Efficient Graphical Interface Research Articles

Analysis of the Application Potential of English Translation Strategy Based on Wireless Widget Technology in 5G Technology Reports

As technology continues to evolve, the process of English translation has become easier. A technology called widget, which is used in modern research, provides an efficient graphical user interface for the interaction between the user and the application. This paper compares the newly proposed wireless widget system with existing models of English translation strategies for internet of things (IoT), cloud computing (CC), artificial intelligence and edge computing (AI+EC), and pure internet concepts. These models were compared on metrics such as accuracy, search completion rate, and throughput. The results show that the proposed system outperforms the existing models with an accuracy rate of 98%, a search completion rate of 96%, and a maximum throughput of 96%. The model shows high performance advantages and can effectively improve the efficiency of translation work.

In-Silico Analysis of Optimal Configurations for Rotational Bioinspired Bone Marrow Biopsy Needle Designs: An ANN Approach.

Medical needle innovations have utilized rotating motion to enhance tissue-cutting capabilities, reducing cutting force and improving clinical outcomes. This study analyzes the effects of six essential factors on insertion and extraction forces during bone marrow biopsy (BMB) procedures. The study uses Taguchi's L32 orthogonal array and numerically simulates the BMB process using the Lagrangian surface-based method on a three-dimensional (3D) heterogeneous Finite Element (FE) model of the human iliac crest. The study evaluates cutting forces in needle insertion and extraction using uni-directional (360° rotation) and bidirectional (180° clock and anti-clock rotation) bioinspired BMB needles. This work aims to create an AI tool that assists researchers and clinicians in selecting the most suitable and safe design parameters for a bio-inspired barbed biopsy needle. An efficient Graphical User Interface (GUI) has been developed for easy use and seamless interaction with the AI tool. With a remarkable accuracy rate exceeding 98%, the tool's predictions hold significant value in facilitating the development of environmentally conscious biopsy needles. The tool demonstrates significantly higher efficiency compared to Abaqus, rendering it a valuable asset for researchers and clinicians engaged in bio-inspired biopsy needle development.

GUILGET: GUI Layout GEneration with Transformer

Sketching out Graphical User Interface (GUI) layout is part of the pipeline of designing a GUI and a crucial task for the success of a software application. Arranging all components inside a GUI layout manually is a time-consuming task. In order to assist designers, we developed a method named GUILGET to automatically generate GUI layouts from positional constraints represented as GUI arrangement graphs (GUIAGs). The goal is to support the initial step of GUI design by producing realistic and diverse GUI layouts. The existing image layout generation techniques often cannot incorporate GUI design constraints. Thus, GUILGET needs to adapt existing techniques to generate GUI layouts that obey to constraints specific to GUI designs. GUILGET is based on transformers in order to capture the semantic in relationships between elements from GUI-AG. Moreover, the model learns constraints through the minimization of losses responsible for placing each component inside its parent layout, for not letting components overlap if they are inside the same parent, and for component alignment. Our experiments, which are conducted on the CLAY dataset, reveal that our model has the best understanding of relationships from GUI-AG and has the best performances in most of evaluation metrics. Therefore, our work contributes to improved GUI layout generation by proposing a novel method that effectively accounts for the constraints on GUI elements and paves the road for a more efficient GUI design pipeline.

The Bioinformatics of Aptamers: HT-SELEX Analysis with AptaSUITE.

Next-generation systematic evolution of ligands by exponential enrichment approaches consistently combine the experimental protocol with high-throughput sequencing after each round of selection. This extension, known as HT-SELEX, results in a vast amount of raw sequencing data that requires tailored bioinformatics approaches to efficiently process and analyze these reads. Here, we present a step-by-step walkthrough of AptaSUITE, a previously published, open-source, and platform-independent software collection of peer-reviewed bioinformatics tools for HT-SELEX data, integrated into a convenient and efficient graphical user interface. We highlight AptaSUITE's main components and illustrate their utility for a variety of usage scenarios. These include, but are not limited to, computational solutions for data preprocessing such as demultiplexing and quality control, aptamer candidate identification, as well as binding motif elucidation. Taken together, AptaSUITE comprises a complete bioinformatics solution for HT-SELEX data analysis while providing real-time, intuitive, and graphical access to the aptamer information.

