An ICA-based method for stress classification from voice samples

Emotion detection is a hot topic nowadays for its potential application to intelligent systems in different fields such as neuromarketing, dialogue systems, friendly robotics, vending platforms and amiable banking. Nevertheless, the lack of a benchmarking standard makes it difficult to compare results produced by different methodologies, which could help the research community improve existing approaches and design new ones. Besides, there is the added problem of accurate dataset production. Most of the emotional speech databases and associated documentation are either privative or not publicly available. Therefore, in this work, two stress-elicited databases containing speech from male and female speakers were recruited, and four classification methods are compared in order to detect and classify speech under stress. Results from each method are presented to show their quality performance, besides the final scores attained, in what is a novel approach to the field of study.

     

Immersive and interactive virtual reality applications based on 3D web browsers

This study explores the possibility of effectively using web-standard technologies (i.e., HTML5, JavaScript, WebGL, and WebRTC) to deploy full immersive and interactive virtual reality applications. These applications are based on computer clusters and run in multi-projection environments, such as CAVEs, Panoramas and Power Walls. Until recently, these applications were build using tailored solutions, such low-level libraries to distribute data. We discuss the modern-day web technology which allows these applications meet a multi-platform requirement. This paper also evaluates the communication and synchronization requirements of these applications that are traditionally the main bottleneck. As a proof-of-concept to show the feasibility of our study, we devised and implemented an immersive and interactive virtual reality application employing only web technologies. Our proof-of-concept runs on a miniCAVE environment with three displays and a 6-node cluster.     

How the R community creates and curates knowledge: an extended study of stack overflow and mailing lists

One of the effects of social media’s prevalence in software development is the many flourishing communities of practice where users share a common interest. These large communities use many different communication channels, but little is known about how they create, share, and curate knowledge using such channels. In this paper, we report a mixed methods study of how one community of practice, the R software development community, creates and curates knowledge associated with questions and answers (Q&A) in two of its main communication channels: the R tag in Stack Overflow and the R-Help mailing list. The results reveal that knowledge is created and curated in two main forms: participatory, where multiple users explicitly collaborate to build knowledge, and crowdsourced, where individuals primarily work independently of each other. Moreover, we take a unique approach at slicing the data based on question score and participation activities over time. Our study reveals participation patterns, showing the existence of prolific contributors: users who are active across both channels and are responsible for a large proportion of the answers, serving as a bridge of knowledge. The key contributions of this paper are: a characterization of knowledge artifacts that are exchanged by this community of practice; the reasons why users choose one channel over the other; and insights on the community participation patterns, which indicate an evolution of the community and a shift from knowledge creation to knowledge curation.     

Virtual reality software package for implementing motor learning and rehabilitation experiments

Virtual reality games for rehabilitation are attracting increasing growth. In particular, there is a demand for games that allow therapists to identify an individual’s difficulties and customize the control of variables, such as speed, size, distance, as well as visual and auditory feedback. This study presents and describes a virtual reality software package (Bridge Games) to promote rehabilitation of individuals living with disabilities and highlights preliminary researches of its use for implementing motor learning and rehabilitation. First, the study presents seven games in the software package that can be chosen by the rehabilitation team, considering the patient’s needs. All game characteristics are described including name, function presentation, objective and valuable measurements for rehabilitation. Second, preliminary results illustrate some applications of two games, considering 343 people with various disabilities and health status. Based on the results, in the Coincident Timing game, there was a main effect of movement sensor type (in this instance the most functional device was the keyboard when compared with Kinect and touch screen) on average time reached by sample analyzed, F(2, 225) = 4.42, p < 0.05. Similarly, in the Challenge! game, a main effect was found for movement sensor type. However, in this case, touch screen provided better performance than Kinect and Leap Motion, F(2, 709) = 5.90, p < 0.01. Thus, Bridge Games is a possible software game to quantify motor learning. Moreover, the findings suggest that motor skills might be practiced differently depending on the environmental interface in which the game may be used.     

An I&I‐Based Observer to Solve the Output‐Feedback Synchronization Problem for a Class of Chaotic Systems

A novel robust observer, intended to solve the output‐feedback chaos synchronization problem for the Master/Slave Configuration, is proposed here. Assuming that the given Master system belongs to a specific class of feedback‐linearized systems, our solution is based on the well‐known Immersion and Invariance (I&I) method. The proposed observer is devoted to the asymptotic estimation of the Master system's underlying dynamics, and its effectiveness is illustrated via computer‐based simulations that involve both the so‐called Duffing's oscillator and the Genesio & Tesi system.     

