Subjective Evaluation Method Research Articles

Holographic Communication: A Study of the Quality of Holographic Copies Perception

Relevance. Holography is becoming one of the most promising areas of visualization of three-dimensional objects, which justifies the emergence of a certain scientific interest in this area of research. There is a general global trend of intensifying the work of specialists on the problem of using holographic technologies in various areas of human activity. Trends in the implementation of holographic services and holographic communication today already require a revision of the principles of planning, designing and building existing communication networks, as well as approaches to the implementation of sixth-generation networks 6G, which are based on the integration of various technologies and communication networks into a single network. A separate issue is the assessment of the quality of service and the quality of perception of holographic services by both objective and subjective assessment methods. There are practically no criteria for assessing the quality of a holographic image, including scales and methods for subjective assessment of the quality of holographic services. Moreover, the properties of the holographic flow are poorly understood, and even less so its influence on communication networks and requirements for network parameters, which makes the tasks of studying traffic characteristics and assessing the quality of service of holographic services very relevant.The aim of the work is to evaluate the quality of perception of holographic conference calls using a subjective evaluation method on a model network. The work uses methods of subjective assessment of the quality of perception. The materials presented in the article reflect the results of the authors' experimental research work on studying the problem of the quality of perception of holographic copies. A description of the developed scheme of a full-scale experiment is given.Results. The data obtained as a result of the work of an expert group on assessing the quality of perception are presented. The subjective assessment of the quality of perception of a holographic image begins to deteriorate with 8 connections and becomes unsatisfactory with 12 connections, which must be taken into account when planning experimental studies of work on assessing the quality of perception. Novelty. For the first time, an assessment of the quality of perception of the provision of a holographic conferencing service was carried out using a subjective assessment method. Theoretical significance. The influence of increasing the number of holographic traffic flows on the quality of perception of the received content is analyzed. Practical significance. Expanding the possibilities for assessing the degree of user satisfaction with holographic services.

Measure letter recognition performance: A subjective evaluation method

Measure letter recognition performance: A subjective evaluation method

Evaluating the Geospatial Thinking of Pre-Service Geography Teachers Through an Orienteering Design Task: Analysis Using the Many-Faceted Rasch Model

Measurement is significant in geospatial thinking research. This study evaluated the geospatial thinking of pre-service geography teachers through an orienteering design tasks and subjective evaluation methods. Moreover, it analyzed their level of geospatial thinking, difficulty of evaluation indicators and rater severity with the Many-Faceted Rasch Model. The results showed the geospatial thinking of participating pre-service geography teachers was at a moderate level. The estimation results of the model were well fitted. The evaluation indicators had a good degree of differentiation. Therefore, using the MFRM helps interpret the results of a geospatial thinking assessment in a more comprehensive way.

Vocational Education Skill Assessment and Intelligent Assistance: A Study on the Application of Machine Learning Algorithms in the Assessment of Vocational Information Literacy Teaching Ability

Investigating vocational educators' knowledge-based teaching skills across China's Vocational Education (VE) institutions, this research focuses on the practical use of Machine Learning (ML) algorithms. Instructors' efficacy must be evaluated, and this work addresses the gap. VE performs an essential role in connecting learning abilities with the demands of industry. The investigation plans on developing an adaptable, subjective assessment technique that extends within the boundaries of conventional subjective evaluation methods using modern ML techniques such as Support Vector Machines (SVM), Decision Trees (DT), and Neural Networks (NN). Each ML model's accuracy, reliability, and feasibility have been determined using data collected from 120 vocational educators encompassing various fields and regions. Researchers predict that our findings will provide perspective on how to improve vocational education settings' teaching methods and governance.

