Search Results (5,329)

The remarkable increase in published medical imaging datasets for chest X-rays has significantly improved the performance of deep learning techniques to classify lung diseases efficiently. However, large datasets require special arrangements to make them suitable, accessible, and practically usable in remote clinics and emergency rooms. Additionally, it increases the computational time and image-processing complexity. This study investigates the efficiency of converting the 2D chest X-ray into one-dimensional texture representation data using descriptive statistics and local binary patterns, enabling the use of feed-forward neural networks to efficiently classify lung diseases within a short time and with cost effectiveness. This method bridges diagnostic gaps in healthcare services and improves patient outcomes in remote hospitals and emergency rooms. It also could reinforce the crucial role of technology in advancing healthcare. Utilizing the Guangzhou and PA datasets, our one-dimensional texture representation achieved 99% accuracy with a training time of 10.85 s and 0.19 s for testing. In the PA dataset, it achieved 96% accuracy with a training time of 38.14 s and a testing time of 0.17 s, outperforming EfficientNet, EfficientNet-V2-Small, and MobileNet-V3-Small. Therefore, this study suggests that the dimensional texture representation is fast and effective for lung disease classification. Full article

Privacy and security is very critical for mobile users and in-depth research into the area highlights a need for more scientific literature on the perception and challenges of end users to better align the design of privacy and security controls with user expectations. In this paper, we have explored the perceptions of the usability of privacy and security settings in mobile applications from mobile users in Saudi Arabia. The findings highlight that gender, age, and education level of users do not have any positive correlation with the privacy and security usability perceptions of mobile users. On the other hand, user concerns about privacy and security and the trustworthiness levels of end users regarding mobile phone privacy and security have a positive impact on end users’ perception of privacy and security usability. Furthermore, privacy usability perception has a positive impact on users’ feelings about their control over the privacy and security of their mobile phones. Based on the results of this empirical study, we propose that user-centric design of privacy and security controls, transparent data handling policies, periodic data management status preview and validation by end users, user education guidelines, strict governmental policies, and automated security settings recommendations can enhance the usability of the privacy and security of mobile phone applications. Our study did not take the geographical location of respondents into account, nor were the respondents balanced based on age and gender. In future work, these weaknesses need to be taken into account, and more qualitative studies can help to extract design guidelines for usable and secure mobile applications. Full article

Working memory (WM) is a crucial cognitive function, and a deficit in this function is a critical factor in learning difficulties (LDs). As a result, there is growing interest in exploring different approaches to training WM to support students with LDs. Following the PRISMA 2020 guidelines, this systematic review aims to identify current computer-based WM training applications and their theoretical foundations, explore their effects on improving WM capacity and other cognitive/academic abilities, and extract design principles for creating an effective WM application for children with LDs. The 22 studies selected for this review provide strong evidence that children with LDs have low WM capacity and that their WM functions can be trained. The findings revealed four commercial WM training applications—COGMED, Jungle, BrainWare Safari, and N-back—that were utilized in 16 studies. However, these studies focused on suggesting different types of WM tasks and examining their effects rather than making those tasks user-friendly or providing practical guidelines for the end-user. To address this gap, the principles of the Human–Computer Interaction, with a focus on usability and user experience as well as relevant cognitive theories, and the design recommendations from the selected studies have been reviewed to extract a set of proposed guidelines. A total of 15 guidelines have been extracted that can be utilized to design WM training programs specifically for children with LDs. Full article

Rail accidents have decreased in recent years, although not significantly if measured by train accidents recorded in the last six years. Therefore, it is essential to identify weaknesses in the implementation of security and prevention systems. This research aims to study the trend and classification of railway accidents, as well as analyze public databases. Using the business management method of benchmarking, descriptive statistics, and a novel approach to the Ishikawa diagram, this study demonstrates best practices and strategies to reduce accidents. Unlike previous studies, this research specifically examines public databases and provides a framework for developing the standardization of railway accident causes and recommendations. The main conclusion is that the proposed classification of railway accident causes, and its associated database, ensures that agencies, researchers, and the government have accessible, easily linkable, and usable data references to enhance their analysis and support the continued reduction of accidents. Full article

