Visual Indicators Research Articles

Label-free liquid crystal-based optical detection of norfloxacin using an aptamer recognition probe in soil and lake water.

Norfloxacin (NOX), a broad spectrum fluoroquinolone (FQ) antibiotic, is commonly detected in environmental residues, potentially contributing to biological drug resistance. In this paper, an aptamer recognition probe has been used to develop a label-free liquid crystal-based biosensor for simple and robust optical detection of NOX in aqueous solutions. Stimuli-receptive liquid crystals (LCs) have been employed to report aptamer-target binding events at the LC-aqueous interface. The homeotropic alignment of LCs at the aqueous-LC interface is due to the self-assembly of the cationic surfactant cetyltrimethylammonium bromide (CTAB). In the presence of the negatively charged NOX aptamer, the ordering changes to planar/tilted. On addition of NOX, the aptamer-NOX binding causes redistribution of CTAB at the LC-aqueous interface and the homeotropic orientation is restored. This results in a bright-to-dark optical transition under a polarized optical microscope (POM). This optical transition serves as a visual indicator to mark the presence of NOX. The devised aptasensor demonstrates high specificity with a minimum detection limit of 5 nM (1.596 ppb). Moreover, the application of the developed aptasensor for the detection of NOX in freshwater and soil samples underscores its practical utility in environmental monitoring. This proposed LC-based method offers several advantages over conventional detection techniques for a rapid, feasible and convenient way to detect norfloxacin.

2003–2021年呼伦湖藻华数据集

The presence of cyanobacteria blooms is an intuitive visual indicator of the eutrophication levels in lakes. It is of great importance to precisely assess the extent, coverage, location and other pertinent details of algal blooms and to monitor the eutrophication degree of water in real time, which is essential for ecological restoration and human life quality protection. Using MODIS Aqua satellite image as the primary data source, in the dataset we eliminated the influence of cloud, flare, aquatic vegetation, high turbidity water and other potential factors of interference in the extraction of algal blooms, calculated the algal bloom coverage at the individual pixel level, and finally obtained the data algal blooms in Hulun Lake spanning 19 years, from 2003 to 2021. The accuracy verification process generally met the stipulated requirements. The format of this dataset is * tif, which is compatible with GIS professional software for reading and editing. The dataset can provide data reference for professionals in the field, offering valuable data support for the ecological environment monitoring of Hulun Lake.

A Framework to Identify Rock Glaciers and Model Mountain Permafrost in the Jhelum Basin, Kashmir Himalaya, India

AbstractDeglaciation has led to the transformation of glaciers into rock glaciers in various mountainous regions worldwide. However, the science of permafrost and rock glaciers remains under‐researched in the Himalayan region. This study presents a detailed inventory, dynamics, and permafrost distribution map for the Jhelum basin in the Kashmir Himalaya. The Permafrost Zonation Map (PZM) is created using a Logistic Regression Model based on topographic and climatic variables. High‐resolution satellite images are used to identify rock glaciers as visual indicators. Active and relic rock glaciers are classified based on surface topography and geomorphology. Results reveal 207 rock glaciers in the Jhelum basin, covering ∼50 km2, with over 100 falling into the active category. The PZM aligns well with the global permafrost zonation index map. Slope, aspect, and elevation of rock glaciers are computed using the ASTER Digital Elevation Model. The average elevations range from 3,700 m to 4,550 m, and the average surface slope ranges from 12° to 26°, with maximum slopes from 25° to 65°. Most rock glaciers are oriented toward the south or southeast. Field investigations confirm that these rock glaciers occur in highly elevated regions with steep slopes. This study provides valuable information on the high areal abundance of permafrost in the Himalayan region and suggests increased risks of thawing permafrost due to climate warming in the future. The findings contribute to the understanding of permafrost and rock glaciers, filling knowledge gaps in the Himalayan context.

