Intuitive Design Research Articles

Reinforcement Learning-Based Optimal Hull Form Design with Variations in Fore and Aft Parts

Abstract With recent advancements in artificial intelligence technology, various studies are being conducted in the shipbuilding industry. Traditionally, hull form variation methods have relied on the intuition and expertise of designers, leading to inconsistent results and unintended changes in the ship's main dimensions depending on the designer's competence. Moreover, the iterative process of design variation and analysis to derive the optimal hull form is both costly and time-consuming. To address these issues, this study proposes an optimal hull design technique utilizing reinforcement learning, a type of unsupervised learning in machine learning. Reinforcement learning allows the model to learn from past policies by recording and accumulating the rewards associated with various actions taken by an agent in a specific environment. In this study, after calculating the main parameters of the ship, the agent defines a state representing hull information and performs local transformations of the bow and stern. The reward of reinforcement learning is defined as the change in total resistance due to the hull deformation, constrained by limiting the tolerance of the ship's prismatic coefficient (CP) and longitudinal center of buoyancy (LCB). In this study, the problem is solved by comparing the proximal policy optimization (PPO) algorithm and the deep deterministic policy gradient (DDPG) algorithm to find the best deep reinforcement learning (DRL) model for the hull optimization problem. The results were compared with the genetic algorithm and speed-constrained multi-objective particle swarm optimization (SMPSO), and the optimal hull resistance values were less different, but the time of the reinforcement learning model was five times shorter.

Pemodelan Teknologi dalam Aplikasi KitaLulus untuk Lowongan Pekerjaan Menggunakan Metode Technology Acceptance Model (TAM)

Technological advancements have increased the need for job vacancy information, while the unemployment rate in Indonesia remains high. The KitaLulus application is designed to facilitate job seekers in finding opportunities that match their qualifications and preferences. This study adopts the Technology Acceptance Model (TAM) to analyze user acceptance of this application, focusing on perceived usefulness and perceived ease of use. The objective of this research is to evaluate users' perceptions of the KitaLulus application and analyze the influence of perceived usefulness, perceived ease of use, and behavioral intention on actual system usage. The results indicate that perceived usefulness and perceived ease of use significantly influence the acceptance and use of the KitaLulus application. These findings emphasize the importance of intuitive and beneficial application design to enhance technology adoption, while contributing to the development of job search applications and the academic literature on technology acceptance.

Utilizing Human Factors to Improve Surgeons’ Data Access

Improving health care quality has been a focus for human factors practitioners in the past decades. Built on the new computerized information provided by Robot-Assisted Surgery (RAS), we conducted interviews with 21 surgeons to explore how this surgical information can help improve surgeons’ efficiency and proficiency. Almost all the participants we interviewed considered their surgical data access to be limited. In addition, they indicated that insights from surgical data could help improve their efficiency and proficiency. We present our findings in two main categories: the surgeons’ current data access and the tools surgeons use to access surgical data. We also documented what surgical data surgeons need, why they need the data and how the data could help improve surgeons’ efficiency and proficiency. Our findings and proposed designs were incorporated in My Intuitive App designs to implement values identified by our Human Factors analysis.

Data-Driven Modelling of Substituted Pyrimidine and Uracil-Based Derivatives Validated with Newly Synthesized and Antiproliferative Evaluated Compounds.

The pyrimidine heterocycle plays an important role in anticancer research. In particular, the pyrimidine derivative families of uracil show promise as structural scaffolds relevant to cervical cancer. This group of chemicals lacks data-driven machine learning quantitative structure-activity relationships (QSARs) that allow for generalization and predictive capabilities in the search for new active compounds. To achieve this, a dataset of pyrimidine and uracil compounds from ChEMBL were collected and curated. A workflow was developed for data-driven machine learning QSAR using an intuitive dataset design and forwards selection of molecular descriptors. The model was thoroughly externally validated against available data. Blind validation was also performed by synthesis and antiproliferative evaluation of new synthesized uracil-based and pyrimidine derivatives. The most active compound among new synthesized derivatives, 2,4,5-trisubstituted pyrimidine was predicted with the QSAR model with differences of 0.02 compared to experimentally tested activity.

