Subjective Judgment Research Articles

Pixel-level concrete bridge crack detection using Convolutional Neural Networks, gabor filters, and attention mechanisms

Cracks are prominent defects that significantly impact concrete bridges' structural safety and serviceability assessments. The conventional manual bridge inspection is often limited by multiple challenges related to the heavy workload of data processing and the subjective judgment of inspectors. Several vision-based methods, from traditional image processing techniques to segmentation deep learning models, have been employed for pixel-level crack detection to detect cracks in various scenes and surfaces automatically. The present paper proposes an end-to-end framework for crack segmentation combining UNet, Gabor filters, and Convolutional Block Attention Modules leveraging the complementary strengths of both spatial and frequency domains to enhance crack feature extraction and mitigate the impact of image disturbances. The designed network is trained and evaluated on a multi-source annotated crack dataset established by the authors to expose the model to multiple instances of crack appearance and background complexity and enhance its generalization ability. The proposed model achieves an Intersection over Union (IoU) of 60.62 % and an F1-score of 74.49 %, outperforming benchmark segmentation networks. Experimental results demonstrate the effectiveness of cross-domain feature fusion and multi-source data utilization in segmenting cracks with diverse patterns and background interference scenarios.

Research on the Judgement Standard of the Duty of Care of Internet Service Providers

The internet service providers tort liability for general fault tort liability, which means that network service providers bear the tort liability need to subjective fault for the elements, then for the network service provider's subjective fault judgement standard objectively to rise to the network service provider's reasonable duty of care judgement standard above the problem. Up to now, about the network service provider's duty of care standard judgement is still no clear provisions, in the legal and judicial fields are more controversial. This paper explores these issues through an analysis of trial practices, seeking to establish a more standardized approach to evaluating ISPs' duty of care. The findings suggest that adopting the "good manager" standard could significantly enhance the clarity and effectiveness of managing ISPs' tort liabilities. It proposes the establishment of a dedicated management association within ISPs to implement and oversee these management policies consistently across the sector. This approach aims to not only define but also enforce a reasonable duty of care standard that is both fair and practicable.

The Safe Catch: AI Protects Your Health from Formalin-Laced Fish

In Bangladesh, where fish is a staple food, ensuring its safety from formalin contamination poses a critical challenge due to its perishable nature. This study introduces an intelligent application employing digital image processing for the rapid and non-intrusive detection of formalin in fish. Leveraging image analysis of fish eyes, the system distinguishes between formalin and non-formalin treated fish. The proposed architecture, utilizing EfficientNet-B3 and VGG-16 models, achieved a 98.05% and 98% accuracy rate in training and validation on the dataset. This method offers a swift and accurate means of examination without damaging sample preparation, particularly beneficial in large-scale operations where manual inspection is impractical. Unlike human senses, digital image processing algorithms remain impartial, overcoming human biases and subjective judgments. Challenges persist, such as the diverse appearance of fish and external factors like varying illumination, which may impact the reliability and effectiveness of image processing programs for formalin detection. Nonetheless, this technology holds promise in addressing the pressing need for dependable and automated formalin detection in the fish supply chain, ensuring food safety and public health.

Detection method for unrecognized spatial disorientation based on optical flow stimuli.

Flight accidents caused by spatial disorientation (SD) greatly affect flight safety. Few studies have been devoted to the evaluation of SD. 10 pilots and 10 non-pilots were recruited for the experimental induction of SD. Videos for giving optical flow stimuli were played at two different flow speeds to induce SD. Subjective judgment and center of foot pressure (CoP) data were collected from the tests. The data were combined to determine the occurrence of SD and analyze the SD types. The number of self-reported SD events was slightly smaller in the pilots than in the non-pilots. The average upper bound of the confidence interval for the standard deviation of CoP was 0.32 ± 0.09 cm and 0.38 ± 0.12 cm in the pilots and non-pilots, respectively. This indicator was significantly lower in the pilots than in the non-pilots (P= 0.03). The success rate of the experimental induction of unrecognized SD was 26.7% and 45.0% in the pilots and non-pilots, respectively. The method offered a new to analyze unrecognized SD. We could determine the occurrence unrecognized SD. This is an essential means of reducing flight accidents caused by unrecognized SD.

