Method For Quantitative Analysis Research Articles

GT-CAM: Game Theory Based Class Activation Map for GCN.

Graph Convolutional Networks (GCN) have shown outstanding performance in skeleton-based behavior recognition. However, their opacity hampers further development. Researches on the explainability of deep learning have provided solutions to this issue, with Class Activation Map (CAM) algorithms being a class of explainable methods. However, existing CAM algorithms applies to GCN often independently compute the contribution of individual nodes, overlooking the interactions between nodes in the skeleton. Therefore, we propose a game theory based class activation map for GCN (GT-CAM). First, GT-CAM integrates Shapley values with gradient weights to calculate node importance, producing an activation map that highlights the critical role of nodes in decision-making. It also reveals the cooperative dynamics between nodes or local subgraphs for a more comprehensive explanation. Second, to reduce the computational burden of Shapley values, we propose a method for calculating Shapley values of node coalitions. Lastly, to evaluate the rationality of coalition partitioning, we propose a rationality evaluation method based on bipartite game interaction and cooperative game theory. Additionally, we introduce an efficient calculation method for the coalition rationality coefficient based on the Monte Carlo method. Experimental results demonstrate that GT-CAM outperforms other competitive interpretation methods in visualization and quantitative analysis.

Unveiling the Impact of Emotional Regulation on Academic Procrastination

This study examines how consumer perceptions of the Skintific brand, product quality, and pricing influence product selections among 110 FBHIS students at Muhammadiyah University of Sidoarjo. Using online questionnaires and quantitative analysis methods, including validity and reliability tests, multiple linear regression, and t-tests, the research reveals significant relationships between brand image, product quality, pricing, and consumer purchasing decisions. The findings emphasize the importance of these factors in shaping consumer behavior, particularly among university students, and offer insights for skincare companies targeting this demographic to enhance brand image, maintain product quality, and offer competitive pricing strategies. Highlight: Quantitative Analysis: Validity, reliability tests, regression for consumer behavior research. University Sample: Investigated FBHIS students' purchasing choices at Sidoarjo University. Strong Associations: Brand image, product quality, pricing linked to consumer decisions. Keywoard: Consumer perceptions, Skintific brand, Product quality, Pricing, Decisions

Stations of the Publicum Portorium Illyrici are a Strong Predictor of the Mithraic Presence in the Danubian Provinces: Geographical Analysis of the Distribution of the Roman Cult of Mithras

Abstract The article examines the relationship between the Roman cult of Mithras and members of the publicum portorium Illyrici, the Roman customs office active in the Danubian provinces, who have been discussed in previous research as potentially important carriers of this cult. To investigate this relationship and its extent, spatial proximity analysis is performed with respect to documented portorium stations and confirmed Mithraic finds. For comparative purposes, the spatial proximity between portorium stations and finds relating to other selected Graeco-Roman deities was also examined. On the basis of the results of this analysis, it is possible to conclude that Mithraic finds are located significantly closer to customs stations than those of other Graeco-Roman deities (with the exception of Jupiter, the main Graeco-Roman god) and that the presence of a portorium station strongly predicts the presence of a Mithraic cult at a given site or in its immediate vicinity, especially in the Western cluster of portorium provinces. Thus, in a nuanced form and using a quantitative method of geographical analysis, the study supports previous conclusions about the importance of portorium officials as a social group significantly involved in the spread of the Roman cult of Mithras in the Danubian provinces.

Application of Natural Science Methods in Social Science Research

The introduction of natural science methodologies into social science research aims to enhance the scientific rigor and validity of studies through precise techniques. By employing quantitative analysis, data mining, and model construction, researchers are able to delve deeper into the complexities of social phenomena, injecting new vitality into traditional qualitative research. Quantitative analysis methods render research outcomes more objective and reproducible, while data mining techniques can extract underlying patterns and trends from vast amounts of data. Model construction offers a systematic understanding of social dynamic processes, supporting the prediction and intervention of future social developments. Computer simulation technologies, particularly with the backing of big data and high-performance computing, enable hypothesis testing and virtual experiments on social systems, allowing for multi-level and multi-perspective observations of social phenomena. This interdisciplinary integration not only provides new research tools and methodologies for the social sciences but also effectively fosters the interchange of knowledge between different disciplines. However, continuous reflection and adjustment in practical applications are necessary to address the potential pitfalls and limitations that may arise from the complexity of these methods.

