Shared-ride trip planning is one potential field of application within the research domain of geosensor-networks. Such a system is envisioned to provide people in need of transportation (clients) and transportation providers (hosts) with an ad-hoc, peer-to-peer communication, positioning, and planning infrastructure within an urban environment. By doing this, shared-ride trip planning can contr...

Introduction: Travel health centers offer very important health services for individuals traveling abroad. Little is known about the health status and knowledge of travel health, travel-related diseases, and vaccinations of individuals who travel abroad and visit travel health centers. This research studied travelers who visited a travel health center in order to evaluate their...

In this research work, we have the theme of destiny that each person tries to do everything possible obtain a good future in his destiny, I chosen two writers, one from Spain Rosa Chacel and other Iraq Beder Shaker Al-Sayab; them through works taught us different what read.

Citizens are increasingly sharing their location and movements through‘check-ins’ on location based social networks (LBSNs). These services are collecting unprecedented amounts of big data that can be used to study how we travel and interact with our environment. This paper will present the development of a destination choice model for Ontario, Canada which uses data from Foursquare, the larges...

In recent years, mobile phones and access points to free Wi-Fi services have been enhanced, which has made it easier for travellers to share their stories, pictures, and video clips online during a trip. At the same time, online travel review (OTR) websites have grown significantly, allowing users to post their travel experiences, opinions, comments, and ratings in a structured way. Moreover, I...

We analyze the work of urban trip planners and the relevance of trips they recommend upon user queries. We propose to improve the planner recommendations by learning from choices made by travelers who use the transportation network on the daily basis. We analyze individual travelers’ trips and convert them into pair-wise preferences for traveling from a given origin to a destination at a given ...

This paper describes the winning solution to the Taxi Trip Time Prediction Challenge run by Kaggle.com. The goal of the competition was to build a predictive framework that is able to predict the final destination and the total traveling time of taxi rides based on their (initial) partial trajectories. The available data consists of all taxi trips of 442 taxis running in the city of Porto withi...

In this article, we describe the development of a transit trip planner (TTP) for mobile devices called Transitr, and evaluate its performance. The system predicts the shortest paths between any two points in the transit network using real-time information provided by a third party bus arrival prediction system, relying on GPS equipped transit vehicles. Users submit their origin and destination ...