범행현장에서의 특별사법경찰관의 절차상 의무와 영상촬영의 적법성에 대한 검토

Unlike ordinary judicial police officers, special judicial police officers have the dual status of being enforcement officers for administrative criminal law violations and special judicial police officers for criminal proceedings, and it is a peculiarity that whether an investigation falls under administrative or criminal proceedings depends on the specific case at the time of initiation of the investigation, and the applicable law at each stage. Therefore, the applicable law and procedural obligations may vary depending on the nature of each specific act, and the special investigative police officer should fully consider this when making a judgment on the admissibility of evidence collected by the special investigative police officer. In addition, our precedents have recognized the legality of video recording by investigative agencies as a method of evidence collection at the scene of a crime, emphasizing that it is a substantial method of recording in a public place, and [the subject judgment] ruled to the same effect. In the reality that there is a growing need to regulate the verification behavior of investigative agencies according to the new compromise theory beyond the conflict between arbitrary and compulsory investigation theories, the point of precedent is extremely appropriate.

Global Overview of the Application of the Braun-Blanquet Approach in Research

Environmental classifications are of paramount importance for assessing the impacts of land-use changes, for prioritizing conservation efforts, and for developing effective management strategies to mitigate the negative impacts of human activities. The aim of our research was to provide as complete an analysis as possible of the studies that have been carried out using the Braun-Blanquet approach. The global review of studies based on the Braun-Blanquet approach includes 1168 papers and was conducted using the PRISMA 2009 methodological recommendations, strict criteria for the selection/quality of papers, and modern methods of data analysis and visualization using VOSviewer software developed by Nees Jan van Eck and Ludo Waltman (Centre for Science and Technology Studies (CWTS) of Leiden University in the Netherlands) (version 1.6.18), which ensures a representative sample, minimization of subjective judgements, and reliability of conclusions. It was noted that the number of publications on Braun-Blanquet is growing exponentially. This is an indication of the scientific interest in this methodology and its continuous further development. Based on a detailed analysis of the keywords, the main research directions and challenges are identified. These include improving the conceptual and methodological foundations of the Braun-Blanquet approach; improvement in regional vegetation classifications, synthesizing them and producing a comprehensive classification for large areas as a basis for biodiversity conservation and sustainable land use; expansion of the geography; compilation and updating of databases of phytosociological data; management of dynamics and vegetation; discussion of the important problem of continuity and discreteness of vegetation in the context of ecological classifications; and vegetation mapping. The top 20 journals publishing the most cited articles were identified, as well as the top 20 most cited journals whose high citation rate is due to the large number of high-quality articles. The analysis of the bibliographic network of papers in dynamics has shown that the structure of relationships is not constant and has changed significantly. The analysis of the authors’ publication activity showed that the vast majority of researchers have a low publication activity and have published only one to three papers. A peculiarity also emerges: if all the most cited authors are concentrated in Eurasia, then most of the most actively published authors are outside Eurasia. The importance of the Braun-Blanquet approach for the study and classification of forest vegetation should be emphasized. In this case, the Braun-Blanquet approach is integrated into forest typologies, increasing their ecological validity and environmental relevance.

Inequivalent and uncorrelated response priming in motor imagery and execution.

