Evolution feature oriented model driven product line engineering approach for synergistic and dynamic service evolution in clouds: A04BPEL3.0 proposal.

Model Driven based approach for Service Evolution in Clouds will mainly focus on the reusable evolution patterns' advantage to solve evolution problems. During the process, evolution pattern will be driven by MDA models to pattern aspects. Weaving the aspects into service based process by using Aspect-Oriented extended BPEL engine at runtime will be the dynamic feature of the evolution.

Automatic Glaucoma Detection Based on Optic Disc Segmentation and Texture Feature Extraction

The use of digital image processing techniques is prominent in medical settings for the automatic diagnosis of diseases. Glaucoma is the second leading cause of blindness in the world and it has no cure. Currently, there are treatments to prevent vision loss, but the disease must be detected in the early stages. Thus, the objective of this work is to develop an automatic detection method of Glaucoma in retinal images. The methodology used in the study were: acquisition of image database, Optic Disc segmentation, texture feature extraction in different color models and classification of images in glaucomatous or not. We obtained results of 93% accuracy

ALCOHOL AS A SOCIAL MEDIATOR AMONG UNIVERSITY STUDENTS

Objective: To identify the prevalence of alcohol consumption in Psychology students of a higher education institution in the city of Montes Claros, MG. Methods: Quantitative crosssectional descriptive research conducted from September to October 2014. The population consisted of 116 Psychology students from the city of Montes Claros, MG. Data were collected using the Alcohol Use Disorders Identification Test (AUDIT), the Inventário de Expectativas e Crenças Pessoais Acerca do Álcool – IECPA (Inventory of Expectations and Personal Beliefs about Alcohol), the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) and the Escala de Satisfação com o Suporte Social – ESSS (Social Support Satisfaction Scale). Descriptive analysis of data was performed using SPSS 19.0. Results: The sample had a predominance of female gender (82.75%, n=96), pardos (65.51%, n=76) and single (60.34%, n=70) individuals. Regarding the AUDIT risk classification, it was found that 49.13% (n=57) of the respondents were in the level 4, considered alcohol dependence. They reported occasional use of alcohol, smoking and other substances, which refer to ASSIST level 1 classification, with 94.82% (n=110). Regarding the IECPA, 87.06% (n=101) of the individuals were classified as level 1, with low vulnerability to the effects of alcohol. As to the ESSS, 68.10% (n=79) of the students showed high social support. Conclusion: Regarding the sample studied, it was found a high prevalence of dependence on alcohol and other legal and illegal drugs.

Investigating the Mediator role of Social Safeness on the Relationship between Forgiveness and Life Satisfaction

The aim of the present study is to examine the mediating effect of social safeness on the relationship between forgiveness and life satisfaction. Participants were 311 university students who completed a questionnaire package that included the Trait Forgiveness Scale, the Social Safeness and Pleasure Scale, and the Life Satisfaction Scale. According to the results, social safeness and life satisfaction were predicted positively by forgiveness. On the other hand, life satisfaction was predicted positively by social safeness. In addition, social safeness mediated on the relationship between forgiveness and life satisfaction. The results were discussed in the light of the related literature and dependent recommendations to the area were given.

Mediator framework for inserting xDRs into hadoop

During the last decades, we assisted to what is called “information explosion”. With the advent of the new technologies and new contexts, the volume, velocity and variety of data has increased exponentially, becoming what is known today as big data. Among them, we emphasize telecommunications operators, which gather, using network monitoring equipment, millions of network event records, the Call Detail Records (CDRs) and the Event Detail Records (EDRs), commonly known as xDRs. These records are stored and later processed to compute network performance and quality of service metrics. With the ever increasing number of collected xDRs, its generated volume needing to be stored has increased exponentially, making the current solutions based on relational databases not suited anymore. To tackle this problem, the relational data store can be replaced by Hadoop File System (HDFS). However, HDFS is simply a distributed file system, this way not supporting any aspect of the relational paradigm. To overcome this difficulty, this paper presents a framework that enables the current systems inserting data into relational databases, to keep doing it transparently when migrating to Hadoop. As proof of concept, the developed platform was integrated with the Altaia - a performance and QoS management of telecommunications networks and services.

The impact of event sponsorship on children’s brand image and purchase intentions: The mediator effects of product involvement and brand familiarity

Field lab in marketing: Children consumer behaviour

Pensamento de Remo Bodei sobre a filosofia do século XX : da estagnação ao retorno da responsabilidade

Dissertação (mestrado)—Universidade de Brasília,Instituto de Ciências Humanas, Programa de Pós-Graduação em Filosofia, 2014.

Psychological Ownership of Employees as a Mediator in the Justice - Affective Commitment Relationship

Numerous scholars have accumulated evidence on the positive effects that employees' organizational justice perceptions exert on work-related outcomes such as affective commitment. However, research still lacks understanding of the underlying mechanisms connecting the two constructs. In this article we aim to narrow this gap by examining the concept of psychological ownership as a possible mediator between organizational justice perceptions and affective commitment. Investigating a sample of 619 employees, we find distributive justice to be positively related to psychological ownership, and observe psychological ownership as a full mediator of the distributive justice and affective commitment relationship. These insights offer a new explanation in understanding the justice-commitment connection, contributing to both organizational justice and psychological ownership literature and opening up ways for promising future research

Exploring Hidden Coherent Feature Groups and Temporal Semantics for Multimedia Big Data Analysis

