Identification and tracking of robots in an intelligent space using static cameras and an XPFCP

This paper tackles the problem of identification and tracking of multiple robots in an intelligent space using an array of cameras placed in fixed positions within the environment. Several types of agent can be found in an intelligent space: controlled agents (mobile robots) and uncontrolled ones (users and obstacles). The information transferred between the controlled agents and the intelligent space is limited to the control commands sent to the robots and the measurements of the odometers received from the robots. The proposed solution allows the localization of mobile agents, even if they are not robots; however, we have focused on the controlled agents. The proposal does not require prior knowledge or invasive landmarks on board the robots. It starts from the segmentation of different agents in motion that allows obtaining the boundaries of all robots and an estimation of all 3D points that define those boundaries. Then, the identification of the robots is obtained by comparing the components of the linear velocity estimated by the motion segmentation algorithm and received from the odometers. In order to track the robots, an eXtended Particle Filter with Classification Process (XPFCP) is employed. Several experimental tests have been carried out, and the results obtained validate the proposal.     

Reduction of the size of L-fuzzy contexts. A tool for differential diagnoses of diseases

ABSTRACT

Information extraction from an L-fuzzy context becomes a hard problem when we work with a large set of objects and/or attributes. The goal of this paper is to present two different and complementary techniques to reduce the size of the context. First, using overlap indexes, we will establish rankings among the elements of the context that will allow us to determine those that do not provide relevant information and eliminate them. Second, by means of Choquet integrals, we will aggregate some objects or attributes of the context in order to jointly use the provided information. One interesting application of the developed theory consists on helping in the differential diagnoses of diseases that share a large number of symptoms and, therefore, that are difficult of distinguish.     

Maturity Model for Interoperability Potential Measurement

Interoperability potential concerns the preparation level of an enterprise to establish an efficient collaboration with possible partners. In order to improve their interoperability, enterprises need to know witch level of maturity they have achieved. This article proposes a complete maturity model composed by a methodology and a reference set of parameters to measure interoperability potential. In order to clarify the proposal, an example of application in a real case is described.     

Generating request streams on Big Data using clustered renewal processes

The performance evaluation of large file systems, such as storage and media streaming, motivates scalable generation of representative traces. We focus on two key characteristics of traces, popularity and temporal locality. The common practice of using a system-wide distribution obscures per-object behavior, which is important for system evaluation. We propose a model based on delayed renewal processes which, by sampling interarrival times for each object, accurately reproduces popularity and temporal locality for the trace. A lightweight version reduces the dimension of the model with statistical clustering. It is workload-agnostic and object type-aware, suitable for testing emerging workloads and ‘what-if’ scenarios. We implemented a synthetic trace generator and validated it using: (1) a Big Data storage (HDFS) workload from Yahoo!, (2) a trace from a feature animation company, and (3) a streaming media workload. Two case studies in caching and replicated distributed storage systems show that our traces produce application-level results similar to the real workload. The trace generator is fast and readily scales to a system of 4.3 million files. It outperforms existing models in terms of accurately reproducing the characteristics of the real trace.     

Disjoint pattern matching and implication in strings

We deal with the problem of deciding whether a given set of string patterns implies the presence of a fixed pattern. While checking whether a set of patterns occurs in a string is solvable in polynomial time, this implication problem is well known to be intractable. Here we consider a version of the problem when patterns in the set are required to be disjoint. We show that for such a version of the problem the situation is reversed: checking whether a set of patterns occurs in a string is NP-complete, but the implication problem is solvable in polynomial time.     