Remote Sensing Application in Ecological Restoration Monitoring: A Systematic Review

In the context of the continuous degradation of the global environment, ecological restoration has become a primary task in global environmental governance. In this process, remote sensing technology, as an advanced monitoring and analysis tool, plays a key role in monitoring ecological restoration. This article reviews the application of remote sensing technology in ecological restoration monitoring. Based on a comprehensive analysis of the literature in the field of ecological remote sensing, it systematically summarizes the major in-orbit spaceborne and airborne sensors and their related products. This article further proposes a series of evaluation indicators for ecological restoration from four aspects: forests, soil, water, and the atmosphere, and elaborates on the calculation methods for these indicators. In addition, this paper also summarizes the methods for evaluating the effectiveness of ecological restoration, including subjective evaluation, objective evaluation, and comprehensive evaluation methods. Finally, we analyze the challenges faced by remote sensing technology in evaluating ecological restoration effectiveness, such as issues with the precision of indicators extraction, the limitations of spatial resolution, and the diversity of evaluation methods. This review also looks forward to future ecological restoration technologies, such as the potential applications of integrated aerospace and terrestrial remote sensing, multi-data fusion, and machine learning technologies. This study reveals the effectiveness of remote sensing technology in ecological restoration monitoring, aiming to provide efficient tools and innovative strategies for future remote sensing monitoring and assessment of ecological restoration.

Assessing the Impact of Street Visual Environment on the Emotional Well-Being of Young Adults through Physiological Feedback and Deep Learning Technologies

Investigating the impact of street visual environments on young adults’ emotions is crucial for the promotion of walkable and healthy streets. However, the applicability and accuracy of existing studies are limited by a lack of large-scale sample validation. Moreover, many studies have determined emotions through subjective evaluation methods or relied solely on a single physiological indicator to assess levels of emotional arousal, neglecting the significance of emotional valence. In response, this study aims to enhance our understanding of the emotional impact of street visual environments by employing a method that integrates physiological feedback technology and deep learning. We collected videos of 100 streets from five districts in Chengdu to serve as experimental stimuli, and utilizing physiological feedback technology, we gathered data on electrocardiograms (ECG), electrodermal activity (EDA), and respiratory responses (RESP) from 50 participants as they observed these street environments. Subsequently, we applied deep learning techniques to process the video and physiological data, ultimately obtaining 500 data entries on street visual environment elements and 25,000 data entries on emotional arousal and valence. Additionally, we established multiple linear regression and multinomial logistic regression models to explore the relationship between visual street environments and emotions. The results reveal that elements such as green view factor (GVF), sky view factor (Sky VF), and sidewalk view factor (SVF) not only reduce emotional arousal levels but also facilitate the shift from negative to positive emotions, positively affecting emotional regulation. In contrast, visual enclosure (VE), vehicle view factor (VVF), and person view factor (PVF) are associated with negative emotional arousal, adversely affecting emotional valence. Moreover, the impact of specific visual environmental elements on different emotional states may vary. This study introduces a novel, multidisciplinary approach to accurately quantify the relationship between the environment and emotions, providing significant theoretical and practical insights for the development of healthier cities.

Exploring Methodological Considerations: A Literature Review on How Lighting Affects the Sleep and Cognition in Healthy Older Adults

The impacts of lighting conditions on human circadian rhythms, sleep quality, and cognitive performance have been extensively investigated in the past two decades; however, these studies have yielded inconclusive and variable outcomes. For older adults who are at a higher risk of developing serious physiological and mental illnesses, such as Alzheimer’s or dementia, light therapy has emerged as a low-risk intervention to improve sleep quality and cognitive function. Nevertheless, the optimal methodology for evaluating the efficacy of light therapy in older adults remains unclear. This review has been conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and critically analyzes methodologies in previous studies on lighting's impact on sleep and cognitive performance in healthy older adults, focusing on how these approaches affect the findings. The review is structured into six domains: study setting and type, participant characteristics, lighting conditions, study design, sleep quality evaluation methods, and cognitive performance evaluation methods. Diverse study designs, methods, and population characteristics have influenced the outcomes. Bright light, applied from early morning to early evening, has been shown to enhance sleep and cognitive functions, notably working memory and concentration. It also benefits from dawn simulation throughout the day, which regulates circadian rhythms and improves sleep quality, although the ideal timing is yet to be determined. Intense short-wavelength lights and strong placebo conditions can counteract these positive effects, and using bright light in the evening may impair sleep and indirectly worsen cognitive performance in older adults. Further real-world experimental studies on this demographic, meticulous study designs, a combination of objective and subjective evaluation methods, and comprehensive reporting of lighting interventions are crucial for identifying the optimal lighting design approach for this population.

