3This study presents a data mining approach for modeling TripAdvisor score using 504 reviews 4 published in 2015 for the 21 hotels located in the Strip, Las Vegas. Nineteen quantitative features 5 characterizing the reviews, hotels and the users were prepared and used for feeding a support 6 vector machine for modeling the score. The results achieved reveal the model demonstrated 7 adequate predictive performance. Therefore, a sensitivity analysis was applied over the model for 8 extracting useful knowledge translated into features' relevance for the score. The findings 9 unveiled user features related to TripAdvisor membership experience play a key role in 10 influencing the scores granted, clearly surpassing hotel features. Also, both seasonality and the 11 day of the week were found to influence scores. Such knowledge may be helpful in directing 12 efforts to answer online reviews in alignment with hotel strategies, by profiling the reviews 13 according to the member and review date. Keywords 16Customer feedback; customer reviews; online reviews; knowledge extraction; data mining; 17 modeling; sensitivity analysis; Las Vegas. Introduction 21The Online Travel Agencies (OTA) are now the most used tool of travel booking, both for the 22 means of transport and accommodation (Mauri & Minazzi, 2013) and, consequently, online 23 reviews have been exponentially increasing its use and impact in the hospitality industry over the 24 last years, due to the social media and technological evolution. In fact, nowadays potential hotel 25 customers search for online feedback before travelling and base their purchase decisions on 26 online reviews (Mauri & Minazzi, 2013). Therefore, electronic word-of-mouth (eWOM), which 27 according to Henning-Thurau et al. (2004, pp. 39) is defined as "any positive or negative 28 statement made by potential, actual or former customers about a product or company, which is 29 made available to a multitude of people and institutions via the internet", has become a huge 30 aspect when travelling, since currently every consumer has access to the internet and can easily 31 express either positive or negative feedback. Most importantly, it is an online tool to be used 32 when others seek for advice as part of the decision-making process, such as where to stay, 33 especially in hospitality industry, as consumers are purchasing an experience and cannot predict 34 its evaluation (Sparks & Browning, 2011). Moreover, holidays can be considered as a high risk 35 and involvement purchase, due to its usual personal importance and also high value of money 36 (Papathanassis & Knolle, 2011). Service quality is a determinant of the customer's perceptions 37 and their feedback. The ideal would be that the target's expectations meet the perceptions, which 38 will directly influence a positive word of mouth, contributing for a development of reputation 39 and trust (Corbitt et al., 2003). Hence, research contributions that unveil and provide in-depth 40 understanding on the features that have the mo...

The static stability of hexapods motivates their design for tasks in which stable locomotion is required, such as navigation across complex environments. This task is of high interest due to the possibility of replacing human beings in exploration, surveillance and rescue missions. For this application, the control system must adapt the actuation of the limbs according to their surroundings to ensure that the hexapod does not tumble during locomotion. The most traditional approach considers their limbs as robotic manipulators and relies on mechanical models to actuate them. However, the increasing interest in model-free models for the control of these systems has led to the design of novel solutions. Through a systematic literature review, this paper intends to overview the trends in this field of research and determine in which stage the design of autonomous and adaptable controllers for hexapods is.

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A new method to classify and identify different types of road pavements by analysing the near field sound profile and texture using statistical learning methods is proposed. A set of characteristics were extracted from the noise profile and from the road surface texture. Sound measurements were carried out following the close-proximity method with the texture descriptors being provided by a high speed profilometer system. As a first approach, it is assumed that the features extracted from the noise and texture characteristics follow normal distributions. However, this assumption is not completely verified for all types of road surfaces. The method presented herein exploits the use of Bayesian analysis complemented by a neural network in order to improve the classification results.

Hexapod locomotion in unstructured environments relies on an efficient posture adjustment with the terrain topology. This paper presents a strategy to adapt the hexapod torso orientation through ground plane estimation. With an Inertial Measurement Unit (IMU) and the robot kinematic model, the current supporting feet coordinates are calculated, and the relative inclination between the ground and the torso angular position can be obtained. This information is used to adjust the novel foothold positions, in order to ensure the hexapod posture remains stable. The torso height is also controlled to avoid collisions with the ground asperities and decrease its deviation during motion. The proposed method is evaluated in a complex terrain made of 0.1×0.1 m blocks with variable height, causing different slopes across the field. Through result analysis, a significant behavior improvement is observed, due to the reduction of the torso posture oscillation and the increase of its locomotion efficiency.

In controlled environments, the hexapod limbs actuation can be controlled as a closed system. However, the increase of the terrain complexity implies an adaptation of their trajectory based on the robot interactions with the environment. Thus, the implementation of terrain data to the legs actuation potentially improves the hexapod quasi-static stability in these scenarios. This paper presents an adaptive control system based on the limbs reactive behavior for navigation across complex environments. Through force sensors placed on the foot-tips, the model detects the foot-ground interactions and adjusts the limbs trajectory accordingly. Furthermore, to ensure that the robot posture remains stable throughout locomotion, an impedance control is implemented in each limb. The proposed control architecture was tested in an irregular ground through dynamic simulations with five different configurations. Through result analysis, an optimized model was achieved which reduces the oscillations of the torso and slippage of the feet when walking across obstacles.

The functional Magnetic Resonance Imaging (fMRI) is a technique with increasing applications in studying the brain function. The blood-oxygenation-level-dependent (BOLD) is a fMRI method that allows the detection of brain activated regions after the application of an external stimulus, e.g., visual or auditive. This technique is based on the assumption that the metabolism increases in activated areas as well as the oxygen uptake. Analising this information is a challenging problem because the BOLD signal is very noisy and its changes due to the application of a stimulus are very weak. Therefore, the detection of temporal correlations with the applied stimulus requires sophisticated statistical algorithms to understand if the changes on the BOLD signal are pure noise or are related with the applied stimulus, called paradigm in the fMRI scope.

Generating adaptive locomotion has seen a growing interest for the design of hexapods due to improving the autonomy of these robots, allowing them to execute tasks in more demanding environments. Data from the robot's surrounding must be acquired and processed to adjust the locomotion, and aid with the actuation of the six limbs. This paper aims at using force sensors placed on the feet of a hexapod to control the changes of the gait phase of each limb. These sensors also assist in the search of new footholds when no contact forces are established with the ground. The system is tested in a smooth irregular terrain with obstacles, steps, and ramps, using CoppeliaSim and ROS (Robot Operating System), to dynamically evaluate the behavior of the hexapod.