User Errors Research Articles

Development of a Machine Learning Tool to Predict Deep Inspiration Breath Hold Requirement for Locoregional Right-Sided Breast Radiation Therapy Patients.

&#xD;This study presents machine learning (ML) models that predict if deep inspiration breath hold (DIBH) is needed based on lung dose in right-sided breast cancer patients during the initial computed tomography (CT) appointment. &#xD;Materials and methods. &#xD;Anatomic distances were extracted from a single-institution dataset of free breathing (FB) CT scans from locoregional right-sided breast cancer patients. Models were developed using combinations of anatomic distances and ML classification algorithms (gradient boosting, k-nearest neighbors, logistic regression, random forest, and support vector machine) and optimized over 100 iterations using stratified 5-fold cross-validation. Models were grouped by the number of anatomic distances used during development; those with the highest validation accuracy were selected as final models. Final models were compared based on their predictive ability, measurement collection efficiency, and robustness to simulated user error during measurement collection. &#xD;Results. &#xD;This retrospective study included 238 patients treated between 2016 and 2021. Model development ended once eight anatomic distances were included, and the validation accuracy plateaued. The best performing model used logistic regression with four anatomic distances achieving 80.5% average testing accuracy, with minimal false negatives and positives (< 27%). The anatomic distances required for prediction were collected within 3 minutes and were robust to simulated user error during measurement collection, changing accuracy by < 5%. &#xD;Conclusion. &#xD;Our logistic regression model using four anatomic distances provided the best balance between efficiency, robustness, and ability to predict if DIBH was needed for locoregional right-sided breast cancer patients.&#xD.

Reconstruction errors in clinical intraoperative TRUS–based prostate HDR-BT detected using electromagnetic tracking

PurposeTo investigate the occurrence of errors in transrectal ultrasound (TRUS)-based implant reconstructions for high-dose-rate brachytherapy (HDR-BT) in prostate cancer using an afterloader-integrated electromagnetic tracking (EMT) system. Materials and MethodsFourteen patients were treated with one TRUS-based treatment fraction in an intraoperative setting while under general anesthesia, as part of their prostate HDR-BT (2×13.5 Gy) treatment. EMT measurements were performed before the start of the treatment in all implanted needles at dwell positions (DPs) with an interval of 5 mm. The Euclidean distances (EDs) between clinically reconstructed and EMT-measured DPs after registration were calculated. Errors were evaluated per needle (minimum ED of 2mm) and stratified into 4 severity levels (minor, moderate, major and severe). Error causes were investigated through retrospective inspection of TRUS imaging. ResultsThe median (range) ED between EMT-measured and clinically reconstructed DPs was 1.0 (0.1 – 9.4) mm. Higher EDs were observed in the anterior and lateral regions of the prostate. From 265 evaluated needle reconstructions, 23% (61/265) had minor errors or higher, while 9% (24/265) had major or severe errors. Severe errors were mostly caused by incorrect needle or depth selection. Major, moderate and minor errors were mostly caused by artifact, shadowing, and user errors, respectively. ConclusionsThis study found that a quarter of needle reconstructions contained errors > 2mm, and that high and severe errors were not uncommon. EMT can play an important role in detecting and preventing these reconstruction errors without disrupting the clinical workflow.

Comparing typing methods for uppercase input in virtual reality: Modifier Key vs. alternative approaches

Typing tasks are basic interactions in a virtual environment (VE). The presence of uppercase letters affects the meanings of words and their readability. By typing uppercase letters on a QWERTY keyboard, the layers can be switched using a modifier key. Considering that VE controllers are typically used in a VE, this input method can result in user fatigue and errors. Thus, this study proposed new alternative interactions for the modifier key input and compared their typing performance and user experience. In an experiment, 30 participants were instructed to type 10 sentences using different typing interaction methods (shift, long press, and double-tap) on a virtual keyboard in a VE. The typing speed, error rate, and number of backspace inputs were measured to compare typing performance. Upon the completion of the typing task, the usability, workload, and sickness associated with each typing method were evaluated. The results showed that the double-tap method exhibited significantly higher typing speed, error rate, ease of use, satisfaction, and workload. This result is consistent with those of previous studies demonstrating that selection tasks were more efficient with fewer hand movements. Thus, this study implies that the double-tap method can be considered as a potential typing interaction for the VEs instead of the traditional method using the shift as a modifier key. Therefore, this study is expected to contribute to the design and development of user-friendly interactions.

