User Interface Research Articles

User interface design of context-input-process-product evaluation application based on weighted product

This study aimed to show the user interface design form of the <br /> context-input-process-product (CIPP) evaluation application based on weighted product as a measuring tool for the effectiveness level of blended learning in health colleges. This research approach was development research. The development model used was Borg and Gall. It focused on the design stage, initial trials, and revisions. The initial test of the user interface design involved 32 respondents. The tool for conducting it was in the form of a questionnaire, which contains 16 questions. The research was at the health colleges in Buleleng Regency. The data analysis technique of the initial test results was quantitative descriptive. It compared the percentage level of user interface design quality from the weighted product-based CIPP evaluation application with a quality standard which referred to a five scale. The results of this study indicated that the quality of the user interface design was relatively good. The research result’s impact on educational evaluation was new knowledge for pedagogic evaluators in maximizing the development of digital-based evaluation tools by integrating the decision support system method (weighted product) with the educational evaluation model (CIPP model).

Performance evaluation of low energy adaptive clustering hierarchy-based cluster routing protocols in wireless sensor networks using a new graphical user interface

Wireless sensor network (WSN) is widely used for field data acquisition and monitoring in different domains. To make this type of network functional, efficient routing protocols must be implemented. Nevertheless, WSNs have an energy constraint due to limited batteries. Many clustered protocols are proposed to overcome it. However, the implementation of these protocols would be difficult to understand without a simulation tool, as some problems may arise during their development. Testing real-world applications requires a lot of effort and cost because they often use many nodes in large networks. Therefore, the simulation tool is the most relative way to evaluate these protocols. This paper presents graphical-based cluster protocols simulation interface for WSN(GCPS-WSN), a new interface to simulate some clustered protocols in WSNs. GCPS-WSN allows the user to evaluate the performance of certain low energy adaptive clustering hierarchy (LEACH) enhanced protocols to choose the most appropriate one for his system. The user can simulate protocols without any knowledge of software programming.

Clip Outliner

Abstract: In today's digital era, the influx of video content inundates online platforms daily, presenting a formidable challenge for users seeking relevant information within these extensive recordings, particularly under time constraints. The process of extracting crucial insights fromlengthy videos often proves daunting and time- consuming. Clip Outliner is an innovative project that offers a versatile solution for summarizing both textual and video content. This tool combinesthe capabilities of a text summarizer with advanced video analysis features, providing users with concise textual summaries while also offeringinsights into video content. Leveraging Python APIs for text transcription and employing natural language processing (NLP)techniques, transcripts are efficiently condensed. The user interface is meticulously crafted using Streamlit serving as the robust open-source framework in Python.

Crack Detection of Structures using Artificial Intelligence System

Abstract: Structural Health Monitoring (SHM) having wider scope of operations such as structural audit, rehabilitation of structures and along with it a major scope of crack detection is also included. Effective crack detection is vital for ensuring the safety and longevity of civil engineering structures. Crack Detection in existing methods is tedious process, it requires costly equipment’s as well as time consuming, and inaccuracy in mechanical equipment’s. The technological advancements especially in the field of Artificial Intelligence (AI) maybe an acceptable solution for crack identification through mobile app using Image processing techniques. The mobile app can be used to accurately identify crack pattern and measure the size of cracks in structures (concrete and steel). The app needed to capture and process data from diverse sources, such as images, in real time. It allows for real-time monitoring of structures and ensures safety and integrity of it. The image processing algorithm is used for to accurately identifying various types of cracks in different lighting, environmental conditions, effective and optimized solution. This project explained about real-time data processing for crack detection and its challenges. This demanded robust backend infrastructure and efficient data processing techniques to deliver prompt and accurate results. User Interface and Experience developing an intuitive and user-friendly interface for the app while maintaining high performance.

