Prototype Web Application Research Articles

DEVELOPING THE STRUCTURE OF A WEB APPLICATION FOR PERSONAL FINANCE ACCOUNTING

Modern payment services in the form of online banks and accounting services are designed to monitor the user’s funds. This allows you to track bank transactions through a personal account of the web-application, to keep track of the receipt or expenditure of funds. However, for a user who has several credit cards, current accounts, deposits in banks it is necessary to integrate information about current funds in a single information space.
 The purpose of the study is to develop a prototype web application for accounting personal finances.
 Method or methodology of work: methods of designing information systems.
 Results: the analysis of financial accounting applications has shown that they have a number of similar functionalities. These features are related to the registration of the user, the cardholder of a particular bank, tracking the progress of transactions, and ensuring security. However, the applications are limited in terms of the ability to record personal finances of third-party bank cards or electronic virtual accounts (e.g., mobile operators). Therefore, in our work we have developed an application architect, consisting of seven pages. The main page of the site is needed to ensure the safety of the application, receiving notifications from the banks by the user. The main functional purpose of the pages of the site - cards, credits, payments and transfers is aimed at interactive interaction of user with different banks, providing control of receipt and expenditure of money kept on different accounts. It is suggested to introduce the pages goals and calendar into the structure of the site to enable the user to plan expenses by specifying the list of goods and services at certain periods of time. The site page “settings” is used for tweaking the styles of the web-application.
 Scope of the results: the developed prototype of web-application for accounting of personal finances is needed for practical implementation of the application, which will allow integrating information about the current state of the user’s money.

Green-blue infrastructure in the built environment – sustainable and resource-saving designs for urban structures and open spaces

Urban grey infrastructure, as it generally consists of monofunctional, sealed, impervious, heating up and reflecting surfaces, has led to a series of serious challenges (urban heat stresses, loss of biodiversity, flood risks and natural hazards) decreasing urban resilience. Ongoing construction activities result in irreversible soil consumption and loss of its numerous and vital functions. However, a common understanding has been evolving that the establishment of green-blue infrastructure (GBI) supports compensating for functional losses, as they are integrative and provide pervious, absorbent, shading and non-heating up surfaces. We present a concept to holistically interconnect stand-alone approaches to improve and support constructional design for transforming green open spaces addressing specifically urban landscape construction and building greenery. The underlying state of knowledge emerges from currently four ongoing projects on advancing GBI for re-establishing ecosystem functions and diverse habitats: 1. The Circular Soil Concept targets the reuse of excavated soil materials from construction sites to produce engineered soils. These are applied as functional vegetation substrates for landscape construction and installing building greenery, saving scarce soil resources while generating large scale and vegetated areas with climate change adaptation performance. 2. The StreetTREE-Planter is designed to install urban trees in a given street infrastructure. The advanced planter systems will support extended tree lifespans, microclimatic benefits, flood protection and urban resilience. The design is based on targeted rainwater harvesting for irrigation management in alignment with water requirements and the desired microclimatic performance. 3. The GLASGrün projects generates plant-based shading designs for glass facades. As plants and their leaves do not heat up from solar radiation, vertical greenery is promising, however challenging, for green shading of glazed surfaces and for indoor and outdoor microclimatic regulation. 4. The INReS rainwater management tool was developed as a prototype web application to integrate sustainable, plant-based rainwater management systems into BIM-(Building Information Modeling)-based construction projects. It provides up-to-date design for the wider public and specific planning guidelines. In synthesis with the present and upcoming findings of these projects, a parameter-based and BIM-compatible GBI-design management tool is foreseen to better and sustainably integrate GBI systems into construction projects, and to consider the resource question.

