A constraint-based querying system for exploratory pattern discovery

In this paper we present ConQueSt, a constraint based querying system devised with the aim of supporting the intrinsically exploratory (i.e., human-guided, interactive, iterative) nature of pattern discovery. Following the inductive database vision, our framework provides users with an expressive constraint based query language which allows the discovery process to be effectively driven toward potentially interesting patterns. Such constraints are also exploited to reduce the cost of pattern mining computation. We implemented a comprehensive mining system that can access real world relational databases from which extract data. After a preprocessing step, mining queries are answered by an efficient pattern mining engine which entails several data and search space reduction techniques. Resulting patterns are then presented to the user, and possibly stored in the database. New user-defined constraints can be easily added to the system in order to target the particular application considered.

Various numerical techniques have been developed for modeling electromagnetic field propagation in various novel complex media. The validity of these techniques is usually verified by comparison to the exact solutions of canonical problems. Recently, research has focused on chiral media, a subclass of materials known as bianisotropic materials, and numerical techniques have been developed in order to calculate the interaction of electromagnetic fields with chiral objects. One canonical problem for these techniques is plane-wave scattering from a chiral sphere. This work presents a software package that displays and saves the calculated data for the scattering from a chiral, dielectric, or perfectly conducting sphere using a friendly graphical user interface (GUI).

TheGESTsoftware has been developed for the solution of molecular crystal structures from powder diffraction data. In this package, a genetic algorithm is used for global optimization to search for the structural model. For more efficient calculation time, a modified BraggRfactor is used as the evaluation function for the genetic algorithm. Applications of this program for structure determination of molecular crystals from powder diffraction data are demonstrated with known and previously unknown structures. A friendly graphical user interface (GUI) is used to generate the control file and run the program. TheGESTprogram with GUI, for Linux and Windows platforms, is freely available from the authors upon request.

This paper presents a novel prototype platform that uses the same LaTeX mark-up language, commonly used to typeset mathematical content, as an input language for modeling optimization problems of various classes. The platform converts the LaTeX model into a formal Algebraic Modeling Language (AML) representation based on Pyomo through a parsing engine written in Python and solves by either via NEOS server or locally installed solvers, using a friendly Graphical User Interface (GUI). The distinct advantages of our approach can be summarized in (i) simplification and speed-up of the model design and development process (ii) non-commercial character (iii) cross-platform support (iv) easier typo and logic error detection in the description of the models and (v) minimization of working knowledge of programming and AMLs to perform mathematical programming modeling. Overall, this is a presentation of a complete workable scheme on using LaTeX for mathematical programming modeling which assists in furthering our ability to reproduce and replicate scientific work.

Propagation prediction software for wireless communications is developed based on efficient ray-tracing simulation. The software has a friendly graphical user interface (GUI) and provides calculations for propagation parameters including path loss, delay spread, and angles of arrival/departure. Users can upload AutoCAD files of indoor or outdoor environments and assign wall geometries and electrical parameters easily. User defined radiation patterns can also be incorporated in the simulation. The software provides colored graphs for the simulated results.

Magnetoencephalography(MEG) is a functional, noninvasive technology for recording neuronal activity of human brain in real-time. MEG has been approved as an efficient and powerful functional detection method which has been used in clinical practices relate with epilepsy, depression, and other diseases that cannot be well-diagnosed by traditional structural methods, e.g., CT and MRI. By using MEG, very weak magnetic signals typically in the range of 10 femtotesla (fT)-1 picotesla (pT) that originate from electric currents flowing in neurons, can be recorded. Compared with scalp EEG, MEG provides much better spatial resolution. Meanwhile, MEG is a noninvasive technology for preoperative workup for epilepsy surgery, which means it may replace traditional invasive methods. As the development of high-sampling rate MEG systems as well as the discovery high-frequency oscillations (HFOs) in the brain, MEG is now typically digitally analyzed in very high-frequency range. Although MEG has been clinically used for two decades, it is not so widely-used as EEG. The lack of a powerful software platform is an important reason which hinders the development of MEG. A MEG-specific software, MEG processor, was released here. With the friendly graphical user interface (GUI) of MEG Processor, researcher can easily identify/mark HFOs and project the signal to MRI receiving a precise 3D reconstruction. We hope such a platform will help and encourage more clinicians to uncover the magnificent features of MEG.

