User Interface Research Articles

PERANCANGAN STRATEGI VALIDASI DATA DENGAN PEMANFAATAN APLIKASI VALIDASI BERBASIS GMAPS UNTUK PRODUK INDIHOME

Guaranteeing the accuracy and completeness of data is a critical aspect in the scope of telecommunications services. In this context, this research aims to design an effective data validation strategy through the use of a Google Maps (GMaps) based validation application in Indihome products. The design involved an approach that combined GMaps interactive map technology, the React JS framework, and the MongoDB database. Using the React JS framework, an interactive user interface has been developed to facilitate the use of validation applications. Utilization of Google Maps allows visual integration of validation data with precise geographic locations. The use of the MongoDB database supports efficient storage and management of validation data, ensuring that the data obtained meets requirements. Application testing has been carried out to ensure the effectiveness of the designed data validation strategy. The result of this research is the design of an effective data validation strategy, through the application of GMaps, React JS, and MongoDB technology. This implementation is expected to provide a more accurate, efficient and intuitive solution in ensuring data quality in Indihome services. This research can also provide benefits for technological developments in the field of data validation and the application of map concepts in user experience

Unified Steganography for Concealing and Extracting Secret Messages

Abstract: With the increasing significance of data security in the digital age, steganography has emerged as a crucial technique for concealing information within various forms of media. This paper presents a unified steganographic framework designed to embed and extract secret messages in images, audio, and text files. Utilizing the Least_Significant_Bit (LSB) method, our approach ensures minimal distortion of the host media while maintaining high security and robustness of the hidden messages. The system is implemented in Python, featuring an intuitive graphical user interface (GUI) to facilitate user interaction. Comprehensive experiments and analyses demonstrate the effectiveness of our method in maintaining the imperceptibility and integrity of the steganographic media. This unified solution offers a versatile and efficient tool for secure communication, digital watermarking, and protection of intellectual property. Our findings underline the potential of integrating steganographic techniques across different media formats to enhance data security and privacy.

Handwritten Digit Recognition System using Machine Learning

Abstract: Handwritten digit recognition remains a crucial area of research in pattern recognition and machine learning. In this paper, we present a novel approach to enhance handwritten digit recognition systems by incorporating deep learning techniques and an interactive graphical user interface (GUI). Our system employs convolutional neural networks (CNNs) for feature extraction and classification, allowing for improved accuracy and robustness in digit recognition tasks.

Medication Recommendation System Using AI

Abstract: In an era marked by the convergence of personal and technical facets of life, the need for a versatile and intelligent companion becomes increasingly apparent. This project introduces the development of a novel Chatbot, aptly named the "Personal and Technical Companion," designed to seamlessly integrate into users' lives by offering personalized support and technical assistance. The Chatbot employs state-of-the-art Natural Language Processing (NLP) techniques to engage users in natural language conversations, providing a unique blend of personal and technical guidance. The system architecture encompasses a user-friendly interface, a robust NLP engine for intent recognition, a dynamic backend server handling logic and personalization, and integration with external services to enrich the user experience. Simultaneously, it serves as a technical companion by offering code assistance, troubleshooting guidance, and recommending relevant learning resources. Implementation leverages cutting-edge technologies, including Python for backend logic, Flask for the server, TensorFlow for NLP processing, and HTML/CSS for the user interface.

Development of a Smart Shopping Cart for Enhanced Retail Experience

Abstract: This research introduces a novel approach to revolutionize the shopping experience through the development of a Smart Shopping Cart. The system integrates technologies such as RFID, weight sensors, and real-time inventory management to provide instantaneous updates and an engaging user interface. The project’s primary objectives include enhancing inventory management efficiency and establishing a seamless RFID connection. Future enhancements envisage increased automation, enhanced security measures, personalization options, and connectivity improvements. The system employs RFID, weight sensors, a Tkinter GUI, and MySQL for database management. Key performance indicators include response time, database efficiency, RFID scanning speed, and overall system throughput. By amalgamating these technologies, this project aspires to transform the retail sector, augmenting customer satisfaction and operational efficiency

The remarkable potential of machine learning algorithms in estimating water permeability of concrete incorporating nano natural pozzolana