ResumeCraft: A Machine Learning-powered Web Platform for Resume Building

Abstract: The competitive job market necessitates well-crafted resumes that resonate with both human recruiters and Applicant Tracking Systems (ATS). This paper introduces ResumeCraft, a web-based platform empowering users to build strong resumes and optimize them for ATS compatibility. ResumeCraft leverages Machine Learning (ML) for data analysis and user guidance, while the user interface is built with Hypertext Markup Language (HTML), Cascading Style Sheets (CSS), and JavaScript for a user-friendly experience. The system allows users to input their personal and professional details through a series of form fields, and provides a real-time preview of the resume design as the user inputs their data. The resume generator uses JavaScript to dynamically populate the preview with the user's input, and allows users to select from a range of pre-designed templates and color schemes to customize the look and feel of their resume. It processes the user input and generates a downloadable Portable Document Format (PDF) of the final resume. The platform analyzes user-provided information through ML models, offering suggestions on skill extraction, keyword matching, and action verb usage. This combination empowers users to create impactful resumes that are more likely to pass through ATS filters and reach human reviewers.

Design and Construction of 3 DOF Prototype Delta Parallel Robot

Abstract: The design and construction of a prototype delta robot to utilize for upper secondary educational institutes is presented. The focus is on leveraging 3D printing technology in AutoCAD for component fabrication, detailing electrical schematics, and integrating Arduino for its intuitive User Interface (UI). The project’s objective is to construct a delta robot prototype equipped with essential features to serve as an educational tool for teaching fundamental robotics principles. Additionally, the design allows for customization of specific robot parts in future iterations to adapt it to various applications as needed

Remote Controlled Agricultural Robot

Abstract: The Agri Bot project presents a pioneering endeavor in the realm of autonomous agriculture by seamlessly integrating robotics, IoT, and mobile application development. Utilizing an Arduino UNO microcontroller, ESP32 camera module, servo motors, and various sensors, the system excels in executing precise agricultural tasks such as digging, filling, seed sowing, and fertilizer dispensing. The accompanying mobile application, developed through MIT App Inventor and utilizing Bluetooth communication, provides an intuitive interface for users to remotely oversee and manage the Agri Bot's operations. Beyond its successful hardware and software integration, the project holds transformative potential for traditional farming practices, evident in the incorporation of advanced technologies such as obstacle detection sensors and machine learning for crop recognition. The modular design and collaborative potential of swarm robotics hint at scalability and adaptability for evolving agricultural needs. As the project lays the groundwork for autonomous agriculture, future prospects include autonomous navigation, sustainable power solutions, data analytics for decision support, and enhanced remote monitoring. Collaboration with agricultural experts and ongoing refinements based on real-world feedback are crucial for optimal deployment in diverse farming environments. The Agri Bot project represents a significant milestone in the convergence of technology and agriculture, heralding a future where autonomous systems play a central role in shaping the agricultural landscape.

Four Quadrant Operation of DC Motor Controlled by Android Application

Abstract: The project is designed to develop a four quadrant speed control system for a DC motor. The motor is operated in four quadrants i.e. clockwise; counter clock-wise, forward brake and reverse brake. It also has a feature of speed control. The four quadrant operation of the dc motor is best suited for industries where motors are used and as per requirement as they can rotate in clockwise, counter-clockwise and also apply brakes immediately in both the directions. In case of a specific operation in industrial environment, the motor needs to be stopped immediately. In such scenario, this proposed system is very apt as forward brake and reverse brake are its integral features. Instantaneous brake in both the directions happens as a result of applying a reverse voltage across the running motor for a brief period and the speed control of the motor can be achieved with the PWM pulses generated by the microcontroller. The microcontroller used in this project is from 8051 family. Remote operation is achieved by any smart-phone/Tablet etc., with Android OS, upon a GUI (Graphical User Interface) based touch screen operation. Bluetooth device is provided to connect with android application device for the operation of the motor which are interfaced to the microcontroller that provides an input signal to it and in turn controls the speed of the motor through a motor driver IC. This project can be enhanced by using higher power electronic devices to operate high capacity DC motors. Regenerative braking for optimizing the power consumption can also be incorporated

Home Automation using Android App

Abstract: The rapid expansion of smart technology has changed many aspects of daily life, with home automation taking the lead. This study examines the creation, advancement, and deployment of a Bluetooth-based home automation system. Utilizing a microcontroller, the system enables seamless communication between household appliances and user-controlled devices. By integrating Bluetooth communication protocols, users can manage and monitor their home environment from a distance, enhancing convenience, efficiency, and energy conservation. The document delves into system architecture, hardware elements, software algorithms, and user interface design, providing insights into the technical aspects of the configuration. It also covers practical considerations such as security protocols and scalability to ensure a stable and reliable operation. Through experimental outcomes, the efficacy and usability of the proposed home automation solution are illustrated, demonstrating its potential to transform traditional houses into intelligent, interconnected ecosystems. This research contributes to the existing knowledge in home automation and serves as a valuable resource for researchers, professionals, and enthusiasts keen on exploring the capabilities of Bluetooth technology to enhance everyday living experiences.