Theoretical considerations on motor imagery and motor execution have long been dominated by the functional equivalence view. Previous empirical works comparing these two modes of actions, however, have largely relied on subjective judgments on the imagery process, which may be exposed to various biases. The current study aims to re-examine the commonality and distinguishable aspects of motor imagery and execution via a response repetition paradigm. This framework aims to offer an alternative approach devoid of self-reporting, opening the opportunity for less subjective evaluation of the disparities and correlations between motor imagery and motor execution. Participants performed manual speeded-choice on prime-probe pairs in each trial under three conditions distinguished by the modes of response on the prime: mere observation (Perceptual), imagining response (Imagery), and actual responses (Execution). Responses to the following probe were all actual execution of button press. While Experiment 1 compared the basic repetition effects in the three prime conditions, Experiment 2 extended the prime duration to enhance the quality of MI and monitored electromyography (EMG) for excluding prime imagery with muscle activities to enhance specificity of the underlying mechanism. In Experiment 1, there was no significant repetition effect after mere observation. However, significant repetition effects were observed in both imagery and execution conditions, respectively, which were also significantly correlated. In Experiment 2, trials with excessive EMG activities were excluded before further statistical analysis. A consistent repetition effect pattern in both Imagery and Execution but not the Perception condition. Now the correlation between Imagery and Execution conditions were not significant. Findings from the current study provide a novel application of a classical paradigm, aiming to minimize the subjectivity inherent in imagery assessments while examining the relationship between motor imagery and motor execution. By highlighting differences and the absence of correlation in repetition effects, the study challenges the functional equivalence hypothesis of imagery and execution. Motor representations of imagery and execution, when measured without subjective judgments, appear to be more distinguishable than traditionally thought. Future studies may examine the neural underpinnings of the response repetition paradigm to further elucidating the common and separable aspects of these two modes of action.

Assessing Refereeing Proficiency in Chinese University Basketball Leagues

This research examines the perspectives of athletes and coaches on the competence of basketball referees, with a specific emphasis on important aspects such as understanding the rules, making decisions, communicating, managing the game, maintaining consistency, and resolving conflicts. By conducting an extensive survey that incorporates both quantitative and qualitative data-gathering methods, this study aims to provide a thorough understanding of the existing difficulties encountered by those involved in the field of basketball officiating. The results indicate that there is a general discontent with the level of officiating, as both players and coaches evaluated officials' performance low across all measured categories. In addition, the research reveals recurring obstacles that substantially influence the integrity and fairness of basketball tournaments. These issues encompass uneven officiating, communication hurdles, difficulty in game management, concerns over transparency and accountability, and subjective judgment calls. The research highlights the pressing necessity for focused development programs that aim to enhance the abilities of referees and tackle the highlighted obstacles in order to enhance the overall quality of basketball officiating.

Decision process for industry 5.0

ABSTRACT Industry 5.0 is an emerging paradigm that enhances the established Industry 4.0. Automation, digitalisation, big data, and artificial intelligence are becoming complemented by human-centricity, active cooperation between people and machines, and decision-making based on human expertise. This research introduces a generic decision-making process for Industry 5.0. It defines the underlying principles to incorporate multi-criteria decision models, decision procedures, and decision support technology into business and production processes for Industry 5.0. We justify the motivation to aggregate holistic objectivedecisions, which are inferred automatically from big data, with subjective judgements and knowledge of human decision-makers to guarantee unbiased actions. We draw parallels with the aggregation-disaggregation paradigm and constructive learning to address the human-centric specification of preferences in cooperation with technology-driven entities. We assess the relevance and efficiency of decision support for Industry 5.0 with a SWOT analysis. Finally, we apply the introduced generic process to the use case of the flexible electricity supply market.

Analysing impact of corporate attributes on sustainability disclosures through India’s new BRSR framework

Purpose The purpose of this study is to analyse the impact of corporate attributes like a company’s profitability, size, age, leverage and board size on companies’ sustainability reporting as measured through India’s new business responsibility and sustainability reporting (BRSR) framework. Design/methodology/approach A random sample of 130 companies was taken from the top 1,000 listed companies on the National Stock Exchange. Sequential mixed methods research approach was used to prepare a sustainability quality index. Then, a hierarchical multiple regression analysis was performed to examine the impact on the quality of reporting by Indian companies. Findings Interestingly, the analysis revealed that traditional metrics like age, profitability, board size and leverage did not have significant associations with reporting quality. Rather, the size of a company in terms of market capitalisation was found to have a strong positive impact on sustainability reporting. Research limitations/implications This was a cross-sectional study, as time series data for BRSR reporting is not yet available. Also, only five parameters were taken for analysis. Lastly, subjective judgment in content analysis may be involved. Practical implications This suggests that only larger companies in India are prioritising sustainability reporting over smaller ones. It affirms the legitimacy and stakeholder theory in the Indian context. Originality/value To the best of the authors’ knowledge, this study is one of the first endeavours to assess the efficacy of the new Indian BRSR framework and test its primary objectives. Furthermore, significant implications have been given for managers to catalyse and reinforce the sustainability momentum down the lane across companies of all sizes in India.

