Interactive visual steering--rapid visual prototyping of a common rail injection system

Interactive steering with visualization has been a common goal of the visualization research community for twenty years, but it is rarely ever realized in practice. In this paper we describe a successful realization of a tightly coupled steering loop, integrating new simulation technology and interactive visual analysis in a prototyping environment for automotive industry system design. Due to increasing pressure on car manufacturers to meet new emission regulations, to improve efficiency, and to reduce noise, both simulation and visualization are pushed to their limits. Automotive system components, such as the powertrain system or the injection system have an increasing number of parameters, and new design approaches are required. It is no longer possible to optimize such a system solely based on experience or forward optimization. By coupling interactive visualization with the simulation back-end (computational steering), it is now possible to quickly prototype a new system, starting from a non-optimized initial prototype and the corresponding simulation model. The prototyping continues through the refinement of the simulation model, of the simulation parameters and through trial-and-error attempts to an optimized solution. The ability to early see the first results from a multidimensional simulation space--thousands of simulations are run for a multidimensional variety of input parameters--and to quickly go back into the simulation and request more runs in particular parameter regions of interest significantly improves the prototyping process and provides a deeper understanding of the system behavior. The excellent results which we achieved for the common rail injection system strongly suggest that our approach has a great potential of being generalized to other, similar scenarios.     

Empirical validation of referential integrity metrics

Databases are the core of Information Systems (IS). It is, therefore, necessary to ensure the quality of the databases in order to ensure the quality of the IS. Metrics are useful mechanisms for controlling database quality. This paper presents two metrics related to referential integrity, number of foreign keys (NFK) and depth of the referential tree (DRT) for controlling the quality of a relational database. However, to ascertain the practical utility of the metrics, experimental validation is necessary. This validation can be carried out through controlled experiments or through case studies. The controlled experiments must also be replicated in order to obtain firm conclusions. With this objective in mind, we have undertaken different empirical work with metrics for relational databases. As a part of this empirical work, we have conducted a case study with some metrics for relational databases and a controlled experiment with two metrics presented in this paper. The detailed experiment described in this paper is a replication of the later one. The experiment was replicated in order to confirm the results obtained from the first experiment.

As a result of all the experimental works, we can conclude that the NFK metric is a good indicator of relational database complexity. However, we cannot draw such firm conclusions regarding the DRT metric.     

Segmentation of news videos based on audio-video information

In this paper, we propose an innovative architecture to segment a news video into the so-called “stories” by both using the included video and audio information. Segmentation of news into stories is one of the key issues for achieving efficient treatment of news-based digital libraries. While the relevance of this research problem is widely recognized in the scientific community, we are in presence of a few established solutions in the field. In our approach, the segmentation is performed in two steps: first, shots are classified by combining three different anchor shot detection algorithms using video information only. Then, the shot classification is improved by using a novel anchor shot detection method based on features extracted from the audio track. Tests on a large database confirm that the proposed system outperforms each single video-based method as well as their combination.

Safety implications of cultural and cognitive issues in nuclear power plant operation

This research project was designed to investigate cultural and cognitive issues related to the work of nuclear power plant operators during their time on the job in the control room and during simulator training (emergency situations), in order to show how these issues impact on plant safety. The modeling of the operators work deals with the use of operational procedures, the constant changes in the focus of attention and the dynamics of the conflicting activities. The paper focuses on the relationships between the courses of action of the different operators and the constraints imposed by their working environment. It shows that the safety implications of the control room operators' cognitive and cultural issues go far beyond the formal organizational constructs usually implied. Our findings indicate that the competence required for the operators are concerned with developing the possibility of constructing situation awareness, managing conflicts, gaps and time problems created by ongoing task procedures, and dealing with distractions, developing skills for collaborative work.     