Novel hybrid WOA-GBM model for patch loading resistance prediction of longitudinally stiffened steel plate girders

In steel plate girders (SPGs), a patch loading usually causes a local failure in the vicinity of the loading area of the girder web. However, estimating the patch loading resistance (PLR) of SPGs is challenging due to the complexity of the problem. This paper aims to develop a novel hybrid WOA-GBM model based on a whale optimization algorithm (WOA) and a gradient boosting machine (GBM) for predicting the PLR of longitudinally SPGs. Firstly, 137 tests of longitudinally stiffened SPGs subjected to patch loading are carefully collected and divided into training and test sets. Then, the most critical parameters of the GBM model are determined using 10-fold cross-validation integrated with the WOA. The results obtained from the WOA-GBM model are compared with those from adaptive boosting (AdaBoost) and extreme gradient boosting (XGBoost) models. The results show that the WOA-GBM model outperforms other models. Additionally, SHapley Additive exPlanation (SHAP) method is used to explain the prediction of the proposed WOA-GBM model globally and locally. Finally, an efficient graphical user interface (GUI) tool and a web application (WA) are developed to apply the proposed WOA-GBM model for practical use.

Precise design and characteristics prediction of Ultra-High Performance Concrete (UHPC) based on artificial intelligence techniques

Recently, with the rapid development of artificial intelligence (AI) techniques, there is a strong motivation to promote the intelligent development of the Ultra-High Performance Concrete (UHPC). To achieve this goal, this paper addresses an approach for precise design and characteristics prediction of UHPC by employing the Modified Andreasen and Andersen (MAA) model and Genetic Algorithm based Artificial Neural Network (GA-ANN) technique. Herein, 80 mixtures in total are conducted as a training dataset, and then a GA-ANN model is created for characteristics prediction of UHPC, which exhibits significant superiorities in fitting goodness and prediction accuracy compared to other classical prediction models. Furthermore, a prediction software based on GA-ANN technology with an efficient Graphical User Interface (GUI) is developed. Finally, a novel method for mix-design of UHPC by the use of MAA and GA-ANN models is proposed as follows: 1) conduct preliminary mixture design by MAA model; 2) further optimize the mixture by GA-ANN according to the property requirements. In general, a new UHPC with dense particle packing skeleton can be precisely designed by this method, which effectively verifies the feasibility of the application of AI technique in the UHPC field.

A machine learning-based formulation for predicting shear capacity of squat flanged RC walls

The squat flanged reinforced concrete (RC) walls have been widely utilized in nuclear power plant and building structures. Nevertheless, the empirical equations in current design codes and published studies show a significant discrepancy in calculating the shear strength of the walls. The purpose of this study is to develop an effective machine learning model, namely artificial neural network (ANN), for predicting the shear strength of squat flanged RC walls. A total of 369 test results of squat flanged RC walls were collected from the literature and used to develop the ANN model. The results of the proposed model were compared with those of existing design codes and published studies. The comparisons emphasized that the developed ANN model in this paper can predict the shear capacity of squat flanged RC walls more accurately than the existing equations. Moreover, the effect of input parameters on the predicted shear capacity of the walls was sufficiently investigated. A predictive formula based on the ANN model, which can cover thirteen input parameters, was then proposed to compute the shear strength of the squat flanged walls. Additionally, an efficient graphical user interface (GUI) platform has been established for facilitating the practical design process of the squat flanged RC walls.

Heimdall, a Computer Program for Electronic Health Records Data Visualization.