From perception to prediction: A comparative study of thermal comfort assessment techniques in school facilities

Indoor environmental quality (IEQ) significantly affects learning, health, and productivity in educational buildings, particularly classrooms. Thermal comfort is crucial to IEQ in classrooms, and various approaches have been developed to assess it. This study compares subjective evaluation, fieldwork measurement, and simulation methods in naturally ventilated secondary school classroom environments in Abuja, Nigeria. It evaluates their reliability, validity, advantages, and limitations. In achieving this objective, fieldwork measurements, questionnaire surveys, and building simulations were conducted in 83 classrooms with 2758 respondents. The data were subjected to descriptive and inferential statistical analysis using the analytical software programs SPSS version 23 and Microsoft Excel. The study found that the Actual Mean Vote (AMV) comfort operative temperature for classrooms was 28.7 °C. Findings from the comparative analysis of the methods indicate that the PMV generally overestimates students’ thermal sensation and that the fieldwork measurement Predicted Mean Votes (PMVf) undervalues the neutral temperature by 4.2 °C. In contrast, the computer-simulated Predicted Mean Votes (PMVs) undervalues it by 3.9 °C. The study found that all three methods are valid and reliable, with some advantages and limitations, depending on the assessment’s specific context and goals. The findings provide valuable insights into improving indoor environmental quality and occupant satisfaction in educational buildings, contributing to the discourse on assessing thermal comfort in classrooms and informing the development of more effective assessment methods. The systematic comparison of these methods addresses a notable gap in the literature, providing practical insights to optimize thermal conditions in learning environments.

Fatigue Driving Detection Technology: An Overview

In order to reduce the loss of life and property to the public caused by fatigue driving, the advantages and disadvantages of various fatigue detection methods are comprehensively analyzed based on the subjective evaluation method and objective measurement method of fatigue driving detection technology. At the same time, the future research trends based on detection standards and information fusion are proposed. This review can provide a reference for technicians who are committed to the research of fatigue driving detection.

A Method for Assessing Dogs in a Test Evaluating Dogs' Suitability for Animal-Assisted Education.

In objective behavioral rating (BR), dogs are rated for behavior based on the observations made during a behavioral test. However, behavioral definitions can differ between raters, and the definitions proposed by artificial intelligence (AI) can help standardize the applied measures. The aim of this study was to propose a new approach for assessing dogs' suitability for animal-assisted education (AAE) with the use of the BR method and the definitions of dog behaviors proposed by AI. The analysis relied on video footage of 25 dogs that participated in tests assessing the animals' suitability for AAE. The dogs were rated by five independent observers. Inter-rater reliability was satisfactory in 7 out of 9 subtests (0.715-0.856) and low in the remaining 2 subtests (0.667 in Subtest 2 and 0.617 in Subtest 5). The results indicate that the BR method based on AI definitions produced satisfactory inter-rater reliability in a test evaluating dog behavior. A comparison of subtest scores in the BR method and the subjective rating method did not reveal significant differences. Thus, it can be concluded that the proposed approach gives promising outcomes and can be used to develop new tests for assessing dogs' suitability for AAE and, perhaps, other types of work.

Data driven assessment of rock mass quality in red-bed hilly area: a case study of Guang’an city, SW China