MHealth learning strategies to support behaviour change in individuals using wheelchairs and/or scooters: a systematic review.

The purpose of this systematic review of the literature is to build understanding of the key elements and recommendations for the design of mHealth technology for individuals using wheelchairs and/or scooters and identify key features associated with the use of mHealth to support healthy behaviour changes for this population. Eight major electronic databases were systematically searched to identify mobile health (mHealth) interventions, which targeted adult WC/S users. Independent reviewers used Endnote and Covidence to manage articles meeting review criteria and to exclude duplicates. A quality assessment was conducted on each included article. Nine articles describing studies with diverse study designs met criteria to be included in this review. Several interactive application intervention features, such as participant collaboration and goal setting, and key technical features to support mHealth app development and utilisation were identified. Results found intuitive and simple designs of mHealth apps, with the ability to customise to support learning styles and preferences, support usability and acceptability by participants. More research is needed to evaluate best practices to support initial training of end-users, mHealth apps' ability to support long-term behaviour change and maintenance, and the understanding of active ingredients in complex interventions that include mHealth apps. Both interactive mHealth application intervention and technical features support healthy behaviour change among individuals using wheelchairs and scooters.

Enhancing Healthcare Efficiency: Integrating ChatGPT in Nursing Documentation.

Our study at Chi Mei Medical Center introduced "A+ Nurse," a ChatGPT-based LLM tool, into the nursing documentation process to enhance efficiency and accuracy. The tool offers optimized recording and critical reminders, reducing documentation time from 15 to 5 minutes per patient while maintaining record quality. Nurses appreciated the tool's intuitive design and its effectiveness in improving documentation. This successful integration of AI-generated content in healthcare illustrates the potential of AI to streamline processes and improve patient care, setting a precedent for future AI-driven healthcare innovations.

Divergent effects of visual interfaces on teleoperation for challenging jobsite environments

In challenging work environments, teleoperation has been adopted for executing tasks over long distances, ensuring worker safety off-site. The physical distance from jobsites typically poses challenges to teleoperators, limiting their cognition and perception of sites. Particularly, these human-machine interface challenges vary depending on the work environment conditions. This paper analyzes the impact of different visual interfaces on teleoperators and their work performance in challenging jobsite environments, using interactive workplace modeling and simulation to execute teleoperation tasks. Based on experiments with 33 subjects in construction-related fields with industrial experience, the study observed data overload problems and distraction with effects varying by work environment. Additionally, the analysis includes how their eye gaze patterns could demonstrate these effects. The findings contribute valuable insights into human factors crucial for designing user-centered teleoperation interfaces in construction, forming the basis for an intuitive and informative interface design in task-specific settings.

VoiceBack: Design of Artificial Intelligence-Driven Voice-Based Feedback System for Customer-Agency Communication in Online Travel Services

Online travel booking has become increasingly popular; however, most travel websites do not yet offer voice interaction. This study introduces VoiceBack, an artificial intelligence (AI)-driven voice-based feedback system conceptualized to support both customers and online travel agencies during the booking process. It proposes a theoretically and empirically underpinned design concept that involves a voice user interface (VUI) for customer feedback. This feedback, collected by an AI agent, is analyzed and converted into actionable statistics, which are then presented to online travel agencies through a visual interface. The interface is designed to highlight problem areas and usability issues during the booking process. This study contributes to the field of human-centered AI, by offering insight into the complex process of designing and integrating voice, emotion, and feedback within user interfaces. This integrated approach can enrich the user experience of customers when booking travel online, and pave the way for more intuitive and responsive interaction designs in the future.

