing along the supply chain (SC). Firstly, we perform a systematic literature review on inaccuracy in demand information sharing and its impact on supply chain dynamics. Secondly, we model several SC settings using system dynamics and assess the impact of such information inaccuracies on SC performance. More specifically, we study the impact of four factors (i.e., demand error, demand delay, demand variability, and average lead times) using three SC dynamic performance indicators (i.e., bullwhip effect, inventory variability, and average inventory). The results suggest that demand …

Methodological advances in brain connectivity

2012

Determining how distinct neurons or brain regions are connected and communicate with each other is a crucial point in neuroscience, as it allows to investigate how the functional integration of specialized neural populations enables the emergence of coherent cognitive and behavioral states. The general concept of brain connectivity encompasses different aspects: structural connectivity is related to the description of anatomical pathways and synaptic connections; functional connectivity investigates statistical dependencies between spatially separated brain regions; effective connectivity refers to models aimed at elucidating driver-response relationships. The study of these different modes…

New Objective Refraction Metric Based on Sphere Fitting to the Wavefront

2017

Purpose. To develop an objective refraction formula based on the ocular wavefront error (WFE) expressed in terms of Zernike coefficients and pupil radius, which would be an accurate predictor of subjective spherical equivalent (SE) for different pupil sizes.Methods. A sphere is fitted to the ocular wavefront at the center and at a variable distance,t. The optimal fitting distance,topt, is obtained empirically from a dataset of 308 eyes as a function of objective refraction pupil radius,r0, and used to define the formula of a new wavefront refraction metric (MTR). The metric is tested in another, independent dataset of 200 eyes.Results. For pupil radiir0≤2 mm, the new metric predicts the equ…

Intraocular Telescopic System Design: Optical and Visual Simulation in a Human Eye Model

2016

Purpose. To design an intraocular telescopic system (ITS) for magnifying retinal image and to simulate its optical and visual performance after implantation in a human eye model. Methods. Design and simulation were carried out with a ray-tracing and optical design software. Two different ITS were designed, and their visual performance was simulated using the Liou-Brennan eye model. The difference between the ITS was their lenses’ placement in the eye model and their powers. Ray tracing in both centered and decentered situations was carried out for both ITS while visual Strehl ratio (VSOTF) was computed using custom-made MATLAB code. Results. The results show that between 0.4 and 0.8 mm of d…

Collecting and Using Students’ Digital Well-Being Data in Multidisciplinary Teaching

2018

This article examines how students (N=198; aged 13 to 17) experienced the new methods for sensor-based learning in multidisciplinary teaching in lower and upper secondary education that combine the use of new sensor technology and learning from self-produced well-being data. The aim was to explore how students perceived new methods from the point of view of their learning and did the teaching methods provide new information that could promote their own well-being. We also aimed to find out how to collect digital well-being data from a large number of students and how the collected big data set can be utilized to predict school success from the students’ well-being data by using machine lear…

Comparison of Micro X-ray Computer Tomography Image Segmentation Methods: Artificial Neural Networks Versus Least Square Support Vector Machine

2013

Micro X-ray computer tomography (XCT) is a powerful non-destructive method for obtaining information about rock structures and mineralogy. A new methodology to obtain porosity from 2D XCT digital images using artificial neural network and least square support vector machine is demonstrated following these steps: the XCT image was first preprocessed, thereafter clustering algorithms such as K-means, Fuzzy c-means and self-organized maps was used for image segmentation. Then artificial neural network was applied for image classification. For comparison, least square support vector machine approach was used for classification labeling of the scan images. The methodology shows how artificial ne…