Front-end Graphical User Interface Research Articles

Real-time Sentiment Analysis from Data Streaming

Public sentiment is a potent indicator of how people perceive and receive a topic. It has the power to make or break companies and people. Twitter is one of the best platforms in today’s generation to gauge public sentiment. [10] Utilizing the power and influence Twitter has we decided to create a service that would enable us to know how a trending topic is being viewed by the masses in real-time. The user gives the topic as input to the front-end graphical user interface that topic is then taken and fed to the Twitter streaming API. Tweets containing the hashtag of the topic mentioned by the user are returned and the sentiment of those tweets is predicted and sent to the front end where analysis prediction of the sentiment of the tweets is done dynamically as the tweets come in. By using our service for a few minutes the user will get to know what the overall outlook of a topic is and use that information as a guiding beacon for any future decisions regarding that topic.

Mobile Sensing for Multipurpose Applications in Transportation

Routine and consistent data collection is required to address contemporary transportation issues. The cost of data collection increases significantly when sophisticated machines are used to collect data. Due to this constraint, State Departments of Transportation struggle to collect consistent data for analyzing and resolving transportation problems in a timely manner. Recent advancements in sensors integrated into smartphones have resulted in a more affordable method of data collection. The primary objective of this study is to develop and implement a smartphone-based application for transportation-related data collection. The app consists of three major modules: a frontend graphical user interface (GUI), a sensor module, and a backend module. While the frontend GUI enables interaction with the app, the sensor modules collect relevant data such as video, gyroscope, motion and accelerometer readings while the app is in use. The backend leverages a real-time database to stream and store data from sensors, together with providing the computational resources needed to support the application. In comparison to other developed apps for transportation data collection, this app is not overly reliant on the internet enabling the app to be used in internet-restricted areas. Additionally, the app is designed for multipurpose applications in transportation. The collected data were analyzed for a variety of purposes, including calculating the International Roughness Index (IRI), identifying pavement distresses, and understanding driver’s behaviors and environment. From the sensor data, we detected turning movements, lane changes and estimated IRI values. In addition, several pavement distresses were identified from the video data with machine learning.

Development of a Maths Learning System for High School Students using the Java Desktop Platform

This paper presents the development of a math learning system for high school math students. The development process involved the creation of the front-end graphical user interface and the back-end database, with both being implemented to near-commercial standard. The front-end consists of two main screens; a separate one each for the teacher and the student. The teacher's screen displays and allows the editing of all data in the database through the use of tables. The student is presented with all the math questions from the database on their screen in a structured form for the practice of math problems of various difficulty levels. Three types of final tests were performed to examine the effectiveness of math learning system. The results showed that the system is consistent and usable for learning math at high school.

Azure-Based Smart Monitoring System for Anemia-Like Pallor

Increasing costs of diagnostic healthcare have necessitated the development of hardware independent non-invasive Point of Care (POC) systems. Although anemia prevalence rates in global populations vary between 10% and 60% in various demographic groups, smart monitoring systems have not yet been developed for screening and tracking anemia-like pallor. In this work, we present two cloud platform-hosted POC applications that are directed towards smart monitoring of anemia-like pallor through eye and tongue pallor site images. The applications consist of a front-end graphical user interface (GUI) module and two different back-end image processing and machine learning modules. Both applications are hosted on a browser accessible tomcat server ported to an Azure Virtual Machine (VM). We observe that the first application spatially segments regions of interest from pallor site images with higher pallor classification accuracy and relatively longer processing times when compared to the lesser accurate yet faster second application. Also, both applications achieve 65%–98% accuracy in separating normal images from images with pallor or abnormalities. The optimized front-end module is significantly light-weight with a run-through time ratio of 10−5 with respect to the back-end modules. Thus, the proposed applications are portable and hardware independent, allowing for their use in pallor monitoring and screening tasks.

A collection of open source applications for mass spectrometry data mining.