Learning management systems (LMS) have become central to modern education, enabling accessible, personalized, and engaging learning experiences. This study aims to investigate Saudi university students’ perception of LMS in order to explore the critical factors that shape their engagement, satisfaction, and acceptance of these platforms. Drawing from the existing literature that points out the usability challenges of LMS, this study hopes to derive actionable insights to optimize e-learning outcomes. Using Kelly’s repertory grid analysis technique, this study systematically captured and analyzed the personal constructs students associate with LMS, focusing on ease of use, interactivity, and content alignment with educational needs. A sample of 20 university students provided insights on their experiences with LMS features related to usability, functionality, and interactivity, which are critical to engagement. Findings indicate that ease of use is a major determinant of acceptance, along with interactivity and relevant content delivery that supports diverse learning preferences. The study identifies key elements to improve LMS platforms, fostering a more engaging digital learning environment and supporting students’ learning needs. The findings highlight the key aspects: usability of LMS and students’ satisfaction through user-friendly interfaces and interactive features. Institutions that incorporate student feedback into LMS development will likely see improved e-learning outcomes. This research contributes to a deeper understanding of LMS user perceptions and implies refinements that can align platforms with pedagogical demands in higher education. Full article

The enthusiastic adoption of make-on-demand chemical libraries for virtual screening has highlighted the need for methods that deliver improved hit-finding discovery rates. Traditional virtual screening methods are often inaccurate, with most compounds nominated in a virtual screen not engaging the intended target protein to any detectable extent. Emerging machine learning approaches have made significant progress in this regard, including our previously described tool vScreenML. The broad adoption of vScreenML was hindered by its challenging usability and dependencies on certain obsolete or proprietary software packages. Here, we introduce vScreenML 2.0 to address each of these limitations with a streamlined Python implementation. Through careful benchmarks, we show that vScreenML 2.0 outperforms other widely used tools for virtual screening hit discovery. Full article

The EXO+ hip protector was developed to minimize the risk of hip fractures in seniors following falls. This study evaluated its usability in a Singapore nursing home from the perspective of the staff, focusing on learnability, efficiency, and satisfaction. A mixed-method design was employed, with nursing home residents wearing the EXO+ daily for eight weeks. Quantitative data on wear time were collected alongside qualitative insights from four repeated focus group discussions with care staff. In total, 15 residents (including 8 residents with cognitive impairments) and 9 staff participated. The analysis revealed six themes and fourteen subthemes related to EXO+’s usability. The residents wore the device for an average of 1.54 h per day, with those having cognitive impairments showing increased wear times, especially in the mornings and on weekdays. The findings indicated that the EXO+ was learnable and satisfactory for nursing home use, provided there are adequate supporting features. The efficiency of the EXO+ was not fully measured since no falls were reported during the study period. The study offers valuable insights for potential design modifications and workflow adaptations to enhance the implementation of hip protectors in healthcare settings, highlighting facilitators and barriers to support device uptake. Full article

In this study, we present a framework to develop and evaluate a virtual reality exposure therapy system with biofeedback toward scorpion phobia treatment. The system is developed based on the methodology for the development of virtual reality educational environments; usability is evaluated with the System Usability Scale (SUS), the affects are measured with the Positive and Negative Affect Schedule (PANAS), and the biofeedback heart rate is measured in real time using a wearable device and the HypeRate app. A descriptive study was conducted with a non-probabilistic convenience sample of undergraduate students. The non-clinical sample consisted of 51 participants (11 women and 40 men) (mean = 20.75, SD = 2.42 years). The system usability score was 75.49, higher than the average of 68. For positive affects, the average value of the overall sample was 28.18, while for negative affects it was 13.67. The results of this preliminary study, while not determining that the system could currently be applied in clinical settings, demonstrate however that the system can initially be considered as a pre-feasibility study, and if the limitations of the unbalanced non-clinical sample are addressed, it could be used in the future for this purpose. The main contribution is the proposed framework to integrate usability and affects evaluation, as well as biofeedback in a VRET system toward scorpion phobia treatment. Full article

