In-store music and aroma influences on shopper behavior and satisfaction

Retail markets are increasingly competitive and retailers continuously look to differentiate their retail offering. One way to differentiate is by providing a pleasant and exciting shopping ambience. This paper experimentally tests the effects of music (volume high or low) and aroma (vanilla scent present/absent) on young fashion shoppers in a real retail setting. Results show that volume of music and the presence of a vanilla aroma both have a significant impact on shoppers' emotions and satisfaction levels. Additional analysis reveals that the arousal induced by music and aroma results in increased pleasure levels, which in turn positively influences shopper behaviors, including time and money spend, approach behavior, and satisfaction with the shopping experience. Direct effects of arousal on behaviors as well as an interaction effect between music and aroma on pleasure and time spent in the store are also present. The paper contributes to the better understanding of shoppers' emotions and shopper behaviors in response to in-store atmospherics and offers retailers practical insights into how to create competitive advantage by customizing the atmosphere in their stores.

Nonparametric discovery of learning patterns and autism subgroups from therapeutic data

Autism Spectrum Disorder (ASD) is growing at a staggering rate, but, little is known about the cause of this condition. Inferring learning patterns from therapeutic performance data, and subsequently clustering ASD children into subgroups, is important to understand this domain, and more importantly to inform evidence-based intervention. However, this data-driven task was difficult in the past due to insufficiency of data to perform reliable analysis. For the first time, using data from a recent application for early intervention in autism (TOBY Play pad), whose download count is now exceeding 4500, we present in this paper the automatic discovery of learning patterns across 32 skills in sensory, imitation and language. We use unsupervised learning methods for this task, but a notorious problem with existing methods is the correct specification of number of patterns in advance, which in our case is even more difficult due to complexity of the data. To this end, we appeal to recent Bayesian nonparametric methods, in particular the use of Bayesian Nonparametric Factor Analysis. This model uses Indian Buffet Process (IBP) as prior on a binary matrix of infinite columns to allocate groups of intervention skills to children. The optimal number of learning patterns as well as subgroup assignments are inferred automatically from data. Our experimental results follow an exploratory approach, present different newly discovered learning patterns. To provide quantitative results, we also report the clustering evaluation against K-means and Nonnegative matrix factorization (NMF). In addition to the novelty of this new problem, we were able to demonstrate the suitability of Bayesian nonparametric models over parametric rivals.

Can music therapy in medical contexts ever be evidence-based?

This essay seeks to consider some of the issues around evidencethat provide an ongoing challenge to the profession of music therapyto be vigilant and critical with regards the undertaking, butalso the appropriation or application, of research in our alliedhealth discipline. It is written in response to the statement that“medical music therapists need to continue to discuss and debateour views as to what constitutes knowledge, expertise and ‘evidence’in our profession.” (Edwards, 2002, p. 33). A critical perspectiveto current demands for evidence is provided, and the useof quantitative method as the basis for trustworthy research inmusic therapy is discussed. The paediatric medical context is themain site of professional research of the author, however, some ofthe points made will have relevance for other fields of clinicalservice.

We did the how to teach it: music teaching and learning in higher education in Australia

The Australian Government recognizes that the Arts are acritical part of formal school education and it should not be viewedas subordinate or extra. This paper forms part of a wider researchproject titled “Pre-service teacher attitudes and understandings ofMusic Education” that started in 2013. The focus of this paperinvestigates music teaching and learning in a core unit within theBachelor of Education (Primary) course at Deakin University(Australia). Using questionnaire and interview data gathered in 2014,I employ Interpretative Phenomenological Analysis to analyse andcodify the data. Three themes are discussed in relation to: Why it isimportant to include music in the primary school? What wasenjoyable and what aspects were challenging in the musicworkshops? What can students integrate as generalist teachers intotheir future classrooms? Though the findings focus on “we did thehow to teach it”, it also highlights some challenges and opportunitiesfor students and staff. Tertiary educators are challenged to raise thecapacity and status of music when preparing students to translate themusic curriculum into their future classrooms.