Usability Evaluation For Child Development Website Interface

This study aims to evaluate the usability of the child development website interface using the usability testing method. The evaluation was conducted by involving 20 participants consisting of parents and caregivers of children, who were asked to complete a series of tasks on the website. The assessment was carried out based on five main dimensions of usability: learnability, efficiency, memorability, errors, and satisfaction. The results showed that the website had good learnability, with the majority of participants being able to understand the interface on first use. User satisfaction was also high, with an average score of 4 out of 5. However, some problems were found in terms of efficiency, especially related to navigation which sometimes required too many steps. In addition, the level of user error increased on more complex tasks, such as using child development aids, which required clearer instructions. These findings provide recommendations for improving the usability of the website, including simplifying navigation, providing more comprehensive guidance, and improving feedback from the system. Implementation of these improvements is expected to increase the effectiveness of the website in helping parents monitor their child's development more efficiently.

Perancangan Sistem Aplikasi Support Ticketing Berbasis Web pada PT ABCD

PT ABCD is one of the big companies based in Jakarta. PT ABCD has several branches in several cities. PT ABCD uses Information Technology to run operational activities more effectively. But in these activities, various departments also experience problems caused by user errors or system bugs. Therefore, the IT team has a helpdesk division that functions as the first person to be contacted if users experience problems. To make reports of problems experienced by users more effectively, a web-based support ticketing application is designed. The function of the application is that reporting can be done so that it can be reported to superiors and this incident does not occur if the same incident occurs with the helpdesk team knowing what the solution is. Intisari: Web, helpdesk, ticketing, IT.

Perancangan Sistem Informasi Pengolahan Data Morbiditas Rawat Inap Guna Menunjang Tata Kelola Pelaporan Rawat Inap

Morbidity is a crucial aspect that must be reported regularly, specifically quarterly (RL4a). This study aims to support the governance of inpatient unit reporting, especially in the aspect of morbidity, and make it easier for medical record officers as system users to process morbidity data of inpatient unit patients into a report that is needed quickly, accurately, and efficiently. This research is qualitative, and data is collected using observation techniques. This research's system development method is the waterfall model, which is a consecutive development method analogous to a waterfall that flows across all project stages. Designing an inpatient morbidity data processing system to support inpatient reporting governance is described using a flow map, Context diagram, Data flow diagram, and Entity relationship diagram. Then, it was implemented into the website using Microsoft Visual Studio Code using the Hypertext Preprocessor, Javascript programming language, and supported by MySQL as a data store. This study results in a system that can quickly process the morbidity of inpatient units, make the extensive ten disease reports, and reduce user error. Therefore, the governance of inpatient reporting can run accurately and efficiently.

Establishing a user demand hierarchy model driven by a mental model for complex operating systems

In complex human-computer interactions, issues such as task failures, system malfunctions, and frequent accidents caused by user errors are common. Therefore, it is necessary to study complex system interactions to enhance overall efficiency. This study focuses on the task interface of a digital twin system for computer numerical control (CNC) machine tools and examines the relationship between the user mental model and interface design elements. Key mental information is obtained through questionnaires and interviews, forming the basis for establishing a user mental model. High-frequency information words are extracted, experimental samples are designed, and importance rating surveys are conducted. Quantitative analysis methods, including factor analysis and weight calculation, are utilized to analyze the needs of target users. Consequently, a user demand hierarchy model is constructed. This approach aims to effectively reduce user errors in the human-computer interaction process within complex systems and enhance cognitive efficiency.

