Designing a graphical user interface for the decision support system of driving fatigue

The Multiscale Epidemiologic/Economic Simulation and Analysis (MESA) Decision Support System (DSS) is the product of investments that began in FY05 by the Department of Homeland Security (DHS) Science and Technology Directorate and continue today with joint funding by both DHS and the US Department of Agriculture (USDA). The DSS consists of a coupled epidemiologic/economic model, a standalone graphical user interface (GUI) that supports both model setup and post-analysis, and a Scenario Bank archive to store all content related to foreign animal disease (FAD) studies. The MESA epi model is an object-oriented, agent-based, stochastic, spatio-temporal simulator that parametrically models FAD outbreaks and response strategies from initial disease introduction to conclusion over local, regional, and national scales. Through its output database, the epi model couples to an economic model that calculates farm-level impacts from animal infections, responsive control strategies and loss of trade. The MESA architecture contains a variety of internal models that implement the major components of the epi simulation, including disease introduction, intra-herd spread, inter-herd spread (direct and indirect), detection, and various control strategies (movement restrictions, culling, vaccination) in a highly configurable and extensible fashion. MESA development was originally focused to support investigations into the economic and agricultural industry impacts associated with Foot-and-Mouth Disease (FMD outbreaks). However, it has been adapted to other FADs such has Highly Pathogenic Avian Influenza (HPAI), Classical Swine Fever (CSF) and Exotic Newcastle Disease (END). The MESA model is highly parameterized and employs an extensible architecture that permits straightforward addition of new component models (e.g., alternative disease spread approaches) when necessary. Since its inception, MESA has been developed with a requirement to enable simulation of the very large scale, nationwide disease outbreaks that are of special interest to DHS. MESA has been developed at Lawrence Livermore National Laboratory (LLNL) and has benefited from the world-class experience in supercomputing application development held by LLNL staff as well as the best-in-class high performance computing infrastructure in place at LLNL. MESA incorporates novel architectural features that permit it to make efficient use of available compute cycles by dynamically increasing the fidelity of the simulation in spatial (geopolitical) regions where relevant activity is occurring and keeping other regions aggregated into a computationally simpler representation. In addition to the MESA epi and economic models, the MESA DSS incorporates other key components. Integral to the parametric approach MESA employs to setup and define disease outbreak scenarios is a GUI that enables the MESA user to efficiently manage the thousands of parameters required by the simulator. The GUI provides individual parameter editors for groups of variables that support a common high level function, such as disease introduction, spread, control strategies, etc. It also provides a capability to browse through multiple study projects and develop n-additional outbreak scenarios per project through successive refinement of existing scenarios. Finally, the MESA GUI links post-processing applications that permit extraction of key data from MESA raw output, generation of spreadsheets, and geospatial mapping of simulation results. The MESA GUI is a standalone application that normally runs on the user's desktop, although its Java source code is portable and can execute under virtually any modern operating system. The final major component of the MESA DSS is the Scenario Bank, which is a web-served archive of unclassified FAD study content. The Scenario Bank implements a hierarchy of spaces, structured primarily along organizational lines (e.g., 'USDA', 'LLNL', etc), that permits participants to store simulator inputs, outputs, analysis results, reports, etc. and explicitly control who among Bank users may access them. Documents can be shared within organizations or across organizations at the owner's discretion. The Scenario Bank is intended to be the system of record for USDA and DHS sponsored FAD study efforts and as such will archive content from a variety of models employed by USDA and DHS-sponsored researchers and analysts.

In software development process, the last step is usually the Graphic User Interface(GUI) test, which is part of the final user experience (UE) test. Traditionally, there exist some GUI test tools in the market, such as Abbot Java GUI Test Framework and Pounder, in which testers pre-configure in the script all desired actions and instructions for the computer, nonetheless requiring too much of invariance of GUI environment; and they require reconfiguration in case of GUI changes, therefore still to be done mostly manually and hard for non-programmer testers to. Consequently, we proposed GUI tests by image recognition to automate the last process; we managed to innovate upon current algorithms such as SIFT and Random Fern, from which we develop the new algorithm scheme retrieving most efficient feature and dispelling inefficient part of each algorithm. Computers then apply the algorithm, to search for target patterns themselves and take subsequent actions such as manual mouse, keyboard and screen I/O automatically to test the GUI without any manual instructions. Test results showed that the proposed approach can accelerate GUI test largely compared to current benchmarks.