Altered response of the anterolateral abdominal muscles to simulated weight-bearing in subjects with low back pain

An important aspect of neuromuscular control at the lumbo-pelvic region is stabilization. Subjects with low back pain (LBP) have been shown to exhibit impairments in motor control of key muscles which contribute to stabilization of the lumbo-pelvic region. However, a test of automatic recruitment that relates to function has been lacking. A previous study used ultrasound imaging to show that healthy subjects automatically recruited the transversus abdominis (TrA) and internal oblique (IO) muscles in response to a simulated weight-bearing task. This task has not been investigated in subjects with LBP. The aim of this study was to compare the automatic recruitment of the abdominal muscles among subjects with and without LBP in response to the simulated weight-bearing task. Twenty subjects with and without LBP were tested. Real-time ultrasound imaging was used to assess changes in thickness of the TrA and internal oblique IO muscles as well as lateral movement ("slide") of the anterior fascial insertion of the TrA muscle. Results showed that subjects with LBP showed significantly less shortening of the TrA muscle (P < 0.0001) and greater increases in thickness of the IO muscle (P = 0.002) with the simulated weight-bearing task. There was no significant difference between groups for changes in TrA muscle thickness (P = 0.055). This study provides evidence of changes in motor control of the abdominal muscles in subjects with LBP. This test may provide a functionally relevant and non-invasive method to investigate the automatic recruitment of the abdominal muscles in people with and without LBP.

Music therapy and medical ethnomusicology: distinctive and connected

A music therapist and an ethnomusicologist who is also qualified as a music therapist explore some of the ways in which music therapy and medical ethnomusicology might engage a dialogue that is helpful to expanding thinking and practice in both fields. We begin by describing music therapy and outlining some core concepts of therapeutic work. We then discuss ethnomusicology and reflect on the ways in which music therapy and ethnomusicology may complement one another in the field of medical ethnomusicology. We consider how an exploration of concepts informing cultural safety might be enacted in healthcare through the use of music and whether this might serve as a useful joint future enterprise between music therapists and medical ethnomusicologists. Finally we explain why we encourage medical ethnomusicologists to cease attempts to become applied therapeutic practitioners without further therapy skills training.

The influence of emotional contagion on products evaluation

Emotional Contagion is the mechanism that includes mimicking and the automatic synchronization of facial expressions, vocalizations, postures, and movements with another person and, consequently, convergence of emotions between the sender and receiver. Researches of this mechanism conducted usually in the fields of Psychology and Marketing tends to investigate face-to-face interactions. However, the question remains to what extent, if any, emotional contagion may occur with facial expressions in photos, since many purchase situations are brought on by catalogues or websites. This thesis has the goal to verify this gap and, in addition, verify whether emotional contagion is more common in females than in males as stated in previous studies. Emotions have been studied because it is intuitively apparent that emotions affect the dynamics of the interaction between a salesperson and customers (Verbeke, 1997); in other words, emotions may significantly affect consumer behavior. Therefore, this thesis also verified whether the facial expressions that transmit emotions could be associated to product evaluations. To investigate these questions, an experiment was done with 171 participants, which were exposed to either smiling (positive emotion) or neutral advertising. The differences between the individual advertisements were limited to the facial expressions of figures in the advertisements (either smiling or neutral/without smiling). One specialist and two students analyzed videotaped records of the participants’ responses, and found that participants who saw the positive stimulus mimicked the picture (smiling back) confirming the Emotional Contagion in Photos (the first hypothesis). The second hypothesis was to analyze if there is difference based in gender. The results demonstrated that there is not a significant difference between genders; female and male equally suffer Emotional Contagion. The third hypothesis was related to whether the positive emotions vs. neutral emotions acquired from the positive facial expression in the photo are associated to a positive evaluation of the product also displayed in the photo. Evidences show that the ad with a positive expression could change more positively the attitude, the sympathy, the reliability, and the intention of purpose of the participant compared to those who were exposed to the neutral condition. Therefore, the analysis concludes that the facial expressions displayed in photos produce emotional contagion and may interfere on the evaluation product. A discussion of the theoretical and practical implications and limitations for these findings are presented.

