Pricing Bundles for Airline Revenue Management

International audienceRevenue management (RM) has become a critical asset for airlines performances. The common RM strategy used to be capacity based, but the industry gradually started to move to dynamic pricing RM, where the notion of class is no longer used and prices are freely chosen in real time. Recent airline marketing strategies are trying to push the purchase of ancillaries and the main challenge lays in the choice of which bundles to show, given that there is a combinatorial number of possible ancillaries groups. We proposed an efficient way to calculate the bundle subset which maximize the revenue

A flexible and scalable architecture for human-robot interaction

Recent developments and advancements in several areas of Computer Science such as Semantic Web, Natural Language Understanding, Knowledge Representation, and more in general Artificial Intelligence have enabled to develop automatic and smart systems able to address various challenges and tasks. In this paper, we present a scalable and flexible humanoid robot architecture which employs artificial intelligent technologies and developed on top of the programmable humanoid robot called Zora. The framework is composed by three different modules which enable the interaction between Zora and a human for tasks such as Sentiment Understanding, Question-Answering, and automatic Object Recognition. The framework is flexible and extensible, and can be augmented by other modules. Moreover, the embedded modules we present are general, in the sense that they can be easily enriched by adding training resources for the presented sub-components. The design of each module consists of two components (i) a front-end system which is responsible for the interaction with humans, and (ii) a back-end component which resides on server side and performs the heavy computation

Pricing Bundles for Airline Revenue Management

International audienceRevenue management (RM) has become a critical asset for airlines performances. The common RM strategy used to be capacity based, but the industry gradually started to move to dynamic pricing RM, where the notion of class is no longer used and prices are freely chosen in real time. Recent airline marketing strategies are trying to push the purchase of ancillaries and the main challenge lays in the choice of which bundles to show, given that there is a combinatorial number of possible ancillaries groups. We proposed an efficient way to calculate the bundle subset which maximize the revenue

An Abstraction Layer Exploiting Voice Assistant Technologies for Effective Human—Robot Interaction

A lot of people have neuromuscular problems that affect their lives leading them to lose an important degree of autonomy in their daily activities. When their disabilities do not involve speech disorders, robotic wheelchairs with voice assistant technologies may provide appropriate human–robot interaction for them. Given the wide improvement and diffusion of Google Assistant, Apple’s Siri, Microsoft’s Cortana, Amazon’s Alexa, etc., such voice assistant technologies can be fully integrated and exploited in robotic wheelchairs to improve the quality of life of affected people. As such, in this paper, we propose an abstraction layer capable of providing appropriate human–robot interaction. It allows use of voice assistant tools that may trigger different kinds of applications for the interaction between the robot and the user. Furthermore, we propose a use case as a possible instance of the considered abstraction layer. Within the use case, we chose existing tools for each component of the proposed abstraction layer. For example, Google Assistant was employed as a voice assistant tool; its functions and APIs were leveraged for some of the applications we deployed. On top of the use case thus defined, we created several applications that we detail and discuss. The benefit of the resulting Human–Computer Interaction is therefore two-fold: on the one hand, the user may interact with any of the developed applications; on the other hand, the user can also rely on voice assistant tools to receive answers in the open domain when the statement of the user does not enable any of the applications of the robot. An evaluation of the presented instance was carried out using the Software Architecture Analysis Method, whereas the user experience was evaluated through ad-hoc questionnaires. Our proposed abstraction layer is general and can be instantiated on any robotic platform including robotic wheelchairs

Psychometric properties of the Autism Spectrum Disorder in Adults Screening Questionnaire (ASDASQ) in a sample of Italian psychiatric outpatients

Background: The present study aimed to examine the reliability and validity of the Italian version of the Autism Spectrum Disorder in Adults Screening Questionnaire (ASDASQ), a screening tool for autism spectrum disorder (ASD) among psychiatric outpatients. Methods: We recruited 340 subjects via an outpatient psychiatric service in Italy. Forty-eight had a diagnosis of ASD, confirmed after a comprehensive clinical assessment and the administration of the Autism Diagnostic Observation Schedule-2 (ADOS-2). The remaining 292 participants had other diagnoses, confirmed after a careful psychiatric evaluation and the administration of the Structured Clinical Interview for DSM-5 (SCID-5). The ASDASQ was administered to contact clinicians of each subject. Results: The ASDASQ showed outstanding accuracy (AUC = 0.96) in discriminating between ASD and non-ASD patients, with good sensitivity (0.85) and specificity (0.92). Agreement with clinical diagnosis was substantial (k = 0.68). Internal consistency of the tool was good (Cronbach's alpha = 0.82), while intra- (ICC = 0.97) and inter-rater reliability (ICC = 0.92) were excellent. We found also a moderate correlation between ASDASQ and ADOS-2 scores in the ASD sample (r = 0.56). Conclusion: Our findings suggest that the ASDASQ, in the Italian adaptation, may be considered a quick, simple, and effective tool to screen for ASD among psychiatric outpatients. Further studies are needed to evaluate its utility in other clinical settings