Let’s Bid: A Web Application for Online Auctions

Abstract: Auctions are processes where selling and buying of products takes place by offering them for a bid and the buyer with the highest bid price buys the product or the seller with lowest ask price sells the product. Due to the emergence of e-commerce , the world has become a universal marketplace which grants every individual the right to become a seller and buyer of products irrespective of geographical barriers. In this project, we aim to create a web application for online auction system where every product is offered for bidding and the interested buyers can bid on them and buy them at fair prices. We have used the ReactJS library for developing the frontend and Django for the backend development. Initially, we have created an e-commerce web application prototype with all the typical features in it like user and admin system, login / authentication system, catalogue of products, shopping cart, payment page,etc. We have introduced bidding functionality after development of the base e-commerce system. The purpose of this project is to create a simulated environment for research in this domain to test the different fraud detection algorithms for shill bidding , bid shielding, etc. Keywords: Auctions, Unified Modeling Language, React JS library, Django framework, web application

An mHealth App for Fibromyalgia-like Post-COVID-19 Syndrome: Protocol for the Analysis of User Experience and Clinical Data.

BackgroundPost–COVID-19 syndrome, also referred as “long covid,” describes persisting symptoms after SARS-CoV-2 infection, including myalgia, fatigue, respiratory, or neurological symptoms. Objective symptoms are often lacking, thus resembling a fibromyalgia-like syndrome. Digital therapeutics have shown efficiency in similar chronic disorders such as fibromyalgia, offering specific disease monitoring and interventions such as cognitive behavioral therapy or physical and respiratory exercise guidance.ObjectiveThis protocol aims to study the requirements and features of a new mobile health (mHealth) app among patients with fibromyalgia-like post–COVID-19 syndrome in a clinical trial.MethodsWe created a web application prototype for the post–COVID-19 syndrome called “POCOS,” as a web-based rehabilitation tool aiming to improve clinical outcomes. Patients without organ damage or ongoing inflammation will be included in the study. App use will be assessed through user experience questionnaires, focus groups, and clinical data analysis. Subsequently, we will analyze cross-sectional and longitudinal clinical data.ResultsThe developed mHealth app consists of a clinically adapted app interface with a simplified patient-reported outcome assessment, monitoring of medical interventions, and disease activity as well as web-based instructions for specific physical and respiratory exercises, stress reduction, and lifestyle instructions. The enrollment of participants is expected to be carried out in November 2021.ConclusionsUser experience plays an important role in digital therapeutics and needs to be clinically tested to allow further improvement. We here describe this process for a new app for the treatment of the fibromyalgia-like post–COVID-19 syndrome and discuss the relevance of the potential outcomes such as natural disease course and disease phenotypes.International Registered Report Identifier (IRRID)PRR1-10.2196/32193

Using Median-LBPH Algorithm for Real-Time Face Recognition System

Abstract: The LBPH algorithm is used ubiquitously for Face Recognition applications in modern times because of its simplicity of implementation, despite providing high accuracy and less computation time. However, in conditions of varied illumination, face expression and angles at which face images are captured, its confidence is decreased. We propose a slightly modified algorithm that considers the median of the neighbourhood pixels rather than the pixel itself to overcome this issue. This algorithm is called Median-LBPH. The grey value of every pixel is replaced by the median of all the neighbourhood pixel values. Then the features are extracted, and a histogram representing the original image is saved in the model. This model, in turn, can be used to compare with histograms obtained from the faces in real-time footage to find a potential match. This algorithm is used in an end-to-end face recognition system, a web application prototype for Law Enforcement Agencies to maintain a central criminal database shared and accessed across various departments. A live surveillance system is added as part of this novel application so that whenever an already registered criminal appears live on surveillance cameras, a notification will be received, and personnel appropriate Law Enforcement authorities will receive e-mail and text messages through a secured channel. Keywords: Face Recognition, Median-Local Binary Pattern Histogram (MLBPH), Haar Cascade, Adaboost, Neighbourhood Median

Remote Gait Type Classification System Using Markerless 2D Video.