We present several bioinformatics applications for the identification and quantification of phosphoproteome components by MS. These applications include a front-end graphical user interface that combines several Thermo RAW formats to MASCOT™ Generic Format extractors (EasierMgf), two graphical user interfaces for search engines OMSSA and SEQUEST (OmssaGui and SequestGui), and three applications, one for the management of databases in FASTA format (FastaTools), another for the integration of search results from up to three search engines (Integrator), and another one for the visualization of mass spectra and their corresponding database search results (JsonVisor). These applications were developed to solve some of the common problems found in proteomic and phosphoproteomic data analysis and were integrated in the workflow for data processing and feeding on our LymPHOS database. Applications were designed modularly and can be used standalone. These tools are written in Perl and Python programming languages and are supported on Windows platforms. They are all released under an Open Source Software license and can be freely downloaded from our software repository hosted at GoogleCode.

Supervisory control and data acquisition system development for superconducting current feeder system of SST-1

The Current Feeders System (CFS) is essentially an optimized bridge between the power supply at room temperature and Super Conducting Magnet System (SCMS) of the SST- 1 machine at 4.5 K.CFS is a complex electrical and cryogenic network which consists of ten pairs of 10 KA rating helium Vapor cooled Conventional Current Leads (VCCLs), superconducting (SC) current feeder and associated components. For the safe and reliable operation of CFS, it is equipped with different physical process parameters measuring instruments like flow, pressure, temperature, level, vacuum, voltage taps and final control element like control valves, heaters, vacuum pumps etc. PLC program is developed in ladder language for acquiring and controlling the process parameters. Independent SCADA applications developed in Wonderware Intouch software for data communication from PLC, front-end Graphical User Interface (GUI), auto-manual interface, real time trends, history trends, events and alarm pages. Time synchronized communication established between CFS control system and Industrial SQL server (InSQL) Historian for centralized storage of CFS process parameters which intern provides the CFS process data to SST-1 central control room. SCADA based data acquisition and data retrieval system is found to be satisfactory during the recent SST-1 cool down experiment. This paper describes the SCADA and PLC application development and their communication to InSQL server.

Implementation of Decision Support System (DSS) through the Integration of Commercial Remote Sensing (CRS), Model-View-Controller (MVC) Architecture and Object-Relational Mapping (ORM)

order to aid in the processes of data collection, interpolation, analysis, and predictive model development the integration of commercial remote sensing and spatial information technologies (CRS&SI) with object oriented modeling (OOM) using the model view controller architecture (MVC) has been applied. A Decision Support System (DSS) application that uses CRS&SI for collecting atmospheric, subsurface, and predicted weather data, is used to compare, interpolate, measure, predict, and determines the depth of frost and thaw penetration into the subsurface of roadways across New England, This process is used in order to guide State Departments of Transportation (DOT) in determining when to impose Seasonal Load Restrictions (SLR). Seasonal load restrictions limit the travel of heavy trucks on certain roads such that state DOT's can limit the damage to the roadway surface. The implemented DSS consists of a web based front end graphical user interface (GUI) that leverages popular web based technologies, programming interfaces, data collection scripts, data evaluation scripts, data interpolation scripts, predictive modeling, and a centralized database. The database was developed for storing newly collected, historic, and predicted data. This paper includes the description of the general purpose and use of the system and a discussion regarding the architecture, individual components, interactions, and a description of the sequence of events for data collection, processing, prediction, and interpolation.

Interactive object-based image retrieval and annotation on iPad

Apple iPad is a portable tablet computer that offers users a generic platform for consumer media including games, books, and movies. Though iPad is gaining popularity very quickly, its application in content-based image retrieval and annotation is still in its infancy. This paper aims to develop an interactive system to efficiently retrieve and annotate image objects on iPad, which mainly consists of two components of the front-end GUI (graphical user interface) and the back-end retrieval model. In the first component, an iPad-based GUI is implemented, which can provide users with an efficient way to select query objects and facilitate annotations. In the second component, we propose an object-based image retrieval algorithm that combines a novel feature descriptor based on context-preserving bags-of-words (BoW) and a two-stage re-ranking technique to measure the similarity between the query image and each image in the database. The retrieval results are returned and visualized on the iPad-based GUI, and annotations offered by users can be propagated among them. The communication between the front-end GUI and the back-end module is through the use of wireless networks. Comprehensive experiments on several benchmark datasets demonstrated the effectiveness of the proposed framework.