In Vivo Corneal Confocal Microscopy for Detecting Corneal Nerve Fiber Changes in Patients with Different Types of Optic Neuritis: A Cross-Sectional Study

Purpose Optic neuritis (ON), a demyelinating disease of the central nervous system, is often a precursor manifestation of neuromyelitis optica spectrum disorders (NMOSD) or multiple sclerosis (MS). Reduced corneal nerve fiber counts have been found in patients with NMOSD or MS. This study aimed to observe and compare the corneal subbasal nerve plexus in patients with three types of ON and controls without ON using in vivo corneal confocal microscopy (IVCM). Methods Data were analyzed for 77 eyes of 48 patients with ON, grouped according to seropositivity for anti-aquaporin-4 IgG, myelin oligodendrocyte glycoprotein antibody, or no seropositivity, and 35 healthy eyes in the control group. Corneal parameters were quantified based on IVCM images. Visual function indicators were recorded, following which their correlations with IVCM parameters were analyzed. Results Significant differences in IVCM parameters were detected among the different groups. Reductions in corneal nerve fiber counts were negatively correlated with visual acuity. Corneal nerve fibers were significantly more damaged in the affected eye than in the unaffected eye in patients with ON. Conclusion IVCM revealed corneal nerve fiber loss of varying degrees, depending on the type of ON. This indicates that, although ON primarily affects the central nervous system, peripheral nerves, such as the trigeminal nerve, which innervates the corneal subbasal nerve plexus may also be damaged in affected patients.

Investigation of Chlorophyll Mutations in Gamma Irradiated Naked Barley Genotypes

The consumption of naked barley is significantly increasing as more people become aware of its benefi-cial role as a source of dietary fiber and β-glucan. As a result, breeding programs paid more attention to naked barley. Improvement of yield and quality of naked barley is hindered by the lack of available germplasm. Mutation breeding is an effective tool for generating variation for plant breeding. Chlorophyll mutations are often used as visual indicators in breeding research to determine the optimum mutagen dosage. The purpose of this study was to identify the types and frequency of chlorophyll mutations brought on by different gamma radiation doses in two genotypes of hulless barley and determine the effective dose (ED50) based on the mutation frequency. Seeds of naked barley line YAA7050-14 and cv. Yalin that have been irradiated with doses of 100, 150, 200, and 300 Gy gamma rays delivered by a Cobalt-60 source. Chlorophyll mutations were observed in 8-day-old M2 plants grown under greenhouse conditions. In the M2 plants of cv. Yalin, the highest mutagen frequency was observed at 250 and 300 Gy, while in line YAA7050-14, the highest mutation frequency was found at 300 Gy. The rate of chlorophyll mutation rose in both genotypes as the gamma ray doses increased. The albino type of chlorophyll muta-tion was found in the cv. Yalin at the greatest rate, whereas the xantha type was found in the line YAA7050-14. The most common chlorophyll mutation type was albino, while the least common type was viridis when both genotypes were considered together. Based on the mutation frequency, 250-300 Gy doses could be used to effectively in further research to create mutations in the naked barley genotypes.

Potential Chair-side Test for Gingival Inflammation Screening of Patients With and Without Comorbidities

Objectives: To evaluate a diagnostic kit prototype for salivary total protein (TP), as a complementary clinical examination, for the diagnosis and monitoring of gingival inflammation during periodontal treatment. Materials and Methods: Patients (n=57) were divided into six groups: systemically and Periodontally Healthy (H), Systemically Healthy with Periodontal Disease (PD), Periodontal Health and Diabetes (D), Periodontal Disease and Diabetes (PDD), Periodontal Health and Rheumatoid Arthritis (RA) and Periodontal Disease and Rheumatoid Arthritis (PDRA). Collection of non-stimulated saliva, oral hygiene instructions and basic periodontal treatment were performed. Clinical parameters, gingival index (GI), visible plaque index (PI), probing pocket depth (PPD), bleeding on probing (BOP) and clinical attachment level (CAL), were evaluated at days 0 and 45. Results: Most groups showed clinical improvements with significant changes in H, PD and PDRA for PI, PD and PDRA for PPD and PD for BOP (p<0.05). Total protein reduction was significant only in the PD group (p<0.05). Correlations analysis between salivary TP with BOP or with GI, showed that the salivary test can detect the GI variation (p<0.05). Conclusion: The salivary test has the potential to customize the therapeutic approach, as a complementary clinical examination, serving as a visual indicator for the patient to perceive the clinical signs of their evolution throughout the treatment, and to validate the improvement of the clinical parameters in a practical and accessible quantitative way. Clinical Relevance: The use of saliva for disease monitoring has been consolidated as a versatile diagnostic tool, the results demonstrated its usage to monitor gingival inflammation, a potential visual test to present to patients, and a much less invasive method than the conventional Gingival Index.

