Generating Explanatory Captions for Information Graphics

Graphical presentations can be used to communicate information in relational data sets succinctly and effectively. However, novel graphical presentations about numerous attributes and their relationships are often difficult to understand completely until explained. Automatically generated graphical presentations must therefore either be limited to simple, conventional ones, or risk incomprehensibility. One way of alleviating this problem is to design graphical presentation systems that can work in conjunction with a natural language generator to produce "explanatory captions." This paper presents three strategies for generating explanatory captions to accompany information graphics based on: (1) a representation of the structure of the graphical presentation (2) a framework for identifyingthe perceptual complexity of graphical elements, and (3) the structure of the data expressed in the graphic. We describe an implemented system and illustrate how it is used to generate explanatory cap..

Broadening the interface bandwidth in simulation based training

Currently most computer based simulations rely exclusively on computer generated graphics to create the simulation. When training is involved, the method almost exclusively used to display information to the learner is text displayed on the cathode ray tube. MICROEXPERT Systems is concentrating on broadening the communications bandwidth between the computer and user by employing a novel approach to video image storage combined with sound and voice output. An expert system is used to combine and control the presentation of analog video, sound, and voice output with computer based graphics and text. Researchers are currently involved in the development of several graphics based user interfaces for NASA, the U.S. Army, and the U.S. Navy. Here, the focus is on the human factors considerations, software modules, and hardware components being used to develop these interfaces

Intelligent visualisation and information presentation for civil crisis management

This paper describes an ongoing research work on developing methods for effective visualisation support for situation analysis, decision making, and communication in the course of disaster management. The major goals are to reduce the information load of the analyst, decision maker, or information recipient without omission of anything important and to ensure quick and accurate comprehending of the information. The work embraces the issues of selection of the relevant information and defining the appropriate level of detail, data preparation (aggregation and other transformations), and selection of the appropriate methods for visual representation depending on the user's tasks or communication goals, recipient's profile, and the target presentation medium. A practical outcome from the research will be a knowledge base that can be used to support analysis, decision making, and information communication in emergency situations. A great part of the knowledge, specifically, knowledge on data transformation and representation, is generic and can be used for different applications

The Development Methodology Of Operational Dashboard As A Tool For Organizational Performance Monitoring (A Case Study: Telkom Polytechnic)

The management needs to monitor and measure the performance of the organization continuously to restrain that business processes aims at the organization's mission and vision. This study assist management to monitor the organization performance continuously to restrain that business processes aims at the organization's goals. Providing the information about the achievement on KPIs that really fit the needs of its users, conveying the information are accurately and timely in the comfortable presentation format that effective. The information comes from various units within organization, so the management can take action or strategic decision-making quickly and precisely targeted for the improvement of the organization. The problems can be solved with information provider tools of the dashboard software. Dashboard software to be built is operational dashboard for the study program. Operational dashboard provides information on the ongoing activities, along with changes in real time to provide awareness to the things that need to be responded quickly, the information presented is very specific to the sufficient depth detail level, it is dynamic because it uses the data with higher frequency real time updates. The methodology proposed by Eva Hariyanti [5] was modified to suitable with environment condition. Her methodology aimed to develop dashboard at strategic and tactical level, while this study to produced operational dashboard. Her methodology concerns in provide data/information, personalized and collaboration among user. The methodology to develop operational dashboard was not cover analytical and trackability characteristic. Keywords : monitor, KPI, performance, operational dashboar

Generating multimedia briefings: coordinating language and illustration

AbstractCommunication can be more effective when several media (such as text, speech, or graphics) are integrated and coordinated to present information. This changes the nature of media-specific generation (e.g., language or graphics generation), which must take into account the multimedia context in which it occurs. This paper presents work on coordinating and integrating speech, text, static and animated three-dimensional graphics, and stored images, as part of several systems we have developed at Columbia University. A particular focus of our work has been on the generation of presentations that brief a user on information of interes

Artificial intelligence in steam cracking modeling : a deep learning algorithm for detailed effluent prediction

