Intelligent Visualization Research Articles

Research on Database and Information Technology in the Decision Tree of Communication Construction Scheme

With the development of database technology as well as the widespread application of Database management system, our capabilities of both generating and collecting data have been increasing rapidly. In addition, popular use of the World Wide Web as a global information system has flooded us with a tremendous amount of data and information. This explosive growth in stored or transient data has generated an urgent need for new techniques and automated tools that can intelligently assist us in transforming the vast amounts of data into useful information and knowledge. The Data Mining technology brought forward. Data mining, also popularly referred to knowledge discovery from data (KDD), is the automated or convenient extraction of patterns representing knowledge implicitly stored or captured in large databases, data warehouses, the Web, other massive information repositories, or data streams. Data mining is a multidisciplinary field, drawing work from areas including database technology, machine learning, statistics, pattern recognition, information retrieval, neural networks, knowledge-based systems, artificial intelligence, high-performance computing, and data visualization. Database and Information Technology in the Decision Tree of is very important for the military. The Data Mining had been applied and studied in these years, and it has been applied in many domains successfully, such as business, finance and medical treatment. However, little is applied in communication construction scheme.

R&D of Visualization Control System for Differential Reactor

An intelligent control system for Differential Reactor is proposed based on the intelligent visualization control system, in order to reduce the complexity of process and temperature control during the operation. The Man-Machine Interface Unit is developed based on touch human-machine interface, this unit can be used to monitor and test the change of the parameters during Differential Reactor operation. At last the unit in combined with the Fuzzy PID-type controller. The practical tests performed in this article show that the new system can monitor the Differential Reactor in real-time, can effectively improve the visibility of the production process, simplify the system control, and effectively reduce the system failure rate.

Automated Protection Performance Assessment and Enhancement

New strategies and methods for assessing the security of protection systems to reduce the risk of unnecessary disturbances and blackouts are the main topic of the present paper. The system behavior of a protection system and network is analyzed and assessed as a whole. Hence, the established algorithms are capable to handle complex network structures with regard to an intelligent data management as well as data validation. Protection security assessment comprised two different aspects: on the one hand the behavior regarding dependability and security in terms of speed and sensitivity, on the other hand the behavior regarding the response on dynamic network phenomena as voltage stability and transient stability. A new automated method for assessing the dependability and security of protection systems is shown. The short-circuit simulation tool is used to provide a simulation system including network and protection devices as a whole. The handling of the large amount of resulting data is done by an intelligent visualization method like a “fingerprint” analysis. Further on the paper is focused on the protection response on dynamic network phenomena and presents innovative strategies for this investigation aspect. The structure of simulation environment will be described. Results of a case study show the application of this method on a real network. The system tool which is concluding these two aspects of protection assessment is called SIGUARD? PSA.

Short-term Cyber-physical Production Management

For most manufacturing companies a high adherence to delivery dates is their main logistic target. In consideration of the fact that for example material and information flows in production plants are getting more intersected and networked than ever before and customer demand tailored products in short throughput times, keeping an overview as well as responding properly becomes a huge challenge for the production manager. In the paper the new approach of cyber-physical short-term assistance of the production manager will be described. Its goal is to support the production controller by providing prioritized short-term actions through new sensor technologies, big data processing and simulation. The paper will outline how the roadmap to short-term cyber-physical production management is developed and what the real benefit for the production manager will be. With the help of intelligent visualization the application will display the effects of a performed action therefore be an optimal basis for decision for the production manager.

