Incident detection using data from social media

This is an accepted manuscript of an article published by IEEE in 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC) on 15/03/2018, available online: https://ieeexplore.ieee.org/document/8317967/citations#citations The accepted version of the publication may differ from the final published version.© 2017 IEEE. Due to the rapid growth of population in the last 20 years, an increased number of instances of heavy recurrent traffic congestion has been observed in cities around the world. This rise in traffic has led to greater numbers of traffic incidents and subsequent growth of non-recurrent congestion. Existing incident detection techniques are limited to the use of sensors in the transportation network. In this paper, we analyze the potential of Twitter for supporting real-time incident detection in the United Kingdom (UK). We present a methodology for retrieving, processing, and classifying public tweets by combining Natural Language Processing (NLP) techniques with a Support Vector Machine algorithm (SVM) for text classification. Our approach can detect traffic related tweets with an accuracy of 88.27%.Published versio

Traffic event detection framework using social media

This is an accepted manuscript of an article published by IEEE in 2017 IEEE International Conference on Smart Grid and Smart Cities (ICSGSC) on 18/09/2017, available online: https://ieeexplore.ieee.org/document/8038595 The accepted version of the publication may differ from the final published version.© 2017 IEEE. Traffic incidents are one of the leading causes of non-recurrent traffic congestions. By detecting these incidents on time, traffic management agencies can activate strategies to ease congestion and travelers can plan their trip by taking into consideration these factors. In recent years, there has been an increasing interest in Twitter because of the real-time nature of its data. Twitter has been used as a way of predicting revenues, accidents, natural disasters, and traffic. This paper proposes a framework for the real-time detection of traffic events using Twitter data. The methodology consists of a text classification algorithm to identify traffic related tweets. These traffic messages are then geolocated and further classified into positive, negative, or neutral class using sentiment analysis. In addition, stress and relaxation strength detection is performed, with the purpose of further analyzing user emotions within the tweet. Future work will be carried out to implement the proposed framework in the West Midlands area, United Kingdom.Published versio

Electron Depletion Due to Bias of a T-Shaped Field-Effect Transistor

A T-shaped field-effect transistor, made out of a pair of two-dimensional electron gases, is modeled and studied. A simple numerical model is developed to study the electron distribution vs. applied gate voltage for different gate lengths. The model is then improved to account for depletion and the width of the two-dimensional electron gases. The results are then compared to the experimental ones and to some approximate analytical calculations and are found to be in good agreement with them.Comment: 16 pages, LaTex (RevTex), 8 fig

Multi-hazard response analysis of a 5MW offshore wind turbine

Wind energy has already dominant role on the scene of the clean energy production. Well-promising markets, like China, India, Korea and Latin America are the fields of expansion for new wind turbines mainly installed in offshore environment, where wind, wave and earthquake loads threat the structural integrity and reliability of these energy infrastructures. Along these lines, a multi-hazard environment was considered herein and the structural performance of a 5 MW offshore wind turbine was assessed through time domain analysis. A fully integrated model of the offshore structure consisting of the blades, the nacelle, the tower and the monopile was developed with the use of an aeroelastic code considering the interaction between the elastic and inertial forces, developed in the structure, as well as the generated aerodynamic and hydrodynamic forces. Based on the analysis results, the dynamic response of the turbine's tower was found to be severely affected by the earthquake excitations. Moreover, fragility analysis based on acceleration capacity thresholds for the nacelle's equipment corroborated that the earthquake excitations may adversely affect the reliability and availability of wind turbines

Synthesis of glutathione analogues and screening as substrates & inhibitors for human glutathione transferase p1‐1

A major detoxification mechanism of the cell involves the glutathione transferase (GST)‐catalyzed formation of glutathione (GSH) conjugates with various xenobiotics Based on the same mechanism, GST overexpression may lead to multidrug resistant phenotypes Therefore, several compounds with inhibitory potency against GSTs have been developed as potential tools fortackling GST-­‐attributed MDR. Several individual compounds and prodrugs have been proposed as GST‐inhibiting substances. In addition, GSH analogues have been considered as specific GST inhibitors, with particular attention been directed towards the synthesis of GSH analogues stable against γ‐glutamyltranspeptidase (γGT) and peptidases, as GST inhibitors

Natural ventilation in urban areas : results of the European Project URBVENT Part 1: urban environment

The application of natural ventilation is more difficult in urban than in rural environment, especially in street canyons due to reduced wind velocity, urban heat island, noise and pollution, which are considered to be important barriers to the application of natural ventilation. The wind, temperature, noise attenuation and outdoor-indoor pollution transfer were measured in a large range of variation and various types of urban configuration. The models obtained can be used in the initial stages of building design in order to assess the viability of natural ventilation in urban environment, especially in street canyons

Robust statistical frontalization of human and animal faces

The unconstrained acquisition of facial data in real-world conditions may result in face images with significant pose variations, illumination changes, and occlusions, affecting the performance of facial landmark localization and recognition methods. In this paper, a novel method, robust to pose, illumination variations, and occlusions is proposed for joint face frontalization and landmark localization. Unlike the state-of-the-art methods for landmark localization and pose correction, where large amount of manually annotated images or 3D facial models are required, the proposed method relies on a small set of frontal images only. By observing that the frontal facial image of both humans and animals, is the one having the minimum rank of all different poses, a model which is able to jointly recover the frontalized version of the face as well as the facial landmarks is devised. To this end, a suitable optimization problem is solved, concerning minimization of the nuclear norm (convex surrogate of the rank function) and the matrix ℓ1 norm accounting for occlusions. The proposed method is assessed in frontal view reconstruction of human and animal faces, landmark localization, pose-invariant face recognition, face verification in unconstrained conditions, and video inpainting by conducting experiment on 9 databases. The experimental results demonstrate the effectiveness of the proposed method in comparison to the state-of-the-art methods for the target problems

Investigation of hydrostatic fluid forces in varying clearance turbomachinery seals

Varying clearance, rotor-following seals are a key technology for meeting the demands of increased machine flexibility for conventional power units. These seals follow the rotor through hydrodynamic or hydrostatic mechanisms. Forward-facing step (FFS) and Rayleigh step designs are known to produce positive fluid stiffness. However, there is very limited modeling or experimental data available on the hydrostatic fluid forces generated from either design. A quasi-one-dimensional (1D) method has been developed to describe both designs and validated using test data. Tests have shown that the FFS and the Rayleigh step design are both capable of producing positive film stiffness and there is little difference in hydrostatic force generation between the two designs. This means any additional hydrodynamic features in the Rayleigh step design should have a limited effect on hydrostatic fluid stiffness. The analytical model is capable of modeling both the inertial fluid forces and the viscous fluid losses, and the predictions are in good agreement with the test data