The evaluation of geological suitability for urban underground space (UUS) development is an indispensable prerequisite for its optimal utilization. As the actual carrier of underground facilities, the evaluation of rock mass quality plays a crucial role in assessing geological suitability. However, it is notable that the evaluation of rock mass quality has regrettably remained somewhat marginalized within the broader framework of the geological suitability assessment in recent years. The selection of pertinent indicators for the evaluation of rock mass quality inherently presents an appreciable degree of subjectivity. Predominantly subjective evaluation methods continue to dominate the field, while the application of objective algorithms, such as unsupervised clustering, remains in its nascent stage. Furthermore, there is a lack of comprehensive investigations into distinct combinations of attributes. This limitation confines the broader applicability of the evaluation outcomes in the context of urban underground space. Within this study, we meticulously amassed rock core test data from over 40 boreholes of engineering geological significance within the urban planning ambit of Guang'An City. Utilizing the K-means unsupervised clustering algorithm and the Principal Component Analysis (PCA) algorithm. We successfully conducted an unsupervised clustering procedure with nine distinct physical and mechanical attributes. This yielded an aggregation into five discernible clusters. Building upon the derived clustering outcomes, a stratification of rock mass quality was effectuated into three distinct tiers: Level 1 (characterized by pure sandstone), Level 2 (primarily dominated by sandstone), and Level 3 (denoting fair conditions predominantly influenced by mudstone). This structured stratification facilitates a relatively objective and comprehensive evaluation of rock mass quality within the context of the red-bed hilly terrain. In the course of this analytical trajectory, we conducted a dissection of the clustering efficacy. For strongly correlated attributes, we propose a preliminary dimensionality reduction procedure prior to the clustering endeavor. Moreover, we recommend intervals of 10 m for the stratified evaluation in red bed hilly urban terrains.

The effectiveness of the SESFAR intervention program in supporting the phonological awareness of children with autism spectrum disorder

The purpose of this research was to determine the effectiveness of the Phonological Awareness Intervention Program in supporting the phonological awareness skills of two six- and seven-year-old children with autism spectrum disorder. Additionally, we collected follow-up and generalization data. The social validity data were evaluated by social comparison and subjective evaluation methods. The findings from the study showed that children with autism acquired phonological awareness skills with the Phonological Awareness Intervention Program presented with the direct instruction method. They maintained these skills in the follow-up sessions held after 1, 3, and 5 weeks and could generalize them to different people, tools, and settings. On the other hand, the social validity findings showed that children with autism who were the study participants exhibited similar phonological awareness skills to their peers. The findings obtained from the parents and teachers of the participating children indicated the study's social validity.

Modeling and Subjective Evaluation Method of Driveability for Fuel Cell Vehicles

Aiming at the demand for subjective evaluation of driveability for fuel cell vehicles, the modeling and evaluation method of driveability for fuel cell vehicles were studied in this paper. Firstly, a real-time model of the fuel cell vehicle powertrain system was established, which included the fuel cell model, power battery model, DC/DC converter model and drive motor model. Secondly, it was integrated with the vehicle dynamics model to form a virtual prototype of a fuel cell vehicle. And a virtual subjective evaluation platform for fuel cell vehicles was built by combining the virtual prototype and high-fidelity driving simulator. Thirdly, a subjective evaluation method of driveability for fuel cell vehicles was proposed, which included the starting performance, acceleration performance, uniform speed performance and tip-in/tip-out performance. Finally, the paper used the platform and method mentioned above to conduct subjective evaluations of the fuel cell vehicles.

The effect of sovereign credit ratings on democracy in sub-Saharan Africa

PurposeThis study investigates (1) whether democratization drives sovereign credit ratings (SCR) changes (the “democratic advantage”) or whether SCR changes affect democratization, (2) whether the degree of democratization in sub-Saharan African (SSA) countries affects the associations and (3) whether the associations are significantly affected by resource dependence.Design/methodology/approachThis study investigates the effects of SCR changes on democracy in 22 SSA countries over the period of 2000–2020 VEC Granger causality/block exogeneity Wald tests, and impulse responses and variance decomposition analyses with Cholesky ordering and Monte Carlo standard errors in a panel VECM framework.FindingsThe full sample impulse responses find that a SCR shock has a long-run detrimental effect on the democracy and political rights but only a short-run positive impact on civil liberties. Among the sub-samples, it is found that the extent of natural resource dependence does not affect the magnitude of SCR shocks on democratization mentioned above but it is found that a SCR shock affects long-run democracy in SSA countries that are relatively more democratic but is more likely to drive democratic deepening in less democratic SSA countries. The full sample variance decompositions further finds that the variance of SCR to a political rights shock outweighs the effects of all the macroeconomic factors, whereas in more diversified SSA countries, the variances of SCR are much greater for democracy and political rights shocks, which suggests that democratization and political rights in diversified SSA economies are severely affected by SCR changes. In the case of the high and low democracy sub-samples, it is found that the variance of SCR in the relatively higher democracy sub-sample is greater than in the low democracy sub-sample.Social implicationsThese results have three implications for democratization in SSA. First, the effect of a SCR change is not a democratically agnostic and impacts political rights to a greater extent than civil liberties. Second, SCR changes have the potential to spark a negative cycle in SSA countries whereby a downgrade leads to a deterioration in socio-political stability coupled with increased financial economic constraints that in turn drive further downgrades and macroeconomic hardship. Finally, SCR changes are potentially detrimental for democracy in more democratic SSA countries but democratically supportive in less democratic SSA countries. Thus, SSA countries that are relatively politically sophisticated are more exposed to the effects of SCR changes, whereas less politically sophisticated SSA countries can proactively shape their SCRs by undertaking political reforms.Originality/valueThis study is the first to examine the associations between SCR and democracy in SSA. This is critical literature for the Africa’s scholarly work given that the debate on unfair rating actions and claims of subjective rating methods is ongoing.