Chemical processes can benefit tremendously from fast and accurate effluent composition prediction for plant design, control, and optimization. The Industry 4.0 revolution claims that by introducing machine learning into these fields, substantial economic and environmental gains can be achieved. The bottleneck for high-frequency optimization and process control is often the time necessary to perform the required detailed analyses of, for example, feed and product. To resolve these issues, a framework of four deep learning artificial neural networks (DL ANNs) has been developed for the largest chemicals production process-steam cracking. The proposed methodology allows both a detailed characterization of a naphtha feedstock and a detailed composition of the steam cracker effluent to be determined, based on a limited number of commercial naphtha indices and rapidly accessible process characteristics. The detailed characterization of a naphtha is predicted from three points on the boiling curve and paraffins, iso-paraffins, olefins, naphthenes, and aronatics (PIONA) characterization. If unavailable, the boiling points are also estimated. Even with estimated boiling points, the developed DL ANN outperforms several established methods such as maximization of Shannon entropy and traditional ANNs. For feedstock reconstruction, a mean absolute error (MAE) of 0.3 wt% is achieved on the test set, while the MAE of the effluent prediction is 0.1 wt%. When combining all networks-using the output of the previous as input to the next-the effluent MAE increases to 0.19 wt%. In addition to the high accuracy of the networks, a major benefit is the negligible computational cost required to obtain the predictions. On a standard Intel i7 processor, predictions are made in the order of milliseconds. Commercial software such as COILSIM1D performs slightly better in terms of accuracy, but the required central processing unit time per reaction is in the order of seconds. This tremendous speed-up and minimal accuracy loss make the presented framework highly suitable for the continuous monitoring of difficult-to-access process parameters and for the envisioned, high-frequency real-time optimization (RTO) strategy or process control. Nevertheless, the lack of a fundamental basis implies that fundamental understanding is almost completely lost, which is not always well-accepted by the engineering community. In addition, the performance of the developed networks drops significantly for naphthas that are highly dissimilar to those in the training set. (C) 2019 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company

Presenting Arguments as Fictive Dialogue

Presentation of an argument can take many different forms ranging from a monologue to advanced graphics and diagrams. This paper investigates the presentation of one or more arguments in the form of a fictive dialogue. This technique was already employed by Plato, who used fictive conversations between Socrates and his contemporaries to put his arguments forward. Ever since, there have been influential authors – including Desiderius Erasmus, Sir Thomas More and Mark Twain – that have used dialogue in this way. In this paper, we define the notion of a fictive dialogue, motivate it is as a topic for investigation, and present a qualitative and quantitative study of five fictive dialogues by well-known authors. We conclude by indicating how our preliminary and ongoing investigations may inform the development of systems that automatically generate argumentative fictive dialogue

Automatic design of multimodal presentations

We describe our attempt to integrate multiple AI components such as planning, knowledge representation, natural language generation, and graphics generation into a functioning prototype called WIP that plans and coordinates multimodal presentations in which all material is generated by the system. WIP allows the generation of alternate presentations of the same content taking into account various contextual factors such as the user\u27s degree of expertise and preferences for a particular output medium or mode. The current prototype of WIP generates multimodal explanations and instructions for assembling, using, maintaining or repairing physical devices. This paper introduces the task, the functionality and the architecture of the WIP system. We show that in WIP the design of a multimodal document is viewed as a non-monotonic process that includes various revisions of preliminary results, massive replanning and plan repairs, and many negotiations between design and realization components in order to achieve an optimal division of work between text and graphics. We describe how the plan-based approach to presentation design can be exploited so that graphics generation influences the production of text and vice versa. Finally, we discuss the generation of cross-modal expressions that establish referential relationships between text and graphics elements

EEG-informed fMRI reveals spatiotemporal characteristics of perceptual decision making

Single-unit and multiunit recordings in primates have already established that decision making involves at least two general stages of neural processing: representation of evidence from early sensory areas and accumulation of evidence to a decision threshold from decision-related regions. However, the relay of information from early sensory to decision areas, such that the accumulation process is instigated, is not well understood. Using a cued paradigm and single-trial analysis of electroencephalography (EEG), we previously reported on temporally specific components related to perceptual decision making. Here, we use information derived from our previous EEG recordings to inform the analysis of fMRI data collected for the same behavioral task to ascertain the cortical origins of each of these EEG components. We demonstrate that a cascade of events associated with perceptual decision making takes place in a highly distributed neural network. Of particular importance is an activation in the lateral occipital complex implicating perceptual persistence as a mechanism by which object decision making in the human brain is instigated