Effectiveness is a key feature of good governance, as the public sector must make the best use of resources to comply with the needs of the population. Several indicators can be analyzed to evaluate the effectiveness of a service. This study analyzes theoretical references and presents a systematic research of indicators to assess the effectiveness of digital public services in the perspective of the user. First, a literature review was carried out to identify the most common indicators employed to evaluate effectiveness in the public sector; then, the perception of academics and professionals regarding digital government was assessed to analyze the relevance of these indicators. As a result, two groups of indicators were found: technical factors based on service quality and usefulness of the service. This work contributes to enrich the discussion on how to create an effective model to evaluate the effectiveness of public services to guarantee quality standards and comply with the expectations of users.

Evaluating public services has become an important task in order to direct actions that may positively affect with the quality of the service provided by governments. To undertake an effective evaluation, it is necessary to analyze data and information on the impact of the services. A wide range of studies have been proposed to measure how an organization delivers its services according to the expectations of the stakeholders. This paper investigates approaches for evaluating public services from the perspective of users. The goal is to identify and describe evaluation-based models, as well as the instruments and tools employed in the service evaluation process. A systematic literature review was conducted to search and analyze studies published in the last 15 years. From the analysis of 31 studies, we identified four main dimensions regarding service evaluation: quality, success and acceptance of information systems, user satisfaction, and user experience. This work contributes to the identification of models, dimensions, instruments, and tools to evaluate public services from the perspective of users. The results of this work can be used as a guide to the Public Administration in the construction of effective models to evaluate their public services and to guarantee quality standards that meet the expectations of the users.

The Bag-of-Visual-Words has emerged as an effective modeling approach to represent local image features. It describes local image features by assigning them a visual word according to a visual dictionary. The image representation is given by the frequency of each visual word in the image, as a similar representation used in textual documents. In this paper, we present a novel approach building a high-level description using a group of words (phrases) for representing an image. We introduce the use of n-grams for image representation, based on the idea of "Bag-of-Visual-Phrases". In the field of computational linguistics, an n-gram is a phrase formed by a sequence of n-consecutive words. As analogy, we represent an image by a combination of n-consecutive visual words. We made representative experiments using three public benchmark databases of textures and nature scenes and two medical databases to demonstrate an area that can benefit from the proposed technique. Our proposed Bag-of-Visual-Phrases approach improved up to 44% the retrieval precision and up to 33% the classification rate compared to the traditional Bag-of-Visual-Words, being a valuable asset for content-based image retrieval and image classification.

This paper presents a segmentation approach guided by the user for extracting the vertebral bodies of spine from MRI. The proposed approach, called VBSeg, takes advantage of super pixels to reduce the image complexity and then making easy the detection of each vertebral body contour. Super pixels adapt themselves to the image structures, once their formation law follows the homogeneity of the image regions. However, for some diseases or abnormalities, the boundary of each super pixel does not fit well in the vertebra contour. To avoid this drawback, we propose to use the Otsu's method as a possegmentation step to divide the super pixels into smaller ones. The final segmentation is obtained through a region growing approach using points manually selected by the specialist. It can produce masks of the five lumbar vertebrae with an average precision of 80% and recall of 87%, when compared to the manual segmentation of a trained specialist. These values show that the VBSeg is a valuable asset to assist the medical specialist in the task of vertebral bodies' segmentation, with much less effort and time demand.