Special issue of selected articles from visualization and data analysis 2012

This special issue features the best articles that were selected from the 19th SPIE Conference on Visualization and Data Analysis (VDA 2012). This annual conference is a major international forum for researchers and practitioners interested in data visualization and analytics research, development, and applications. VDA 2012 was held in the city of Burlingame outside San Francisco, California, during 23–25 January 2012. VDA 2012 received 50 high-quality submissions from around the world. In total, 24 articles were selected for full conference articles. Of the top eight articles that were invited for this special issue, six were expanded and reviewed. The following is a synopsis of these articles. In ‘‘Designing a better weather display,’’ Colin Ware and Matthew Plumlee describe a set of interactive weather displays that depict two meteorological scalar fields and the wind vector field. They evaluate the effectiveness of their approach by implementing three alternative representations each showing the temperature, atmospheric pressure, wind speed, and wind direction simultaneously in one display. By taking advantage of the fragment shader on the graphics card, they first map a combination of scalar fields to color and texture. Then, additional layers of weather and geographical data are rendered on top of the base color layer. In ‘‘A new approach to interactive viewpoint selection for volume data sets,’’ Han Kim and colleagues introduce a new algorithm for finding the best view direction for volume rendering. Their viewpoint selection algorithm is very fast and takes less than a second, which makes it attractive for interactive volume visualization. The key features that make their algorithm fast are the simplicity of their algorithm and an efficient implementation on the graphics card. In ‘‘Animating streamlines with orthogonal advancing waves,’’ Chih-Kuo Yeh and his coauthors present a new flow visualization technique that depicts dense, accurate visualization of complex real-world flows using animated streamlines of an elegant placementcoupled visually appealing orthogonal advancing waves. Their work is motivated by the self-animating image of flow through repeated asymmetric patterns (RPA), which is an innovative approach for creating illusory motion using a single image. They introduce a smooth cyclic variable-speed RPA animation model that emulates orthogonal advancing waves from a geometry-based flow representation. In ‘‘Visual sentiment analysis of customer feedback streams using geo-temporal term associations,’’ Ming Hao and her colleagues present a business intelligence visualization tool that analyzes customer feedback streams harvested from both commercial product web surveys and Twitter. The tool provides four different visualization techniques for sentiment analysis, term association analysis, self-organizing map analysis, and geo-based association analysis. In ‘‘Exploring biological data: mappings between ontologyand cluster-based representations,’’ Ilir Jusufi and colleagues present a new visualization that combines the strengths of hierarchical clustering and ontologies into one analytical platform to study highthroughput data in biology and medicine. This article gives a detailed discussion on system architecture and

Developing and Applying the Information Construction Analysis Visualization System

Tunnel information construction is more and more concerned because of the uncertainty and complexity of geological body. Based on the back analysis principle of tunnel and intelligent science arithmetic, the paper self-developed tunnel information construction analysis visualization system by Visual C# platform and VTK techniques in order to the confliction between tunnel construction expending too much time and the construction period demand. Firstly introduced global optimization method-Difference Evolution (DE) Algorithm and combined it with finite element method (FEM) in order to back analyze the surrounding rock parameters. Then constructed the total software framework and developed the program of the information construction analysis intelligent visualization system. Applied the system to the Dalian Metro tunnel engineering construction and got satisfied results. The soft system developed by the paper has active meaning to promote the intelligence, visualization and automation of the tunnel construction.

Розробка моделей елементів гідроаеродинамічних систем на основі засобів інтелектуальної візуалізації

For identifying and studying the hydro-aerodynamic processes influence the hydraulic resistance in the elements of a complex shape complex modeling tools are developed. These tools allow receive the visual and intellectual models. For receiving of hydrodynamic intellectual models of hydro-aerodynamic structural primitives in the implementations array of the hydro-aerodynamic flows in major and minor hydro-aerodynamic systems' elements analysis and search of regularities for a more compact description of the data were carried out. The analysis was carried out in four phases: a priori alphabet classes preparation based on the clustering procedure, a priori attributes dictionary preparation, the classification algorithm implementation; clarify the description of all the classes in the signs language considering the classification quality index. For determining the prototype classes it was proposed to carry out the clustering of the visual data based on the method of intelligent visualization (MIV) using Kohonen self-organizing maps (SOM) in the form of coherent regions (coherent region) (SOM-CR).MIV SOM-CR is implemented in the form of two procedures: the classical self-organization and the modified calibration.At the stage of classification for separating surfaces building the multilayer perceptron (multilayer perceptron – MLP) is used. It was trained on the basis of back-propagation (back-propagation learning – BPL)

Methodology for the Assessment of Structural Complexity in Global Production Networks

The structure of production networks is mainly determined by the amount of production sites, the number of people working in these production sites and the distribution of products and production processes. Due to the dynamic and unpredictable changes in global market requirements production networks have become more and more complex driven by the growth of multinational companies through acquisitions and set ups of production plants. This paper presents an approach to design production networks with an optimal level of structural complexity in order to increase the efficiency of production processes around the world. The approach consists of two basic elements: firstly, the structural complexity is captured via characteristic parameters and quantified. The main characteristics of a production network such as the amount of production sites, the number of employees and the product and process distribution form the basis for the quantification. The second cornerstone is set by the intelligent visualization of the structural complexity with respect to organizational and communication aspects. Organization and communication structure of a company can be optimized comparing different production network scenarios, hence increasing the overall efficiency within global production networks. A validation of our approach is presented using a data set of a recently conducted industry project. Different network scenarios of a global manufacturer in the mechanical engineering field are compared to point out design rules for the optimization of structural complexity within the company.

