Subjective Tests Research Articles

An Unsupervised Error Detection Methodology for Detecting Mislabels in Healthcare Analytics.

Medical datasets may be imbalanced and contain errors due to subjective test results and clinical variability. The poor quality of original data affects classification accuracy and reliability. Hence, detecting abnormal samples in the dataset can help clinicians make better decisions. In this study, we propose an unsupervised error detection method using patterns discovered by the Pattern Discovery and Disentanglement (PDD) model, developed in our earlier work. Applied to the large data, the eICU Collaborative Research Database for sepsis risk assessment, the proposed algorithm can effectively discover statistically significant association patterns, generate an interpretable knowledge base for interpretability, cluster samples in an unsupervised learning manner, and detect abnormal samples from the dataset. As shown in the experimental result, our method outperformed K-Means by 38% on the full dataset and 47% on the reduced dataset for unsupervised clustering. Multiple supervised classifiers improve accuracy by an average of 4% after removing abnormal samples by the proposed error detection approach. Therefore, the proposed algorithm provides a robust and practical solution for unsupervised clustering and error detection in healthcare data.

Eye Tracking-Based Characterization of Fixations during Reading in Children with Neurodevelopmental Disorders.

An efficient mode of evaluation for eye movements is the use of objective eye tracking systems combined with subjective tests (NSUCO or DEM), which are easily applicable across all age groups and in eye care clinical settings. The objective of this study was to characterize fixations during reading in two groups: a group of children with neurodevelopmental disorders (NDDG, 24 children, age: 6-12 years) and a group of children with oculomotor anomalies but without NDD (OAG, 24 children, age: 6-12 years). The results obtained were compared with those from a control group (CG, 20 children, age: 6-12 years). Specifically, the outcomes obtained with two subjective score systems, the Northeastern State University College of Optometry's Oculomotor (NSUCO) test and the Developmental Eye Movement (DEM) test, were compared with the objective analysis obtained through a commercially available eye tracker (Tobii Eye X, Tobii, Stockholm, Sweden). Specialized analysis software, namely Clinical Eye Tracker 2020 (Thomson Software Solutions, Welham Green, UK), was used. It was found that children with NDD had impaired oculomotor skills. A higher number of regressions, more fixations, and longer durations of fixations appear to be characteristic signs of this population group. Additionally, children with NDD took longer to complete the DEM test, as well as exhibiting more errors. The use of objective videoculographic systems for eye tracking and subjective tests like the NSUCO or DEM are good tools to assess saccadic movements, allowing the detection of oculomotor abnormalities in children with NDD.

Subjective tests of speaker recognition for selected voice disguise techniques

Subjective tests of speaker recognition for selected voice disguise techniques

JACQLQ subjective symptom questionnaire score and clinical test results for patients with allergic conjunctival disease

We investigated the relationship between subjective symptoms and objective findings in patients with allergic conjunctival diseases (ACD) and test results for tear total IgE (t-tIgE), conjunctival eosinophils (c-Eo), serum total IgE (s-tIgE), serum-antigen specific IgE (s-sIgE), and serum eosinophils (s-Eo). Subjective symptoms and objective findings of patients with ACD were evaluated using Japanese Allergic Conjunctival Disease Quality of Life Questionnaire (JACQLQ), which described disability score and emotional score written by patient and clinical findings score written by ophthalmologist. We investigated the relationship between questionnaire scores and laboratory data for t-tIgE, c-Eo, s-tIgE, s-sIgE, and s-Eo. Scores of impediments to life and of moods were highest in vernal keratoconjunctivitis among ACD. Cases with positive pollen-sIgE showed significantly more nasal symptom score than those with negative pollen-sIgE (P < 0.05). Cases with positive t-tIgE or c-Eo showed significantly more objective symptoms’ JACQLQ score than those with negative t-tIgE or c-Eo (P < 0.05), respectively. Cases positive for house dust/mite-sIgE, showed significantly more objective symptoms’ JACQLQ score than those without for house dust/mite-sIgE (P < 0.05). These results indicate that ACD could be analyzed more accurately by the combination of JACQLQ and laboratory data.