Interactive visual analysis of families of function graphs

The analysis and exploration of multidimensional and multivariate data is still one of the most challenging areas in the field of visualization. In this paper, we describe an approach to visual analysis of an especially challenging set of problems that exhibit a complex internal data structure. We describe the interactive visual exploration and analysis of data that includes several (usually large) families of function graphs f_i(x, t). We describe analysis procedures and practical aspects of the interactive visual analysis specific to this type of data (with emphasis on the function graph characteristic of the data). We adopted the well-proven approach of multiple, linked views with advanced interactive brushing to assess the data. Standard views such as histograms, scatterplots, and parallel coordinates are used to jointly visualize data. We support iterative visual analysis by providing means to create complex, composite brushes that span multiple views and that are constructed using different combination schemes. We demonstrate that engineering applications represent a challenging but very applicable area for visual analytics. As a case study, we describe the optimization of a fuel injection system in diesel engines of passenger cars     

Resampling Feature and Blend Regions in Polygonal Meshes for Surface Anti-Aliasing

Efficient surface reconstruction and reverse engineering techniques are usually based on a polygonal mesh representation of the geometry: the resulting models emerge from piecewise linear interpolation of a set of sample points. The quality of the reconstruction not only depends on the number and density of the sample points but also on their alignment to sharp and rounded features of the original geometry. Bad alignment can lead to severe alias artifacts. In this paper we present a sampling pattern for feature and blend regions which minimizes these alias errors. We show how to improve the quality of a given polygonal mesh model by resampling its feature and blend regions within an interactive framework. We further demonstrate sophisticated modeling operations that can be implemented based on this resampling technique.     

Instructional effectiveness of a computer-supported program for teaching reading comprehension strategies

This article examines the effectiveness of a computer-based instructional program (e-PELS) aimed at direct instruction in a collection of reading comprehension strategies. In e-PELS, students learn to highlight and outline expository passages based on various types of text structures (such as comparison or cause-and-effect) as well as to paraphrase, self-question, and summarize. The study involved 1041 fourth-grade elementary students from 21 schools distributed in three regions in central Chile. Participant teachers integrated this program into the Spanish language curriculum, instructing their students during thirty sessions of 90 min each during one school semester. Pretest-to-posttest gains in reading comprehension scores were significantly greater for students instructed with this program than for students who received traditional instruction (d = .5), with particularly strong effects for lower-achieving students (d = .7). The findings support the efficacy of direct instruction in specific learning strategies in a computer-based environment.     

Distance maps from unthresholded magnitudes

A straightforward algorithm that computes distance maps from unthresholded magnitudes is presented, suitable for still images and video sequences. While results on binary images are similar to classic Euclidean Distance Transforms, the proposed approach does not require a binarization step. Thus, no thresholds are needed and no information is lost in intermediate classification stages. Experiments include the evaluation of spatial and temporal coherence of distance map values, showing better results in both measurements than those obtained with Sobel or Deriche gradients and classic chessboard distance transforms.     

A case study on business process recovery using an e‐government system

Business processes have become one of the key assets of organization, since these processes allow them to discover and control what occurs in their environments, with information systems automating most of an organization's processes. Unfortunately, and as a result of uncontrolled maintenance, information systems age over time until it is necessary to replace them with new and modernized systems. However, while systems are aging, meaningful business knowledge that is not present in any of the organization's other assets gradually becomes embedded in them. The preservation of this knowledge through the recovery of the underlying business processes is, therefore, a critical problem. This paper provides, as a solution to the aforementioned problem, a model‐driven procedure for recovering business processes from legacy information systems. The procedure proposes a set of models at different abstraction levels, along with the model transformations between them. The paper also provides a supporting tool, which facilitates its adoption. Moreover, a real‐life case study concerning an e‐government system applies the proposed recovery procedure to validate its effectiveness and efficiency. The case study was carried out by following a formal protocol to improve its rigor and replicability. Copyright © 2011 John Wiley & Sons, Ltd.     

Cluster Size Optimization in Sensor Networks with Decentralized Cluster-Based Protocols

Network lifetime and energy-efficiency are viewed as the dominating considerations in designing cluster-based communication protocols for wireless sensor networks. This paper analytically provides the optimal cluster size that minimizes the total energy expenditure in such networks, where all sensors communicate data through their elected cluster heads to the base station in a decentralized fashion. LEACH, LEACH-Coverage, and DBS comprise three cluster-based protocols investigated in this paper that do not require any centralized support from a certain node. The analytical outcomes are given in the form of closed-form expressions for various widely-used network configurations. Extensive simulations on different networks are used to confirm the expectations based on the analytical results. To obtain a thorough understanding of the results, cluster number variability problem is identified and inspected from the energy consumption point of view.