Several pathologies can alter the way people walk, i.e., their gait. Gait analysis can be used to detect such alterations and, therefore, help diagnose certain pathologies or assess people’s health and recovery. Simple vision-based systems have a considerable potential in this area, as they allow the capture of gait in unconstrained environments, such as at home or in a clinic, while the required computations can be done remotely. State-of-the-art vision-based systems for gait analysis use deep learning strategies, thus requiring a large amount of data for training. However, to the best of our knowledge, the largest publicly available pathological gait dataset contains only 10 subjects, simulating five types of gait. This paper presents a new dataset, GAIT-IT, captured from 21 subjects simulating five types of gait, at two severity levels. The dataset is recorded in a professional studio, making the sequences free of background camouflage, variations in illumination and other visual artifacts. The dataset is used to train a novel automatic gait analysis system. Compared to the state-of-the-art, the proposed system achieves a drastic reduction in the number of trainable parameters, memory requirements and execution times, while the classification accuracy is on par with the state-of-the-art. Recognizing the importance of remote healthcare, the proposed automatic gait analysis system is integrated with a prototype web application. This prototype is presently hosted in a private network, and after further tests and development it will allow people to upload a video of them walking and execute a web service that classifies their gait. The web application has a user-friendly interface usable by healthcare professionals or by laypersons. The application also makes an association between the identified type of gait and potential gait pathologies that exhibit the identified characteristics.

Spatio‐Temporal Analysis of Hypoxia in the Central Basin of Lake Erie of North America

AbstractWe develop a spatio‐temporal geostatistical interpolation framework to estimate hypoxia extent (dissolved oxygen [DO] concentrations below 2 mg/L) with data from a network of DO loggers. The framework uses empirical orthogonal functions and Bayesian kriging to identify the spatially varying temporal pattern and estimate the distribution of hypoxia, including estimation uncertainty. A prototype web application is also developed in R. The framework is applied to analyze spatio‐temporal dynamics of DO in the central basin of Lake Erie in North America using data sampled from a logger network placed on the lake bottom during the summers of 2014, 2015, and 2016. Cross‐validation results demonstrate that the framework is capable of capturing the dynamic nature of bottom hypoxia over offshore areas, but nearshore areas have poor interpolation performance due to the impacts of complex physical processes such as seiche events. The findings showed that in the central basin, hypoxia started to emerge in early August of 2014, while in 2015 and 2016 hypoxia began in July. The peak hypoxia extent occurred in late September 2014, mid‐August 2015, and early September 2016. The prediction error of the overall spatial extent of hypoxia was as large as 25% of the interpolation area based on current logger deployment. Based on the cross‐validation and interpolation error, we suggest placing more loggers in nearshore areas to reduce prediction error near the margins of the hypoxic zone.

UI/UX Design Web-Based Learning Application Using Design Thinking Method

Humans are basically inseparable from education in carrying out life. The implementation and development of educational studies must also be adapted to the conditions and social situations that exist in the community. The main focus of Goal 4 on Sustainable Development Goals (SDGs) is to provide inclusive quality education or to ensure everyone has an equal opportunity to get good quality of education. In fact, Indonesia is still struggling in the quality of teacher issue. In the school year of 2019/2020, there are 8.98% unqualified teachers and headmasters on primary school level, 6.16% on junior high school level, 10.07% on senior high school level, and 10% on vocational high school level. Cumulatively, from primary school level to vocational high school level, there are 247.462 unqualified teachers and headmasters in Indonesia. This is a serious problem, considering that teachers are important component in determining the quality of education itself. In this research, UI/UX design prototype of learning web application named “IdeIn” was developed using Design Thinking method that consists of empathize, define, ideate, prototype, and test stages. The main focus of this learning web application is to provides an opportunity to the whole community to support education in Indonesia by conducting online classes.

Deep Learning-Based Visual Identification of Signs of Bat Presence in Bridge Infrastructure Images: A Transfer Learning Approach

Bat inventory surveys on bridges, structures, and dwellings are an important step in protecting threatened and endangered bat species that use the infrastructure as roosting locations. Observing guano droppings and staining is a common indicator of bat presence, but it can be difficult to verify whether certain stains originated from bats or other sources such as water seeps, rust staining, asphalt leaching, or other structural deterioration mechanisms. While humans find it hard to distinguish bat indicators without training, from a computer vision perspective they show different features that, coupled with expert opinion, can be used for automated detection of bat presence. To facilitate bat presence detection and streamline bat surveys, this paper leverages recent advances in visual recognition using deep learning to develop an image classification system that identifies bat indicators. An array of state-of-the-art convolutional neural networks were investigated. To overcome the shortage of data, parameters previously trained on large-scale datasets were used to transfer the learned feature representations. Using a pool of digital photographs collected by Virginia Department of Transportation (VDOT), a visual recognition model was developed and achieved 92.0% accuracy during testing. To facilitate the application of the developed model, a prototype web application was created to allow users to interactively upload images of stains on structures and receive classification results from the model. The web application is being deployed by VDOT in a pilot study and the success of the proposed approach is expected to help facilitate bat inventory surveys and the resulting conservation efforts.

