Judgment Method Research Articles

Early Detection Depression Based On Action Unit and Eye Gaze Features Using a Multi-Input CNN-WoPL Framework

Depression is a common mental disorder with significant life impact, including a high risk of suicide. Patients with depression attempt suicide five times more often than the general population. Self-reporting, subjective judgement and clinician expertise influence conventional diagnostic methods. For timely intervention and effective treatment, early and accurate diagnosis of depression is essential. This study proposes a framework called Multi-Input CNN-WoPL, a CNN-based method without a pooling layer that combines two features - action units and gaze - to improve accuracy and robustness in automatic depression detection. Pooling layer reduces spatial dimension of feature map, resulting in loss of information related to expression data, affecting depression detection result. The performance of the proposed method results in an accuracy of 0.994 and F1 score = 0.993, the F1 score value close to 1.0 indicates that the proposed method has good precision, recall and performance.

Effect of Leadership Styles on Employee Productivity in Nepalese Commercial Banks

Different leadership styles can significantly affect organizational outcomes and employee well-being. There are many distinct leadership philosophies, and a leader may choose to implement a certain style depending on their inclinations, the circumstances, and the demands of their group. The aim of this study was to investigate the impact of different leadership styles on employee productivity in the banking sector. The study employed a descriptive and causal comparative research design. This quantitative research aimed to establish the relationships between dependent and independent variables. The population consisted of employees from Nepalese commercial banks, with 384 complete responses gathered through a judgmental sampling method from initial 390 questionnaires distributed. The findings shows the transformational leadership, transactional leadership, charismatic leadership and laissez-faire leadership are all positive and statistically significant on the employee productivity. The consistency in the positive effects of transformational charismatic leadership and laissez-faire leadership across different contexts suggests that these styles may be universally beneficial, although the degree of impact may vary depending on the organizational environment and culture. Transactional leadership, while effective, may need to be complemented with other styles, especially transformational and charismatic, to achieve optimal outcomes.

ResNest-SVM-based method for identifying single-phase ground faults in active distribution networks

Single-phase grounding fault is the most common fault type in the distribution network. An accurate and effective single-phase grounding fault identification method is a prerequisite for maintaining the safe and stable operation of the power grid. Most neutral points of the active distribution network are grounded through arc suppression coils. In the active distribution network, the power supply in the network changes from one to multiple, which may change the direction of the fault current. In this paper, the superposition theorem is used to analyze the difference in the boosting effect of different types of distributed generators (DG) on line mode current in the sequence network diagram when DG is connected upstream or downstream of the fault point. Secondly, the composition of the zero-mode transient current of the fault line is analyzed. A judgment method based on the superposition diagram of transient zero-sequence voltage and current is proposed. Then, this paper improves the ResNest network and modifies the classifier of the last fully connected layer to SVM. Finally, the model in PSCAD is used to simulate single-phase grounding faults to obtain the training set and validation set. These datasets are used to train and test AlexNet, ResNet50, ResNeSt, and ResNeSt-SVM. The results show that under different fault points, transition resistances, DG access upstream and downstream of the fault point, and different fault initial phase angles, the ResNest-SVM model method can accurately identify the fault line and has better anti-noise ability than the other three network structures.

An indoor thermal comfort model for group thermal comfort prediction based on K-means++ algorithm

Predicting indoor thermal comfort plays an essential role in controlling energy consumption in buildings. Existing studies have used supervised machine learning to predict thermal comfort, which were more accurate than traditional models. However, these models required occupants’ subjective feedback for model training, which reduced the accuracy of the model. In this study, a prediction model that didn’t require feedback was proposed for the first time using the K-means++ algorithm based on the ASHRAE Global Thermal Comfort Database II. Firstly, the data quality was improved through feature selection, dimensional processing, and feature weighting. Then the influence of different outlier judgment methods, feature weight and data set size on model accuracy were compared. Finally, the K-means++ algorithm was applied for thermal comfort clustering analysis. The result showed that the model with an accuracy higher than 90 % could be constructed using only three factors (CLO, TA, RH), and the proposed model could predict indoor group thermal comfort reliably, and provide a foundation for the indoor thermal sensation evaluation.