Refinery advanced process control planning system

In this research, a prototype rule-based expert system for travel demand management (TDM) in selecting suitable policy was designed and developed. This expert system suggests a process for travel demand management policy implementation, and offers guidance and advice on the selection of effective and appropriate policies. The system is supported with an object-oriented modeling in the knowledge abstraction and representation, and the interactions with the system are performed through a friendly graphical user interface (GUI). The prototype of the system was developed in shell expert system platform (KAPPA-PC). The outcomes obtained by the current prototype show that the used rule-based expert system architecture resulted in successful computerized intelligent decision support software that is easy to maintain, modify, and extend.

The paper presents a graphical blockdiagram based programming tool, which is a new software development system for digital signal processing (DSP). This system provides a blockdiagram editor; therefore, the DSP system can be easily built by connecting functional blocks as described in the signal-flow graph. A block library is set up, which includes basic signal processing functions and some frequently used high level signal processing functions like FIR, IIR, FFT, etc. A friendly graphic user interface (GUI) based on the ‘X-Window’ system is developed to support each design step. Users can then improve their design easily according to the GUI's response. To guarantee the correctness of the circuits designed, the debugging and verifying capabilities are embedded in our system. The full system is combined with a structural silicon compiler, which we developed previously. Several designs will be illustrated as examples. It has been shown that this tool will be suitable for DSP system design by using a silicon compiler

In this paper, a Graphical User Interface (GUI) is designed and developed using Python programming language for detection of forest fires at early stages, which is efficient, cost-effective, flexible, secure and uses open-source technologies. The user-friendly Graphical User Interface is interfaced directly with the computer port to fetch the data with the help of Python modules, performs an analysis on the data and predict whether there is a situation of fire or not and displays the status on the Graphical User Interface. Data is also stored in an Excel file for further analysis. The possibility to detect forest fire situation at its early stages makes this GUI a valuable software in environmental disasters and research applications. Numerical results along with future work have been discussed in this paper.

We developed a user-friendly numerical model, Shoreline Bioremediation Model (SBM), to simulate the biodegradation and bioremediation of oil entrapped within shorelines. The model takes oil properties and environmental conditions as input and produces variation of oil concentration with time, up to several years from the time of the spill. SBM is equipped with a user-friendly graphical user interface (GUI). The accessibility and easy-to-use interface allow the user to quickly produce several biodegradation and bioremediation scenarios before they are implemented at the contaminated shoreline. The model has been calibrated to predict the biodegradation rate of saturates and aromatics, but it can be also used to predict the biodegradation rates of individual oil components and to decide on bioremediation studies in shorelines based on the enhancement due to biostimulation (addition of nutrients) or bioaugmentation (addition of hydrocarbon degrading organisms). The GUI provides the oil concentration with time along with best case and worst case scenarios, which is commonly needed for decision making.

A new Graphical User Interface (GUI) was developed using Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW) for a high-resolution, high-sensitivity Solid State X-ray Image Intensifier (SSXII), which is a new x-ray detector for radiographic and fluoroscopic imaging, consisting of an array of Electron-Multiplying CCDs (EMCCDs) each having a variable on-chip electron-multiplication gain of up to 2000× to reduce the effect of readout noise. To enlarge the field-of-view (FOV), each EMCCD sensor is coupled to an x-ray phosphor through a fiberoptic taper. Two EMCCD camera modules are used in our prototype to form a computer-controlled array; however, larger arrays are under development. The new GUI provides patient registration, EMCCD module control, image acquisition, and patient image review. Images from the array are stitched into a 2k×1k pixel image that can be acquired and saved at a rate of 17 Hz (faster with pixel binning). When reviewing the patient's data, the operator can select images from the patient's directory tree listed by the GUI and cycle through the images using a slider bar. Commonly used camera parameters including exposure time, trigger mode, and individual EMCCD gain can be easily adjusted using the GUI. The GUI is designed to accommodate expansion of the EMCCD array to even larger FOVs with more modules. The high-resolution, high-sensitivity EMCCD modular-array SSXII imager with the new user-friendly GUI should enable angiographers and interventionalists to visualize smaller vessels and endovascular devices, helping them to make more accurate diagnoses and to perform more precise image-guided interventions.