A knowledge with ontology representation for product life cycle to support eco-design activities

PurposeThis study aims to develop a synthetic knowledge repository consisted of interrelated Web Ontology Language.Design/methodology/approachThe ontology composes the main framework to categorize data of product life cycle with eco-design mode (PLC-EDM) and automatically infer specialists’ knowledge for data confirmation, eventually assisting the utilizations and generation of strategies toward decision-makingFindings(i) utilization of a novel model with ontology mode for information reuse cross the different eco-design applications; (ii) generation of a sound platform toward life cycle evaluation; and (iii) implementation of the PLC-EDM model along the product generation process.Research limitations/implicationsIt cannot substitute an evaluation tool of life cycle. Certainly, this model does not predict the “target and range” and/or the depiction of the “utility module” that are basic activities in life cycle assessments as characterized through the international organization for standardization regulations.Practical implicationsAs portion of this framework, a prototype Web application is presented which is applied to produce, reuse and verify knowledge of product life cycle.Social implicationsBy counting upon the ontology, the information conducted by the utilization is certainly semantically represented to promote the data sharing among various participants and tools. Besides, the data can be verified against possible faults by inferring over the ontology. Hence, a feasible way to a popular topic in the domain of eco-design applications extension in the industry.Originality/valueThe goals are: to lean on rigid modeling principles; and to promote the interoperability and diffusion of the ontology toward particular utilization demands.

Patient similarity analytics for explainable clinical risk prediction

BackgroundClinical risk prediction models (CRPMs) use patient characteristics to estimate the probability of having or developing a particular disease and/or outcome. While CRPMs are gaining in popularity, they have yet to be widely adopted in clinical practice. The lack of explainability and interpretability has limited their utility. Explainability is the extent of which a model’s prediction process can be described. Interpretability is the degree to which a user can understand the predictions made by a model.MethodsThe study aimed to demonstrate utility of patient similarity analytics in developing an explainable and interpretable CRPM. Data was extracted from the electronic medical records of patients with type-2 diabetes mellitus, hypertension and dyslipidaemia in a Singapore public primary care clinic. We used modified K-nearest neighbour which incorporated expert input, to develop a patient similarity model on this real-world training dataset (n = 7,041) and validated it on a testing dataset (n = 3,018). The results were compared using logistic regression, random forest (RF) and support vector machine (SVM) models from the same dataset. The patient similarity model was then implemented in a prototype system to demonstrate the identification, explainability and interpretability of similar patients and the prediction process.ResultsThe patient similarity model (AUROC = 0.718) was comparable to the logistic regression (AUROC = 0.695), RF (AUROC = 0.764) and SVM models (AUROC = 0.766). We packaged the patient similarity model in a prototype web application. A proof of concept demonstrated how the application provided both quantitative and qualitative information, in the form of patient narratives. This information was used to better inform and influence clinical decision-making, such as getting a patient to agree to start insulin therapy.ConclusionsPatient similarity analytics is a feasible approach to develop an explainable and interpretable CRPM. While the approach is generalizable, it can be used to develop locally relevant information, based on the database it searches. Ultimately, such an approach can generate a more informative CRPMs which can be deployed as part of clinical decision support tools to better facilitate shared decision-making in clinical practice.