This paper aims to estimate the permeability of concrete by replacing the laboratory tests with robust machine learning (ML)-based models. For this purpose, the potential of twelve well-known ML techniques was investigated in estimating the water penetration depth (WPD) of nano natural pozzolana (NNP)-reinforced concrete based on 840 data points. The preparation of concrete specimens was based on the different combinations of NNP content, water-to-cement (W/C) ratio, median particle size (MPS) of NNP, and curing time (CT). Comparing the results estimated by the ML models with the laboratory results revealed that the hist-gradient boosting regressor (HGBR) and K-nearest neighbors (KNN) algorithms were the most and least robust models to estimate the WPD of NNP-reinforced concrete, respectively. Both laboratory and ML results showed that the WPD of NNP-reinforced concrete decreased with the increase of the NNP content from 1 to 4%, the decrease of the W/C ratio and the MPS, and the increase of the CT. To further aid in the estimation of concrete’s WPD for engineering challenges, a graphical user interface for the ML-based models was developed. Proposing such a model may be effectively employed in the management of concrete quality.

Performance Evaluation on Resolution Time Prediction Using Machine Learning Techniques

The quality of customer service emphasizes support tickets. An excellent support ticket system qualifies businesses to provide clients with the finest level of customer support. This enables enterprises to guarantee the consistency of quality customer service delivered successfully, ensuring all clients have a good experience regardless of the nature of their inquiry or issue. To further achieve a higher efficiency of resource allocation, this is when the prediction of ticket resolution time comes into place. The advancing technologies, including artificial intelligence (AI) and machine learning (ML), can perform predictions on the duration required to tackle specific problems based on past similar data. ML enables the possibility of automatically classifying tickets, making it possible to anticipate the time resolution for cases. This paper explores various ML techniques widely applied in the Resolution Time Prediction system and investigates the performance of three selected ML techniques via the benchmarking dataset obtained from the UCI Machine Learning Repository. Implementing selected techniques will involve creating a graphical user interface and data visualization to provide insight for data analysis. The best technique will be concluded after performing the ML technique evaluation. The evaluation metrics involved in this step include Root Mean Square Error (RMSE) and Root Mean Absolute Error (MAE). The experimental evaluation shows that the best performance among the selected ML techniques is Random Forest (RF).

Cyber Chatter

Abstract: Cyber Chatter, a web-based application built on the MERN stack, uses the power of GPT (Generative Pre-trained Transformer) technology to provide basic educational chat services and staff Building and ensure efficiency and they have been able to do it well. Cyber Chatter uses GPT-3.5, an advanced generic bid process, to provide accurate and meaningful answers to customer questions. With prior training in a large body of content knowledge, this demonstration demonstrates the incredible ability to develop and generate human-like emotions The application uses machine learning techniques to analyze customer data and continues to improve response quality over time. The use of Cyber Chatter has expanded to include Content Summarizer, Section Generator, Chat with Chatbot, Sci-fi image generator. Understudies can post questions, get answers, and engage in interesting conversations by using its natural user interface with GPT -a chatbot, Cyber Chatter. Cyber Chatter not only covers educational topics but also includes such features as content generators and JavaScript converters. Combining innovative features and an easy-to-use system, Cyber Chatter turns into a versatile punch where students can explore educational tools and interact with intelligent chatbots on a regular basis has enriched their learning experience

Nourish: Food Donation App Using Android and ML

Abstract: This research paper introduces an App designed to modernize food donation practices by digitizing the process and offering support to volunteers, from organizations such, as NGOs orphanages and other charitable institutions. Encouraged by the recurring difficulties of food waste together with worldwide food scarcity the task looks for to develop an easy-to-use system promoting smooth and also clear contributions from people, services as well as dining establishments. To minimize the wastage of food this effort attempts to link the space in between excess food and hunger among the poorer. The Mobile application display the advancement of a user-friendly application user interface streamlining the uploading, with organized functions as well as a focus on transparency. Especially, the application integrates identity confirmation system enabling contributors to post and also confirm their identity by verifying their Aadhar card therefore guaranteeing authenticity of donors and recipients. Furthermore, the app serves as a hub, for resources providing people with access, to guidelines, best practices and other information aimed at raising awareness to combat food waste. By fostering neighborhood interaction and also forging collaborations with neighborhood organizations this study adds to a much more lasting future by making excess food easily offered to those encountering food instability therefore dealing with the double obstacles of food waste as well as needs while harnessing modern technology for favorable social effect

Smart Occupancy Lighting System

This project introduces a sophisticated system designed to streamline lighting management in seminar halls, effectively addressing the diverse needs of both stage activities and audience engagement. Leveraging the Arduino Uno R3 microcontroller, alongside infrared (IR) sensors, a toggle switch, jumper wires, and an LED display, this system offers a comprehensive solution for dynamically adjusting lighting levels based on real-time occupancy data. By integrating sensor technology at strategic entry and exit points within the seminar hall, the system accurately detects the flow of attendees, enabling precise control over both stage and audience lights. The innovative use of a toggle switch provides manual control over stage lighting, granting presenters and event organizers the flexibility to tailor the lighting environment to suit specific presentation styles and event dynamics. Through seamless automation and intuitive user interface design, this system enhances energy efficiency, optimizes attendee comfort, and facilitates smooth event management processes. This abstract provides a succinct overview of the project's objectives, components, and anticipated benefits, setting the stage for a detailed exploration of its design, implementation, and potential applications in seminar hall environments.