Dynamic Software Product Line (DSPL) Engineering has gained interest through its promise of being able to unify software adaptation whereby software adaptation can be realised at compile time and runtime. While previous work has enabled program logic adaptation by the use of language extensions and platform support, little attention has been placed on Graphical User Interface (GUI) variability. Different design patterns including the Model View Controller are commonly used in GUI implementation, with GUI documents being used for declaring the GUI. To handle dynamic GUI variability currently, the developer needs to implement GUI refinements using multiple techniques. This paper proposes a solution for dealing with GUI document variability, statically and dynamically, in a unified way. In our approach, we currently use a compile time method for producing GUI variants, and code transformations to handle these variants within the application at runtime. To avoid GUI duplicates, only GUI variants that are unique, and related to a valid product configuration, are produced. To validate our approach, we implemented tool support to enable this for Android based applications.

There are several spatial problems in the water resources sector such as flood control and management, which can be managed efficiently if there is a case-based decision-making process. These types of problems need human intervention and amicable management is possible by decision making based on various possible alternatives. The recent advances in computational facilities, quick and real time access to various types of data and development in graphical user interface (GUI), have led to the frequent application of decision support system (DSS) in complex water resources management problems like flood management. This review paper summarises past efforts employing DSS, risk-based DSS and future research for DSS used in flood management. The main purpose of this review is to assess the progress made in the development of DSS and to understand how efficient it is in solving flood management problems.

Software testing in general and graphical user interface (GUI) testing in particular is one of the major challenges in the lifecycle of any software system. GUI testing is inherently more difficult than the traditional and command-line interface testing. Some of the factors that make GUI testing different from the traditional software testing and significantly more difficult are: a large number of objects, different look and feel of objects, many parameters associated with each object, progressive disclosure, complex inputs from multiple sources, and graphical outputs. The existing testing techniques for the creation and management of test suites need to be adapted/enhanced for GUIs, and new testing techniques are desired to make the creation and management of test suites more efficient and effective. In this article, a methodology is proposed to create test suites for a GUI. The proposed methodology organizes the testing activity into various levels. The tests created at a particular level can be reused at higher levels. This methodology extends the notion of modularity and reusability to the testing phase. The organization and management of the created test suites resembles closely to the structure of the GUI under test.

A Decision Support System for market-driven product positioning and design

Purpose – The purpose of this paper is to present a real world application of an innovative hybrid system reliability optimization algorithm combining Tabu search with an evolutionary algorithm (TSEA). This algorithm combines Tabu search and Genetic algorithm to provide a more efficient search method. Design/methodology/approach – The new algorithm is applied to an aircraft structure to optimize its reliability and maintain its structural integrity. For retrofitting the horizontal stabilizer under severe stall buffet conditions, a decision support system (DSS) is developed using the TSEA algorithm. This system solves a reliability optimization problem under cost and configuration constraints. The DSS contains three components: a graphical user interface, a database and several modules to provide the optimized retrofitting solutions. Findings – The authors found that the proposed algorithm performs much better than state-of-the-art methods such as Strength Pareto Evolutionary Algorithms on bench mark problems. In addition, the proposed TSEA method can be easily applied to complex real world optimization problem with superior performance. When the full combination of all input variables increases exponentially, the DSS become very efficient. Practical implications – This paper presents an application of the TSEA algorithm for solving nonlinear multi-objective reliability optimization problems embedded in a DSS. The solutions include where to install doublers and stiffeners. Compromise programming is used to rank all non-dominant solutions. Originality/value – The proposed hybrid algorithm (TSEA) assigns fitness based upon global dominance which ensures its convergence to the non-dominant front. The high efficiency of this algorithm came from using Tabu list to guidance the search to the Pareto-optimal solutions.

The practitioner interested in reducing software verification effort may found herself lost in the many alternative definitions of Graphical User Interface (GUI) testing that exist and their relation to the notion of system testing. One result of these many definitions is that one may end up testing the same parts of the Software Under Test (SUT), specifically the application logic, twice. To clarify two important testing activities and avoid duplicate testing effort, this paper empirically evaluates to what extent GUI tests exercise the application logic of the software under test (and not only the GUI code). Experimental results show that GUI tests do not necessarily entirely exercise application logic functionality, at least not as much as system tests directly interacting with application logic code.

The wide use of GUI (Graphic User Interface - graphical User Interface) is one of the great achievements in today's computer development. μC/GUI, as one of the mature GUI technology, becomes more and more common in embedded products. It has a small kernel, occupying less resources, high performance and high reliability etc, and can be designed as powerful and complex man-machine interface for embedded system. it uses the STM32 development board as the carrier. Software system is composed of hardware drivers, μC/OS-Ⅱ real-time operating system, FATFS file system, μC/GUI graphical interface system and so on. Analyzing the process and steps of μC/GUI transplantation, through the design of interface we can realizes simple human-computer interaction function. After tested, it works well.