Education Management Information System - Three-Tier Web Application Prototype for Education Workflow

Agriculture education in India is unique with a flexible course credit system.The workflow behind this unique education system needs customizededucation management information software for educational planningand management with a reduced process time in education workflow. Thispaper put forth a prototype of the Education Management InformationSystem (EMIS) developed for Forest College and Research Institute (FCRI),Tamil Nadu Agricultural University, Mettupalayam. Three-tier architectureis used for FCRI-EMIS to be an effective distributed client/server system.The development is carried out in an open-source development platform.FCRI-EMIS is developed with four modules namely: College ManagementInformation System, Degree Management Information System, SyllabusManagement Information System and Student Management InformationSystem to access, generate a report and analyze the identified entities. Thedeveloped prototype is executed and found an effective tool for decisionmaking towards education planning and management

Prototype Web Application to Reduce Time for Cross Kidney Donations in Lima, Peru

Prototype Web Application to Reduce Time for Cross Kidney Donations in Lima, Peru

Linked-Data based Constraint-Checking (LDCC) to support look-ahead planning in construction

In the construction sector, complex constraints are not usually modeled in conventional scheduling and 4D building information modeling software, as they are highly dynamic and span multiple domains. The lack of embedded constraint relationships in such software means that, as Automated Data Collection (ADC) technologies become used, it cannot automatically deduce the effect of deviations to schedule. This paper presents a novel method, using semantic web technologies, to model and validate complex scheduling constraints. It presents a Linked-Data based Constraint-Checking (LDCC) approach, using the Shapes Constraint Language (SHACL). A prototype web application is developed using this approach and evaluated using an OpenBIM dataset. Results demonstrate the potential of LDCC to check for constraint violation in distributed construction data. This novel method (LDCC) and its first prototype is a contribution that can be extended in future research in linked-data, BIM based rule-checking, lean construction and ADC.

IoT Solution for Intelligent Pond Monitoring

Channa striata or the striped snakehead fish is one of snakehead fish species which inhabits all types of freshwater bodies distributed across Asian countries. Because this fish is known to have higher albumin fraction (64.61%) of protein and other economic values, domestication, and cultivation of this fish has been done in many Asian countries such as Indonesia, China, Malaysia, Thailand, Bangladesh, and India. Environmental factors such as temperature, water pH, dissolved oxygen, total dissolved solids, and turbidity are important parameters must be considered inbreeding and growing this type of fish. The aim of this paper is to propose an IoT solution to automatically monitor these environmental factors. It is designed with affordable and open-source electrical components to provide a cost-efficient solution for farmers. Five sensors are used to measure each parameter. A web application prototype is also presented as a companion application for the users to get useful information from the IoT device. It is developed using a Pythonframework. By accessing this web application, the users can immediately detect any abnormal conditions of the pond.

A blueprint for electronic utilization of ambiguous molecular HLA typing data in organ allocation systems and virtual crossmatch

Virtual crossmatch (VXM) compares a transplant candidate’s unacceptable antigens to the HLA typing of the donor before an organ offer is accepted and, in selected cases, supplant a prospective physical crossmatch. However, deceased donor typing can be ambiguous, leading to uncertainty in compatibility prediction. We have developed a prototype web application that utilizes ambiguous HLA molecular typing data to predict which unacceptable antigens are present in the donor HLA genotype as donor-specific antibodies (DSA). The application compares a candidate’s listed unacceptable antigens to computed probabilities of all possible two-field donor HLA alleles and UNOS antigens. The VIrtual CrossmaTch for mOleculaR HLA typing (VICTOR) tool can be accessed at http://www.transplanttoolbox.org/victor. We reanalyzed historical VXM cases where a transplant center’s manual interpretation of molecular typing results influenced offer evaluation. We found that interpretation of ambiguous donor molecular typing data using imputation could one day influence VXM decisions if the DSA predictions were rigorously validated. Standardized interpretation of molecular typing data, if applied to the match run, could also change which offers are made. HLA typing ambiguity has been an underappreciated source of immunological risk in organ transplantation. The VICTOR tool can serve as a testbed for development of allocation policies with the aim of decreasing offers refused due to HLA incompatibility.

