Topic Tomographies (TopTom): a visual approach to distill information from media streams

In this paper we present Top Tom, a digital platform whose goal is to provide analytical and visual solutions for the exploration of a dynamic corpus of user‐generated messages and media articles, with the aim of i) distilling the information from thousands of documents in a low‐dimensional space of explainable topics, ii) cluster them in a hierarchical fashion while allowing to drill down to details and stories as constituents of the topics, iii) spotting trends and anomalies. Top Tom implements a batch processing pipeline able to run both in near‐real time with time stamped data from streaming sources and on historical data with a temporal dimension in a cold start mode. The resulting output unfolds along three main axes: time, volume and semantic similarity (i.e. topic hierarchical aggregation). To allow the browsing of data in a multiscale fashion and the identification of anomalous behaviors, three visual metaphors were adopted from biological and medical fields to design visualizations, i.e. the flowing of particles in a coherent stream, tomographic cross sectioning and contrast‐like analysis of biological tissues. The platform interface is composed by three main visualizations with coherent and smooth navigation interactions: calendar view, flow view, and temporal cut view. The integration of these three visual models with the multiscale analytic pipeline proposes a novel system for the identification and exploration of topics from unstructured texts. We evaluated the system using a collection of documents about the emerging opioid epidemics in the United States.     

A Nonformal Interactive Therapeutic Multisensory Environment for People With Cerebral Palsy

A new multisensory system that aims at fostering the interaction of people with cerebral palsy is presented. This article describes the strategies and technologies used to provide people who have moderate to severe cerebral palsy with playful and fun activities designed according to their abilities. These activities are based on interactive systems that use computer vision and generate graphics and sounds in real time. The well-being that is achieved through the use of these activities is the result of gaining a significant degree of autonomy by the users. The presented system was first developed in the Cerebral Palsy Centre of Tarragona, Spain. Its motivation came from the low rate of users able to interact with computers. Although several assistive technology gadgets and special software applications (e.g., cause–effect and educational activities, simple navigation environments, etc.) were used, most users simply did not understand the interaction mechanisms. It was thought that a highly interactive activity (reinforced with sounds and images closely related with gestures) would be more accessible to most users in spite of their sensory, motor, and cognitive impairments. Tests with impaired users show that the proposal promotes participation, engagement, and play. In this article, the experimental methodology, the used and developed tools, and the results that were obtained are explained.     

Practice-based research at the University of Art and Design Helsinki

The text describes the status of practice-based research at the University of Art and Design Helsinki and Finland, particularly from the point of view of digital interactive media, and states some basic principles of their research approach.     

Batch and Fed‐Batch Degradation of Enrofloxacin by the Fenton Process

Enrofloxacin is a synthetic second‐generation fluoroquinolone used as an antimicrobial agent exclusively in veterinary medicine. To simulate the treatment of wastewater contaminated by enrofloxacin, four‐day long fed‐batch runs were carried out according to the Fenton process with an enrofloxacin solution as model, to which hydrogen peroxide and ferrous ion were added twice a day. The residual enrofloxacin concentration was practically coincident to that detected at the end of the batch tests. Hydrogen peroxide was almost completely consumed after each feeding period, while the total organic carbon (TOC) concentration decreased gradually within three days, corresponding to a reduction > 58 %. From the third day on, the TOC falling rate was quite low. A yellow sludge settled due to the precipitation of both Fe(OH)₃ and a complex formed by ferric ion with adsorbed enrofloxacin and/or its oxidation products.     

Numerical Model for the Characterization of Retro-reflective Materials Behavior in an Urban Street Canyon

In this work, a preliminary numerical model of the behavior of retro-reflective materials used as envelope coatings on street canyon buildings fa?ades has been tested. Retro-reflective materials have a surface finish that allows to reflect the solar radiation back in the same direction of the incident radiation. In the last years this kind of materials has been studied as buildings envelope coating for their potentials in the reduction of the UHI effect. As a matter of fact, the angular dependence of their optical–radiative response would help to mitigate the phenomenon of radiative entrapment due to the urban fabric environment. For this reason, an urban canyon was selected as the most common urban architecture to perform the analysis. A virtual retroreflective material has been simulated considering its response as almost diffusive but in the same direction of the incident radiation. The assessment of the energy advantages of the adoption of a virtual retro-reflective material as envelope coating is investigated by means of a numerical model developed in MATLAB and based on the Gebhart factors theory. The final purpose of the numerical model is the evaluation of the surfaces solar loads by a comparison between perfectly diffusive materials and RR materials used as fa?ades coating.     

Fingerprint Clustering with Bounded Number of Missing Values

The problem of clustering fingerprint vectors with missing values is an interesting problem in Computational Biology that has been proposed in Figueroa et al. (J. Comput. Biol. 11(5):887–901, 2004). In this paper we show some improvements in closing the gaps between the known lower bounds and upper bounds on the approximability of variants of the biological problem. Moreover, we have studied two additional variants of the original problem proposed in Figueroa et al. (Proc. 11th Computing: The Australasian Theory Symposium (CATS), CRPIT, vol. 41, pp. 57–60, 2005). We prove that all such problems are APX-hard even when each fingerprint contains only two unknown positions and we present a greedy algorithm that has constant approximation factors for these variants. Despite the hardness of these restricted versions of the problem, we show that the general clustering problem on an unbounded number of missing values such that they occur for every fixed position of an input vector in at most one fingerprint is polynomial time solvable.     

Intravascular Ultrasound Tissue Characterization with Sub-class Error-Correcting Output Codes

Intravascular ultrasound (IVUS) represents a powerful imaging technique to explore coronary vessels and to study their morphology and histologic properties. In this paper, we characterize different tissues based on radial frequency, texture-based, and combined features. To deal with the classification of multiple tissues, we require the use of robust multi-class learning techniques. In this sense, error-correcting output codes (ECOC) show to robustly combine binary classifiers to solve multi-class problems. In this context, we propose a strategy to model multi-class classification tasks using sub-classes information in the ECOC framework. The new strategy splits the classes into different sub-sets according to the applied base classifier. Complex IVUS data sets containing overlapping data are learnt by splitting the original set of classes into sub-classes, and embedding the binary problems in a problem-dependent ECOC design. The method automatically characterizes different tissues, showing performance improvements over the state-of-the-art ECOC techniques for different base classifiers. Furthermore, the combination of RF and texture-based features also shows improvements over the state-of-the-art approaches.     

Direct torque control as variable structure control: Existence conditions verification and analysis

The aim of this paper is to propose a formal approach to derive direct torque control (DTC). Using the theory of variable structure control (VSC) and in particular the sliding mode approach, a detailed analysis of the possible operating regions for both induction and brushless machines are described. This analysis allows to clarify the consequences of a specific switching table in terms of control stability. In particular, DTC is presented and analysed as a special case of sliding mode strategy. Sliding mode existence conditions are verified and the most critical operating regions are obtained. The proposed formal analysis allows to define more sophisticated switching tables which assure stable operation.