Comparison of biuret and refractometery method for serum total protein measurements in cattle and goat

ObjectivesThe biuret method is frequently used to determine serum total protein. On the other hand refractometer, a quicker and less expensive option, is available to determine serum total protein. However, there is no study conducted in Ethiopia to compare serum total protein measurement in veterinary settings. Therefore, this study was conducted to compare the serum total protein concentration measurement in cattle and goats obtained by the biuret method and refractometer.ResultsSerum samples from 60 cattle and 60 goats were assayed by both methods and data were analyzed with a paired t-test, Pearson’s correlation, and Bland-Altman plots. There was a strong positive correlation between the total protein values determined with the refractometer and the biuret method in cattle (r = 0.93) and goats (r = 0.97). There were no significant differences (p > 0.05) in the protein values measured with the refractometer and those evaluated with the biuret method in both species. Bland-Altman plots showed that biases indicating the analytic and user error were 8.33% in both species which is below the acceptable total error (< 10%). Thus, refractometer can be used in place of biuret method since it is valid enough to measure serum total protein in cattle and goats.

Path-based and triplification approaches to mapping data into RDF: User behaviours and recommendations

Mapping complex structured data to RDF, e.g. for the creation of linked data, requires a clear understanding of the data, but also a clear understanding of the paradigm used by the mapping tool. We illustrate this with an empirical study comparing two different mapping tools, in particular considering the likelihood of user error. One tool uses path descriptions, e.g. JSONPath or XPath, to access data elements; the other uses a default triplification which can be queried, e.g. with SPARQL. As an example of the former, the study used YARRRML, to map from CSV, JSON and XML to RDF. As an example of the latter, the study used an extension of SPARQL, SPARQL Anything, to query the same data and CONSTRUCT a set of triples. Our study was a qualitative one, based on observing the kinds of errors made by participants using the two tools with identical mapping tasks, and using a grounded approach to categorize these errors. Whilst there are difficulties common to the two tools, there are also difficulties specific to each tool. For each tool, we present recommendations which help ensure that the mapping code is consistent with the data and the desired RDF. We propose future developments to reduce the difficulty users experience with YARRRML and SPARQL Anything. We also make some general recommendations about the future development of mapping tools and techniques. Finally, we propose some research questions for future investigation.

When user error calls for a product redesign: Poverty in the United States

When user error calls for a product redesign: Poverty in the United States

Diagnostic QR Codes

This work describes the development of a revolutionary new class of universal perception-based sensor capable of diagnosing a wide range of diseases, and compatible with low-cost mass production. This sensor takes the form of an array of fluorescent, environmentally sensitive single walled carbon nanotubes (SWCNTs), resembling a conventional two dimensional QR code. Each group of pixels of the QR code is formed from carbon nanotubes with different surface functionalisation and different environmental sensitivity. Addition of an analyte such as serum causes each pixel to change its fluorescence, generating a unique spectral ‘fingerprint’ characteristic for each disease. A machine-learning approach is then trained to identify the disease based on their corresponding fingerprint.The basic principle of this technology has been previously described by the Heller Lab for the detection of ovarian cancer, but exclusively in a microplate-based format which requires extensive liquid handling. Translating this technology into a microarray format offers a number of significant advantages, including easier handling, lower production cost, less training required for operation, simpler read-out system that can be based on mobile phone devices and the ability to simultaneously screen for multiple diseases. In this way, this technology advances beyond the current state of the art of SWCNT-based sensors. In a microarray format, hundreds of nanotube assemblies can be analysed simultaneously.By creating an array of sufficient complexity, we hope to remove the need to tailor an array for a specific disease that act as a universal platform for diagnosis of a range of different diseases. This format also significantly lowers the number of necessary sample handling steps, reducing the potential for user error and the amount of training necessary to employ the sensor. Figure 1

EXCOR membrane motion analyzer (EMMA) to quantify and assess hemodynamic performance of the EXCOR pediatric heart assist device.