A collaborative augmented reality annotation tool for the inspection of prefabricated buildings

The inspection of prefabricated buildings involves different stages and tasks such as the collection of measurements, the visual inspection of components and the written annotation of defects. Traditionally, inspectors have documented the process, the kind of defects and the proposed correction measures in paper format, hindering the collaboration with other experts (either simultaneously or asynchronously) and the collection of other types of annotations (e.g. images, 3D elements). In this paper, we present an AR tool designed to aid inspectors during this process. The tool has many benefits, as it allows simultaneously performing a collaborative inspection, taking multitype and geolocated annotations, their monitoring and edition, and performing in situ augmented visualizations. The quantitative and qualitative user evaluation carried out with our tool in a real environment (including usability and satisfaction evaluations) shows the relevance that such a technology might bring to the field and prove that our tool is usable and fulfils most of the inspectors’ expectations.

     

View-dependent pruning for real-time rendering of trees

The main problem in the real-time rendering of vegetation is the massive amount of primitives to be rendered. These primitives are needed to fully describe the geometry of the plants. However, some of them are not visible depending on the location of the viewer. This work focuses on this fact to interactively reduce the amount of geometry needed to represent the foliage through a view-dependent multiresolution scheme. Following a camera-dependent criterion, the less visible parts of the foliage are detected in real time, and rendered with a decreased level of detail for improving efficiency. This fact considerably reduces the extraction and the visualization time of the geometry that represents the foliage. The novelty of the presented method is that its design is oriented to being efficient on massively parallel architectures, such as the graphics processing unit. Moreover, we introduce a new management system for efficiently handling level of detail objects in order to improve performance for forest scenes.     

Excellence in Engineering Education: Views of Undergraduate Engineering Students

The purpose of this study was to understand the views and perceptions of engineering undergraduate students on engineering education. The method of content analysis was used to analyze the language used by engineering undergraduate students, and to extract the underlying common factors or perceived characteristics of “Excellence in Engineering Education.” These common factors were then used to identify and compare the similarities and differences in views between engineering students and perspectives from three types of stakeholders in the field. Forty‐seven undergraduate engineering students (17 females and 30 males) participated voluntarily in this study to answer four individual questions and ten group questions. The results showed that students strongly emphasized the importance of their own roles in the educational system and the value of instructional technology and real work examples in enhancing the quality of engineering education. The implications of the research results on excellence in engineering education are discussed.     

Effect of personalized nutritional counseling in maintenance hemodialysis patients

Monitoring nutritional parameters is an integral part of hemodialysis (HD) patient treatment program. The purpose of this study was to evaluate the impact of the personalized nutritional counseling (PNC) on calcium–phosphorus metabolism, potassium, albumin, protein intake, interdialytic weight gain (IDWG), body composition parameters and fluid overload in HD patients. This was a multicenter longitudinal intervention study with 6 months of follow‐up and 731 patients on maintenance HD from 34 dialysis units in Portugal were enrolled. Biochemical and body composition parameters were measured at baseline, 1, 3 and 6 months after the PNC. Patient's mean age was 64.9 (95% confidence interval [CI]: 63.8–66.0) years and mean HD time was 59.8 (95% CI: 55.3–64.3) months. Regarding data comparison collected before PNC vs. 6 months after, we obtained, respectively, the following results: patients with normalized protein catabolic rate (nPCR) ≥ 1 g/kg/day = 66.5% vs. 73.5% (P = 0.002); potassium > 5.5 mEq/L = 52% vs. 35.8% (P < 0.001); phosphorus between 3.5 and 5.5 mg/dL = 43.2% vs. 52.5% (P < 0.001); calcium/phosphorus (Ca/P) ratio ≤ 50 mg/dL = 73.2 % vs. 81.4% (P < 0.001); albumin ≥ 4.0 g/dL = 54.8% vs. 55% (P = 0.808); presence of relative overhydration = 22.4% vs. 25% (P = 0.283); IDWG > 4.5% = 22.3% vs. 18.2% (P = 0.068). PNC resulted in a significant decrease in the prevalence of hyperkalemia, hypophosphatemia and also showed amelioration in Ca/P ratio, nPCR and an increase in P of hyphosphatemic patients. Our study suggests that dietetic intervention contributes to the improvement of important nutritional parameters in patients receiving hemodialysis treatment.