MyPEEPS Mobile App for HIV Prevention Among Transmasculine Youth: Adaptation Through Community-Based Feedback and Usability Evaluation.

Transgender men and transmasculine youth are at high risk for acquiring HIV. Growing research on transgender men demonstrates increased HIV risk and burden compared with the general US population. Despite biomedical advancements in HIV prevention, there remains a dearth of evidence-based, sexual health HIV prevention interventions for young transgender men. MyPEEPS (Male Youth Pursuing Empowerment, Education, and Prevention around Sexuality) Mobile is a web-based app that builds on extensive formative community-informed work to develop an evidence-based HIV prevention intervention. Our study team developed and tested the MyPEEPS Mobile intervention for 13- to 18-year-old cisgender young men in a national randomized controlled trial, which demonstrated efficacy to reduce sexual risk in the short term-at 3-month follow-up. Trans men and transmasculine youth resonated with basic HIV educational information and sexual scenarios of the original MyPEEPS app for cisgender men, but recognized the app's lack of transmasculine specificity. The purpose of this study is to detail the user-centered design methods to adapt, improve the user interface, and enhance the usability of the MyPEEPS Mobile app for young transgender men and transmasculine youth. The MyPEEPS Mobile app for young transgender men was adapted through a user-centered design approach, which included an iterative review of the adapted prototype by expert advisors and a youth advisory board. The app was then evaluated through a rigorous usability evaluation. MyPEEPS Mobile is among the first mobile health interventions developed to meet the specific needs of young transgender men and transmasculine youth to reduce HIV risk behaviors. While many of the activities in the original MyPEEPS Mobile were rigorously developed and tested, there was a need to adapt our intervention to meet the specific needs and risk factors among young transgender men and transmasculine youth. The findings from this study describe the adaptation of these activities through feedback from a youth advisory board and expert advisors. Following adaptation of the content, the app underwent a rigorous usability assessment through an evaluation with experts in human-computer interaction (n=5) and targeted end users (n=20). Usability and adaptation findings demonstrate that the MyPEEPS Mobile app is highly usable and perceived as potentially useful for targeting HIV risk behaviors in young transgender men and transmasculine youth.

Designing a Smartphone-Based Pulse Oximeter for Children in South Africa (Phefumla Project): Qualitative Analysis of Human-Centered Design Workshops With Health Care Workers.

Pulse oximeters noninvasively measure blood oxygen levels, but these devices have rarely been designed for low-resource settings and are inconsistently available at outpatient clinics. The Phefumla project aims to develop and validate a pediatric smartphone-based pulse oximeter designed specifically for this context. We present the process of human-centered oximeter design with health care workers in South Africa. We purposively sampled 19 health care workers from 5 clinics in Khayelitsha, Cape Town. Using a human-centered design approach, we conducted participatory workshops with four activities with health care workers: (1) they received 3D-printed prototypes of potential oximeter designs to provide feedback; (2) we demonstrated on dolls how they would use the novel oximeter; (3) they used pile sorting to rank design features and suggest additional features they desired; and (4) they designed their preferred user interface using a whiteboard, marker, and magnetized features that could be repositioned. We audio recorded the workshops, photographed outputs, and took detailed field notes. Analysis involved iterative review of these data to describe preferences, identify key design updates, and provide modifications. Participants expressed a positive sentiment toward the idea of a smartphone pulse oximeter and suggested that a pediatric device would address an important gap in outpatient care. Specifically, participants expressed a preference for the prototype that they felt enabled more diversity in the way it could be used. There was a strong tendency to prioritize pragmatic design features, such as robustness, which was largely dictated by health care worker context. They also added features that would allow the oximeter device to serve other clinical functions in addition to oxygen saturation measurement, such as temperature and respiratory rate measurements. Our end user-centered rapid participatory approach led to tangible design changes and prompted design discussions that the team had not previously considered. Overall, health care workers prioritized pragmatism for pediatric pulse oximeter device design.

