Abstract
Human beings have developed a number of evolutionary mechanisms that allows the distinction between different objects and the triggering of events based on their perception of reality. Visual impairment has a significant impact on individuals' quality of life, including their ability to work and to develop personal relationships as they often feel cut off people and things around them, due to their impairment. The need for assistive technologies has long been a constant in the daily lives of people with visual impairments, and will remain a constant in future years. Cognitive mapping is of extreme importance for individuals in terms of creating a conceptual model of the surrounding space and objects around them, thereby supporting their interaction with the physical environment. This work describes the use of computer vision techniques, namely feature detectors and descriptors, to detect objects in the scene and help contextualize the user within the surrounding space, enhancing their mobility, navigation and cognitive mapping of a new environment.

Abstract

Abstract
Image matching algorithms are used in image search, classification and retrieval but are also useful to show how urban structures evolve over time. Images have the power to illustrate and evoke past events and can be used to show the evolution of structures such as buildings and other elements present in the urban landscape. The paper describes a process and a tool to provide a chronological journey through time, given a set of photographs from different time periods. The developed tool provides the ability to generate visualizations of a geographic location, given a set of related images, taken at different periods in time. It automatically processes comparisons of images and establishes relationships between them. It also offers a semi-automated method to define relationships between parts of images.

Abstract
Modeling and building software systems for a given specific domain is a complex task. Domain-Specific Languages (DSLs) have been increasingly gaining attention because they are developed to cope with particularities of specific domains. However, DSL development consists in a set of tasks to be performed and some can be error-prone. Identifying the correct set of elements within a DSL and their constraints can be very demanding. Alloy is a popular lightweight intuitive formal language with a simple notation that is easy to read and write. When models of a DSL are specified using Alloy, it becomes possible to generate instances that should represent valid models. So, this paper presents a generic innovative methodology using Alloy in DSL engineering, in order to find and tune language constraints in a systematic way. It also presents an empirical study illustrating the applicability of the proposed methodology.

Abstract
In the last decade, the FlexRay communication protocol has been promoted as a standard for dependable in-vehicular communications. In the FlexRay protocol, the communication timeline is organized as a sequence of four segments, whereas the Static Segment assigns a set of static slots for the transmission of synchronous messages. In this paper, we address the following problems: "How to efficiently transmit periodic messages in the Static Segment without requiring their periods to be multiples of, or to be synchronized with the FlexRay Communication Cycle?" "Is it possible to guarantee that periodic messages are transferred before their deadlines, without imposing such strict synchronization?" Unlike traditional approaches that use linear-programming based techniques, we evaluate the minimum number of allocated slots using traditional Response Time Analysis (RTA). The use of RTA techniques allows us to consider the timing requirements associated to each of the asynchronous message streams. Unlike other approaches, the RTA-based technique proposed in this paper: (a) is able to deal with message stream sets where periods are not multiple of the FlexRay cycle duration and (b) does not require the strict synchronization between tasks/signals at the application layer and slots at the FlexRay communication controller. The proposed slot allocation scheme may be of high practical interest when considering the interconnection of FlexRay/CAN in-vehicular communication systems, allowing the remapping of existing CAN message streams to FlexRay.

Abstract
Eye detection is a complex issue and widely explored through several applications, such as human gaze detection, human-robot interaction and driver's drowsiness monitoring. However, most of these applications require an efficient approach for detect the ocular region, which should be able to work in real time. In this paper, it is proposed and compare two approaches for online eye detection. The proposed schemes, work under real variant illumination conditions, using the conventional appearance method that is known for its discriminative power especially in texture analysis. In the first stage, the salient eye features are automatically extracted by employing Uniform Local Binary pattern (LBP) operator. Thereafter, supervised machine learning methods are used to classify the presence of an eye in image path, which is described by an LBP histogram. For this stage, two approaches were tested; Support Vector Machine and Long Short-Term Memory Recurrent Neural Network, both are trained for discriminative binary classification, between two classes namely eye / non eye. The human eyes were successfully localized in real time videos, which were obtained from a laptop with uncalibrated web camera. In these tests, different people were considered and light illumination. The experimental results are reported.