Design and Implementation of Digital Collection of Past Questions Papers in Auchi Polytechnic Library

This paper presents an overview of the implementation and implications of an electronic repository of past question papers within a polytechnic library setting. The electronic repository represents a significant advancement in academic resource management, offering a streamlined and accessible platform for students and staff to access past question papers. Through intuitive interface design and robust search functionalities, users can efficiently navigate through vast collections of question papers spanning various academic disciplines, courses and semesters. The repository enhances accessibility by allowing users to retrieve materials remotely, thereby eliminating the constraints of physical visits to the library. Security measures ensure the integrity and confidentiality of question papers, while also promoting sustainability by reducing paper usage. The availability of a comprehensive repository of past question papers fosters a culture of academic excellence by empowering students to enhance their understanding of course material and improved examination preparation. Overall, the electronic repository of question papers signifies a transformative approach to information management within educational institutions, reflecting a commitment to innovation and efficiency in academic processes.

Enabling intuitive design capabilities for in-practice 3D printing.

Enabling intuitive design capabilities for in-practice 3D printing.

Design and Development of Cybersecurity Suite

Protecting personal, corporate and government data in the digital age requires cybersecurity. Traditional cybersecurity methods sometimes lack comprehensive and dynamic protection mechanisms as cyber-attacks change and become more sophisticated. A new cybersecurity suite is proposed in this study. It integrates various advanced security technologies into a single user-friendly platform interaction. This paper specifically combines techniques for real-time phishing detection, strong password management, safe encryption and decryption services and an interactive module to promote user awareness and behaviours to improve digital security for individuals and organization. Rapid prototyping is used in iterative and incremental development phases to adapt to changing security needs and user input. This method allows the platform to be constantly improved to satisfy the current cybersecurity standards and react to new threats. The prototyped developed provides proactive digital defence, a complete cybersecurity platform that equips users to defend their digital presence. With the intuitive design and advanced feature set, the prototype aspires to democratize cybersecurity. Empirical testing of the prototype revealed that makes an effective protection of a wider audience without the complexities of security software. This paper contributes in the advances cybersecurity technology and shaping the digital protection measures.

Trauma-Informed Technology Design in Digital Sexual Health Interventions.

Digital health provides a great opportunity to increase access to sexual health information and/or services. However, it can inadvertently cause emotional trauma to end users depending on how it is designed or deployed. In this study, we explored recommendations for designing trauma-informed digital health technologies and identified three preliminary themes. These include considerations for privacy and confidentiality, intuitive and representative designs and inclusive language.

Software cost estimation tool: A App based application, estimate the cost of software project

This paper presents the design and implementation of a software cost estimation tool integrated into a mobile application developed using Flutter. The tool incorporates various techniques for software cost estimation, including expert judgment, function point analysis, 3D point analysis, and the COCOMO model. The purpose of the program is to give software engineers and project managers a practical and effective tool for calculating the time and money needed for software development projects. The paper provides a thorough explanation of each estimation technique’s implementation, along with a discussion of the app’s main features and functionalities. Because of the app’s intuitive and user-friendly design, users can quickly enter project data and get precise cost estimates. The tool’s efficacy is assessed using case studies and contrasts with other software cost estimation methods currently in use. The outcomes show that the app can produce trustworthy and precise cost estimates, which makes it an important resource for software development projects.