The effect of quiet eye training on golf putting performance in pressure situation

To explores the effect and mechanism of quiet eye training on the accuracy of golfers´ putts in pressure situations and provides methods and basis for targeted attention training and control. 22 young golfers in China golf team aged from 13 to 18 were randomly assigned to the experimental group (quiet eye training group) and the control group (technical guidance group) according to gender. Both groups of participants underwent two consecutive weeks of push training (3 sets per day, 20 golf putts per set, rest for 3 min between sets) separately in accordance with the guidance of a professional psychological research group and an expert coach. Eye tracking technology, biofeedback technology, and subjective evaluation methods were used to test and analyze the push process of the two groups of participants before and after training under pressure situations (Eye movement behaviors and the heart rate were recorded by ASL Mobile Eye-XG and NeXus-2 biofeedback, pressure and state anxiety were evaluated by self-rating pressure scale and S-AI. Golf putting performance was recorded by a research graduate assistant). A higher hit ratio as well as lower pressure and SAI level was founded in quiet eye training group in the pressure situation, the quiet eye movement time and total fixation time was longer than technical group. The quiet eye training group has a better putting performance. Quiet eye training can improve the golf putting performance in pressure situations. After quiet eye training, the state anxiety decreased, the quiet eye movement time and the total fixation time increased in pressure situations.

Acoustics Perception in Special-Shaped Spaces: A Systematic Review

The purpose of this paper is to review the acoustic perception of special-shaped spaces. Peer-reviewed English-language journal articles published between 2003 and 2023 were searched in the Web of Science and Scopus databases by using the keywords “perception”, “acoustics”, “flat space”, “extra-large space”, “coupled space”, “long space”, and spatial function and their synonyms. The inclusion criteria were as follows: (1) Included articles should focus on the field of psychoacoustics. (2) Spaces should be clearly identified as one or more of the four special spaces described above. (3) Subjective evaluation methods for spatial acoustic perception should be used. Finally, a total of 31 studies were included. A standardised data extraction form was used to collect spatial information, subject information, sound environment information, and other information. The results show that comfort expresses positive perception results in all four different spaces, whereas annoyance is negative in both flat and extra-large spaces, and satisfaction shows the opposite results in flat and coupled spaces, whereas perceived reverberation is the specific dimension for coupled space. In addition, unique conclusions were obtained for each type of space and special cases in the spaces were individually characterised.