Assessment of objective visual function following idebenone administration in patients with leber hereditary optic neuropathy.

To objectively assess visual function in Leber's Hereditary Optic Neuropathy (LHON) patients; this study evaluated pre- and post-idebenone treatment changes in primary visual cortical (V1) responses using functional magnetic resonance imaging (fMRI), given the challenges in subjective testing due to central retinal ganglion cell damage. A descriptive study involving four confirmed LHON patients. Four patients received 900 mg/day of oral idebenone for 24 weeks. Baseline and post-treatment visual acuity, visual fields, and BOLD fMRI responses while passively viewed drifting contrast pattern visual stimuli were compared with self-reported symptoms. Post-idebenone, one patient showed positive trends across subjective tests, reported symptoms, and fMRI. Two patients had stable symptoms and fMRI responses; one improved on subjective tests, and another worsened slightly. Another patient improved in visual field tests despite worsening symptoms and fMRI trends. fMRI may offer a valuable objective measure of visual functions in LHON and appears to be more relevant in assessing symptoms. Further research with more participants is needed to ascertain fMRI's role in developing objective visual assessments and treatment evaluation.

Evaluasi Program Pembelajaran Kurikulum Merdeka di Ma’had Utsman bin ‘Affan Binbaz 25 Jambi

This research aims to evaluate the implementation of the Merdeka Curriculum learning program at Ma'had Utsman bin 'Affan BINBAZ 25 Jambi. The aspects evaluated include: planning, implementation, and learning evaluation. The method used in this research is descriptive qualitative. The subjects in this research were 4 teachers, Ma'had Utsman bin 'Affan BINBAZ 25 Jambi, and 4 students. The data were analyzed using critical analysis techniques, with the Miles and Huberman model through data reduction, data presentation, and data verification. The results of the research show that the evaluation process for the Merdeka Curriculum Learning Program at Ma'had Utsman bin 'Affan BINBAZ 25 Jambi has not been implemented optimally. This can be seen from educators who 100% have not made teaching modules in the learning process, 50% of teachers who do not provide teaching materials in the form of learning media, 75% of teachers who do not create small groups in learning, and 75% of teachers who use objective and subjective tests.

Improved Video-Based Point Cloud Compression via Segmentation.

A point cloud is a representation of objects or scenes utilising unordered points comprising 3D positions and attributes. The ability of point clouds to mimic natural forms has gained significant attention from diverse applied fields, such as virtual reality and augmented reality. However, the point cloud, especially those representing dynamic scenes or objects in motion, must be compressed efficiently due to its huge data volume. The latest video-based point cloud compression (V-PCC) standard for dynamic point clouds divides the 3D point cloud into many patches using computationally expensive normal estimation, segmentation, and refinement. The patches are projected onto a 2D plane to apply existing video coding techniques. This process often results in losing proximity information and some original points. This loss induces artefacts that adversely affect user perception. The proposed method segments dynamic point clouds based on shape similarity and occlusion before patch generation. This segmentation strategy helps maintain the points' proximity and retain more original points by exploiting the density and occlusion of the points. The experimental results establish that the proposed method significantly outperforms the V-PCC standard and other relevant methods regarding rate-distortion performance and subjective quality testing for both geometric and texture data of several benchmark video sequences.