Pediatric heart failure is associated with high mortality rates and is a current clinical burden. There is only one FDA approved pediatric VAD, Berlin Heart EXCOR, for treatment. Thrombo-embolic complications are a significant clinical challenge, which can lead to devastating complications such as stroke and impair efficient EXCOR function. Currently, clinicians perform largely qualitative periodic assessment of EXCOR operation by observing the motion of a rapidly moving membrane, which can be prone to human error and can lead to missing out on crucial information. In this study, we design and implement a quantitative early warning system for accurate and quantitative assessment of the EXCOR membrane, named EXCOR Membrane Motion Analyzer (EMMA). Using a combination of image analysis, computer vision and custom designed algorithm, we perform rigorous frame by frame analysis of EXCOR membrane video data. We developed specialized metrics to identify relative smoothness between successive peaks, time between peaks and overall smoothness indicators to quantify and compare between multiple cases. Our results demonstrate that EMMA can successfully identify the motion and wrinkles on each video frame and quantify the smoothness and identify the phases of each cardiac cycle. Moreover, EMMA can obtain the smoothness of each frame and the temporal evolution of membrane smoothness across all image frames for the video sequence. EMMA allows for a fast, accurate, quantitative assessment to be completed and reduces user error. This enables EMMA to be used effectively as an early warning system to rapidly identify device abnormalities.

Algorithm for Reproducible Analysis of Semiconducting 2D Nanomaterials Based on UV‐VIS Spectroscopy

AbstractRapid and reliable analysis of liquid dispersions of 2D materials is essential for fully harnessing their potential, allowing size and quality validation before subsequent processing or device fabrication. Existing UV‐VIS extinction spectroscopy‐based metrics, particularly those related to thickness, have shown promise but rely on manual data processing, which can introduce irreproducibility and user errors. To address this challenge and enable uniform analysis across laboratories, a freely available program is developed for the reproducible analysis of nanosheet dispersions. Specifically, a smoothing routine is applied to the spectral data, takes the second derivative, and use integral areas to find the wavelength of exciton transitions. This program enables rapid measurement of nanosheet concentration, length, and thickness by UV‐VIS spectroscopy and thickness metrics are refined for eight common 2D nanomaterials. The program and methodology are freely available for use and allow metrics for new materials to be implemented easily in the future.

Construction of a model for matching user's linguistic structures to a chat-bot language model

The research object of this work is the linguistic structures of the user when constructing a request to a chatbot with generative artificial intelligence. The study solved the task of improving the communication mediation algorithms of chatbots through the comparison models of linguistic structures by users. Sometimes the user intentionally or due to lack of information forms an inaccurate request. Formally, this is described by logical operations "And" and "And or Not". As a result of the research, a model was built comparing linguistic structures at the input with the information model of the response at the output. The model was based on an approach with recursive creation of an answer. That has made it possible to determine the basic characteristics of the object of the request and form an answer on this basis. Using this approach improved the accuracy of the chatbot response. It also made it possible to consider the linguistic structure of the user through its formalization. The use of logic algebra made it possible to find typical errors of users during dialogs with generative artificial intelligence. A feature of the reported advancement is that the comparison of models of linguistic structures of query formation is carried out through a recurrent algorithm. As a result, it makes it possible to compare the query in such a way as to reduce the absolute error of the primary data by 0.02 % and simplify the process of mathematical calculations. At the same time, the received information becomes more accurate – the number of references increases from 2 to 6 sources. The proposal could be used in practical activities to improve the natural language recognition technologies of users in chatbots with generative artificial intelligence. On this basis, it is possible to devise various applications and services for training and practical activities

ViRgilites: Multilevel Feedforward for Multimodal Interaction in VR

Navigating the interaction landscape of Virtual Reality (VR) and Augmented Reality (AR) presents significant complexities due to the plethora of available input hardware and interaction modalities, compounded by spatially diverse visual interfaces. Such complexities elevate the likelihood of user errors, necessitating frequent backtracking. To address this, we introduce ViRgilites, a virtual guidance framework that delivers multi-level feedforward information covering the available interaction techniques as well as the future possibilities to interact with virtual objects, anticipating the interaction effects and how they fit with the overall user's goal. ViRgilites is engineered to facilitate task execution, empowering users to make informed decisions about action methodologies and alternative courses of action. This paper presents the architecture and functionality of ViRgilites and demonstrates its efficacy through evaluation with a formative user study.