Unraveling the Tapestry of Pain: A Comprehensive Review of Ethnic Variations, Cultural Influences, and Physiological Mechanisms in Pain Management and Perception.

The medical management of pain is a nuanced challenge influenced by sociocultural, demographic, and ethical factors. This review explores the intricate interplay of these dimensions in shaping pain perception and treatment outcomes. Sociocultural elements, encompassing cultural beliefs, language, societal norms, and healing practices, significantly impact individuals' pain experiences across societies. Gender expectations further shape these experiences, influencing reporting and responses. Patient implications highlight age-related and socioeconomic disparities in pain experiences, particularly among the elderly, with challenges in managing chronic pain and socioeconomic factors affecting access to care. Healthcare provider attitudes and biases contribute to disparities in pain management across racial and ethnic groups. Ethical considerations, especially in opioid use, raise concerns about subjective judgments and potential misuse. The evolving landscape of placebo trials adds complexity, emphasizing the importance of understanding psychological and cultural factors. In conclusion, evidence-based guidelines, multidisciplinary approaches, and tailored interventions are crucial for effective pain management. By acknowledging diverse influences on pain experiences, clinicians can provide personalized care, dismantle systemic barriers, and contribute to closing knowledge gaps, impacting individual and public health, well-being, and overall quality of life.

Development of web-based software for environmental impact assessment focusing on road traffic noise

In the Republic of Korea, Environmental Impact Assessment (EIAs) precedes development projects to predict and analyze potential environmental effects. Generally, EIA noise evaluations utilize 2D noise prediction equations and correction coefficients. This method, however, offers only a sectional noise evaluation and has limitations in complex environments with diverse noise sources. Moreover, the determination of various variables during the EIA process based on subjective human judgment raises concerns about the reliability of the results. Thus, this study aims to develop software accessible via a web environment for user-friendly EIA noise evaluations. This software supports integrated data management and generates a 3D noise prediction model for more precise and realistic analysis of noise impacts, specifically focusing on road-traffic noise at this stage of development. The 3D noise prediction model and noise map generated by the developed software have been validated against through comparison with the results of onsite noise measurements and commercial EIA software, SoundPLAN. This validation aimed to assess the practical utility of the application.

Similarity judgements: the comparison of normative predictions and subjective evaluations - A study of the ratio model of similarity in social context.

This study examines the consistency between subjective similarity evaluations and the theoretical predictions derived from Tversky's ratio model of similarity, alongside the impact of additional positive and negative features on perceived similarity to ideal and bad politicians. Using a sample of 120 participants, we assessed the similarity of eight candidate profiles to an ideal and bad politician, varying in positive and negative features. Participants' subjective evaluations were compared with theoretical predictions derived from Tversky's ratio model. The analysis focused on how candidate and referent valence influenced observed versus theoretical similarity. Subjective similarity judgments deviated systematically from theoretical predictions, especially for positively featured candidates, indicating a negativity effect. Additional positive features decreased the perceived similarity of favorable candidates to an ideal politician, while additional negative features did not significantly affect similarity judgments of unfavorable candidates. Our findings underscore a significant disparity between subjective and objective similarity judgments, notably for favorable candidates. While the ratio model performs well for unfavorable candidates, its applicability diminishes for favorable ones, emphasizing the role of feature valence in decision-making. Further research on feature valence is crucial for a comprehensive understanding across contexts.