While our world consistently presents complicated, interdisciplinary problems with STEM foundations, most pre-university curricula do not encourage drawing on multidisciplinary knowledge in the sciences and engineering to create solutions. We developed an instructional approach, Iterative Science and Engineering (ISE), that cycles through scientific investigation and engineering design and culminates in constructing a solution to a local environmental challenge. Next, we created, revised, and evaluated a six-week ISE curricular program, Invasive Insects, culminating in 6th–9th-grade students building traps to mitigate local invasive insect populations. Over three Design-Based Research (DBR) cycles, we gathered and analyzed identical pre and post-test data from 554 adolescents to address the research question: what three-dimensional (3D) science and engineering knowledge do adolescents demonstrate over three DBR cycles associated with a curricular program following the Iterative Science and Engineering instructional approach? Results document students’ significant statistical improvements, with differential outcomes in different cycles. For example, most students demonstrated significant learning of 3D science and engineering argument construction in all cycles—still, students only significantly improved engineering design when they performed guided reflection on their designs and physically built a second trap. Our results suggest that the development, refinement, and empirical evaluation of an ISE curricular program led to students’ design, building, evaluation, and sharing of their learning of mitigating local invasive insect populations. To address complex, interdisciplinary challenges, we must provide opportunities for fluid and iterative STEM learning through scientific investigation and engineering design cycles. Full article

In this paper, we study a novel static bike-sharing repositioning problem. There is a set of stations spread over a given area, each containing a number of operative bikes, damaged bikes, and free slots. The customers may pick up an operative bike from a station, use it, and return it to another station. Each station should have a target number of operative bikes to make it likely to meet customer demands. Furthermore, the damaged bikes should be removed from the stations. Given a fleet of available vehicles, the repositioning problem consists of designing the vehicles’ routes and calculating the number of operative (usable) and damaged (unusable) bikes that will be moved (loading instructions/loading policy) between stations and/or the depot. The objective is to minimize the weighted sum of the deviation from the target number of bikes for each station, the number of damaged bikes not removed, and the total time used by vehicles. To solve this problem, we propose a matheuristic based on a variable neighborhood search combined with several improving algorithms, including an integer linear programming model to optimize loading instructions. The algorithm was tested in instances based on real-world data and could find good solutions in reasonable computing times. Full article

Recent development in mobile technology has significantly improved the quality of life. Everyday life is increasingly becoming dependent on mobile devices as mobile applications are targeting the needs of the end users. However, many end users struggle with navigating mobile applications, leading to frustration, especially with sophisticated and unfamiliar interfaces. This study focuses on addressing specific usability issues in mobile applications by investigating the impact of introducing a floating action button (FAB) and icons with names at the bottom in popular applications such as YouTube, Plex, and IMDb. The current research includes three studies: Study-1 explores the navigation issues that users face; Study-2 measures the experiences of the users with improved navigation designs; and Study-3 compares the results of Study-1 and Study-2 to evaluate user experience with both existing and improved navigation designs. A total of 147 participants participated and the systems usability scale was used to evaluate the navigation design. The experiments indicated that the existing design patterns are complex and difficult to understand leading to user frustration compared to newly designed and improved navigation designed patterns. Moreover, the proposed newly designed navigation patterns improved the effectiveness, learnability, and usability. Consequently, the results highlight the imperativeness of effective navigation design in improving user satisfaction and lowering frustration with mobile applications. Full article

Evidence is increasing for digital health programs targeting the secondary prevention of stroke. We aimed to determine the feasibility of the novel Care Assistant and support Program for people after Stroke (CAPS) or transient ischaemic attack (TIA) by combining person-centred goal setting and risk-factor monitoring through a web-based clinician portal, SMS messages, a mobile application (app), and a wearable device. We conducted a 12-week mixed-methods, open-label feasibility study. Participants (6 months–3 years after stroke or TIA, access to the internet via a smartphone/tablet) were recruited via the Australian Stroke Clinical Registry. Participants set one or two secondary prevention goals with a researcher and provided access and training in technology use. Feasibility outcomes included recruitment, retention, usability, acceptability, and satisfaction. Secondary outcomes included goal attainment, health outcomes, and program costs. Following 600 invitations, 58 responded, 34/36 (94%) eligible participants commenced the program (one withdrawal; 97% retention), and 10 were interviewed. Participants (27% female, 33% TIA) generally rated the usability of the mobile application as ‘Good’ to ‘Excellent’ (System Usability Scale). Most (94%) agreed the program helped with engagement in health self-monitoring. Overall, 52 goals were set, predominantly regarding exercise (21/52), which were the most frequently achieved (9/21). At 12 weeks, participants reported significant improvements (p < 0.05) in self-efficacy (Cohen’s d = 0.40), cardiovascular health (d = 0.71), and the mental health domain of the PROMIS GH (d = 0.63). CAPS was acceptable, with good retention and engagement of participants. Evaluation of this program in a randomised controlled trial is warranted. Full article