Research on Multi-Objective Evolutionary Algorithms Based on Large-Scale Decision Variable Analysis

Large-scale high-dimensional many-objective optimization problems (LaMaOPs) are prevalent in fields such as autonomous driving, cloud resource scheduling, and smart grids. LaMaOPs involve a large number of decision variables and multiple conflicting objectives that need to be optimized simultaneously. The challenges posed by the curse of dimensionality due to the vast number of decision variables, and the conflict between convergence and diversity caused by the numerous objective variables, make traditional optimization methods inadequate. To address these issues, this paper proposes a two-population cooperative evolutionary algorithm based on large-scale decision variable analysis (DVA-TPCEA). This algorithm integrates quantitative analysis methods for decision variables to deeply examine their impact on each objective and introduces a contribution-based objective detection method. Additionally, a dual-population cooperative evolution mechanism is employed, with targeted optimization strategies designed for convergence and diversity populations, achieving synergistic and complementary optimization between the two populations. To validate the algorithm’s effectiveness in practical applications, a large-scale container resource scheduling strategy based on the DVA-TPCEA algorithm is also proposed. The experimental results indicate that the proposed algorithm demonstrates significant advantages in both general datasets DTLZ, WFG, and LSMOP, and practical models.

Planning and Construction Strategies for Infrastructure in Traditional Villages of the Grand Canal from the Perspective of Villager Needs

The traditional villages along the Jiangsu section of the Grand Canal are facing the threat of decline and disappearance due to the decline of the canal transportation function and the advancement of urbanization, and it is urgent to study the protection and renewal of these villages. Based on the needs of villagers, this study aims to explore the planning and construction strategies of traditional village infrastructure in the Jiangsu section of the Grand Canal. Through a literature review, field investigation, and qualitative and quantitative analysis methods, this paper conducts in-depth research and data analysis on the status quo of six types of infrastructure in 29 traditional villages, including road traffic, water supply and drainage, garbage sanitation, energy utilization, postal communication, and ecological disaster prevention. The research results show that, although the infrastructure construction has made some progress, there are still problems such as unreasonable planning, low construction quality, and the lack of cultural characteristics, which cannot fully meet the actual needs of villagers. Through a regional comparative analysis, it is found that the infrastructure condition of the Jiangnan Canal section is better than that of the Huaiyang Canal section and Middle Canal section, but they all face challenges of protection and renewal. Based on the needs of villagers, this study puts forward corresponding protection and optimization strategies, which provide theoretical guidance and practical methods for the sustainable development of traditional village infrastructure, and it has important reference significance for the infrastructure protection and development of traditional villages in other regions.

Use of spectral transmittance model to improve the detection accuracy of chromium in soil

As a new quantitative analysis method for heavy-metal elements in soil, the main function of the polarization resolution model is to filter out the disturbance of other elements on the spectral signal of target plasma. In order to quantify the mechanism of improving detection performance, the spectral transmittance of plasma intensity in the polarization-resolved optical path has been derived, and the relationship between the intensity of polarization-resolved laser-induced breakdown spectroscopy (PRLIBS) and the characteristic peak wavelength has been defined. Using the spectral data in the wavelength range of 424.50–429.24 nm as the characteristic signal, a quantitative analysis method for detection of the Cr element in soil has been developed. The improvement of spectral intensity stability at the characteristic peak of Cr I 425.7 was analyzed, and the mechanism of enhancing the detection accuracy was elucidated. Research has shown that, based on the polarization characteristics of Cr element plasma, PRLIBS is not affected by the matrix effects of soil and characterizes the amplitude conversion from the reference concentration of Cr element to the plasma spectral intensity. The spectral transmittance of plasma spectra depends not only on the characteristic peak wavelength and complex refractive index of heavy-metal elements but also on the measurement conditions such as spatial geometric angles and reflectivity of the transmission medium.

Communication Strategies & Mobile Banking Adoption

This article, as research study, employed a mixed method research approach; which utilized both qualitative and quantitative methods of data collection and analysis. The utilised tools were an interview schedule and questionnaires. A target population of 3000 customers and 17 staff members from whom the sample of 353 respondents among the bank customers all 17 staff members purposively were selected. Simple stratified random sampling and purposive sampling were applied in selecting customers and staff members for the study respectively. Quantitative data collected was analysed using descriptive statistics and presented in form of tables, graphs and charts. The qualitative statistics were analysed thematically. Its findings revealed that good communication strategies influenced mobile banking adoption by enhancing the good corporate relationship with customers through word of mouth rated at 84.4 %, social media at 71.8%and mass media communication at 68.9%. It recommends creating awareness and elevating customers’ attitude by making the mobile banking platform affordable, easy and accessible to customers of all segments, easing the customers into the technology rather than forcing it on them while being innovative to stay competitive in the current market.

Thermo-electric coupling dynamic modeling and response behavior analysis of PEMEC based on heat current method

Complete analysis of the dynamic characteristics of the proton exchange membrane electrolytic cell (PEMEC) is significant for its efficient and flexible utilization. To fully reflect the dynamic process including thermo-electric interactions within PEMEC, this paper disassembles this process and simplifies it for representation through a clear diagram of dynamic power flow. On this basis, we proposed a novel combined qualitative and quantitative analytical method for the comprehensive response by defining the evaluating indexes for PEMEC's response performance. Meanwhile, we analyzed the change pattern of dynamic response behavior, response time and the influence of thermo-electric interaction under multi-scenarios, like different voltage abrupt change magnitudes, different cathode operating pressures, and different inlet water temperatures. The results show that the PEMEC has the biggest response behavior with the longest response time under the largest external voltage variation magnitude. Besides, there is the shortest response time and smallest parameters total changes after response when the cathode operating pressure is 15bar Moreover, when the inlet water temperature is 40 °C it has the characteristic of quick action time and small response magnitude. The model, analysis method, and findings in this paper provide an effective reference for the operational regulation of PEMEC's thermal and electrical parameters.