Development of a decision support system for client acceptance in independent audit process

Intelligent Information Technology (IIT) applications are crucial in the audit process, enhancing quality, effectiveness, and efficiency. The client acceptance process (CAP), one of the critical audit steps, involves subjective evaluations where business managers' claims intersect with independent audit firm managers' expectations. This subjective nature introduces the potential for errors or misjudgments, impacting audit time and costs. In this paper, therefore, we propose a decision support system considering both auditors' subjective judgments and financial data variations for accepting or rejecting a client enterprise. The decision support system consisting of the Fuzzy Analytic Hierarchy Process (AHP), the logistic regression model, and the fuzzy inference system comprises four phases. In the first phase, a logistic regression model is developed using financial ratios to determine the client's probability of being in a close monitoring market (CMM) which represents publicly traded firms that are struggling to meet specific financial indicators or that are exposed to certain risks. In the second phase, the evaluation criteria used by the audit firm to measure the market reputation of the client enterprise are defined, and the weights of the evaluation criteria are obtained by using Fuzzy AHP. In the third phase, the Client Acceptance Score (CAS) representing market reputation of the client is calculated by incorporating the results of a reputation survey and applying the weights assigned to the evaluation criteria obtained in the second phase. Finally, client acceptance risk level (CARL) is obtained by using a fuzzy inference system and a rule-based defined by auditors. The CMM probability value and CAS score obtained in previous phases are used as input values of the fuzzy inference system. The CARL score guides the audit firm in deciding whether to engage with the client. To illustrate the applicability of the proposed model, a case study has been given in the paper.

Identification of Critical Areas of Openness–Vitality Intensity Imbalance in Waterfront Spaces and Prioritization of Interventions: A Case Study of Xiangjiang River in Changsha, China

Identification of Critical Areas of Openness–Vitality Intensity Imbalance in Waterfront Spaces and Prioritization of Interventions: A Case Study of Xiangjiang River in Changsha, China

Development and Evaluation of Patient Safety Interventions: Perspectives of Operational Safety Leaders and Patient Safety Organizations.

The purpose of this study is to understand how patient safety professionals from healthcare facilities and patient safety organizations develop patient safety interventions and the resources used to support intervention development. Semistructured interviews were conducted with patient safety professionals at nine healthcare facilities and nine patient safety organizations. Interview data were qualitatively analyzed, and findings were organized by the following: patient safety solutions and interventions, use of external databases, and evaluation of patient safety solutions. Development of patient safety interventions across healthcare facilities and patient safety organizations was similar and included literature searches, internal brainstorming, and interviews. Nearly all patient safety professionals at healthcare facilities reported contacting colleagues at other healthcare facilities to learn about similar safety issues and potential interventions. Additionally, less than half of patient safety professionals at healthcare facilities and patient safety organizations interviewed report data to publicly available patient safety databases. Finally, most patient safety professionals at healthcare facilities and patient safety organizations stated that they evaluate the effectiveness of patient safety interventions; however, they mentioned methods that may be less rigorous including audits, self-reporting, and subjective judgment. Patient safety professionals often utilize similar methods and resources to develop and evaluate patient safety interventions; however, many of these efforts are not coordinated across healthcare organizations and could benefit from working collectively in a systematic fashion. Additionally, healthcare facilities and patient safety organizations face similar challenges and there are several opportunities for optimization on a national level that may improve patient safety.

Spatial Image-Based Walkability Evaluation Using Regression Model

Spatial Image-Based Walkability Evaluation Using Regression Model

Differences in preoperative frailty assessment of surgical candidates by sex, age, and race