Targeting the Highly Conserved 3' Untranslated Region of Iris Severe Mosaic Virus for Sensitive Monitoring of the Disease Prevalence in Iris Production.

Iris severe mosaic virus (ISMV, Potyviridae) can threaten the sustainability of iris production and the marketability of the plants. Effective intervention and control strategies require rapid and early detection of viral infections. The wide range of viral symptoms, from asymptomatic to severe chlorosis of the leaves, renders diagnosis solely based on visual indicators ineffective. A nested PCR-based diagnostic assay was developed for the reliable detection of ISMV in iris leaves and in rhizomes. Considering the genetic variability of ISMV, two primer pairs were designed to detect the highly conserved 3' untranslated region (UTR) of the viral genomic RNA. The specificity of the primer pairs was confirmed against four other potyviruses. The sensitivity of detection was enhanced by one order of magnitude using diluted cDNA and a nested approach. Nested PCR facilitated detecting ISMV on field-grown samples beyond the capabilities of a currently available immunological test and in iris rhizome, which would facilitate ensuring clean stock is planted. This approach dramatically improves the detection threshold of ISMV on potentially low virus titer samples. The study provides a practical, accurate, and sensitive tool for the early detection of a deleterious virus that infects a popular ornamental and landscape plant.

Google Earth Augments Viewing the Spectacle of Ruin in Selected ‘In-Between Places’ of Old Industrial Johannesburg

South Africa is said to have the worst social inequality in the world, and examples of this inequality can be seen in the shack settlements, backyard shacks and hijacked properties in many parts of the city of Johannesburg. These unsafe and neglected ‘interstitial places’ are where the poor live in inadequate housing, squeezed between factory buildings, railway lines and motorways in the city. One of the challenges of capturing visual information about these settlements in these difficult settings is getting access to the areas where photographs can be taken. In Johannesburg, many areas are no longer safe for outsiders to visit. These unsafe, informal and often well-hidden areas can be considered ‘interstitial’ in relation to other areas where middle-income earners live in decent houses in pleasant suburbs with amenities. It is these ‘unsafe’ areas that the author wished to explore as a source of images and impressions for creative works.
 This study takes an autoethnographic approach to exploring three neglected suburbs of Johannesburg, South Africa (Cleveland, Denver and Jeppestown), which all date from soon after the first discovery of gold in 1886. Through this work, the author hoped to make sense of observed changes within the city and the proliferation of informal, survivalist settlements seemingly arising without town planning interventions. Many open areas and dilapidated buildings are now occupied by low-income earners, perhaps because city governance has been overwhelmed by the thousands of work-seeking migrants arriving in the city on an ongoing basis.
 To explore the many visual indicators of poverty in these selected areas of Johannesburg, the author used Google Earth remote sensing images and Google Earth Street View to augment site visits. Google Earth is a valuable research tool, as one can quickly explore marginal areas that are not safe for outsiders to visit. One can also view activities that are not visible from the street – for example, illegal motor repair operations occurring behind high walls. Ethical issuesabound in these acts of anonymous looking at the poor and destitute and finding the picturesque in neglected buildings, dismal living conditions and slums, as well as the privacy and surveillance issues relating to those being observed. This essay will dwell on some of the benefits of the Google Earth virtual globe software, as well as the ethical discomfort that can result when observing people, poverty and informal living places – whether using remote sensing methods and driving around these areas with a camera, or using the images and perceptions gained for personal use as a source of inspiration for art making and fiction writing.