Electronic health records (EHR) comprehend structured and unstructured data, that are usually time dependent, enabling the use of timelines. However, it is often difficult to display all data without inducing information overload. In both clinical usual care and medical research, users should be able to quickly find relevant information, with minimal cognitive overhead. Our goal was to devise simple visualization techniques for handling medical data in both contexts. An abstraction layer for structured EHR data was devised after an informal literature review and discussions between authors. The "Heimdall" prototype was developed. Two experts evaluated the tool by answering 5 questions on 24 clinical cases. Temporal data was abstracted in three simple types: events, states and measures, with appropriate visual representations for each type. Heimdall can load and display complex heterogeneous structured temporal data in a straightforward way. The main view can display events, states and measures along a shared timeline. Users can summarize data using temporal, hierarchical compression and filters. Default and custom views can be used to work in problem- oriented ways. The evaluation found conclusive results. The "Heimdall" prototype provides a comprehensive and efficient graphical interface for EHR data visualization. It is open source, can be used with an R package, and is available at https://koromix.dev/files/R.

PyDEF 2.0: An Easy to Use Post-treatment Software for Publishable Charts Featuring a Graphical User Interface.

Herein we present an open-source program automating the post-treatment of solid-state ab initio calculations performed with VASP, the most used solid-state simulation package. The program plots Density of States (DOS) and Band Diagrams, enabling the user to conduct efficiently a detailed study of electronic properties of a material. Our tool includes a complete module dedicated to point defects studies, proposing various corrections which can be activated at will and innovative property calculations such as defect concentrations. This is the first program of its kind to offer a direct plot of the stability domain of the studied matrix with respect to its components' chemical potentials. We also implemented the retrieval of optical indices ɛ1 and ɛ2 , the computation of the refractive and extinction coefficients (n, k) and the reflexivity R of the material. All features of the piece of software are available through a thoroughly designed user-friendly, elegant and efficient Graphical User Interface (GUI) to be accessible to material scientists with various expertises, from both the experimental and theoretical sides. All figures are of publishable quality and can be customized as desired. © 2018 Wiley Periodicals, Inc.

Argus: An open-source and flexible software application for automated quantification of behavior during social interaction in adult zebrafish

Zebrafish show great potential for behavioral neuroscience. Promising lines of research, however, require the development and validation of software tools that will allow automated and cost-effective behavioral analysis. Building on our previous work with the RealFishTracker (in-house-developed tracking system), we present Argus, a data extraction and analysis tool built in the open-source R language for behavioral researchers without any expertise in R. Argus includes a new, user-friendly, and efficient graphical user interface, instead of a command-line interface, and offers simplicity and flexibility in measuring complex zebrafish behavior through customizable parameters. In this article, we compare Argus with Noldus EthoVision and Noldus The Observer, to validate this new system. All three software applications were originally designed to quantify the behavior of a single subject. We first also performed an analysis of the movement of individual fish and compared the performance of the three software applications. Next we computed and quantified the behavioral variables that characterize dyadic interactions between zebrafish. We found that Argus and EthoVision extract similar absolute values and patterns of changes in these values for several behavioral measures, including speed, freezing, erratic movement, and interindividual distance. In contrast, the manual coding of behavior in The Observer showed weaker correlations with the two tracking methods (EthoVision and Argus). Thus, Argus is a novel, cost-effective, and customizable method for the analysis of adult zebrafish behavior that may be utilized for the behavioral quantification of both single and dyadic interacting subjects, but further sophistication will be needed for the proper identification of complex motor patterns, measures that a human observers can easily detect.

Dynamic optimization of trajectory for ramp‐up current profile in tokamak plasma

AbstractIn this paper, we consider an open‐loop, finite‐time, optimal control problem of attaining a specific desired current profile during the ramp‐up phase by finding the best open‐loop actuator input trajectories. Average density, total power, and plasma current are used as control actuators to manipulate the profile shape in tokamak plasmas. Based on the control parameterization method, we propose a numerical solution procedure directly to solve the original partial differential equation (PDE)‐constrained optimization problem using gradient‐based optimization techniques such as sequential quadratic programming. This paper is aimed at proposing an effective framework for the solution of PDE‐constrained optimization problem in tokamak plasmas. A more user‐friendly and efficient graphical user interface is designed in MATLAB, and the numerical simulation results are verified to demonstrate its applicability. In addition, the proposed framework of combining existing PDE and numerical optimization solvers to solve PDE‐constrained optimization problem has the prospective to target challenge advanced control problems arising in more general chemical engineering processes. © 2016 Curtin University of Technology and John Wiley & Sons, Ltd.