The “objective test” and the downstream market presence requirement in Big Data access cases under the essential facilities doctrine - a critical assessment

One possible way to gain access to competitively relevant sets of Big Data is toapply the essential facilities doctrine. However, the European Commission and theEuropean Court of Justice have established several different criteria for applying thedoctrine. Since neither institution has yet applied the doctrine in Big Data accesscases, it is not clear which of the criteria applies in such positions. This paper attemptsto analyze the impact of the “objective test” and the requirement that the controllingcompany be active in the downstream market (which are included in all assessmentcriteria) in Big Data access cases, with the goal of answering the research question,“Do the application of the “objective test” and the requirement that the controllingcompany be active in the downstream market impede the effectiveness of the doctrinein Big Data access cases under EU competition law, and if so, how should they bechanged?” The conclusion is that in Big Data access cases, the “objective test” shouldbe mitigated and replaced by the “subjective test” or the “average company test” andthe requirement that the controlling company be active in the downstream marketshould be discarded altogether in order for the doctrine to be an effective tool foraccessing competitively relevant sets of Big Data.

Multimodal perception of digital protective materials

The online clothing industry has gained popularity among consumers, and the perception of materials and equipment plays a crucial role in their purchasing decisions. Therefore, accurately representing their appearance in real-time is essential. This study aimed to subjectively evaluate 20 protective textile materials by translating their tactile characteristics into virtual prototypes. This was accomplished by scanning physical materials with an x-Tex scanner and processing them in KeyShot rendering software. Consequently, four scenarios featuring digital materials were created: S1-image, S2-video animation, S3-3D object, and S4-physical materials. Digital visual subjective evaluations were conducted for sensory analysis. Participants were asked to assess four visual and seven tactile characteristics using a seven-point Likert scale. Statistical analysis was employed to evaluate the sensory data collected through subjective testing. The results indicated that agreement values for the four scenarios ranged from 1.25 to 7.0, as illustrated in boxplot diagrams representing the subjects' agreement with the perceptual attributes. Pairwise comparisons of the S4-S1, S4-S2, and S4-S3 scenarios concerning the difference in means revealed that attributes FR with values of 0.045 (S1), RM with values of 0.063 (S1), CR with values of 0.028 (S1), CR with values of 0.039 (S2), and 0.052 (S3) are closely aligned with the actual values, as the values obtained from these scenarios closely approximate 0. In contrast, the values of the remaining attributes were close to 1, indicating the difficulty of translating these attributes into digital format and achieving accurate perception. Assessing textile material properties through digital images remains a challenging task that requires in-depth subjective analysis.

Ambisonics’ setup quality assessment through measurements and computations based on ITD and ILD functions using subbands and a Gammatone Filter Bank

Poznan Supercomputing and Networking Center (PSNC) developed an ambisonic installation and workflow as part of audio-visual 8K VR 360° immersive media experiments. This work aimed to investigate the quality of performance of the PSNC setup through both subjective tests as well as simulations providing objective parameters of interaural characteristics in a real-life scenario of PSNC studio. For the objective part, an algorithm for angle estimation has been proposed and computations were performed.

Non-intrusive method for audio quality assessment of lossy-compressed music recordings using convolutional neural networks

Most of the existing algorithms for the objective audio quality assessment are intrusive, as they require access both to an unimpaired reference recording and an evaluated signal. This feature excludes them from many practical applications. In this paper, we introduce a non-intrusive audio quality assessment method. The proposed method is intended to account for audio artefacts arising from the lossy compression of music signals. During its development, 250 high-quality uncompressed music recordings were collated. They were subsequently processed using the selection of five popular audio codecs, resulting in the repository of 13,000 audio excerpts representing various levels of audio quality. The proposed non-intrusive method was trained with the data obtained employing a well-established intrusive model (ViSQOL v3). Next, the performance of the trained model was evaluated utilizing the quality scores obtained in the subjective listening tests undertaken remotely over the Internet. The listening tests were carried out in compliance with the MUSHRA recommendation (ITU-R BS.1534-3). In this study, the following three convolutional neural networks were compared: (1) a model employing 1D convolutional filters, (2) an Inception-based model, and (3) a VGG-based model. The last-mentioned model outperformed the model employing 1D convolutional filters in terms of predicting the scores from the listening tests, reaching a correlation value of 0.893. The performance of the Inceptionbased model was similar to that of the VGG-based model. Moreover, the VGG-based model outperformed the method employing a stacked gated-recurrent-unit-based deep learning framework, recently introduced by Mumtaz et al. (2022).