Capturing uncertainty intuition in road maintenance decision‐making using an evidential neural network

AbstractDecision‐making of project‐level road maintenance is the process of mapping road information into a maintenance plan. Even though benefitting from deep learning, the decision‐making still faces the problem of maintenance data uncertainty. The data uncertainty derives from imperfect road information collection and arbitrary selection of maintenance plans. Such uncertainty always leads to unreasonable maintenance decision‐making. This study proposes an evidential approach using information entropy (IE) and Dempster–Shafer theory (DST) to capture and handle uncertainty in the decision‐making of project‐level road maintenance. The approach first uses an IE‐based judgment method (IE‐based method) to capture and observe quantitative data uncertainty. The DST‐based method is then developed to handle maintenance data uncertainty through utilizing evidential neural network and set‐valued decision‐making. A numerical experiment is performed on the maintenance data with 280 km of semi‐rigid base highways in China. The results indicate that the IE‐based method can measure the data uncertainty in the information of road sections. The DST‐based method captures the cautious intuition on the selection of maintenance plans, thereby reducing the decision error rate by over 14% under specific conditions when facing data uncertainty.

The effect of distance on audiovisual temporal integration in an outdoor virtual environment

In this study, we explore the influence of stimulus distance on human tolerance for (physical) asynchronies in virtual reality (VR). A repeated audiovisual (AV) stimulus with sound and light bursts was presented to the participants in an outdoor virtual environment (VE) using a head-mounted display (HMD). The investigation focused on quantifying the point of subjective simultaneity (PSS) for both visual and auditory stimuli. A synchrony judgment method (SJ-3) was used for 11 stimulus onset asynchronies (SOA) and five egocentric distances from 10 m up to 50 m with 10 m increments. The data analysis showed negative PSS values that decreased with distance, resulting in a negative slope (-3 ms/m) of the regression line between PSS values and simulated distances. In contrast to the recent study conducted in the indoor VE, we conclude that the presented study in the outdoor VE does not incorporate a distance compensation mechanism and refutes the hypothesis of an ‘implicit estimation’ of sound-arrival time. The reasons behind the observed contrast are discussed in this paper. Moreover, the negative slope of the regression line (−3 ms/m) is similar to previous research, concluding that there is a temporal integration of auditory-visual information within human neural processes without distance compensation.

Интерактивное приложение, реализующее метод уверенных суждений на массовой программной платформе

The article examines the functionality and architecture of an interactive application designed to support multi-criteria decision-making using S.A. Piyavsky's confident judgment method. It provides a description of key components of this method essential for presenting the topic in a computer-oriented format for data and knowledge representation. The application stores and provides access to a bank of universal importance coefficients for specific criteria and serves as the core of an information methodology for decision-making based on the confident judgment method. This methodology includes the following stages: compiling a list of alternative solutions with evaluations by a set of specific quantitative criteria; establishing a selection policy that orders criteria by importance for the decision-maker; normalizing the multi-criteria problem statement in line with a foundational optimization model; evaluating each alternative solution within this model; and selecting the optimal alternatives. The application automatically coordinates the creation and editing of the list of alternative solutions according to variation boundaries set by the selection policy, integrating all solution stages with user feedback. The application’s functionality is represented by a diagram linking the main activities and their outcomes, along with a UML diagram of application use cases. The architecture of the application is presented as a mind map. The application is implemented on the Excel platform using VBA programming language, chosen to ensure accessibility and support the development of advanced multi-criteria decision-making methods for a broad user base who use Excel in their professional work.

O CÓDIGO DE PROCESSO CIVIL NA FORMAÇÃO DOS PRECEDENTES NO BRASIL

True precedent, the result of a scientific method of judgment, is adopted in countries with the Common Law legal system, which is based on customs. In line with global concepts that seek to converge the two main legal systems in the world – Common Law and Civil Law –, the Brazilian legislator included the use of precedents in article 926 of the 2015 Code of Civil Procedure. The objective is to promote legal certainty, standardize judicial decisions, reduce litigation and increase the credibility and efficiency of the Brazilian justice system. However, due to other provisions included in the Code of Civil Procedure and the divergent interpretation of the Judiciary in relation to the adopted system, Brazilian precedents have not yet fully achieved this purpose, requiring further study and possible adjustments by legal practitioners and the Legislature, whose intention is to discourage litigation.