Interactive music visualization: implementation, realization and evaluation

This thesis describes all process of the development of music visualization, starting with the implementation, followed by realization and then evaluation. The main goal is to have to knowledge of how the audience live performance experience can be enhanced through music visualization. With music visualization is possible to give a better understanding about the music feelings constructing an intensive atmosphere in the live music performance, which enhances the connection between the live music and the audience through visuals. These visuals have to be related to the live music, furthermore has to quickly respond to live music changes and introduce novelty into the visuals. The mapping between music and visuals is the focus of this project, in order to improve the relationship between the live performance and the spectators. The implementation of music visualization is based on the translation of music into graphic visualizations, therefore at the beginning the project was based on the existent works. Later on, it was decided to introduce new ways of conveying music into visuals. Several attempts were made in order to discover the most efficient mapping between music and visualization so people can fully connect with the performance. Throughout this project, those attempts resulted in several music visualizations created for four live music performances, afterwards it was produced an online survey to evaluate those live performances with music visualization. In the end, all conclusions are presented based on the results of the online survey, and also is explained which music elements should be depicted in the visuals, plus how those visuals should respond to the selected music elements.

DEMO models based automatic workflow process generation

Nowadays, more than half of the computer development projects fail to meet the final users' expectations. One of the main causes is insufficient knowledge about the organization of the enterprise to be supported by the respective information system. The DEMO methodology (Design and Engineering Methodology for Organizations) has been proved as a well-defined method to specify, through models and diagrams, the essence of any organization at a high level of abstraction. However, this methodology is platform implementation independent, lacking the possibility of saving and propagating possible changes from the organization models to the implemented software, in a runtime environment. The Universal Enterprise Adaptive Object Model (UEAOM) is a conceptual schema being used as a basis for a wiki system, to allow the modeling of any organization, independent of its implementation, as well as the previously mentioned change propagation in a runtime environment. Based on DEMO and UEAOM, this project aims to develop efficient and standardized methods, to enable an automatic conversion of DEMO Ontological Models, based on UEAOM specification into BPMN (Business Process Model and Notation) models of processes, using clear semantics, without ambiguities, in order to facilitate the creation of processes, almost ready for being executed on workflow systems that support BPMN.

Aquatic weed automatic classification using machine learning techniques

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Extraction of Building Roof Contours From LiDAR Data Using a Markov-Random-Field-Based Approach

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Image processing algorithm for the identification of Martian dust devil tracks in MOC and HiRISE images

This paper presents a method for automatic identification of dust devils tracks in MOC NA and HiRISE images of Mars. The method is based on Mathematical Morphology and is able to successfully process those images despite their difference in spatial resolution or size of the scene. A dataset of 200 images from the surface of Mars representative of the diversity of those track features was considered for developing, testing and evaluating our method, confronting the outputs with reference images made manually. Analysis showed a mean accuracy of about 92%. We also give some examples on how to use the results to get information about dust devils, namelly mean width, main direction of movement and coverage per scene. (c) 2012 Elsevier Ltd. All rights reserved.

Application of wavelets to the evaluation of phantom images for mammography quality control

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estimation of crowd density using image processing

Human beings perceive images through their properties, like colour, shape, size, and texture. Texture is a fertile source of information about the physical environment. Images of low density crowds tend to present coarse textures, while images of dense crowds tend to present fine textures. This paper describes a new technique for automatic estimation of crowd density, which is a part of the problem of automatic crowd monitoring, using texture information based on grey-level transition probabilities on digitised images. Crowd density feature vectors are extracted from such images and used by a self organising neural network which is responsible for the crowd density estimation. Results obtained respectively to the estimation of the number of people in a specific area of Liverpool Street Railway Station in London (UK) are presented.

Fuzzy logic to predict thermal damages of ground parts

One of the critical problems in implementing an intelligent grinding process is the automatic detection of workpiece surface burn. This work uses fuzzy logic as a tool to classify and predict burn levels in the grinding process. Based on acoustic emission signals, cutting power, and the mean-value deviance (MVD), linguistic rules were established for the various burn situations (slight, intermediate, severe) by applying fuzzy logic using the Matlab Toolbox. Three practical fuzzy system models were developed. The first model with two inputs resulted only in a simple analysis process. The second and third models have an additional MVD statistic input, associating information and precision. These two models differ from each other in terms of the rule base developed. The three developed models presented valid responses, proving effective, accurate, reliable and easy to use for the determination of ground workpiece burn. In this analysis, fuzzy logic translates the operator's human experience associated with powerful computational methods.