Shift Work System Analysis of Store Employee Fatigue Using the Subjective Self Rating Test and Independent Sample T Test Methods (Case of Sports Station Plaza Surabaya)

This study analyzed the initial symptoms of fatigue and measured the level of fatigue with the subjective self rating test method as the subjective method, the CVL (Cardiovascular Load) method as the objective, and the independent sample t test at the Plaza Surabaya sports station. shop. Shift work in the workshop has the potential to pose health risks in the form of fatigue due to differences in physical workload experienced in each shift. Sports Station Plaza Surabaya outlets face work activity problems that are at risk of ergonomics, with several worker complaints due to work shifts that only do rotating shifts per month and unclear employee jobdesk placements. The Subjective Self Rating Test method is used to identify early symptoms of employee fatigue by filling out a questionnaire, the CVL method is used to measure pulse to obtain the level of physical workload fatigue experienced by employees. While the independent sample t test test is to find out whether there is a significant difference in the level of shift fatigue at the Sports Station Plaza Surabaya store. get the highest classification value in shift 1, for the independent t test test method get a significance value of 0.01 which means there is a significant difference in the level of worker fatigue in shift 1 and shift 2.

Randomized trial comparing the effects of a 3D head-up system and microscope eyepiece-assisted simulated vitrectomy with intraocular illumination on the ocular surface of an operator

BackgroundTo compare the effects of a 3D head-up system and microscope eyepiece-assisted simulated vitrectomy intraocular illumination on the ocular surface of an operator.MethodsThis was a prospective randomized controlled study. According to the application system, thirty ophthalmic operators (60 eyes) were randomly divided into 3D and eyepiece groups. Under different intensities of intraocular illumination, operators in both groups viewed the fundus model through a 3D display screen or microscopic eyepiece for 2 h. Objective examinations and a subjective symptom questionnaire were used immediately after the test to evaluate the ocular surface of the operators. Objective examinations included nonintrusion tear meniscus height (NIKTMH), nonintrusion break-up time (NIKBUT), and bulbar redness and strip meniscometry tube (SMTube) measurements. Statistical analyses were performed by using SPSS 26.0 software.ResultsAfter the test, the NIKTMH, NIKBUT and SMTube measurements decreased; however, the degree of change varied among the groups of different systems. The differences between the 3D group and the eyepiece group in NIKTMH measurements, SMTube measurements, subjective symptom scores (eye dryness, difficulty focusing, and cervical pain), and light intensity reaching the ocular surface of the operators were statistically significant (P < 0.05). All of the objective and subjective tests showed that the 3D group had fewer effects on the NIKTMH and SMTube measurements, and the subjective comfort of the 3D group was greater.ConclusionFor both 3D screens and eyepieces, simulated vitrectomy with intraocular illumination for two hours can lead to discomfort and abnormalities in the operator’s ocular surface; however, these abnormalities are less severe in the 3D group.Trial registrationThis trial was registered on December 22, 2022, at the Chinese Clinical Trials Registry with NO. ChiCTR2200066989.

RealSinger: Ultra-realistic singing voice generation via stochastic differential equations

Synthesizing high-quality singing voice from music score is a challenging problem in music generation and has many practical applications. Samples generated by existing singing voice synthesis (SVS) systems can roughly reflect the lyrics, pitch and duration in a given score, but they fail to contain necessary details. In this paper, based on stochastic differential equations (SDE) we propose RealSinger to generate 22.05kHz ultra-realistic singing voice conditioned on a music score. Our RealSinger learns to find the stochastic process path from a source of white noise to the target singing voice manifold under the conditional music score, allowing to sing the music score while maintaining the local voice details of the target singer. During training, our model learns to accurately predict the direction of movement in the ambient Euclidean space onto the low-dimensional singing voice manifold. RealSinger’s framework is very flexible. It can either generate intermediate feature representations of the singing voice, such as mel-spectrogram, or directly generate the final waveform, as in the end-to-end style which rectify defects and accumulation errors introduced by two-stage connected singing synthesis systems. An extensive subjective and objective test on benchmark datasets shows significant gains in perceptual quality using RealSinger. The mean opinion scores (MOS) obtained with RealSinger are closer to those of the human singer’s original high-fidelity singing voice than to those obtained with any state-of-the-art method. Audio samples are available at https://realsinger.github.io/.