Relationship of knob morphometric analysis with production performance and meat quality in Yangzhou goose (Anser cygnoides).

The development of the knob in Chinese geese (Anser cygnodies) is an outcome of extensive and prolonged selection and breeding. The knob serves not only as a visual indicator of sexual maturity in geese but also holds significance as a crucial packaging trait that attracts attention of consumers attentions, who tend to distinctly prefer geese with larger knobs. Consequently, investigating the formation of the knob holds practical value, as it will help achieving external traits aligned with consumers' preferences. To understand the relationship between knob size, production efficiency, and meat quality in Yangzhou geese, we examined histological and anatomical characteristics in 500- and 120-day-old geese with large and small knobs. Notably, knob size had a pronounced impact on key anatomical and structural parameters, such as chest depth, leg muscle water-binding capacity, and insoluble collagen composition in Yangzhou geese (p < 0.05). In addition, we measured testosterone and estrogen levels in male and female geese, respectively, as well as growth hormone, and found that birds of both sexes with a large knob had higher sex and growth hormone levels in the body. This study established a fundamental theoretical basis for advancing the enhancement of goose knob traits.

Justification of the application of Raman-fluorescence diagnostics to assess dental status of the oral cavity

Purpose: To assess the influence of visibility, grayness and lighting conditions of the dentist’s workplace at the indicators of oral cavity homeostasis as well as to justify the application of digital Raman-fluorescence diagnostics for studying dental status of the oral cavity so as to exclude the subjective factor in visual indicators. Materials and methods. 90 patients took part in the trial. Group 1 (controls): participants with the controlled hygiene of their oral cavity and without pronounced dental pathologies; Group 2 (studied): 2A – patients with uncontrolled hygiene and concomitant unsatisfactory hygienic condition of their oral cavity, 2B – patients with controlled hygiene and previous unsatisfactory hygienic condition of their oral cavity. There were 30 patients in each group, and all of them had carious lesions. Patients of Groups 1 and 2A cleaned their teeth by the generally accepted scheme. In Group 2B, patients cleaned their teeth under control, and the procedure duration had been calculated individually by laser fluorescence diagnostics. In both groups, the degree of hard tissues mineralization was determined with the Raman diagnostics. Patients from the studied group were prescribed remineralisation therapy. Visual methods and Raman-fluorescence diagnostics were used to assess dental status of the oral cavity. Results and discussion. There was a significant improvement in all indicators in Group 2B compared to Group 2A; no changes were observed in the control group. Errors in the visual measurement of oral cavity dental status can range from 200 to 400%. To eliminate disadvantages of the visual assessment of the oral cavity, Raman-fluorescence diagnostics has to be applied, the results of which do not depend on color, grayness and lighting of the examined object. Conclusion. To eliminate disadvantages of the visual method for assessing the oral cavity condition, Raman-fluorescent diagnostics, which does not depend on color, grayness and lighting of the examined object, has to be applied. The Raman-fluorescent and visual diagnostics allow to objectively assess dental status of the oral cavity.

Visual Indicators Representing Avatars' Authenticity in Social Virtual Reality and Their Impacts on Perceived Trustworthiness.

Photorealistic avatars show great potential in social VR and VR collaboration. However, identity and privacy issues are threatening avatars' authenticity in social VR. In addition to the necessary authentication and protection, effective solutions are needed to convey avatars' authenticity status to users and thereby enhance the overall trustworthiness. We designed several visual indicators (VIs) using static or dynamic visual effects on photorealistic avatars and evaluated their effectiveness in visualizing avatars' authenticity status. In this study we explored suitable attributes and designs for conveying the authenticity of photorealistic avatars and influencing their perceived trustworthiness. Furthermore, we investigated how different interactivity levels influence their effectiveness (the avatar was either presented in a static image, an animated video clip, or an immersive virtual environment). Our findings showed that using a full name can increase trust, while most other VIs could decrease users' trust. We also found that interactivity levels significantly impacted users' trust and the effectiveness of VIs. Based on our results, we developed design guidelines for visual indicators as effective tools to convey authenticity, as a first step towards the improvement of trustworthiness in social VR with identity management.