A Systems Biology Approach to Solving the Puzzle of Unknown Genomic Gene-Function Association Using Grid-Ready SVM Committee Machines

Genomic researchers face the common challenge of deriving the functions of genes and proteins from high-throughput data. Experimental validation of protein function is costly and time-consuming. With the increased effectiveness of computational intelligence approaches, researchers aim to target the problem with in silico prediction of protein interactions and functions. We propose a systems biology approach that consists of machine-learning and visualization intelligence and aims to predict protein-protein interactions and enhance protein function annotation. Our machine-learning intelligence, SVM committee machines, is compatible with grid computing and large-scale data analysis. In this paper, we not only elucidate the computational power of protein interactions prediction, but also aim to emphasize the interpretation of protein function annotation through protein interaction network analysis.

Power Grid Maintenance Scheduling Intelligence Arrangement Supporting System Based on Power Flow Forecasting

With the development of intelligent dispatching, the intelligence level of network control center full-service urgent need to raise. As an important daily work of network control center, the application of maintenance scheduling intelligent arrangement to achieve high-quality and safety operation of power grid is very important. By analyzing the shortages of the traditional maintenance scheduling software, this paper designs a power grid maintenance scheduling intelligence arrangement supporting system based on power flow forecasting, which uses the advanced technologies in maintenance scheduling, such as artificial intelligence, online security checking, intelligent visualization techniques. It implements the online security checking of maintenance scheduling based on power flow forecasting and power flow adjusting based on visualization, in order to make the maintenance scheduling arrangement moreintelligent and visual.

Research for the Key Technologies of Smart Grid Dispatching

This paper studied the key technoligies and scientific issues of the smart grid dispatching, combining the status and trends of the development of smart grid, and has done research and analysis from the four aspects respectively as follow, the security and defense of a large network and panoramic information and integrated technology platform of smart grid dispatching, the multi-level integration of security check rechnology, energy saving intelligent optimization technology and multi-dimensional intelligent visualization technology of large grid. Summarized the existing equipment and industrial in the power network dispatching and gave some suggestions for developing the technologies of smart grid dispathching.

An ontology-based visualization for mobile geoinformation services

In mobile geoinformation services, most intelligent systems ignore the users’ states and roles and only include the user's location. However, different user profiles need customized visualization styles in order to provide relevant spatial data. With the availability of a variety of data sources and the ability for continuous data updates, the service is able to perceive and react to instant changes. The aim of this research is to describe contextual ontological model which provides visualization on mobile devices. Therefore, intelligent visualization explained in this study is defined by a complete semantic model of the Ontology Web Language – Description Logic (OWL-DL) and Semantic Web Rule Language (SWRL). Consequently, a mobile visualization service sensitive to the instant changes of the user’s situation has been proposed. Egocentric design of a map-based service has been tested on a scenario-based application of a mobile emulator. Key words: Context, ontology, knowledge-base, mobile, reasoning, visualization.

Intelligent visualization and exploration of time-oriented data of multiple patients