Development of a Subjective Visual Vertical Test System Using a Smartphone With Virtual Reality Goggles for Screening of Otolithic Dysfunction: Observational Study.

The subjective visual vertical (SVV) test can evaluate otolith function and spatial awareness and is performed in dedicated vertigo centers using specialized equipment; however, it is not otherwise widely used because of the specific equipment and space requirements. An SVV test smartphone app was developed to easily perform assessments in outpatient facilities. This study aimed to verify whether the SVV test smartphone app with commercially available virtual reality goggles can be used in a clinical setting. The reference range was calculated for 15 healthy participants. We included 14 adult patients with unilateral vestibular neuritis, sudden sensorineural hearing loss with vertigo, and Meniere disease and investigated the correlation between the SVV test results and vestibular evoked myogenic potential (VEMP) results. The SVV reference range of healthy participants for the sitting front-facing position was small, ranging from -2.6º to 2.3º. Among the 14 patients, 6 (43%) exceeded the reference range for healthy participants. The SVV of patients with vestibular neuritis and sudden sensorineural hearing loss tended to deviate to the affected side. A total of 9 (64%) had abnormal cervical VEMP (cVEMP) values and 6 (43%) had abnormal ocular VEMP (oVEMP) values. No significant difference was found between the presence or absence of abnormal SVV values and the presence or absence of abnormal cVEMP and oVEMP values; however, the odds ratios (ORs) suggested a higher likelihood of abnormal SVV values among those with abnormal cVEMP and oVEMP responses (OR 2.40, 95% CI 0.18-32.88; P>.99; and OR 2, 95% CI 0.90-4.45; P=.46, respectively). The SVV app can be used anywhere and in a short period while reducing directional bias by using virtual reality goggles, thus making it highly versatile and useful as a practical otolith dysfunction screening tool.

Does pro-environmental consumption contribute to subjective well-being? Empirical evidence from Italy

This paper examines the association between pro-environmental consumption and subjective well-being and tests whether this type of decision could be explained as a utility-maximizing choice under welfare economics, or it is subject to systematic deviations from rational choice. The literature provides evidence for positive and significant effects of pro-environmental consumption on subjective well-being; however, studies describing this relationship and drawing comparisons based on specific dimensions are limited. Here we try to fill the gap by proposing two composite indicators, representing preferences for pro-environmental behaviour in different dimensions. The indicator “proactive behaviour” encompasses the consumption of products with better environmental efficiency, while the indicator “avoidance behaviour” pertains to sustainable choices that involve avoiding – or less frequently engaging in – consumption decisions with negative ecological externalities. The findings, based on data from the Aspects of Daily Life survey conducted in Italy by ISTAT, provide that the former has a stronger effect on subjective well-being compared to the latter. Furthermore, the analysis reveals that environmental satisfaction negatively moderates the relationship between sustainable consumption and life satisfaction.