Mobile applications use Accessibility Services to assist users with disabilities (UWDs) in using Graphical User Interface (GUI)-based apps. However, such mobile assistive technologies are not fully secure as these can obtain data from the GUI objects, enhance this data for UWDs and transmit it to a server, thereby potentially exposing sensitive data to the external world. SEAPHISH (SEcuring Accessibility using PHISHing) is a platform aimed towards protecting against such an attack by providing defense by deception. This platform generates a phishing app i.e. an app similar to the original app installed on the user’s smartphone by extracting GUI elements and properties from the original app. A simulation for SEAPHISH can help determine the situations when an attack against a particular app can be performed with a high degree of probability. But performing effective simulations requires a fundamental understanding of the properties of GUI layouts of apps at large. This thesis aims at providing a framework that analyzes GUI layouts and their transitions using a large base of approximately three million Android apps. Various state-of-the-art tools that use different strategies in traversing layouts are explored. We created a framework where the tool Backstage performs static analysis and another tool AndroidRipper performs dynamic analysis of the layouts to help build a GUI model of the app. Using these models, we investigate the layouts of Android apps by collecting statistics on various GUI elements and screens. This investigation enhances SEAPHISH with statistically significant real-world constraints thereby providing defense against malwares and reducing the security vulnerabilities faced by UWDs.

Understanding technological change is important for practitioners and academics who want a realistic perspective on information technology’s role in building Decision Support Systems (DSS). To develop this perspective, the DSS technology outlined by Sprague and Carlson (1982) is compared and contrasted with the technological context of current DSS. Their technology framework of dialogue, database, models, and DSS architecture is reviewed. Current technologies like Graphical User Interfaces (GUI), data warehouses, On-line Analytical Processing (OLAP), and client-server technologies are then discussed in terms of that framework. Several examples are used to illustrate the changing technological context of DSS.KeywordsDecision Support SystemsDSSinformation technologytechnology change

Visual and aural are two most important channels of information processing. While most of the interaction with computers have been designed around the visual channel, there are circumstances where voice based man-machine interaction becomes preferable, and in some cases, necessary, given that voice based interaction comes naturally to humans and can be used by illiterate people easily.

The contemporary theory of metaphor defines the metaphor as a major and indispensable part of our ordinary, conventional way of conceptualizing the world and it asserts that the metaphors are used to define our relationship with the physical environment and to create a context of communication. The metaphors are the core idioms of the contemporary graphical user interface (GUI) and have an important role in helping users interact with computer systems. The desktop metaphor began with the first GUI Xerox Star and was popularized by the Lisa of Apple Macintosh. Realizing the physical-office metaphor and reflecting the familiar world of the potential users by using icons of file, folder and trashcan, the metaphor-based GUIs made it relatively easy for all to use the computer productively. Nowadays almost all of the software industry is based on the desktop metaphor paradigm. However, besides the researchers that favor the use of metaphors in the development of the system image by accentuating their assistance to learning, there are also other researchers, who reject the metaphor-based design approach in GUIs by referring to their limitations. Considering these discussions and various approaches, this study aims to make an outline of the historical development of metaphor-based GUIs; to determine the current state of metaphor within GUI design by brief examples and finally to identify future prospects and research themes. The study claims that metaphor still remains to be an inevitable part of the GUI to communicate it with the users and despite its potential limitations -rather than rejecting the metaphor totally- it seems better-to try compatible and supplementary solutions like visual formalism.

An important component of Early Warning Systems (EWS) for man-made and natural hazards is the command and control unit’s Graphical User Interface (GUI). All relevant information of an EWS is concentrated in this GUI and offered to human operators. However, when designing the GUI, not only the user experience and the GUI’s screens are relevant, but also the frameworks and technologies that the GUI is built on and the implementation of the GUI itself are of great importance. Implementations differ based on their applications in different domains but the design and approaches to implement the GUIs of different EWS often show analogies. The design and development of such GUIs are performed repeatedly on some parts of the system for each EWS. Thus, the generic GUI framework of a geospatial EWS for tsunamis is introduced to enable possible synergistic effects on the development of other new related technology. The results presented here could be adopted and reused in other EWS for man-made and natural hazards.

With the growing usage and migration of interactive applications and systems into today’s environment, the significance of the graphical user interfaces (GUIs) increases as they act as the gates into using systems efficiently. Therefore, extensive efforts are spent to enhance the usability of the GUIs. However, most of the works focus on testing the functional properties of applications’ GUIs rather than nonfunctional features such as performance. For this reason, it is worthwhile to assess the performance of various GUI components at runtime. In this paper, the most popular programming languages used to create GUI based applications namely, Java and C# were compared experimentally to evaluate their performance in terms of the creation and manipulation of GUI components/controls. The experimental results of this study, which is based on 32 testing scenarios, showed that Java outperformed C# in all test scenarios. This might be because of the “HotSpot” performance engine that Java uses. This study is useful for developers to get insights into the performance of different GUI components provided by different programming languages. Also, it helps them to choose the right programming language for their GUI based applications hence enhance the overall applications’ performance and user satisfaction.