Clinicians and medical researchers alike require useful, intuitive, and intelligent tools to process large amounts of time-oriented multiple-patient data from multiple sources. For analyzing the results of clinical trials or for quality assessment purposes, an aggregated view of a group of patients is often required. To meet this need, we designed and developed the VISualizatIon of Time-Oriented RecordS (VISITORS) system, which combines intelligent temporal analysis and information visualization techniques. The VISITORS system includes tools for intelligent retrieval, visualization, exploration, and analysis of raw time-oriented data and derived (abstracted) concepts for multiple patient records. To derive meaningful interpretations from raw time-oriented data (known as temporal abstractions), we used the knowledge-based temporal-abstraction method. The main module of the VISITORS system is an interactive, ontology-based exploration module, which enables the user to visualize raw data and abstract (derived) concepts for multiple patient records, at several levels of temporal granularity; to explore these concepts; and to display associations among raw and abstract concepts. A knowledge-based delegate function is used to convert multiple data points into one delegate value representing each temporal granule. To select the population of patients to explore, the VISITORS system includes an ontology-based temporal-aggregation specification language and a graphical expression-specification module. The expressions, applied by an external temporal mediator, retrieve a list of patients, a list of relevant time intervals, and a list of time-oriented patients' data sets, by using an expressive set of time and value constraints. Functionality and usability evaluation of the interactive exploration module was performed on a database of more than 1000 oncology patients by a group of 10 users-five clinicians and five medical informaticians. Both types of users were able in a short time (mean of 2.5+/-0.2min per question) to answer a set of clinical questions, including questions that require the use of specialized operators for finding associations among derived temporal abstractions, with high accuracy (mean of 98.7+/-2.4 on a predefined scale from 0 to 100). There were no significant differences between the response times and between accuracy levels of the exploration of the data using different time lines, i.e., absolute (i.e., calendrical) versus relative (referring to some clinical key event). A system usability scale (SUS) questionnaire filled out by the users demonstrated the VISITORS system to be usable (mean score for the overall group: 69.3), but the clinicians' usability assessment was significantly lower than that of the medical informaticians. We conclude that intelligent visualization and exploration of longitudinal data of multiple patients with the VISITORS system is feasible, functional, and usable.

Intelligent Interactive Visual Exploration of Temporal Associations among Multiple Time-oriented Patient Records

To design, implement and evaluate the functionality and usability of a methodology and a tool for interactive exploration of time and value associations among multiple-patient longitudinal data and among meaningful concepts derivable from these data. We developed a new, user-driven, interactive knowledge-based visualization technique, called Temporal Association Charts (TACs). TACs support the investigation of temporal and statistical associations within multiple patient records among both concepts and the temporal abstractions derived from them. The TAC methodology was implemented as part of an interactive system, called VISITORS, which supports intelligent visualization and exploration of longitudinal patient data. The TAC module was evaluated for functionality and usability by a group of ten users, five clinicians and five medical informaticians. Users were asked to answer ten questions using the VISITORS system, five of which required the use of TACs. Both types of users were able to answer the questions in reasonably short periods of time (a mean of 2.5 +/- 0.27 minutes) and with high accuracy (95.3 +/- 4.5 on a 0-100 scale), without a significant difference between the two groups. All five questions requiring the use of TACs were answered with similar response times and accuracy levels. Similar accuracy scores were achieved for questions requiring the use of TACs and for questions requiring the use only of general exploration operators. However, response times when using TACs were slightly longer. TACs are functional and usable. Their use results in a uniform performance level, regardless of the type of clinical question or user group involved.

An intelligent visualisation and decision support system for decentralised wastewater treatment plants

Current sanitation concepts of decentralised wastewater treatment and reuse raise the issue of monitoring and maintenance of such systems. To guarantee high quality of the recycled water, systems with high requirements concerning process technology are essential. With increasing numbers of decentralised treatment systems spread over far distances it will become more and more impossible and uneconomic to have expert personnel on site. Therefore, new visualisation and intelligent information systems are necessary. The paper describes the structure and 3D-demonstrations as a base for information visualisation. Up-to-date visualisation techniques, facilitating the cognition of context-adapted information, make it possible to maximise the amount of information presented to the user without overwhelming her or him. Concerning diagnosis and decision support systems in the domain of wastewater treatment, several interesting approaches are presented, estimating their applicability for decentralised wastewater treatment systems. The intelligent decision support system presented here consists of a combined ontology- and case-based reasoning system in addition to a process monitoring system. It is responsible for plausibility checks, error diagnosis, solution proposals, and optimisation suggestions.

Machine Learning to Boost the Next Generation of Visualization Technology

Visualization has become an indispensable tool in many areas of science and engineering. In particular, the advances made in the field of visualization over the past 20 years have turned visualization from a presentation tool to a discovery tool. Machine learning has received great success in both data mining and computer graphics; surprisingly, the study of systematic ways to employ machine learning in making visualization is meager. Like human learning, we can make a computer program learn from previous input data to optimize its performance on processing new data. In the context of visualization, the use of machine learning can potentially free us from manually sifting through all the data. This paper describes intelligent visualization designs for three different applications: (1) volume classification and visualization, (2) 4D flow feature extraction and tracking, (3) network scan characterization.