Haematococcus pluvialis contains valuable bioactive compounds, including astaxanthin, proteins, and fatty acids. Astaxanthin is known for its various health benefits, such as preserving the redox balance and reducing inflammation. However, its low stability and poor water solubility present challenges for various applications. Hot-melt extrusion (HME) technology enhances the aqueous solubility of H. pluvialis extracts, increasing the usable astaxanthin content through nanoencapsulation (HME-DDS-applied extracts, ASX-60F and ASX-100F). This study compared the effects of HME-DDS-derived extracts (ASX-60F and ASX-100F) and the non-applied extract (ASX-C) under inflammatory and oxidative stress conditions. In animal models of sepsis, 60F and 100F treatment exhibited higher survival rates and a lower expression of pro-inflammatory biomarkers compared to those treated with C. In lipopolysaccharide-stimulated RAW 264.7 macrophages, nitric oxide (NO) production and the expression of pro-inflammatory mediators such as cyclooxygenase-2 and inducible NO synthase were reduced by 60F or 100F treatments via ERK/p-38 mitogen-activated protein kinase (MAPK) signaling. Moreover, 60F or 100F inhibited reactive oxygen species production regulated by nuclear factor erythroid 2-related factor 2 (Nrf2)/heme oxygenase-1 (HO-1) signaling. Collectively, these findings suggest that HME-DDS-derived H. pluvialis extracts exert anti-inflammatory and antioxidant effects by inhibiting MAPK phosphorylation and activating Nrf2/HO-1 expression. Full article

Efforts to achieve carbon neutrality, which aims to reduce the net carbon emissions to zero by decreasing carbon emissions from human activities and increasing carbon absorption, are actively underway. Additionally, the search for clean energy alternatives to fossil fuels has become a global research trend. This paper presents research on metal–air batteries, focusing on the development of energy supply technologies that do not generate carbon emissions during power generation and require less space for power generation compared to existing renewable energy sources. The proposed Mg–air battery (MAB) in this study uses magnesium as the metal anode and theoretically offers a maximum open-circuit voltage of 3.1 V and a high energy density of 6.8 kWh/kg. While previous research has primarily focused on designing small-capacity cells and maximizing the performance of metal anodes, this study differentiates itself by designing a large-capacity MAB cell and optimizing its electrical performance. For the large-capacity cell design, the weight, shape, and size of the anode were designed based on MAB performance factors, and research was conducted on manufacturing methods to optimize the performance of the air cathode. Furthermore, to enhance usability and extend the lifespan of the MAB cell, it was designed to allow electrolyte circulation, and the electrolyte circulation performance was verified through simulations of fluid flow within the cell. Based on the study of the power performance of the newly designed large-capacity MAB cell, the feasibility of constructing a kW-class system using multiple Mg–air battery cell stacks was confirmed. Full article

To tackle the issue of poor accuracy in single-snapshot data processing for Direction of Arrival (DOA) estimation in passive radar systems, this paper introduces a method for judiciously leveraging multi-snapshot data. This approach effectively enhances the accuracy of DOA estimation and spatial angle resolution in passive radar systems. Additionally, in response to the non-convex nature of the mixed norm, we propose a hyperbolic tangent model as a replacement, transforming the problem into a directly solvable convex optimization problem. The rationality of this substitution is thoroughly demonstrated. Lastly, through a comparative analysis with existing discrete grid DOA estimation methods, we illustrate the superiority of the proposed approach, particularly under conditions of medium signal-to-noise ratio, varying numbers of snapshots, and close target angles. This method is less affected by the number of array elements, and is more usable in practices verified in real-world scenarios. Full article