PEMILIHAN KEBUTUHAN TENAGA KERJA MAGANG PERUSAHAAN DI MASA PANDEMI COVID-19 BERBASIS WEB

During this Pandemi Covid-19, many students had difficulty getting practical work places for Internships at companies and it was not uncommon for companies to look to fresh graduated internships seekers who had abilities that mathced their needs. To be able to carry out its business continuity, the company reduces workers due to a lack of purchasing power for products both from within and outside the country. In the era of the Industrial Revolution 4.0, current and future Information Technology requires companies to be involved and develop in using new application system according to their needs, which have the principle of being able to streamline operational costs. The effects of the Pandemi Covid-19 and the era of the Industrial Revolution 4.0, many companies made layoffs (PHK) which is a big job for the government, especially for the Ministry of Manpower. To help solve this problem it is necessary to create a virtual communication platform that can bring them together. To design the prototype of this web application, HTML5, Apache, CSS, MySQL and PHP are used. The result of this research is a web application prototype that can build virtual communication. Keywords : Information Technology, internships, web application

Admission Exam Web Application Prototype for Blind People at the University of Sciences and Humanities

Currently, there is a large sector of Peru's population that has some type of disability. Every year, the government creates norms for their integration into society. However, to date, total integration is not achieved. One of the points that can be seen is at the moment of taking an entrance exam, where to this day, they do not have the tools to perform in an autonomous and optimal way. Taking this into account, the objective of this article is the development of a prototype admission test for blind people at the University of Sciences and Humanities. A hybrid methodology is used with between Soft Systems and Scrum. The results were obtained from the analysis of both methodologies and a final product prototyped with Balsamiq, demonstrating an optimal union between these two methodologies. Therefore, the prototype will facilitate the performance of blind people during their entrance exam.

Malaria Data by District: An open-source web application for increasing access to malaria information.

Preventable diseases still cause huge mortality in low- and middle-income countries. Research in spatial epidemiology and earth observation is helping academics to understand and prioritise how mortality could be reduced and generates spatial data that are used at a global and national level, to inform disease control policy. These data could also inform operational decision making at a more local level, for example to help officials target efforts at a local/regional level. To be usable for local decision-making, data needs to be presented in a way that is relevant to and understandable by local decision makers. We demonstrate an approach and prototype web application to make spatial outputs from disease modelling more useful for local decision making. Key to our approach is: (1) we focus on a handful of important data layers to maintain simplicity; (2) data are summarised at scales relevant to decision making (administrative units); (3) the application has the ability to rank and compare administrative units; (4) open-source code that can be modified and re-used by others, to target specific user-needs. Our prototype application allows visualisation of a handful of key layers from the Malaria Atlas Project. Data can be summarised by administrative unit for any malaria endemic African country, ranked and compared; e.g. to answer questions such as, 'does the district with the highest malaria prevalence also have the lowest coverage of insecticide treated nets?'. The application is developed in R and the code is open-source. It would be relatively easy for others to change the source code to incorporate different data layers, administrative boundaries or other data visualisations. We suggest such open-source web application development can facilitate the use of data for public health decision making in low resource settings.

Malaria Data by District: An open-source web application for increasing access to malaria information

Preventable diseases still cause huge mortality in low- and middle-income countries. Research in spatial epidemiology and earth observation is helping academics to understand and prioritise how mortality could be reduced and generates spatial data that are used at a global and national level, to inform disease control policy. These data could also inform operational decision making at a more local level, for example to help officials target efforts at a local/regional level. To be usable for local decision-making, data needs to be presented in a way that is relevant to and understandable by local decision makers. We demonstrate an approach and prototype web application to make spatial outputs from disease modelling more useful for local decision making. Key to our approach is: (1) we focus on a handful of important data layers to maintain simplicity; (2) data are summarised at scales relevant to decision making (administrative units); (3) the application has the ability to rank and compare administrative units; (4) open-source code that can be modified and re-used by others, to target specific user-needs. Our prototype application allows visualisation of a handful of key layers from the Malaria Atlas Project. Data can be summarised by administrative unit for any malaria endemic African country, ranked and compared; e.g. to answer questions such as, ‘does the district with the highest malaria prevalence also have the lowest coverage of insecticide treated nets?’. The application is developed in R and the code is open-source. It would be relatively easy for others to change the source code to incorporate different data layers, administrative boundaries or other data visualisations. We suggest such open-source web application development can facilitate the use of data for public health decision making in low resource settings.