College Management System using Python & Django

The College Management System (CMS) is an advanced web-based application designed to streamline administrative and academic processes within educational institutions. Developed using the Django framework for backend functionalities and HTML, CSS, and JavaScript for frontend presentation, the CMS offers a comprehensive solution for managing various tasks efficiently. Leveraging SQLite as the databadminisratiase management system ensures robust data management capabilities, scalability, and ease of maintenance. The CMS provides a wide array of features to automate routine tasks and enhance collaboration among students, faculty, and administrators. Student admission and enrollment management, course scheduling, curriculum planning, and faculty assignment are seamlessly handled by the system, reducing manual workload and minimizing errors. Integrated messaging systems and announcement boards facilitate communication, fostering a collaborative learning environment. The examination management module automates the entire examination process, including exam scheduling, creation of question papers, venue allocation, and result processing. Online exam registration and automated grading streamline the process, ensuring accuracy and transparency while reducing administrative burden. Attendance tracking is simplified with the CMS, allowing faculty to record and monitor student attendance easily. Integration with biometric systems or RFID technology enhances accuracy and eliminates manual attendance taking. Comprehensive attendance reports provide insights into student progress and compliance with attendance policies. Resource management is optimized through the CMS, which enables efficient allocation and utilization of classrooms, laboratories, library resources, and equipment. Administrators can manage inventory, track asset availability, and schedule resource bookings to prevent conflicts and ensure optimal utilization. Reporting and analytics features empower administrators with real-time insights into various aspects of college operations. Customizable dashboards provide information on enrollment statistics, academic performance, financial data, and more, enabling informed decision-making and continuous improvement. In conclusion, the College Management System developed with Django, HTML/CSS/JS, and SQLite revolutionizes educational institution management. By combining advanced technology with intuitive design, the CMS enhances efficiency, transparency, and collaboration, ultimately contributing to the success and growth of the institution.

Virtual Journeys, Real Engagement: Analyzing User Experience on a Virtual Travel Social Platform

A sustainable smart tourism ecosystem relies on building digital networks that link tourists to destinations. This study explores the potential of web and immersive technologies, specifically the Virtual Romania (VRRO) platform, in enhancing sustainable tourism by redirecting tourist traffic to lesser-known destinations and boosting user engagement through interactive experiences. Our research examines how virtual tourism platforms (VTPs), which include web-based and immersive technologies, support sustainable tourism, complement physical visits, influence user engagement, and foster community building through social features and user-generated content (UGC). An empirical analysis of the VRRO platform reveals high user engagement levels, attributed to its intuitive design and interactive features, regardless of the users’ technological familiarity. Our findings also highlight the necessity for ongoing enhancements to maintain user satisfaction. In conclusion, VRRO demonstrates how accessible and innovative technologies in tourism can modernize travel experiences and contribute to the evolution of the broader tourism ecosystem by supporting sustainable practices and fostering community engagement.

Artificial intelligence in optical lens design

Traditional optical design entails arduous, iterative stages that significantly rely on the intuition and experience of lens designers. Starting-point design selection has always been the major hurdle for most optical design problem, and different designers might produce different final lens designs even if using the same initial specification. Lens designers typically choose designs from existing lens databases, analyse relevant lens structures, or explore patent literature and technical publications. With increased processing capability, producing automated lens designs using Artificial Intelligence (AI) approaches is becoming a viable alternative. Therefore, it is noteworthy that a comprehensive review addressing the latest advancements in using AI for starting-point design is still lacking. Herein, we highlight the gap at the confluence of applied AI and optical lens design, by presenting a comprehensive review of the current literature with an emphasis on using various AI approaches to generate starting-point designs for refractive optical systems, discuss the limitations, and suggest a potential alternate approach for further research.

Sustainable E-Procurement: Key Factors Influencing User Satisfaction and Dissatisfaction

The aim of this study was to identify factors that influence satisfaction and dissatisfaction in the use of public e-procurement. The use of IT solutions promotes sustainable development. Hence, there is a need to conduct research that will allow for the best possible adjustment of e-procurement solutions in order to implement them as widely as possible in business practice. This study used a quantitative exploratory survey-based approach. The obtained research results were analyzed using statistical methods, including factor analysis PCA. Factor analysis identified three main satisfaction factors and two dissatisfaction factors in e-procurement use, highlighting the importance of support, intuitiveness, and security in user satisfaction. This study contributes to the existing literature by providing a nuanced understanding of the factors influencing user satisfaction and dissatisfaction within e-procurement systems, specifically highlighting the role of intuitive design and technical support. It offers a unique perspective by integrating these insights with the specific requirements of public procurement, thereby filling a gap in the research on enhancing user experience in the context of sustainable purchasing practices.