Assessment and optimization of tunnel lighting quality based on drivers' visual comfort: From methodology to application

Drivers' visual comfort is directly affected by tunnel lighting quality. Currently, many built tunnels have poor-quality lighting with varying degrees of visual interference, which may lead to visual discomfort and traffic accidents. To solve this problem, this study proposes a method to assess and optimize the tunnel lighting quality, aiming to evaluate the lighting quality from the perspective of drivers' visual comfort and improve the lighting effect in each lighting zone of the tunnel. First, the visual characteristics of drivers and quantitative relationship between visual comfort and tunnel lighting environment are derived through field tests and mathematical statistics. Second, the comfort range based on visual characteristic indicators (VCIs) is obtained via a comprehensive analysis of objective physiological responses and subjective questionnaire survey results of drivers, which is used as the comfort criteria to assess the tunnel lighting quality. Subsequently, the effects of luminance, luminance uniformity, and flicker frequency on drivers' visual comfort are considered, and a lighting optimization model based on the adaptive penalty function particle swarm optimization algorithm is established by combining comfort constraints and energy-saving objectives. Finally, driving simulation experiments are performed using virtual reality technology, which verify the effectiveness of the assessment and optimization methods. The results show that drivers' visual comfort in the tunnel threshold zone increases with an increase in the luminance reduction coefficient and decrease in the vehicle speed, and drivers' visual comfort in the tunnel interior zone increases with an increase in the road surface illuminance and visibility. The comfort range of the VCIs classify the tunnel lighting quality into four evaluation levels. Therefore, the proposed method can accurately and quantitatively assess the comfort of the tunnel lighting environment, improving drivers' visual comfort in the tunnel by 48.08 %, while saving 12.03 % of energy.

Detection of interacting variables for generalized linear models via neural networks

The quality of generalized linear models (GLMs), frequently used by insurance companies, depends on the choice of interacting variables. The search for interactions is time-consuming, especially for data sets with a large number of variables, depends much on expert judgement of actuaries, and often relies on visual performance indicators. Therefore, we present an approach to automating the process of finding interactions that should be added to GLMs to improve their predictive power. Our approach relies on neural networks and a model-specific interaction detection method, which is computationally faster than the traditionally used methods like Friedman’s H-Statistic or SHAP values. In numerical studies, we provide the results of our approach on artificially generated data as well as open-source data.

Assessing the suitability of lakes and reservoirs for recreation using Landsat 8

Water clarity has long been used as a visual indicator of the condition of water quality. The clarity of waters is generally valued for esthetic and recreational purposes. Water clarity is often assessed using a Secchi disk attached to a measured line and lowered to a depth where it can be no longer seen. We have applied an approach which uses atmospherically corrected Landsat 8 data to estimate the water clarity in freshwater bodies by using the quasi-analytical algorithm (QAA) and Contrast Theory to predict Secchi depths for more than 270 lakes and reservoirs across the continental US. We found that incorporating Landsat 8 spectral data into methodologies created to retrieve the inherent optical properties (IOP) of coastal waters was effective at predicting in situ measures of the clarity of inland water bodies. The predicted Secchi depths were used to evaluate the recreational suitability for swimming and recreation using an assessment framework developed from public perception of water clarity. Results showed approximately 54% of the water bodies in our dataset were classified as “marginally suitable to suitable” with approximately 31% classed as “eminently suitable” and approximately 15% classed as “totally unsuitable–unsuitable”. The implications are that satellites engineered for terrestrial applications can be successfully used with traditional ocean color algorithms and methods to measure the water quality of freshwater environments. Furthermore, operational land-based satellite sensors have the temporal repeat cycles, spectral resolution, wavebands, and signal-to-noise ratios to be repurposed to monitor water quality for public use and trophic status of complex inland waters.