Laser speckle interferometry approach for measuring the first wall surface micro-morphology in fusion devices with only single interferogram based on Hilbert transform

During the operation of the EAST device, the surface morphology of the first wall in will change due to the erosion and redeposition from plasma-wall interaction (PWI). In this paper, a novel phase extraction approach using only single interferogram based on twice Hilbert transform (THT) has been proposed and implemented. The current approach has a significant advance for eliminating the phase-shifting errors in principle, but the problems of phase flipping and loss due to ignoring non-physical negative frequency spectrum must to be overcome. To address these problems a judgement method is proposed in current investigation to distinguish the regions of the negative spatial frequency. Then a binary matrix was developed to modify the wrapped phase of the measured interferogram. The validation of the proposed THT approach has been demonstrated by the micro-morphology reconstruction of laser ablation craters on molybdenum (Mo) and tungsten (W) tiles, which are commonly used as the first wall in EAST device. Results indicate that the THT approach has a reasonable measurement accuracy with relative errors around 10%. Also, the current THT approach presents an enhanced robust under the EAST-like vibrational environments.

An insight of undergraduate students’ attitude and satisfaction with online home-based learning system

The purpose of this study is to investigate different factors associated with remote online home-based learning (thereafter named OHL), including technical system quality, perceived quality of contents, perceived ease of use, and perceived usefulness in relation to the satisfaction of undergraduate students following the post-COVID-19 pandemic in Malaysia. Additionally, the mediating roles of attitude are also investigated. Two hundred questionnaires were distributed using judgmental sampling method and 156 completed responses were collected. The data were subsequently analyzed using PLS-SEM. The findings imply that the OHL system is an effective method although it is challenging to operate. In terms of perceived technical system quality, OHL is currently more gratifying for students; however, some have reported that the quality of the content delivered via the remote system is still unsatisfactory. Moreover, the study found that attitude is a significant determinant of undergraduates’ satisfaction with OHL. This study contributes to the advancement of current knowledge by inspecting the factors of the Undergraduate Level OHL System using the mediating roles of attitude. In terms of underpinning theories, Technology Acceptance Model and Information System Model were employed as the guiding principles of the current study.

MORPHOLOGICAL ANALYSIS OF COMPOUNDING IN THE NOVEL THE BURNING MAZE: THE TRIALS OF APOLLO BY RICK RIORDAN

This research concerned a morphological analysis of compounding within The Burning Maze: The Trials of Apollo by Rick Riordan. This study morphologically described the importance of language in conveying deep emotion and thematic richness. This descriptive qualitative linguistic research employed the observation and auto-expert judgment methods for the data collection and morphological note-taking techniques for the data analysis. The results revealed patterns of word combinations that contributed to the linguistic richness and depth of the themes. The discussion interpreted these findings in the context of the novel’s storytelling, providing further understanding of the role of morphology in character development and plot complexity. The results showed that compounding in The Burning Maze: The Trials of Apollo by Rick Riordan had a combination of elements with the form of the Noun (N) + Verb (V); Noun (N) + Noun (N); Verb (V) + Verb (V); Adjective (Adj) + Noun (N); Verb (V) + Noun (N); Adverb (Adv) + Noun (N); Noun (N) + Adverb (Adv); Adjective (Adj) + Verb (V); Adjective (Adj) + Adjective (Adj); Adverb (Adv) + Adjective (Adj); Verb (V) + Adverb (Adv); Noun (N) + Adjective(Adj); Verb (V) + Adjective (Adj). Besides revealing linguistic nuances in literary works, this research has strived to deepen our understanding of the intricate layers within literature, showcasing how the careful selection of words enhanced the reader’s immersive journey into the literary landscape.