Multifunctional design of lattice metamaterial with desired thermal expansion behaviors using topology optimization

Designing metamaterials with unprecedented coefficients of thermal expansion (CTEs) is an urgent demand for the majority engineering structures suffering from ambient temperature variation. Current studies on such artificial materials are mainly focused on achieving CTE tunnability through the purposeful design of material microstructure using an intuition based mechanism. In this study, the mechanical properties including maximum bulk modulus, specific stiffness and high thermal conductivity are combined with desired CTEs for designing multifunctional lattice metamaterials through the application of a non-intuitive topology optimization method. Toward this end, the continuous variable of member cross-sectional area is adopted to optimize lattice topology, section sizes of lattice members and material distributions, simultaneously. To meet the manufacturing requirements, an improved member intersection constraint that can cooperate with the present continuous design variable is introduced. A self-programmed routine that can be coupled with any commercial FEA software is developed to implement the present optimization method for the design of lattice metamaterials. Four typical optimization cases corresponding to different practical engineering issues are completed. Compared with the previously reported representative lattice metamaterials that are devised from the intuition or experience of designers, the optimization results obtained in this work demonstrate an obvious superiority in bulk modulus and specific stiffness. Additionally, a bimetallic specimen, fabricated using mechanical processing technology and composed of the metallic constituents Invar and Aluminum alloy, is presented to demonstrate the manufacturability of the optimized lattice microstructures.

Real-Time Multi-Map Saliency-Driven Gaze Behavior for Non-Conversational Characters.

Gaze behavior of virtual characters in video games and virtual reality experiences is a key factor of realism and immersion. Indeed, gaze plays many roles when interacting with the environment; not only does it indicate what characters are looking at, but it also plays an important role in verbal and non-verbal behaviors and in making virtual characters alive. Automated computing of gaze behaviors is however a challenging problem, and to date none of the existing methods are capable of producing close-to-real results in an interactive context. We therefore propose a novel method that leverages recent advances in several distinct areas related to visual saliency, attention mechanisms, saccadic behavior modelling, and head-gaze animation techniques. Our approach articulates these advances to converge on a multi-map saliency-driven model which offers real-time realistic gaze behaviors for non-conversational characters, together with additional user-control over customizable features to compose a wide variety of results. We first evaluate the benefits of our approach through an objective evaluation that confronts our gaze simulation with ground truth data using an eye-tracking dataset specifically acquired for this purpose. We then rely on subjective evaluation to measure the level of realism of gaze animations generated by our method, in comparison with gaze animations captured from real actors. Our results show that our method generates gaze behaviors that cannot be distinguished from captured gaze animations. Overall, we believe that these results will open the way for more natural and intuitive design of realistic and coherent gaze animations for real-time applications.

The Psychology in Tech Tactics: Basis for E-Commerce Website Development

This study investigates e-commerce user preferences, revealing key insights that can inform website development and strategy. The findings indicate a predominant user base in the 18-34 age range, with a slightly higher representation of females. Understanding these socio-demographic characteristics is crucial for targeted marketing and design. The psychological impact on user preferences underscores the significance of aesthetics. Users value intuitive layouts, appealing color schemes, and well-chosen fonts. Mobile optimization and fast website performance are essential for user satisfaction, highlighting the importance of responsive design and quick loading times in the mobile era. The study also delves into the profitability of e-commerce, emphasizing the role of data-driven marketing, pricing optimization, and customer feedback management. These factors can significantly impact a business's bottom line. This research provides actionable recommendations for e-commerce businesses. By focusing on intuitive design, mobile optimization, and data-driven strategies, businesses can create more appealing and profitable online shopping experiences.