User-centric design of a 3D search interface for protein-ligand complexes

In this work, we present the frontend of GeoMine and showcase its application, focusing on the new features of its latest version. GeoMine is a search engine for ligand-bound and predicted empty binding sites in the Protein Data Bank. In addition to its basic text-based search functionalities, GeoMine offers a geometric query type for searching binding sites with a specific relative spatial arrangement of chemical features such as heavy atoms and intermolecular interactions. In contrast to a text search that requires simple and easy-to-formulate user input, a 3D input is more complex, and its specification can be challenging for users. GeoMine’s new version aims to address this issue from the graphical user interface perspective by introducing an additional visualization concept and a new query template type. In its latest version, GeoMine extends its query-building capabilities primarily through input formulation in 2D. The 2D editor is fully synchronized with GeoMine’s 3D editor and provides the same functionality. It enables template-free query generation and template-based query selection directly in 2D pose diagrams. In addition, the query generation with the 3D editor now supports predicted empty binding sites for AlphaFold structures as query templates. GeoMine is freely accessible on the ProteinsPlus web server (https://proteins.plus).

Decoding Gender Representation and Bias in Voice User Interfaces (VUIs)

This article offers a thorough exploration of gender representation and bias within Voice User Interfaces (VUIs), delving into their intricate impact on technology design, user interaction, and broader societal dynamics. It scrutinizes the entrenched gender stereotypes inherent in VUI design, revealing the intricate interplay between technology, cultural norms, and gender expectations[1]. It highlights the ethical implications of such biases, emphasizing the need for diverse perspectives in the development of VUIs[2], [3]. the article advocates for a multifaceted approach to understanding and identifying bias in VUIs, incorporating methodologies such as data analysis, algorithmic auditing, and user testing[4]. Beyond individual interactions, it discusses how gender bias in VUIs can erode trust, diminish user satisfaction, and perpetuate systemic inequalities[1]. Proposing a shift towards gender-neutral design principles, it advocates for inclusivity and equity, championing personalized experiences and diverse representation. Looking ahead, the article outlines future directions in VUI technology aimed at advancing gender equality through enhanced natural language understanding, sentiment analysis, and collaborative design approaches[4]. By unraveling and addressing gender representation and bias in VUIs, this article lays a robust foundation for fostering a more inclusive and equitable landscape in voice technology.

TraumaFlow-development of a workflow-based clinical decision support system for the management of severe trauma cases.

The treatment of severely injured patients in the resuscitation room of an emergency department requires numerous critical decisions, often under immense time pressure, which places very high demands on the facility and the interdisciplinary team. Computer-based cognitive aids are a valuable tool, especially in education and training of medical professionals. For the management of polytrauma cases, TraumaFlow, a workflow management-based clinical decision support system, was developed. The system supports the registration and coordination of activities in the resuscitation room and actively recommends diagnosis and treatment actions. Based on medical guidelines, a resuscitation room algorithm was developed according to the cABCDE scheme. The algorithm was then modeled using the process description language BPMN 2.0 and implemented in a workflow management system. In addition, a web-based user interface that provides assistance functions was developed. An evaluation study was conducted with 11 final-year medical students and three residents to assess the applicability of TraumaFlow in a case-based training scenario. TraumaFlow significantly improved guideline-based decision-making, provided more complete therapy, and reduced treatment errors. The system was shown to be beneficial not only for the education of low- and medium-experienced users but also for the training of highly experienced physicians. 92% of the participants felt more confident with computer-aided decision support and considered TraumaFlow useful for the training of polytrauma treatment. In addition, 62% acknowledged a higher training effect. TraumaFlow enables real-time decision support for the treatment of polytrauma patients. It improves guideline-based decision-making in complex and critical situations and reduces treatment errors. Supporting functions, such as the automatic treatment documentation and the calculation of medical scores, enable the trauma team to focus on the primary task. TraumaFlow was developed to support the training of medical students and experienced professionals. Each training session is documented and can be objectively and qualitatively evaluated.