Thanks to the advanced technologies and social networks that allow the data to be widely shared among the Internet, there is an explosion of pervasive multimedia data, generating high demands of multimedia services and applications in various areas for people to easily access and manage multimedia data. Towards such demands, multimedia big data analysis has become an emerging hot topic in both industry and academia, which ranges from basic infrastructure, management, search, and mining to security, privacy, and applications. Within the scope of this dissertation, a multimedia big data analysis framework is proposed for semantic information management and retrieval with a focus on rare event detection in videos. The proposed framework is able to explore hidden semantic feature groups in multimedia data and incorporate temporal semantics, especially for video event detection. First, a hierarchical semantic data representation is presented to alleviate the semantic gap issue, and the Hidden Coherent Feature Group (HCFG) analysis method is proposed to capture the correlation between features and separate the original feature set into semantic groups, seamlessly integrating multimedia data in multiple modalities. Next, an Importance Factor based Temporal Multiple Correspondence Analysis (i.e., IF-TMCA) approach is presented for effective event detection. Specifically, the HCFG algorithm is integrated with the Hierarchical Information Gain Analysis (HIGA) method to generate the Importance Factor (IF) for producing the initial detection results. Then, the TMCA algorithm is proposed to efficiently incorporate temporal semantics for re-ranking and improving the final performance. At last, a sampling-based ensemble learning mechanism is applied to further accommodate the imbalanced datasets. In addition to the multimedia semantic representation and class imbalance problems, lack of organization is another critical issue for multimedia big data analysis. In this framework, an affinity propagation-based summarization method is also proposed to transform the unorganized data into a better structure with clean and well-organized information. The whole framework has been thoroughly evaluated across multiple domains, such as soccer goal event detection and disaster information management.

Feature-based tracking of urethral motion in low-resolution trans-perineal ultrasound

This paper describes a novel algorithm for tracking the motion of the urethra from trans-perineal ultrasound. Our work is based on the structure-from-motion paradigm and therefore handles well structures with ill-defined and partially missing boundaries. The proposed approach is particularly well-suited for video sequences of low resolution and variable levels of blurriness introduced by anatomical motion of variable speed. Our tracking method identifies feature points on a frame by frame basis using the SURF detector/descriptor. Inter-frame correspondence is achieved using nearest-neighbor matching in the feature space. The motion is estimated using a non-linear bi-quadratic model, which adequately describes the deformable motion of the urethra. Experimental results are promising and show that our algorithm performs well when compared to manual tracking.

A stakeholder perspective on heritage branding and digital communication

How does an archaeological museum understand its function in a digital environment? Consumer expectations are rapidly shifting, from what used to be a passive relationship with exhibition contents, towards a different one, in which interaction, individuality and proactivity define the visitor experience. This consumer paradigm is much studied in fast moving markets, where it provokes immediately measurable impacts. In other fields, such as tourism and regional development, the very heterogeneous nature of the product to be branded makes it near to impossible for only one player to engage successfully. This systemic feature implies that museums, acting as major stakeholders, often anchor a regional brand around which SME tend to cluster, and thus assume responsibilities in constructing marketable identities. As such, the archaeological element becomes a very useful trademark. On the other hand, it also emerges erratically on the Internet, in personal blogs, commercial websites, and social networks. This forces museums to enter as a mediator, authenticating contents and providing credibility. What might be called the digital pull factor poses specific challenges to museum management: what is to be promoted, and how, in order to create and maintain a coherent presence in social media? The underlying issue this paper tries to address is how museums perceive their current and future role in digital communication.

Feature-based tracking of urethral motion in low-resolution trans-perineal ultrasound

This paper describes a novel algorithm for tracking the motion of the urethra from trans-perineal ultrasound. Our work is based on the structure-from-motion paradigm and therefore handles well structures with ill-defined and partially missing boundaries. The proposed approach is particularly well-suited for video sequences of low resolution and variable levels of blurriness introduced by anatomical motion of variable speed. Our tracking method identifies feature points on a frame by frame basis using the SURF detector/descriptor. Inter-frame correspondence is achieved using nearest-neighbor matching in the feature space. The motion is estimated using a non-linear bi-quadratic model, which adequately describes the deformable motion of the urethra. Experimental results are promising and show that our algorithm performs well when compared to manual tracking.

TARDI VARISCAN DEFORMATION IN THE IBERIAN PENINSULA; A LATE FEATURE IN THE LAURASIA-GONDWANA DEXTRAL COLLISION

The Late Variscan deformation event in Iberia, is characterized by an intraplate deformation regime induced by the oblique collision between Laurentia and Gondwan. This episode in Iberia is characterized by NNE-SSW strike-slip faults, which are considered by the classic works as sinistral strike-slips. However, the absence of Mesozoic formations constraining the age of this sinistral kinematics, led some authors to consider it as the result of Alpine reworking. Structural studies in Almograve and Ponta Ruiva sectors (SW Portugal), not only shows that NNE-SSW faults presents a clear sinistral kinematics and are occasionally associated with E-W dextral shears, but also that this kinematics is related to the late deformation episodes of Variscan Orogeny. In Almograve sector, the late Variscan structures are characterized by NNE-SSW sinistral kink-bands, spatially associated with E-W dextral faults. These structures are contemporaneous and affect the previously deformed Carboniferous units. The Ponta Ruiva Sector constrains the age of deformation because the E-W dextral shears affect the Late Carboniferous (late Moscovian) units, but not the overlying Triassic series. The new exposed data shows that the NNE-SSW and the E-W faults are dynamically associated and results from the same deformation event. The NNE-SSW sinistral faults could be considered as second order dominoes structures related with first order E-W dextral shears, related with Laurasia-Gondwana collision during Late Carboniferous-Permian Times.