Identifying clinical/translational research cohorts: ascertainment via querying an integrated multi-source database

Ascertainment of potential subjects has been a longstanding problem in clinical research. Various methods have been proposed, including using data in electronic health records. However, these methods typically suffer from scaling effects-some methods work well for large cohorts; others work for small cohorts only. We propose a method that provides a simple identification of pre-research cohorts and relies on data available in most states in the USA: merged public health data sources. The Utah Population Database Limited query tool allows users to build complex queries that may span several types of health records, such as cancer registries, inpatient hospital discharges, and death certificates; in addition, these can be combined with family history information. The architectural approach incorporates several coding systems for medical information. It provides a front-end graphical user interface and enables researchers to build and run queries and view aggregate results. Multiple strategies have been incorporated to maintain confidentiality. This tool was rapidly adopted; since its release, 241 users representing a wide range of disciplines from 17 institutions have signed the user agreement and used the query tool. Three examples are discussed: pregnancy complications co-occurring with cardiovascular disease; spondyloarthritis; and breast cancer. This query tool was designed to provide results as pre-research so that institutional review board approval would not be required. This architecture uses well-described technologies that should be within the reach of most institutions.

Evaluating students' satisfaction using two SAP ERP user interfaces

Companies worldwide use Enterprise Resource Planning (ERP) systems to effectively manage business processes across organizational departments and information among global subsidiaries. Colleges have incorporated ERP systems into their business curricula to provide students with a better understanding of business process theory and information sharing concepts. In this paper, we discuss students' satisfaction with using two end-user interfaces for SAP's ERP software in an online/distance education classroom. The first interface was a front-end graphical user interface (GUI) with a client/server architecture using online transaction processing (OLTP) and an Oracle database management system. The second interface was completely simulated using a JAVA-based program running in a browser. From a computer science viewpoint, we were interested in better understanding the human-computer interaction of students with the two different interfaces. Specifically, we wanted to determine which interface best secured students' satisfaction as users, while learning business process theory and information sharing concepts. Reasons for students' dissatisfaction with using SAP's GUI, and benefits from using a completely simulated environment, are discussed. Other colleges considering implementing SAP's ERP software into their online/distance education curricula may benefit from lessons learned from this human-computer interaction experience.

Design of service-oriented architecture for spatial data integration and its application in building web-based GIS systems

In this paper we propose a service-oriented architecture for spatial data integration (SOA-SDI) in the context of a large number of available spatial data sources that are physically sitting at different places, and develop web-based GIS systems based on SOA-SDI, allowing client applications to pull in, analyze and present spatial data from those available spatial data sources. The proposed architecture logically includes 4 layers or components; they are layer of multiple data provider services, layer of data integration, layer of backend services, and front-end graphical user interface (GUI) for spatial data presentation. On the basis of the 4-layered SOA-SDI framework, WebGIS applications can be quickly deployed, which proves that SOA-SDI has the potential to reduce the input of software development and shorten the development period.

Analysis of nonlinear dynamics on arbitrary geometries with the Virtual Cell.

The Virtual Cell is a modeling tool that allows biologists and theorists alike to specify and simulate cell-biophysical models on arbitrarily complex geometries. The framework combines an intuitive, front-end graphical user interface that runs in a web browser, sophisticated server-side numerical algorithms, a database for storage of models and simulation results, and flexible visualization capabilities. In this paper, we present an overview of the capabilities of the Virtual Cell, and, for the first time, the detailed mathematical formulation used as the basis for spatial computations. We also present summaries of two rather typical modeling projects, in order to illustrate the principal capabilities of the Virtual Cell. (c) 2001 American Institute of Physics.