IntroductionSurgical decision-making often relies on a surgeon's subjective assessment of a patient's frailty status to undergo surgery. Certain patient demographics can influence subjective judgment when compared to validated objective assessments. In this study, we explore the relationship between subjective and objective frailty assessments according to patient age, sex, and race. MethodsPatients were prospectively enrolled in urology, general surgery, and surgical oncology clinics. Using a visual analog scale (0−100), operating surgeons independently rated the patient's frailty status. Objective frailty was classified using the Fried Frailty Criteria ranging from 0 to 5. Multivariable proportional odds models were conducted to examine the potential association of factors with objective frailty, according to surgeon frailty rating. Subgroup analysis according to patient sex, race, and age was also performed. ResultsSeven male surgeons assessed 203 patients preoperatively with a median age of 65. A majority of patients were male (61 %), white (67 %), and 60 % and 40 % underwent urologic and general surgery/surgical oncology procedures respectively. Increased subjective surgeon rating (OR 1.69; p < 0.001) was significantly associated with the presence of objective frailty. On subgroup analysis, a higher magnitude of such association was observed more in females (OR 1.86; p = 0.0007), non-white (OR 1.84; p = 0.0019), and older (>60, OR 1.75; p = 0.0001) patients, compared to male (OR 1.45; p = 0.0243), non-white (OR 1.48; p = 0.0109) and patients under 60 (OR 1.47; p = 0.0823). ConclusionThe surgeon's subjective assessment of frailty demonstrated tendencies to rate older, female, and non-white patients as frail; however, differences in patient sex, age, and race were not statistically significant.

An emergent ontology for digitally modeling existing buildings: examining Kyoto’s Nishiki market

PurposeThis project examines digital modeling strategies for existing buildings. In this context, it aims to question assumptions about the need for geometric accuracy and the efficacy of predefined ontologies. As a counterpoint to prevailing digital modeling strategies, this project proposes a digital modeling approach using a project-specific, emergent ontology.Design/methodology/approachNishiki Market, in Kyoto, Japan, is studied as a test case. The emergent-ontology modeling process is introduced with an initial minimal set of operations including basic fold and trim operations applicable to surfaces. As the model develops iteratively, new situations are encountered for which existing rules are insufficient. In response, the model maker’s subjective judgment is invoked to introduce new operations, and ontological rules are allowed to expand.FindingsThe emergent-ontology approach, when executed on the Nishiki Market test case, enables representation of specific architectural qualities, highlighting semantic distinctions between digitally modeled elements of real-world features. The modeling approach generated project-specific knowledge, informing disciplinary understanding. Ontological emergence enabled semantic relationships to be disclosed and newly constructed.Originality/valueThe project proposes a novel methodology using an emergent ontology for digitally modeling existing buildings. Instead of remaining within the limitations a predefined ontology, the model maker’s subjective decisions shape the model’s ongoing development. This interpretive approach allows project-specific knowledge generation while challenging prevailing assumptions about accuracy and consistency in digital models of existing buildings.

Dual-Level Viewpoint-Learning for Cross-Domain Vehicle Re-Identification

The definition of vehicle viewpoint annotations is ambiguous due to human subjective judgment, which makes the cross-domain vehicle re-identification methods unable to learn the viewpoint invariance features during source domain pre-training. This will further lead to cross-view misalignment in downstream target domain tasks. To solve the above challenges, this paper presents a dual-level viewpoint-learning framework that contains an angle invariance pre-training method and a meta-orientation adaptation learning strategy. The dual-level viewpoint-annotation proposal is first designed to concretely redefine the vehicle viewpoint from two aspects (i.e., angle-level and orientation-level). An angle invariance pre-training method is then proposed to preserve identity similarity and difference across the cross-view; this consists of a part-level pyramidal network and an angle bias metric loss. Under the supervision of angle bias metric loss, the part-level pyramidal network, as the backbone, learns the subtle differences of vehicles from different angle-level viewpoints. Finally, a meta-orientation adaptation learning strategy is designed to extend the generalization ability of the re-identification model to the unseen orientation-level viewpoints. Simultaneously, the proposed meta-learning strategy enforces meta-orientation training and meta-orientation testing according to the orientation-level viewpoints in the target domain. Extensive experiments on public vehicle re-identification datasets demonstrate that the proposed method combines the redefined dual-level viewpoint-information and significantly outperforms other state-of-the-art methods in alleviating viewpoint variations.