Gromita: A Fully Integrated Graphical user Interface to Gromacs 4

Gromita is a fully integrated and efficient graphical user interface (GUI) to the recently updated molecular dynamics suite Gromacs, version 4. Gromita is a cross-platform, perl/tcl-tk based, interactive front end designed to break the command line barrier and introduce a new user-friendly environment to run molecular dynamics simulations through Gromacs. Our GUI features a novel workflow interface that guides the user through each logical step of the molecular dynamics setup process, making it accessible to both advanced and novice users. This tool provides a seamless interface to the Gromacs package, while providing enhanced functionality by speeding up and simplifying the task of setting up molecular dynamics simulations of biological systems. Gromita can be freely downloaded from http://bio.demokritos.gr/gromita/.

Simulating large and heterogeneous networks of spiking neurons with SpiNet

SpiNet is a novel simulation environment for building and analyzing large networks of spiking neurons. Heterogeneous networks with complex architectures can be easily built and simulated without detailed knowledge of a particular programming language or script language interpreter. SpiNet is composed of two components: a simulation engine, written in C programming language for performance purposes, and SpiNet network builder tool, or simply NetBuilder, written in Matlab® for expansibility purposes. The NetBuilder tool provides a flexible and efficient graphical interface allowing the user to easily define and set all the main network model properties. The NetBuilder creates the network model files which can then be simulated with the simulation engine. Neurons are modeled as integrate-and-fire units with dual exponential synaptic conductances and the simulation engine uses a second order Runge-Kutta method with a linear interpolant to find spike times and recalibrate post-spike potentials. The engine is capable of handling a vast number of properties including dynamical synapses, long-term plasticity, stochastic activity, detailed 3-dimensional architecture, external stimuli, among others. SpiNet does not incorporate data analysis tools but provides several channels to export simulation results for off-line analysis by specialized data analysis software. An OpenGL graphical engine is integrated into the simulation environment providing visual information of the model dynamics. SpiNet is far from being as complete and feature rich as NEST, Neuron or Genesis, but has the benefit of facilitating the process of building and simulating heterogeneous network models: it is fast and easy to add new neuron populations, change connectivity properties or assign different types of synaptic plasticity without having to edit or write lines of code; all changes are done within NetBuilder GUI. SpiNet is therefore a valuable tool when analyzing large heterogeneous models where many modifications have to be done in order to better understand the contributions of the different functional components involved.

WinBEST-KIT: WINDOWS-BASED BIOCHEMICAL REACTION SIMULATOR FOR METABOLIC PATHWAYS

We have implemented an efficient, user-friendly biochemical reaction simulator called Web-based BEST-KIT (Biochemical Engineering System analyzing Tool-KIT) for analyzing large-scale nonlinear networks such as metabolic pathways. Users can easily design and analyze an arbitrary reaction scheme through the Internet and an efficient graphical user interface without considering the mathematical equations. The reaction scheme can include several reaction types, which are represented by both the mass action law (mass balance) and approximated velocity functions of enzyme kinetics at steady state, such as Michaelis-Menten, Hill cooperative, Competitive inhibition. However, since all modules in Web-based BEST-KIT have been developed in Java applet style, users cannot optionally make use of original mathematical equations in addition to the prepared equations. In the present study, we have developed a new version of BEST-KIT (for Microsoft Windows called WinBEST-KIT) to allow users to define original mathematical equations and to customize these equations very easily as user-defined reaction symbols. The following powerful system-analytical methods are prepared for system analysis: time-course calculation, parameter scanning, estimation of the values of unknown kinetic parameters based on experimentally observed time-course data of reactants, dynamic response of reactants against virtual external perturbations, and real-time simulation (Virtual Dry Lab).