SIT6: Indirect touch-based object manipulation for DeskVR

Virtual reality (VR) has the potential to significantly boost productivity in professional settings, especially those that can benefit from immersive environments that allow a better and more thorough way of visualizing information. However, the physical demands of mid-air movements make it difficult to use VR for extended periods. DeskVR offers a solution that allows users to engage in VR while seated at a desk, minimizing physical exhaustion. However, developing appropriate motion techniques for this context is challenging due to limited mobility and space constraints. This work focuses on object manipulation techniques, exploring touch-based and mid-air-based approaches to design a suitable solution for DeskVR, hypothesizing that touch-based object manipulation techniques could be as effective as mid-air object manipulation in a DeskVR scenario while less physically demanding. Thus, we propose Scaled Indirect Touch 6-DOF (SIT6), an indirect touch-based object manipulation technique incorporating scaled input mapping to address precision and out-of-reach manipulation issues. The implementation of our solution consists of a state machine with error-handling mechanisms and visual indicators to enhance interaction. User experiments were conducted to compare the SIT6 technique with a baseline mid-air approach, revealing comparable effectiveness while demanding less physical exertion. These results validated our hypothesis and established SIT6 as a viable option for object manipulation in DeskVR scenarios.

Predictive Mental Workload Modeling Methodology for Single-Pilot Operations System Design

Predictive mental workload model is an important tool for evaluating early single-pilot operations (SPO) system design and can be used to explore the impact of different function allocation decisions before prototype or simulator implementation. To build this model, this paper proposes a methodology based on task analysis. Firstly, it selects the approach and landing scenario of the current two-pilot operations (TCO) and completes the task description of the TCO using the hierarchical task analysis. Secondly, it identifies the function allocation requirements for the transition from TCO to SPO using the work domain analysis and proposes the original function allocation decisions based on the SPO’s system framework. Finally, it creates the predictive mental workload model for evaluating different SPO system design options based on temporal network and multiple resource theory. The researchers use the created model to evaluate the original function allocation decisions and find that the designed SPO system has instantaneous workload values that exceed the upper limit at multiple time points. By analyzing the causes of these problems, the researchers introduce audible warnings and visual indicators to the SPO system to improve design decisions and evaluate these decisions. The results show that the continuous workload profile and overall average workload of the redesigned SPO system are better than the current TCO system, and also prove that the predictive mental workload model can be well applied to evaluate the system design of early SPO.

Three-dimensional lumbar spine generation using variational autoencoder.

The disease analysis of the lumbar spine often requires a large number of three-dimensional (3D) models. Currently, there is a lack of 3D model of the lumbar spine for research, especially for the diseases such as scoliosis where it is difficult to collect sufficient data in a short period of time. To solve this problem, we develop an end-to-end network based on 3D variational autoencoder for randomly generating 3D lumbar spine model. In this network, the dual path encoder structure is used to fit two individual variables, i.e., mean and variance. Spatial coordinate attention modules are added to the encoder to improve the learning ability of the network to the 3D spatial structure of the lumbar spine. To enhance the power of the network to reconstruct the lumbar spine, a regularization loss is added to constrain the distribution loss. Additionally, Gaussian noise layers are added to the decoder to improve the authenticity and diversity of generated model. The experiments were conducted on the data of the entire lumbar spine and the individual lumbar vertebra, respectively. The results showed that the voxel intersection over union was 0.588 and 0.684, the voxel Dice coefficient was 0.739 and 0.811, the average surface distance was 0.807 and 1.189, and the Hausdorff distance was 2.615 and 3.710, for the entire lumbar spine and individual lumbar vertebra, respectively. The developed approach is comparable to the most commonly used model generation method of statistical shape model (SSM) in both visual and objective indicators, while the developed approach does not require the landmarks that is needed in the SSM method. Therefore, this fully automatic method can be easily used for population-based modeling of the lumbar spine which has the potential to be a powerful clinical tool.

An Analytical Method for Determination of Total Iron in Pharmaceuticalgrade Intravenous Iron Colloidal Complexes by Redox-Potentiometry.

