Search results for "neural net"

Are customer star ratings and sentiments aligned? A deep learning study of the customer service experience in tourism destinations

2023

AbstractThis study explores the consistency between star ratings and sentiments expressed in online reviews and how they relate to the different components of the customer experience. We combine deep learning applied to natural language processing, machine learning and artificial neural networks to identify how the positive and negative components of 20,954 online reviews posted on TripAdvisor about tourism attractions in Venice impact on their overall polarity and star ratings. Our findings showed that sentiment valence is aligned with star ratings. A cancel-out effect operates between the positive and negative sentiments linked to the service experience dimensions in mixed-neutral reviews.

The forecasting of the roadside pollutant levels to evaluate traffic management measures in Palermo.

2015

The road transport has become the major source of environmental degradation in urban centres. It produces negative externalities (i.e. pollution, delay, etc.) that are usually connected with the queues of traffic flows and the congestion of the road network. The quantitative estimation of roadside pollutant levels is very complex. Many variables are involved such as the type of vehicle (characterized by different antipollution devices, used fuels, engine temperatures, maintenance level of engines, etc.), the different cinematic conditions of the flows, the urban/road network structure, the weather conditions, etc. Therefore it is important to develop scientific tools able to predict roadsid…

An Automatic Method for Assessing Spiking of Tibial Tubercles Associated with Knee Osteoarthritis

2022

Efficient and scalable early diagnostic methods for knee osteoarthritis are desired due to the disease’s prevalence. The current automatic methods for detecting osteoarthritis using plain radiographs struggle to identify the subjects with early-stage disease. Tibial spiking has been hypothesized as a feature of early knee osteoarthritis. Previous research has demonstrated an association between knee osteoarthritis and tibial spiking, but the connection to the early-stage disease has not been investigated. We study tibial spiking as a feature of early knee osteoarthritis. Additionally, we develop a deep learning based model for detecting tibial spiking from plain radiographs. We collected an…

Application of artificial neural network and genetic algorithm to forecasting of wind power output

2007

DL_Track : Automated analysis of muscle architecture from B-mode ultrasonography images using deep learning

2023

B-mode ultrasound is commonly used to image musculoskeletal tissues, but one major bottleneck is data analysis. Manual analysis is commonly deployed for assessment of muscle thickness, pennation angle and fascicle length in muscle ultrasonography images. However, manual analysis is somewhat subjective, laborious and requires thorough experience. We provide an openly available algorithm (DL_Track) to automatically analyze muscle architectural parameters in ultrasonography images or videos of human lower limb muscles.
 We trained two different neural networks (classic U-net [Ronneberger et al., 2021] and U-net with VGG16 [Simonyan & Zisserman, 2015] pretrained encoder) one to detect …

Nonlinear black-box models for short-term forecasting of air temperature in the town of Palermo

2011

Weather data are crucial to correctly design buildings and their heating and cooling systems and to assess their energy performances. In the intensely urbanized towns the effect of climatic parameters is further emphasized by the Urban Heat Island (UHI) phenomenon, known as the increase in the air temperature of urban areas, compared to the one measured in the extra-urban areas. The analysis of the heat island needs detailed local climate data which can be collected only by a dedicated weather monitoring system. The Department of Energy and Environmental Researches of the University of Palermo (Italy) has built up a weather monitoring system that works 24 hours per day and makes data availa…

Wykorzystanie sztucznej sieci neuronowej do diagnostyki związków chemicznych przy pomocy ich widm w podczerwieni

2013

W artykule przedstawiono możliwości zastosowania sztucznej sieci neuronowej w identyfikacji związków chemicznych metodą tzw. „odcisku palca” oraz opisano budowę opracowanego specjalnie do tego celu narzędzia z wykorzystaniem SSN, jak też sprecyzowano wymogi, jakie muszą być spełnione do jej poprawnego funkcjonowania.

Estimation of wind velocity over a complex terrain using the Generalized Mapping Regressor

2010

Abstract Wind energy evaluation is an important goal in the conversion of energy systems to more environmentally friendly solutions. In this paper, we present a novel approach to wind speed spatial estimation on the isle of Sicily (Italy): an incremental self-organizing neural network (Generalized Mapping Regressor – GMR) is coupled with exploratory data analysis techniques in order to obtain a map of the spatial distribution of the average wind speed over the entire region. First, the topographic surface of the island was modelled using two different neural techniques and by exploiting the information extracted from a digital elevation model of the region. Then, GMR was used for automatic …