Differentiation of Cognitive Abilities as a Function of Level of General Intelligence: A Latent Variable Approach

Differentiation of cognitive abilities at different levels of general ability in same-aged subjects was tested by a latent variable approach in a multiple-groups design. Eighteen-year old conscripts (n = 14,720) representing the whole range of general ability in the male population, except for the mentally retarded, were tested by the Swedish Enlistment Battery. The sample of subjects was divided into 8, 16 and 32 groups according to level of general ability (G), and the amount of variance due to the ability factors Crystallized intelligence (Gc) and General visualization (Gv) was studied over the G levels. Variance contributed by Gc and Gv increased as the level of G increased. This effect was, however, not observed up through the highest levels of G, probably due to deficiencies in the measurement properties of the Gc and Gv tests at the highest G levels. Theoretical and methodological implications of the results are discussed, as are the consequences for the assessment of specific cognitive abilities at different levels of general ability.

Intelligent multi-shot 3D visualization interfaces

In next-generation virtual 3D simulation, training, and entertainment environments, intelligent visualization interfaces must respond to user-specified viewing requests so users can follow salient points of the action and monitor the relative locations of objects. Users should be able to indicate which object(s) to view, how each should be viewed, what cinematic style and pace to employ, and how to respond when a single satisfactory view is not possible. When constraints fail, weak constraints can be relaxed or multi-shot solutions can be displayed in sequence or as composite shots with simultaneous viewports. To address these issues, we have developed CONSTRAINTCAM, a real-time camera visualization interface for dynamic 3D worlds.

Independent Confirmatory Factor Analysis of the Cognitive Assessment System (CAS): What Does the CAS Measure?

Hierarchical multi-sample confirmatory factor analysis (CFA) was used to address several unresolved issues concerning the structure of the Cognitive Assessment System (Das & Naglieri, 1997), a new test of intelligence based upon the planning, attention, and simultaneous-successive (PASS) processes theory of human cognition. First, we investigated whether the CAS measures the same constructs from ages 5 to 17 years. Second, we examined the adequacy of the fit provided by the PASS model and the correlations among the PASS factors. Third, and finally, we compared the fit provided by the PASS model with several models that reflect plausible rival hypotheses of the CAS structure. Results of these analyses suggest that the CAS measures the same constructs across its 12-year age span. Nevertheless, although the correlated PASS model provided a better fit to the data than did several competing nonhierarchical models, it did not provide a particularly good fit. Moreover, an hierarchical model reflecting the implied theoretical structure of the CAS provided a marginal fit to the data and a statistically worse fit than a competing hierarchical model. The best-fitting model was a third-order factor model with psychometric g at the apex of the factor hierarchy, an intermediate combined Planning/Attention factor, and four first-order PASS factors. Based on these results, the CAS tests are better understood within the framework of Carroll's (1993) three-stratum theory as measures of processing speed (rather than planning and attention processes), memory span (rather than successive coding), and a mixture of fluid intelligence and broad visualization (rather than simultaneous coding). Results of our CFA of the standardization data do not support use of the CAS for differential diagnosis or for planning treatments based upon the PASS Scales.

A Hybrid Moire-Interferometry and Finite-Element Method Based on a Variational Principle Minimizing Experimental Measurement Errors. Case of Elastic-Plastic Deformation Field.

In a previous study, for the case of elastic deformation field, the authors have developed a hybrid experimental-numerical method based on a variational principle minimizing experimental measurement errors. In this stydy, for the case of elastic-plastic deformation field, first, an incremental variational principle is derived to minimize the errors associated with a full-field displacement measurement such as moire interferometry. Next, on the basis of this variational principle, a new hybrid moire-interferometry and finite element method is developed for the case of elastic-plastic deformation field. The present hybrid method demonstrates automatic detection and elimination of the measurement errors and smooth visualization of stress and strain contours. Furthermore, the present hybrid method automatically achieves the path independence of the T* integral, restoring the path-dependence caused by the measurement errors. This paper provides the foundation of an intelligent measurement and visualization of displacement and stress fields in actual structural components.