Iron carbohydrate complexes are colloidal dispersions made up of polynuclear Fe(III)-oxyhydroxide cores surrounded by a carbohydrate shell that stabilizes the complex in iron colloidal formulations. The current study provides an improved method that is precise, accurate, and linear for quantifying total iron in most Iron Carbohydrate Colloid Drug Products. Redox iodometry with a potentiometric determination is used to evaluate total iron in intravenous formulations. The visual indicator approach is more prone to fluctuations at endpoint calculations. Hence, the voltage potential approach is widely accepted as it is more accurate and sensitive. It tracks the actual change in activity that coincides with the equivalence point that is finally considered an endpoint. The principle is based on the idea that ferric iron in formulation reduces to ferrous iron in the presence of the iodide, which oxidizes to iodine. The released iodine is titrated using sodium thiosulfate. The proposed method was precise, with %RSD (relative standard deviation) not more than 1. The method was linear between 80% and 120%, with a linear regression of 0.999. The percent recovery ranged from 98.20 to 99.98 for the concentration ranges of 80-120. The method's robustness was checked by various analysts using different reagent grades. The proposed potentiometric determination method was precise, accurate, linear, and sensitive. The method was successfully validated, and the total iron content determined for commercial batches agrees with the iron claim on the label. Therefore, this method can be adapted widely for total iron content determination in any Intravenous formulation currently available on the market. The proposed method is more accessible at the Quality Control facilities on an industrial scale.

Analisis Gaya Belajar Siswa Kelas V Pada Pembelajaran Bahasa Inggris di SD Negeri 106156 Klumpang, Kec Hamparan Perak

The aim of this research is to analyze students' learning styles in learning English in class V of SD Negeri 106156 Klumpang, Kec. Silver Overlay 2021/2022 academic year. This research is a descriptive research. The population in this study were all class V students of SD Negeri 106156 Klumpang, Kec. Silver Expanse with a total of 48 students. The technique used in sampling is total sampling, namely the technique of determining the sample when all members of the population are used as samples. The data collection techniques for student learning styles in learning English in class V SD 106156 Klumpang, Kec. Hamparan Perak uses a Likert scale questionnaire consisting of 15 statements that have been validated by expert lecturers. The results showed that the analysis of learning styles on visual learning style indicators was in the very dominant category of students with an average percentage of 75.10% and an average value of 15.02. In the auditory learning style indicator, students are very dominant in the category with an average percentage of 75.93% and an average score of 15.19. In the kinesthetic learning style indicator, students are in the dominant category with an average percentage of 64.89% and an average score of 12.98. So it can be analyzed that students' learning styles in learning English in class V of SD Negeri 106156 Klumpang, Kec. Silver Overlay is the more dominant auditory learning style because it obtains higher average scores and percentages than the visual and kinesthetic learning styles.

Predicting student disengagement: Harnessing visual cues for intelligent tutoring systems

Intelligent tutoring systems have the potential to enhance the learning experience for children, but it is crucial to detect and address early signs of disengagement to ensure effective learning. In this paper, we propose a method that utilizes visual features from a tablet tutor's user-facing camera to predict whether a student will complete the current activity or disengage from it. Unlike previous approaches that relied on tutor-specific features, our method leverages visual cues, making it applicable to various tutoring systems. We employ a deep learning approach based on a Long Short Term Memory (LSTM) model with a target replication loss function for prediction. Our model is trained and tested on screen capture videos of children using a tablet tutor for learning basic Swahili literacy and numeracy in Tanzania. With 40% of the activity remaining, our model achieves a balanced-class size prediction accuracy of 73.3%. Furthermore, we analyze the variation in prediction accuracy across different tutor activities, revealing two distinct causes of disengagement. The findings indicate that our model can not only predict disengagement but also identify visual indicators of negative affective states that may not lead to non-completion of the task. This work contributes to the automated detection of early signs of disengagement, which can aid in improving tutoring systems and guiding pedagogical decisions in real-time.