Development of a methodology for assessing the efficiency of an agribusiness enterprise in using digital technologies

The object of the study is the activity of an agribusiness enterprise in using digital technologies. The problem of the methodology for assessing the effectiveness of using digital technologies by an agribusiness enterprise is solved. The following results were obtained: – the author's methodology for assessing the effectiveness using of digital technologies by an enterprise of AIC based on expert evaluation and a system of indicators was developed. The assessment results are interpreted in accordance with the matrix of intersection of the digitalization index and the effect of digital technologies from Outsider (0–0.25; <1) to Leader (0.95–1; ≥1); – the obtained concordance coefficient (76 %, χ2=41.9) indicates high consistency of the expert group, consistency and qualitative assessment in the process of testing the methodology; – testing of the proposed methodology in Atameken-Agro JSC was successful and showed the validity and convenience of this methodology. The agro-enterprise became the leader in 2023 with the indicators of digitalization level – 0.83 and the effect of using digital technologies – 12.5. The above results are explained by assuming the possibility of using the expert judgment method to evaluate the efficiency of using digital technologies by an enterprise and applying a decision matrix based on two indices. A particular feature of the results obtained is the development of a methodology for assessing the level of digitalization in three main areas and its application in combination with the assessment of the economic effect of digital technologies. The proposed methodology can be used not only by enterprises wishing to evaluate the effectiveness of digital technologies but also by stakeholders.

Kinematic Analysis of Elite Indian National-level Sprinters: a Comprehensive Analysis

A comprehensive research study was undertaken involving ten national-level sprinters selected purposively from the athletics ground of Jawaharlal Nehru Stadium in New Delhi. The primary objective was to identify the key angles influencing movement during predefined steps in sprinting. The age range of the participants was 19 to 27 years, and the selection process followed purposive sampling. Descriptive statistics were employed to interpret the collected data, providing a summary of the sprinters' performances. The study considered various biomechanical aspects, including angles related to knee movement, hip articulation, and other relevant variables. The correlation between angular and linear variables was explored, and KINOVEA software was utilized for precise angle measurements, ensuring high accuracy in recording sprinters' movements. This technological approach facilitated a thorough examination of the kinematic aspects of their performance. Data collection employed a judgmental sampling method, and the results revealed significant relationships. Notably, there was a significant correlation between the angle at the right ankle joint and the angle at the right wrist joint at the 1st step. Additionally, a significant correlation was observed at the right knee joint at the 3rd step, indicating its contribution to the athletes' overall performance.

Teachers' perceptions of ethnomathematics learning in the independent curriculum program in Indonesia

This research aims to determine mathematics teachers’ perceptions of ethnomathematics learning in the independent curriculum program for the 2022/2023 academic year using a qualitative descriptive method. The results of the study were strengthened by quantitative methods to determine the relationship between the variables and the problems that influenced the study. The research sample comprised 60 mathematics teachers in Kudus Regency, Indonesia. The research instrument had a Cronbach’s alpha coefficient value of 0.826 through the expert judgment method, indicating its reliability. The results showed that the mathematics teachers’ perceptions of ethnomathematics learning in the independent curriculum program varied. One teacher (1.67%) saw it as very good, 25 teachers (41.67%) saw it as good, 27 teachers (45%) saw it as adequate, and seven teachers (11.67%) saw it as fair. The conclusion is that mathematics teachers in Kudus Regency, Central Java, have moderate perceptions of ethnomathematics learning in the independent curriculum program implemented in the 2022/2023 academic year. This research has benefits for teachers and school policies related to training, empowerment, and the development of independent curriculum ethnomathematics learning to obtain quality outcomes.

Softskill Base Arabic Language Teaching Model in Improving Talaqul Kalam for College Student in Universitas Sains Al-Quran Jawa Tengah Wonosobo

Arabic language learning has a major problem related to its renewal. Arabic language learning is always identical with grammatical (Qawa’id) aspects which seem to be rigid, complicated, and confusing. There are two major Arabic language learning orientations: as body of knowledge and mastery. The purpose of this research is to produce an Arabic language learning model based on soft skills to effectively improve the students’ Talaqah al kalaam at Universitas Sains Al-Qur’an (UNSIQ), Wonosobo, Central Java, Indonesia. This research was considered as a field study in the form of Research and Development (R&D) involving students from each faculty of Universitas Sains Al-Qur’an (UNSIQ), Wonosobo, Central Java, Indonesia. The research data were collected through observation, in-depth interview, questionnaire, test, and documentation. The collected data were then analyzed through several stages: (a) initial-product test analysis, (b) limited data trial result analysis, (c) extensive data trial result analysis, and (d) student learning response analysis. The research results showed that the Arabic language learning model based on soft skills had fulfilled the validity elements through Expert Judgment method and been considered very effective proven by the significant improvement in post-test results. This model was also proven practical proven by the test results showing that the supporting instruments, such as Course Learning Unit, Learning Module, Semester Learning Plan, Test Instrument, and Learning Implementation Sheet, were very good.