Clinical characteristics and otolith dysfunction in presbyvestibulopathy: A retrospective cross-sectional analysis

ObjectiveThe Bárány Society recently established diagnostic criteria for presbyvestibulopathy, an age-related bilateral vestibular impairments in older individuals. Drawing upon a cross-sectional database, this study delves into the demographic and clinical features of presbyvestibulopathy patients and investigates the implications of otolith dysfunction. MethodsThe study retrospectively analyzed 1218 patients aged 60 years or older who visited the tertiary dizziness clinic in 2020, due to symptoms of dizziness or instability. By reviewing medical records, we gathered clinical information and laboratory vestibular test results, such as cervical and ocular vestibular evoked myogenic potentials, and subjective visual vertical. ResultsOut of 1218 patients aged 60 and above who reported dizziness or unsteadiness, 33 patients (2.7 %, with an average age of 74.2 ± 9.2 years) were diagnosed with presbyvestibulopathy. Deficiencies in horizontal angular vestibulo-ocular reflex were found in caloric tests (75 %), video head impulse tests (51.7 %), and rotatory chair tests (47.8 %), respectively. Otolith dysfunction was also observed, as shown by abnormal ocular and cervical vestibular evoked myogenic potentials in 62.96 % and 51.85 % of patients, and abnormal subjective visual vertical in 45.8 % of the cases. ConclusionsAmong elderly patients experiencing consistent dizziness or instability, the incidence of presbyvestibulopathy was approximately 2.7 % over one year. Alongside the abnormalities detected in the horizontal angular vestibulo-ocular reflex, significant changes were also noted in the ocular and cervical vestibular evoked myogenic potentials, as well as in the subjective visual vertical tests. As a result, it's vital to underscore the significance of both otolithic function and vestibulo-ocular reflex in the fundamental mechanisms of presbyvestibulopathy.

Bimodal deep learning model for subjectively enhanced emotion classification in films

This research delves into the concept of color grading in film, focusing on how color influences the emotional response of the audience. The study commenced by recalling state-of-the-art works that process audio–video signals and associated emotions by machine learning. Then, assumptions of subjective tests for refining and validating an emotion model for assigning specific emotional labels to selected film excerpts were presented. The insights gained from these subjective evaluations facilitated the creation of a comprehensive database of movie excerpts. This database was subsequently employed to both train and evaluate the efficacy of deep learning models. The latter half of the study shifts focus to the intelligent analysis of audio and video signals that form film excerpts. This involved exploring diverse methodologies for parameterizing these signals. Models that demonstrated the highest accuracy on the test dataset on audio/video only were amalgamated to forge a bimodal model, which integrates both audio and video signals for emotion classification. The bimodal model exhibited superior accuracy in tests compared to a model that solely relied on video signal classification. This enhancement in performance was achieved with only a marginal increase in the complexity and the number of parameters within the model.

24‐1: Visible Difference Predictors: A Class of Perception‐Based Metrics

The Visible Difference Predictors are a class of data driven, white box, efficiently implemented image or video difference metrics. They model important aspects of perception like spatial and temporal vision, foveation, and more, and are calibrated on datasets relevant for display and graphics applications. In this paper, we present a historic retrospective of VDPs, and a high‐level technical overview and comparison to other metrics in the literature. Finally, we put forward a practical guide for selecting the appropriate metric for a given engineering problem and discuss how metrics can be effectively combined with subjective testing for high‐confidence assessments.

Analisis Kadar Formalin pada Mie Basah yang Dijual oleh Pedagang Bakso di Kota Sorong Menggunakan Spektrofotometer UV-Visible

Noodles are a popular food among middle class people, both upper and lower classes because they taste delicious and are affordable. Wet noodles have a short shelf life due to their high water content, this is what encourages some sellers to use formaldehyde as a preservative. This examination means to decide if there is formalin content in examples of wet noodles sold by meatball brokers in Sorong City. Formalin investigation was completed subjectively and quantitatively. Subjective tests were done by adding chromatogenic corrosive to wet noodle tests and quantitative tests were completed to see the degree of formaldehyde contained in the examples utilizing an UV-noticeable spectrophotometer. The consequences of the subjective test showed that one example with code (S1) was recognized as sure for containing formaldehyde, which was demonstrated by the adjustment of the shade of the filtrate from brown to purple subsequent to being dribbled with chromatophic corrosive reagent and warmed in bubbling water. The total formalin content contained in sample S1 was 0.905%.