A Collaborative Code Platform with Advanced AI Features and Real-Time Collaboration Tools

Abstract: Good collaboration and code management are crucial in today's software development environment. Our research has launched a new collaborative process that combines AI resources, including AI and global research, to improve products and enhance and facilitate collaboration. The platform features real-time collaboration tools such as dynamic text with multilanguage support, dialog functionality, and notepad functionality. With OAuth authentication, users can seamlessly perform CRUD operations on files and directories, share code repositories, and participate in live coding sessions. The platform supports compilation and execution of a code file and follows good design principles such as caching, microservices architecture, and containerization to ensure scalability and performance. The platform focuses on user experience by providing simple user interface design and easy interface navigation. Users can create workspaces, share them collaboratively, and seamlessly import repositories from Git. The platform's intelligent data manager helps manage files and directories, while the collaborative platform allows developers to collaborate on code libraries efficiently. The platform is modern web-based, using React on the frontend and Node.js on the backend; Supported with syntax highlighting and smart initialization along with Socket.io for runtime with SQL and NoSQL databases. Provides comprehensive language support. All progress is saved, providing users with peace of mind. While the basic design is for desktops, future iterations are expected to support mobile devices.

Handwritten Digit Recognition

Abstract: This paper presents a powerful Handwritten Digit Recognition System that combines a Graphical User Interface (GUI) based on Tkinter with Convolutional Neural Networks (CNNs). Our approach, which makes use of the MNIST dataset, includes careful data pretreatment to facilitate efficient CNN model training. Convolutional and pooling layers are included in the design of the model, and they are optimized with the Adam optimizer for higher learning rates. The evaluation's findings demonstrate excellent memory, accuracy, and precision. Furthermore, real-time digit drawing is made possible via an intuitive Tkinter GUI, which confirms the model's applicability. By showing the effectiveness of CNNs and offering an interactive platform for natural user interaction, the research provides a holistic solution to handwritten digit recognition. This method is promising for various uses in digit recognition scenarios, highlighting its flexibility and usefulness in real-world situations.

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

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

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.

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.

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.

"Intelligent tutoring effects on induced emotions and cognitive load of learning-disabled learners".

This study addresses the learning requirements of learners with learning difficulties by monitoring their learning experience in an Intelligent Tutoring System. Intelligent Tutoring Systems were developed to enrich the teaching-learning process. In the present work, the interface is designed and developed utilizing the potential of Artificial Intelligence to meet their individual needs. Designing an online learning platform for a learners with learning difficulties requires consideration of their learning problems and preferences. The interface was developed focusing on all the requirements of the LD learners. The objective of the present study is to monitor the learning experience in the form of induced emotions and cognitive load of the learners to determine the impact of learning. 83 learners were observed during various stage of learning. The results obtained through the Support Vector machine (SVM) classification technique showed the positive attitude towards intelligent tutoring. The analysis revealed that a total of 0.23% of learners were positively induced. Their learning experience was positive and effective. The cognition load on learners was minimum with single-mode instruction and least disturbed. The system was improved based on preference feedback on design features. This helps in improving content design and creating device independent and responsive visual design. The fatigue effect analysis on cognitive load implied that multiple modes of instruction increased drowsiness. Single mode of instruction have a positive impact on the learning process and it reduces the cognitive load of the learners.Implications for RehabilitationThe user interface designed and developed for learners with Dyslexia, Dysgraphia and Dyscalculia has learning disabled-friendly features. These can be used to create a device-independent and responsive design.Learning experience is monitored along with the impact on cognitive load of the learners.The research helps in understanding the stimulation and response of learners with learning disability for different learning conditions.Most existing learning systems are limited to non-learning-disabled learners. The ITS developed during research presents a Universal learning design helpful for all learners with and without learning disability.