A mixed method evaluation of knowledge, attitude and practice on dengue fever among Lalitpur Metropolitan City residents: a cross-sectional investigation.

Dengue poses a significant global public health challenge, including in Nepal. Understanding community's knowledge, attitudes, and behaviors concerning dengue fever is imperative to developing effective prevention and control strategies. This study aimed to assess the knowledge, attitude, and practices related to dengue fever among residents of Lalitpur Metropolitan City. A descriptive cross-sectional household study was conducted using a mixed-method approach, which included quantitatively studying 636 individuals and conducting 20 qualitative interviews. The data was collected between April 2023 and June 2023. The multistage cluster sampling method was applied for household selection during the quantitative study and a purposive judgmental sampling method was used to identify participants for the qualitative interviews. Face-to-face interviews were conducted using a structured questionnaire for the quantitative study and an interview guide for the qualitative study. Quantitative data were analysed using logistic regression in STATA version 13, and thematic analysis was applied to the qualitative data. The findings were validated through triangulation of results from both the qualitative and quantitative study. Regarding knowledge, 64.94% (n = 413/636) reported being informed about dengue fever. In terms of attitude, a substantial majority, 91.51% (n = 582/636), expressed a positive attitudes toward dengue fever, indicating a favorable perception and knowledge of its significance. Concerning practice, 49.84% (n = 317/636) of respondents reported actively engaging in dengue fever prevention measures. The variables gender, previous history of dengue fever and residency were the determinants of dengue fever knowledge. Additionally, gender, residency, and attitude were predictors of preventive practices concerning dengue fever. Our study revealed that while the community demonstrated good knowledge of dengue fever and positive attitudes toward prevention, their preventive practices were inconsistent, indicating a gap between knowledge and action. A positive attitude was linked to better adherence to preventive measures. To address this gap, it is crucial to promote a positive attitude toward dengue prevention through initiatives like education efforts and social mobilization programs. Implementing Social and Behavior Change Communication (SBCC) programs focused on dengue prevention and control measures can help bridge this knowledge-action gap.

A Three-Dimensional Modeling Approach for Carbon Nanotubes Filled Polymers Utilizing the Modified Nearest Neighbor Algorithm.

Carbon nanotubes (CNTs) are extensively utilized in the fabrication of high-performance composites due to their exceptional mechanical, electrical, and thermal characteristics. To investigate the mechanical properties of CNTs filled polymers accurately and effectively, a 3D modeling approach that incorporates the microstructural attributes of CNTs was introduced. Initially, a representative volume element model was constructed utilizing the modified nearest neighbor algorithm. During the modeling phase, a corresponding interference judgment method was suggested, taking into account the potential positional relationships among the CNTs. Subsequently, stress-strain curves of the model under various loading conditions were derived through finite element analysis employing the volume averaging technique. To validate the efficacy of the modeling approach, the stress within a CNT/epoxy resin composite with varying volume fractions under different axial strains was computed. The resulting stress-strain curves were in good agreement with experimental data from the existing literature. Hence, the modeling method proposed in this study provides a more precise representation of the random distribution of CNTs in the matrix. Furthermore, it is applicable to a broader range of aspect ratios, thereby enabling the CNT simulation model to more closely align with real-world models.

Risk and benefits of expanded donor screening: A viewpoint from Germany.