Use of the National Climate and Energy Policy Simulation Tool in the Policy Making Process

Energy transition towards CO2 neutral energy systems is challenging as the national energy policy depends on numerous factors. In system dynamics approach these factors are identified as causal and feedback loops with lock-ins, as a result constituting stock-and-flow structure. Such a kind of structure is used in different simulation tools. This study analyses the use of the Latvian national climate and energy policy simulation tool in the policy making process. As a hypothesis of the study was set that the simulation tool, which is based on the principles of systemic thinking (explaining causal relationships) and an easy-to-use user interface, significantly improves the national energy and climate policy making process. Accordingly, to verify the hypothesis the task was to evaluate the use of the national climate and energy policy simulation tool in the policy-making process. For the evaluation the relevant literature was reviewed: climate and energy policy goals, policies and legislation in the European Union and Latvia; approaches to modeling national climate and energy policies, including optimization models, simulation models; the use of simulation models in the modeling of national climate and energy policies; the use of system dynamics models in the modeling of national climate and energy policies. Besides using the systemic thinking approach in the process of creating national climate and energy policies, the user experience in building simulation tools was used. Based on the literature analysis, improvements to the interface of the national climate and energy simulation tool developed by Riga Technical University, Institute of Energy Systems and Environment were made and developed training material for the use of the simulation tool, based on explaining the causal relationships built into the model.

Graphical User Interface for Handwritten Mathematical Expression Employing RNN-based Encoder-Decoder Model

Graphical User Interface for Handwritten Mathematical Expression Employing RNN-based Encoder-Decoder Model

WebGestalt 2024: faster gene set analysis and new support for metabolomics and multi-omics.

Enrichment analysis, crucial for interpreting genomic, transcriptomic, and proteomic data, is expanding into metabolomics. Furthermore, there is a rising demand for integrated enrichment analysis that combines data from different studies and omics platforms, as seen in meta-analysis and multi-omics research. To address these growing needs, we have updated WebGestalt to include enrichment analysis capabilities for both metabolites and multiple input lists of analytes. We have also significantly increased analysis speed, revamped the user interface, and introduced new pathway visualizations to accommodate these updates. Notably, the adoption of a Rust backend reduced gene set enrichment analysis time by 95% from 270.64 to 12.41 s and network topology-based analysis by 89% from 159.59to 17.31 s in our evaluation. This performance improvement is also accessible in both the R package and a newly introduced Python package. Additionally, we have updated the data in the WebGestalt database to reflect the current status of each source and have expanded our collection of pathways, networks, and gene signatures. The 2024 WebGestalt update represents a significant leap forward, offering new support for metabolomics, streamlined multi-omics analysis capabilities, and remarkable performance enhancements. Discover these updates and more at https://www.webgestalt.org.

Fintrack (Personal Finance Tracker)

Fintrack is a comprehensive personal finance tracker designed to empower people to take control of their financial well-being. This summary provides an overview of Fintrack's main functions, features and potential impact on personal financial management. Fintrack provides its users with a centralized platform to track and manage their finances easily and efficiently. The platform allows users to add their financial accounts, including bank accounts, credit cards, loans and investments, providing a holistic view of their financial situation. With Fintrack, users can easily categorize transactions, set budgets and track their spending habits in real time. The platform's intuitive user interface and user-friendly design streamline the budgeting process, helping users identify savings goals and optimize their financial habits. Fintrack allows users to set and track financial goals, whether it's saving for a major purchase, paying off debt or planning for retirement. The platform provides users with personalized insights and recommendations based on their financial behavior to guide them to make smarter financial decisions. Security and privacy are paramount as Fintrack uses advanced encryption protocols and strict privacy measures to protect users' sensitive financial information. Overall, Fintrack is a valuable tool for people who want to achieve financial wellness and create a brighter financial future. With its comprehensive features and user-centric approach, Fintrack aims to revolutionize personal financial management and enable users to achieve their financial goals with confidence and clarity. Keywords: Personal Finance Management, Financial Tracking, Investment Tracking.

Automated Time – Table Generator Using Genetic Algorithm

Timetable creation is a very important job in schools as it helps to make sure that all resources are used appropriately and the students get an environment conducive for learning. In this paper, we introduce a new way of making them automatically using genetic algorithms for optimization. The method takes into account several restrictions such as availability of classes or subjects, preference of teachers about rooms they would like to teach in, size of rooms among many others which are necessary when generating optimized timetables for given sets of classes or resources. The structure of our suggested algorithm has been borrowed from genetics. Some objectives were considered during fitness evaluation namely even distribution across days; minimum number of gaps between consecutive periods; conformity with rules. Additionally, a Graphical User Interface (GUI) was developed alongside the algorithmic design which allows easy interaction with the user for better understanding and experience on how the system works. Through this interface users are able to input constraints, view generated timetables and do other customizations thus making it more usable than just having command line-based program. Key Words: Timetable, Genetic Algorithm, Optimization, GUI.