PermutMatrix: a graphical environment to arrange gene expression profiles in optimal linear order

PermutMatrix is a work space designed to graphically explore gene expression data. It relies on the graphical approach introduced by Eisen and also offers several methods for the optimal reorganization of rows and columns of a numerical dataset. For example, several methods are proposed for optimal reorganization of the leaves of a hierarchical clustering tree, along with several seriation or unidimensional scaling methods that do not require any preliminary hierarchical clustering. This program, developed for MS Windows, with MS-Visual C++, has a clear and efficient graphical interface. Large datasets can be thoroughly and quickly analyzed.

Computer assisted osteotomy design for autografts in craniofacial reconstructive surgery

For reconstruction of some craniofacial defects which may be caused by trauma, removal of cancer, or due to congenital absence, the procedure of bone grafting is necessary. In this paper, we propose a method to identify an optimal donor site for autologous grafts. It is done by performing an optimization of appropriate surface based and voxel based similarity measures between donor region and a defined graft template. All generated solutions can be evaluated interactively by the surgeon on the computer display using an efficient graphical interface. By this approach, the operation time can be considerably shortened.

Enhanced computational infrastructure for data analysis at the DIII–D National Fusion Facility

Recently a number of enhancements to the computer hardware infrastructure have been implemented at the DIII–D National Fusion Facility. Utilizing these improvements to the hardware infrastructure, software enhancements are focusing on streamlined analysis, automation, and graphical user interface (GUI) systems to enlarge the user base. The adoption of the load balancing software package LSF Suite by Platform Computing has dramatically increased the availability of CPU cycles and the efficiency of their use. Streamlined analysis has been aided by the adoption of the MDSplus system to provide a unified interface to analyzed DIII–D data. The majority of MDSplus data is made available in between pulses giving the researcher critical information before setting up the next pulse. Work on data viewing and analysis tools focuses on efficient GUI design with object–oriented programming (OOP) for maximum code flexibility. Work to enhance the computational infrastructure at DIII–D has included a significant effort to aid the remote collaborator since the DIII–D National Team consists of scientists from nine national laboratories, 19 foreign laboratories, 16 universities, and five industrial partnerships. As a result of this work, DIII–D data is available on a 24×7 basis from a set of viewing and analysis tools that can be run on either the collaborators’ or DIII–D's computer systems. Additionally, a web based data and code documentation system has been created to aid the novice and expert user alike.

Development of a new density functional program for all-electron calculation of proteins

In this article, we propose a new molecular orbital program for all-electron calculation of proteins which is based on density functional theory. To carry it out in a fully analytical way, we adopted the (pure-) analytical Xα method and modified it for saving a lot of memories for large-scale calculations. The recent software technology sophisticated in information science is inevitably applied to achieve calculations of large molecular systems. The program is coded by the object-oriented language C + +, its output is shown graphically, and the most of the procedures in this program are controlled through an efficient graphical user interface developed by ourselves. Such technology supports the safe construction of the huge software, the tidy representation of enormous data, and the ready control of complex calculations. Test calculations with various sizes of glycine polypeptides indicate that the computation time is proportional to the 1.7 powers of the number of residues. This result suggests that the all-electron calculations of proteins consisting of over 1000 atoms could be performed with distributed and/or massively parallel computers. © 1997 John Wiley & Sons, Inc. Int J Quant Chem 63: 245–256, 1997

Pictorial information retrieval using the random neural network

A technique is developed based on the use of a neural network model for performing information retrieval in a pictorial information system. The neural network provides autoassociative memory operation and allows the retrieval of stored symbolic images using erroneous or incomplete information as input. The network used is based on an adaptation of the random neural network model featuring positive and negative nodes and symmetrical behavior of positive and negative signals. The network architecture considered has hierarchical structure and allows two-level operation during learning and recall. An experimental software prototype, including an efficient graphical interface, has been implemented and tested. The performance of the system has been investigated through experiments under several schemes concerning storage and reconstruction of patterns. These schemes are either based on properties of the random network or constitute adaptations of known neural network techniques.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>