This review describes the risks and benefits of expanding screening for transmissible pathogens in deceased organ donors. The focus is on the experience and procedure in Germany to make a decision on how to proceed with a possible donor. Three issues are of interest in how screening policies impact the process with the aim of mitigating unexpected transmission risks: (1) Should we add universal or targeted nucleic acid testing to serological tests for common blood-borne viruses (BBVs; HIV, HBV, and HCV)? (2) Which tests should be added for screening in a geographically restricted region beyond testing for these BBVs? (3) Being faced with changes (e.g., climate and population) in the own geographically restricted region, what strategies are needed before implementing new tests, and which considerations apply for proper indication to do this? Testing may only be effective when during donor characterization the appropriate conclusions are drawn from the existing findings and screening tests are initiated. This statement overlaps the need to implement universal screening for a pathogen or targeted screening based on the risk that the donor has acquired the transmissible pathogen or is not as possible to identify by current methods of clinical judgment and/or specific tests.

Research on signal denoising algorithm based on ICEEMDAN eddy current detection

This study addresses the challenges of non-stationarity and significant background noise interference in eddy current detection signals by proposing a noise reduction method based on Improved Complete Ensemble Empirical Mode Decomposition with Adapted Noise (ICEEMDAN). The process commences with the signal being decomposed using Improved Complete Ensemble Empirical Mode Decomposition with Adapted Noise into a finite number of Intrinsic Mode Functions (IMFs). Each Intrinsic Mode Function is then evaluated for the presence of high-frequency noise using a Power Spectral Density (PSD) analysis. The high-frequency noise present in the Intrinsic Mode Functions is then reduced using Normalized Least Mean Squares (NLMS) before being reconstructed with the remaining Intrinsic Mode Functions. Subsequently, the reconstructed signals are subjected to another round of decomposition using Improved Complete Ensemble Empirical Mode Decomposition with Adapted Noise. The Pearson Product Moment Correlation Coefficient (PPMCC) is utilised to calculate the correlation between the Intrinsic Mode Functions within each layer, retaining those with a strong correlation to further attenuate noise. Ultimately, the local maxima judgement method selectively amplifies defect signals by assessing changes in peak and valley degrees, thereby improving the signal-to-noise ratio of the eddy current detection signal. The experimental results demonstrate that, in comparison to the use of only the conventional Improved Complete Ensemble Empirical Mode Decomposition with Adapted Noise and Normalized Least Mean Squares denoising methods, the proposed method increases the Signal-to-Noise Ratio (SNR) by 1.08 dB and 2.31 dB, respectively, and decreases the Mean Square Error (MSE) by 106.9 and 223.9, respectively. The false alarm rate for stainless steel welded tubes with defects is 1.4%, while the false alarm rate for stainless steel welded tubes without defects is 0.4%.

A research on resistance spot welding quality judgment of stainless steel sheets based on revised quantum genetic algorithm and hidden markov model

In view of the following problems existed in the data-driven resistance spot welding (RSW) quality judgment methods: relying on expert experience, resulting in a high misjudgment rate; affected by the initial value, it is easy to fall into the local extreme point; multiple parameters needed to be modulated to increase the training time of the model. Therefore, this paper proposed a RSW quality judgment method based on revised quantum genetic algorithm (RQGA) and hidden markov model (HMM). Which used quantum rotation gate to replace the evolution process of genetic algorithm (GA), reducing the number of parameters that needed to be modulated in the model, and optimizing the initial model of HMM by RQGA to avoid falling into local extreme point. At the same time, combining expert experience with HMM to make quality judgment to ensure the accuracy of judgment.Firstly, by RSW test to obtain the main influencing factors of quality, and combining with expert experience to realize the preliminary judgment of it, on this basis, HMM was established. Next, to address the susceptibility of HMM to initial model, quantum genetic algorithm (QGA) was utilized to search for the optimal initial model. Moreover, in view of the limitations of QGA (“coding length disaster” and fixed rotation angle), a corresponding improvement was also presented. At last, the established model was applied to the RSW process of stainless steel sheets railway carriage roof. Compared with the other five models, it took the least time to complete parameter training of HMM in four quality states, less than 15s; when judging the quality, its log-likelihood probability value was −47.8418, which was close to the maximum value of this state; during the classification test, the average classification accuracy of the four quality states were 90.8 %, 92.2 %, 90.8 % and 92.0 %, respectively, which was higher than the other five models. Consequently, the model established in this paper was effective.