Construction of a digital library of vocal music resources based on second-order data decomposition algorithm

Abstract In this paper, in order to solve the modal aliasing problem of the EMD decomposition algorithm and EEMD decomposition algorithm and optimize the vocal audio data decomposition on the basis of the adaptive VMD algorithm, the EEMD-VMD second-order data decomposition algorithm is proposed to decompose the digitized time series of vocal music resources, and to update the construction of the digital library of vocal music resources. Combined with the decomposition steps of the second-order data decomposition algorithm in the vocal resources digitized library, the overall framework of the vocal resources digitized library is designed and constructed with the main line of vocal resource types and the secondary line of content categories. Design the experimental environment, preprocess the vocal audio signal features, explore the modal number K value size of the EEMD-VMD second-order data decomposition algorithm, analyze the vocal audio denoising performance of the algorithm, and compare the correlation coefficients of the IMF components of the decomposition algorithms with the original audio signals. Explore the second-order data decomposition algorithm’s emotional classification of vocal resources and the performance of vocal signal enhancement, add noise sources, and use subjective and objective evaluation methods to assess the quality of vocal PESQ and STOI after decomposition processing. The EEMD-VMD second-order data decomposition algorithm performs the most prominently in street noise environments. The enhancement results in the case of signal-to-noise ratios of -5, -10, and -15 are 3.59, respectively, 4.36, 4.29, and the mean value of the enhancement performance reaches 4.08. The second-order data decomposition algorithm’s precise processing of vocal resources provides better quality digital resources for the construction of a digital library of vocal resources.

Green Marketing Performance Statistics Based on AHP and BP Neural Network Models

In order to promote the development of circular economy, starting from green marketing is the best means. Combining artificial neural network technology and hierarchical analysis subjective evaluation method, the key factors affecting green marketing performance were analyzed by constructing an evaluation index system for green marketing performance statistics, and the relative weights of each performance indicator were calculated by using analytic hierarchy process (AHP) and the relative importance ranking was given. Then the evaluation results were introduced into the neural network model as input variables. The evaluation results are trained and tested by using the inverse inverse propagation neural network. Finally, the simulation results show that the model can not only reduce the defects of subjective randomness, but also improve the predictability, accuracy and effectiveness of green marketing performance statistics. The calculation results are accurate, the method is feasible, and the errors are controllable, which has theoretical scientific significance and practical guiding significance.

Evaluation of Site Suitability for Photovoltaic Power Plants in the Beijing–Tianjin–Hebei Region of China Using a Combined Weighting Method

As the construction of photovoltaic power plants continues to expand, investors have placed great importance on the suitability assessment of site selection. In this study, we have developed a multi-level evaluation system and proposed an AHP–XGBoost–GIS comprehensive evaluation model for assessing site suitability in the Beijing–Tianjin–Hebei region. The findings revealed that approximately 48,800 km2 (21.59% of the total area) constituted a suitable area in this region, surpassing previous research results. Generally suitable areas accounted for the largest proportion at 35.89%. Suitable areas in Beijing and Tianjin were relatively limited, with most of them concentrated in Baoding City, Zhangjiakou City, and Chengde City on the northwest side of the “Yanshan-Taihang Mountains”, where there are ample wastelands with gentle slopes conducive to constructing photovoltaic power plants southeast of the “Yanshan-Taihang Mountains”, and solar radiation conditions were better. However, ecological and economic factors restricted suitable areas resulting in smaller coverage including cities such as Handan, Xingtai, Qinhuangdao, and Tangshan, among others. This study successfully overcame limitations associated with traditional subjective evaluation methods by providing decision support for regional energy allocation planning and spatial planning efforts, as well as environmental protection endeavors.

Safety risk assessment of sustainable construction based on projection pursuit model optimized by multi-intelligent algorithm: a case study of new chemical projects.

With the rapid development of urban and social economies, the safety accidents in the construction process of the new chemical plant have caused huge losses to the city. The purpose of this study is to evaluate the risks in the construction process of chemical projects and propose preventive measures. A novel risk assessment model based on multi-intelligence algorithm optimization projection pursuit was developed to assess the construction safety risk and determine the risk level. In this model, the best-worst method and the entropy weight method were used as subjective and objective evaluation methods, respectively. The theory based on the idea of the distance function was applied to the model to calculate the combined weight value. The results showed that the three evaluation objects with the highest risk value were the air compression station plant, regional control room, and hazardous and solid waste temporary repository. The risk values of these three buildings were 2.2557, 2.2160, and 2.1654, respectively, and the corresponding risk level was high. On-site safety managers should take immediate measures in these high-risk buildings to reduce the possibility of accidents. This study is a new attempt to consider the construction safety risk of the new chemical project.