Perception-based constraint solving for sudoku images

We consider the problem of perception-based constraint solving, where part of the problem specification is provided indirectly through an image provided by a user. As a pedagogical example, we use the complete image of a Sudoku grid. While the rules of the puzzle are assumed to be known, the image must be interpreted by a neural network to extract the values in the grid. In this paper, we investigate (1) a hybrid modeling approach combining machine learning and constraint solving for joint inference, knowing that blank cells need to be both predicted as being blank and filled-in to obtain a full solution; (2) the effect of classifier calibration on joint inference; and (3) how to deal with cases where the constraints of the reasoning system are not satisfied. More specifically, in the case of handwritten user errors in the image, a naive approach fails to obtain a feasible solution even if the interpretation is correct. Our framework identifies human mistakes by using a constraint solver and helps the user to correct these mistakes. We evaluate the performance of the proposed techniques on images taken through the Sudoku Assistant Android app, among other datasets. Our experiments show that (1) joint inference can correct classifier mistakes, (2) overall calibration improves the solution quality on all datasets, and (3) estimating and discriminating between user-written and original visual input while reasoning makes for a more robust system, even in the presence of user errors.

Quality Measurement of Online Single Submission (Oss) Information System with Mc Call Method (Case Study of Plut Kumkm)

The NTB Province Micro, Small and Medium Enterprise Cooperative Integrated Business Service Center (PLUT-KUMKM) under the West Nusa Tenggara Province Small and Medium Enterprise Cooperative Service, provides comprehensive assistance to KUMKM to increase production and competitiveness. With seven service areas, PLUT- KUMKM provides effective solutions for business actors. However, in issuing a Business Identification Number (NIB) via the OSS application. The thing is, like in the Business Licensing menu, there is a business development feature. Carrying out business development cannot be completed in one activity in one feature, users must return to the new application menu to continue the business development process and make updates. And user errors often occur such as entering information or not following the correct procedures when filling out forms. The licensing system seeks to be integrated electronically, aiming to cut bureaucracy and improve public services. This research measures the quality of the OSS system for issuing nibs based on the perceptions of 100 gardatransfumi assistants, using the McCall method . A comprehensive evaluation is carried out to identify weaknesses and necessary improvements. Measuring the quality of OSS systems using McCall's theory is important for understanding product quality attributes from the perspective of users and the software itself. The research results will provide in-depth insight into the condition of the website and recommendations for improvement. With the OSS system, the government is trying to make it easier to manage business legality. The NIB issued through OSS becomes the identity of business actors for import and export activities. Through quality measurements, systems, weaknesses and improvements to the NIB issuance process can be identified thereby ensuring better service for business actors.

Smartphone App Designed to Collect Health Information in Older Adults: Usability Study.

Studies evaluating the usability of mobile-phone assessments in older adults are limited. This study aims to identify design-based barriers and facilitators to mobile app survey completion among 2 samples of older adults; those in the Framingham Heart Study and a more diverse sample from a hospital-based setting. We used mixed methods to identify challenging and beneficial features of the mobile app in participants from the electronic Framingham Heart Study (n=15; mean age of 72 years; 6/15, 40% women; 15/15, 100% non-Hispanic and White) and among participants recruited from a hospital-based setting (n=15; mean age of 71 years; 7/15, 47% women; 3/15, 20% Hispanic; and 8/15, 53% non-White). A variety of app-based measures with different response formats were tested, including self-reported surveys, pictorial assessments (to indicate body pain sites), and cognitive testing tasks (eg, Trail Making Test and Stroop). Participants completed each measure using a think-aloud protocol, while being audio- and video-recorded with a qualitative interview conducted at the end of the session. Recordings were coded for participant usability errors by 2 pairs of coders. Participants completed the Mobile App Rating Scale to assess the app (response range 1=inadequate to 5=excellent). In electronic Framingham Heart Study participants, the average total Mobile App Rating Scale score was 7.6 (SD 1.1), with no significant differences in the hospital-based sample. In general, participants were pleased with the app and found it easy to use. A large minority had at least 1 navigational issue, most committed only once. Most older adults did not have difficulty completing the self-reported multiple-choice measures unless it included lengthy instructions but participants had usability issues with the Stroop and Trail Making Test. Our methods and results help guide app development and app-based survey construction for older adults, while also giving consideration to sociodemographic differences.