Strategic Assessment of Lisbon’s Accessibility and Mobility Problems from an Equity Perspective

Accessibility planning with reference to sustainability and equity principles has been advocated as the best approach to deal with the urban mobility complexity. It has enabled the development of more sustainable and fair policies in relation to access provision. However, despite this paradigm shift, many planning initiatives in practice are still focused on assessing alternatives and proposing solutions, instead of centering on the understanding and assessment of problems as the primary activity of planning. Therefore, in order to contribute for the problem-oriented paradigm in the accessibility planning, this work proposes a strategic assessment methodology for unequal and inequitable distribution problems of accessibility and mobility. This methodology relies on spatial analysis techniques and allows the characterization of accessibility and mobility conditions, as well as the diagnosis of accessibility and mobility problems and their causal relationships. It was applied for the case of Lisbon and the results of the performed assessment allowed an intelligent reading of the problems considered. Specifically, it was found that Lisbon presents an unequal and inequitable distribution of job accessibility and mobility by private car and public transport, and also that job accessibility, along with other transportation, land-use and socioeconomic variables, impact the mobility levels of its citizens.     

A Novel Discrete-time Nonlinear Model Predictive Control Based on State Space Model

This paper proposes a novel finite dimensional discrete-time Nonlinear Model Predictive Control. This technique is based on discrete-time state-space models, Taylor series expansion for prediction and performance index optimization. Furthermore, the technique extends the concept of the Lie derivative for the discrete time case using Euler backwards method. The performance validation for the discrete-time Nonlinear Model Predictive Control uses the simulation of a single-link flexible joint robot and the inverted pendulum. Comparison of the proposed finite dimensional discrete-time Nonlinear Model Predictive Control technique with Feedback Linearization Control is also discussed. Analytical and numerical results show excellent performances for both, the single-link flexible joint and inverted pendulum controllers using the proposed discrete-time Nonlinear Model Predictive Control technique.     

An Intelligent Transportation System Application for Smartphones Based on Vehicle Position Advertising and Route Sharing in Vehicular Ad-Hoc Networks

关于到来的紧急情况车辆和他们的线路警告司机能极大地在拥挤的城市里改进他们的旅行时间,当由于分心减少事故的风险时。这份报纸由建议耶稣,能够关于象救护车一样的到来的紧急情况车辆通知常规车辆的机器人应用,警察汽车和消防队贡献这个目标。这被创造能够直接在他们之间交流的车辆的一个网络使可能。因此,用户能由考虑到来的警戒以一种及时方式作开车决定。用我们的 GRCBox 硬件的支持,申请能在 5 GHz 乐队依靠车辆的特定的网络通讯, V2V (vehicle-to-vehicle ) 通讯通过基于机器人的 smartphone 和我们的 GRCBox 设备的联合正在被提供。申请与阻塞的不同层次在三种不同情形被测试,证明提供有能力第二在不到一个以内提醒起来注意 300 米,和通知车辆。     

A systematic review of provenance systems

Provenance refers to the entire amount of information, comprising all the elements and their relationships, that contribute to the existence of a piece of data. The knowledge of provenance data allows a great number of benefits such as verifying a product, result reproductivity, sharing and reuse of knowledge, or assessing data quality and validity. With such tangible benefits, it is no wonder that in recent years, research on provenance has grown exponentially, and has been applied to a wide range of different scientific disciplines. Some years ago, managing and recording provenance information were performed manually. Given the huge volume of information available nowadays, the manual performance of such tasks is no longer an option. The problem of systematically performing tasks such as the understanding, capture and management of provenance has gained significant attention by the research community and industry over the past decades. As a consequence, there has been a huge amount of contributions and proposed provenance systems as solutions for performing such kinds of tasks. The overall objective of this paper is to plot the landscape of published systems in the field of provenance, with two main purposes. First, we seek to evaluate the desired characteristics that provenance systems are expected to have. Second, we aim at identifying a set of representative systems (both early and recent use) to be exhaustively analyzed according to such characteristics. In particular, we have performed a systematic literature review of studies, identifying a comprehensive set of 105 relevant resources in all. The results show that there are common aspects or characteristics of provenance systems thoroughly renowned throughout the literature on the topic. Based on these results, we have defined a six-dimensional taxonomy of provenance characteristics attending to: general aspects, data capture, data access, subject, storage, and non-functional aspects. Additionally, the study has found that there are 25 most referenced provenance systems within the provenance context. This study exhaustively analyzes and compares such systems attending to our taxonomy and pinpoints future directions.     

Sensitivity versus accuracy in ensemble models of Artificial Neural Networks from Multi-objective Evolutionary Algorithms

Neural Computing and Applications - This paper proposes a framework to obtain ensembles of classifiers from a Multi-objective Evolutionary Algorithm (MOEA), improving the restrictions imposed by...