Abstract

The present analysis is made about the National Survey Well-being (BIARE, for its acronym in Spanish) constructed by National Institute of Statistics and Geography (INEGI) for obtain subjective indicators well-being and happiness. The objective its to know the characteristics and differences between the people who report the lowest well-being and the highest well-being perception. The happiness indicator was selected from the questions: «How satisfied are you? » and «How many happy are you?», which have a ten-point responding scale, happy people was selected from point 10 (totally satisfied). People unhappy was selected from point 0 = «Nothing satisfied» and point 1 = «A little satisfied». Descriptive statistics and hypothesis test was performed for evaluate group differences using chi-square and U Mann-Whitney test. The conclusion its that the unhappy people, compared with the happy people, perceive unhappiness during long time, obtained achievements and recognition were lowest for unhappy people, more presence of diseases, few economic resources, few social contact with family and friends, lower capacity to give support to people and a lower perception of coping capacities.

Abstract

Public transport is one of the main actors of sustainable transportation. To make an increase in the use of public transport systems and a decrease in private car usage are one of the main purposes of decision makers in many countries. Usage of public transport system has a strong relation with the quality of service. Service quality includes many parameters such as comfort, frequency, information system etc. Fare is another important parameter on demand for public transport systems. All of these parameters are varied by users' perceptions. This study focuses on public transport systems of Denizli, Turkey and investigates users ' perceptions. Bus and paratransit (minibus) modes are regarded in the study. The public survey is performed for these modes. In the surveys, different questions have been asked to participants. Answer of each question is evaluated separately and distribution of each question for gender, ages and jobs are analyzed. Results obtained are summarized and discussed. © 2017, IGI Global. All rights reserved. Document type: Part of book or chapter of book

Abstract

With a marked increase in advanced driver assistance systems (ADAS) being designed and deployed for cars, there is a logical emergence of studies that critically examine the influence these have on driver behavior and attitudes towards risk and safety. The research question addressed within this paper asks to what extent the level of perceived criticality or risk on the part of drivers influences their acceptance of advanced assistance. Document type: Part of book or chapter of book

Abstract

The notion of Common Information Space (CIS) has been proposed in the field of Computer Supported Cooperative Work (CSCW) as a conceptual framework for analyzing cooperative work processes. The area is still in its formative years and requires more research to contribute to its development. This paper presents findings from an investigation undertaken for such an endeavor. Three perceptions of CIS are presented, which are, CIS as a sociotechnical arrangement, dynamic arrangement, and dependency management arrangement. These have been derived from review of existing research contributing to CIS notion development and Grounded Theory analysis of collaborative work process in air traffic control setting. The findings presented in this paper provide a comprehensive and consolidated view of the notion development. The paper contributes to the ongoing discussion of CIS notion development by making theoretical as well as methodological contribution. Document type: Part of book or chapter of book

Abstract

Walking may be considered one of the most sustainable and democratic ways of travelling within a city, thus providing benefits not only to pedestrians but also to the urban environment. Besides, walking is also one of the means of transport most likely subjected to factors outside an individual’s control, like social or physical abilities to walk and the presence of comfortable and safe street infrastructures and services. Therefore, improving urban conditions provided to pedestrians has positive impacts on walkability. At the same time technological solutions and innovations have the power to encourage and support people to walk by overcoming immaterial barriers due to a lack of information or boring travel and they give to decision makers the possibility to gain data to understand how and where people travel. Merging these two dimensions into a unique approach can drastically improve accessibility, attractiveness, safety, comfort and security of urban spaces. In this context, this paper aims to draw a more multifaceted context for walkability, where new technologies assume a key role for introducing new approaches to pedestrian paths planning and design and thus for enhancing this mode of transport. Indeed, by combining more traditional spatial-based and perceptual analysis of the urban environment with technological applications and social media exploitation there will be room to better support the decision on and to enhance satisfaction of walking as well as to easier plan and design more walkable cities. Document type: Part of book or chapter of book

Abstract

The Human Centered Design (HCD) of Partial Autonomous Driver Assistance Systems (PADAS) requires Digital Human Models (DHMs) of human control strategies for simulating traffic scenarios. We describe first results to model lateral and longitudinal control behavior of drivers with simple dynamic Bayesian sensory-motor models according to the Bayesian Programming (BP) approach: Bayesian Autonomous Driver (BAD) models. BAD models are learnt from multivariate time series of driving episodes generated by single or groups of users. The variables of the time series describe phenomena and processes of perception, cognition, and action control of drivers. BAD models reconstruct the joint probability distribution (JPD) of those variables by a composition of conditional probability distributions (CPDs). The real-time control of virtual vehicles is achieved by inferring the appropriate actions under the evidence of sensory percepts with the help of the reconstructed JPD. Document type: Part of book or chapter of book

Abstract

In order to make machines perceive their external environment coherently, multiple sources of sensory information derived from several different modalities can be used (e.g. cameras, LIDAR, stereo, RGB-D, and radars). All these different sources of information can be efficiently merged to form a robust perception of the environment. Some of the mechanisms that underlie this merging of the sensor information are highlighted in this chapter, showing that depending on the type of information, different combination and integration strategies can be used and that prior knowledge are often required for interpreting the sensory signals efficiently. The notion that perception involves Bayesian inference is an increasingly popular position taken by a considerable number of researchers. Bayesian models have provided insights into many perceptual phenomena, showing that they are a valid approach to deal with real-world uncertainties and for robust classification, including classification in time-dependent problems. This chapter addresses the use of Bayesian networks applied to sensory perception in the following areas: mobile robotics, autonomous driving systems, advanced driver assistance systems, sensor fusion for object detection, and EEG-based mental states classification. Document type: Part of book or chapter of book

Abstract

International audience; The aim of this paper is to detect and follow the pipeline in sonar imagery. This work is performed in two steps. The first is to split an image (first experiment) or an transformed line image of pipeline image (second experiment) into regions of uniform texture using the Gray Level Co-occurrence Matrix Method (GLCM). The second addresses the unsupervised learning method based on the Artificial Neural Networks (Self-Organizing Map or SOM) used for determining the comparative model of pipeline from the image. To increase the performance of SOM, we propose a penalty function based on data histogram visualization for detecting the position of pipeline. After a brief review of both techniques (GLCM and SOM), we will present our methods and some results from several experiments on the real world data set.

Abstract

Since the emergence and growing popularity of digital technologies and social media platforms, the relationship between professional and citizen journalism has been challenging. In recent years, however, this critical relationship has de-escalated due to a growing collaboration in shaping a complemental news repertoire. This study examines how social and traditional news use and users’ perceptions on professional journalism affect citizens’ news content creation. Based on survey data from Spain, we first find that social media use for news and users’ positive perceptions on professional journalism predict citizens’ news production behavior. Second, social media use for news and traditional media consumption are explored as additive moderators over the relationship of users’ perceptions on professional journalism on citizens’ news content creation, showing a positive significant effect. This study contributes to current conversations on the potential symbiotic association between professional and citizens journalism, arguing that citizens’ perceptual appraisals on professional journalism are key in fostering public’s participation through news content creation.