Software environment: The source code is written in Fortran77. The executable file is compiled for the protected DOS mode (32 bits), Windows 3.1x (using Win32S), Windows 95 and Windows NT. The program offers a user-friendly graphical user interface (GUI) that is fully mouse-controlled. The graphical interface is based on the INTERACTER Library version 4.0. Hardware environment: The program runs on PC-compatible computers under DOS 6.0 or higher, Windows 3.1x (with Win32S), Windows 95 and Windows NT. The DOS version needs about 2.0 Mbytes of disk space (the program is bounded with the DOS-Extender) and 1.2 Mbytes for the other versions. The program uses VGA/SVGA graphics and needs an IBM-compatible mouse. Program specification: Up to about 100 atoms in the asymmetric unit can be used to calculate the contour maps of the bond-valence sum. The program found the higher graphics resolution for DOS and for Windows it needs a Windows video driver with colours 32 k/65 k/ 16 M. There are two forms of output file: HPGL and PostScript. In DOS one can choose a Laserjet or Deskjet printer. Documentation: The program is very easy to use, but a manual is provided in the form of a MS-Word document, with some examples. Availability: VALMAP 1.0 can be freely obtained from the authors by e-mail (jplatas@ull.es).

The increasing importance or concern of health-related risks due to rapidly changing environmental conditions, climate patterns, and lifestyle habits has raised significant concern in recent years. Among these, lung-related diseases have emerged as a leading cause of mortality in India, ranking second only to cardiovascular diseases. In 2022, globally, lung ailments accounted for approximately 2.48 million new cases and 1.8 million deaths, underscoring the urgency for timely detection and management. Early diagnosis remains critical in mitigating severe complications and reducing mortality rates associated with such conditions. Chest X-rays continue to be a primary and reliable tool for clinical diagnosis; however, the integration of advanced technologies, such as deep learning, with medical imaging like chest CT scans has demonstrated transformative potential. This paper proposes a deep learning-based diagnostic framework aimed at facilitating the accurate and timely identification of lung cancer from chest CT images. The system is designed to assist radiologists by providing high-accuracy predictions in real-time, thereby improving diagnostic capabilities, particularly in rural and underserved regions where access to expert radiological consultation is limited. A user-friendly Graphical user interface (GUI) developed using MATLAB enables seamless image loading and direct output generation, allowing for swift deployment in clinical and laboratory settings for real-time diagnosis.

Beginning in 1990, the University of Arizona, Arizona Remote Sensing Center (ARSC) has been involved in a collaborative effort with the Global Information and Early Warning System (GIEWS) and the Remote Sensing Center of the Food and Agriculture Organization (FAO) of the United Nations in designing and developing an integrated computer workstation for famine early warning. The goal of the project is to provide food security analysts with a set of computer tools to manage a very large and diverse set of data for predicting the onset of food security emergencies for every country on Earth. The initial stage of the project involved the conceptual definition of system elements and the development of overall system architecture. We are now developing an open, flexible, and portable system designed to significantly assist the work of the analysts. System architecture provides a task-specific and user-friendly graphic user interface (GUI) within a Windows environment that will link image processing, geographic information system (GIS), spreadsheet, text, and graphics software packages into a single operational environment. A relational database management system (RDBMS) is serving as the back-end of the workstation to facilitate data storage and retrieval and as a means to preserve analysis methodologies.