Product Design Interaction and Experience Based on Virtual Reality Technology

Artificial intelligence involves imitating human thought, consciousness, and other aspects. This is similar to having machine with human brain that can think, produce independently. However, unlike human brain, it has a speed, memory advantage. A virtual reality interactive glove is built using a nine-axis inertial sensor, an artificial intelligence deep learning algorithm. In this research work, Product Design Interaction and Experience Based on Virtual Reality Technology (PDIE-VRT-SCGAN) were proposed. Initially, input gestures data are gathered from the Virtual Reality Experiences (VRE) dataset. The input gestures data is then pre-processed using Multi-Window Savitzky-Golay Filter (MWSGF) to reduce noises, increase overall quality of the gestures data. In order to improving overall user engagement in product design interactions on virtual reality (VR) technology, the pre-processed gestures data are then fed into an adversarial network called a Semi-Cycled Generative Adversarial Network (SCGAN). In general, SCGAN does not express some adaption of optimization strategies for determining optimal parameters to promise exact to improving overall user engagement in product design interactions using VR technology. Therefore, FOX-inspired Optimization (FIO) is proposed to enhance weight parameter of SCGAN method, which precisely improving the user experience in product design interaction. The efficacy of PDIE-VRT-SCGAN method is assessed using a number of performance criteria, including tracking accuracy, frame rate, latency, rendering time, error rate, and user error. The proposed PDIE-VRT-SCGAN method attains 22.36%, 25.42% and 18.17% higher tracking accuracy, 21.26%, 15.42% and 19.27% higher latency, 28.36%, 25.32% and 28.27% higher frame rate compared with existing methods, such as design and implementation of virtual reality interactive product software depend on artificial intelligence deep learning algorithm(DVRI-PS-AI-DL), virtual evaluation system for product designing utilizing virtual reality (VES-PD-VR), and analysis of unsatisfying user experiences with unmet psychological needs for virtual reality exergames utilizing deep learning approach (AUUE-UP-VRE-DLA) respectively.

Point-of-care testing: a critical analysis of the market and future trends

Point-of-care testing (POCT) involves conducting diagnostic tests outside the laboratory. These tests are utilized for their quick and reliable results in detecting chronic diseases and acute infections. We examined the historical market value trends of the POCT industry and projected its future growth. POCT devices offer several advantages, such as portability, no specific storage requirements, and simplicity of use. However, issues such as inaccurate results can reduce demand for POCT compared to traditional laboratory testing alternatives. While the benefits of POCT are clear, it’s important to acknowledge the challenges. The accuracy of POCT devices can be compromised due to factors such as user error, environmental conditions, and limitations in technology. Furthermore, the cost-effectiveness of these devices is often a concern, particularly in resource-limited settings. The regulatory landscape for POCT is also complex and varies by region, which can pose challenges for manufacturers and end-users. Improvements in POCT devices’ sensitivity, specificity, cost, and turnaround time for test results could enhance their utility. Enhancements to a POCT device should be considered if they are economically viable and lead to a significant increase in demand. Our financial analysis of the POCT market revealed a positive growth trend. We identified potential areas for growth that could help the industry progress and expand in line with its projected growth in the coming years. The industry could focus on integrating intelligent technologies into POCT devices and collaborating with the innovative technology sector to increase revenue. It could also develop more sensitive and accurate POCT devices for non-communicable diseases. Another potential area of growth is in diseases that require continuous patient monitoring but where conventional clinical testing is time-consuming. Enhancing the POCT devices used in these areas could revolutionize medical diagnosis and potentially save many lives, provided they meet clinical standards.