Numerical Simulation of Electromagnetic Nondestructive Testing Technology for Elasto–Plastic Deformation of Ferromagnetic Materials Based on Magneto–Mechanical Coupling Effect

A numerical tool for simulating the detection signals of electromagnetic nondestructive testing technology (ENDT) is of great significance for studying detection mechanisms and improving detection efficiency. However, the quantitative analysis methods for ENDT have not yet been sufficiently studied due to the absence of an effective constitutive model. This paper proposed a new magneto–mechanical model that can reflect the dependence of relative permeability on elasto–plastic deformation and proposed a finite element–infinite element coupling method that can replace the traditional finite element truncation boundary. The validity of the finite element–infinite element coupling method is verified by the experimental result of testing electromagnetic analysis methods using TEAM Problem 7. Then, the reliability and accuracy of the proposed model are verified by comparing the simulation results under elasto–plastic deformation with experimental results. This paper also investigates the effect of elasto–plastic deformation on the transient magnetic flux signal, a quantitative hyperbolic tangent model between Bzpp (peak–peak value of the normal component of magnetic flux signal) and elastic stress, and the exponential function relationship between Bzpp and plastic deformation is established. In addition, the difference and mechanism of a magnetic flux signal under elasto–plastic deformations are analyzed. The results reveal that the variation of the transient magnetic flux signal is mainly due to domain wall pinning, which is significantly affected by elasto–plastic deformation. The results of this paper are important for improving the accuracy of quantitative ENDT for elasto–plastic deformation.

Achieving successful gas plant construction: A risk modelling framework with quantitative risk-based approach to schedule management

The construction of gas plants often experiences delays caused by various factors, which can lead to significant financial and operational losses. This research aims to develop an accurate risk model to improve the schedule performance of gas plant projects. The model uses Quantitative Risk Analysis (QRA) and Monte Carlo simulation methods to identify and measure the risks that most significantly impact project schedule performance. A comprehensive literature review was conducted to identify the risk variables that may cause delays. The risk model, pre-simulation modeling, result analysis, and expert validation were all developed using a Focused Group Discussion (FGD). Primavera Risk Analysis (PRA) software was used to perform Monte Carlo simulations. The simulation output provides information on probability distribution, histograms, descriptive statistics, sensitivity analysis, and graphical results that aid in better understanding and decision-making regarding project risks. The research results show that the simulated project completion timeline after mitigation suggested an acceleration of 61–65 days compared to the findings of the baseline simulation. This demonstrates that activity-based mitigation has a major influence on improving schedule performance. This research makes a significant contribution to addressing project delay issues by introducing an innovative and effective risk model. The model empowers project teams to proactively identify, measure, and mitigate risks, thereby improving project schedule performance and delivering more successful projects.

Integration of bifunctional silver dendrite membranes with surface-enhanced Raman scattering for sensitive detection of polystyrene microplastics in aquatic environments

Microplastics (MPs) are emerging environmental pollutants that are present in aquatic environments and accumulate within the food chain, posing significant threats to human health. Over 8 million tons of MPs enter these ecosystems annually. However, existing rapid qualitative and quantitative analytical methods for trace MPs are limited, hindering comprehensive research on their impact in water environments. This study presents a novel composite membrane with both adsorption and filtration functions, integrated with surface enhanced-Raman scattering technology for detecting trace MPs in water. The silver dendrites, modified with n-hexanethiol and loaded onto filter paper, facilitate enhanced enrichment and simultaneous sensitive detection of MPs. The composite membrane exhibited excellent retention rates for standard polystyrene (PS) MPs of various sizes (200, 500, and 1000 nm), achieving high enrichment efficiency. Sensitive detection was realized with a linear response in a concentration range of 0.01 to 0.5 g/L, yielding optimal enhancement factors exceeding 2.92 × 103, enabling detection at μg/L levels. Recovery rates for PS in spiked environmental water samples ranged from 96.86 % to 102.96 %. This innovative method offers a promising approach for the rapid and sensitive detection of trace MPs in aquatic environments, contributing significantly to the assessment of MPs pollution.

Analisis Efisiensi Biaya Tenaga Kerja Langsung pada PT. Davincy Airindo

This study was conducted with the aim to determine the efficiency of direct labor costs carried out by the company PT Davincy Airindo. In this study using literature review and observation, namely by conducting research in the field through direct interviews and data collection, related documents from the company through internet media. The data obtained is analyzed using the quantitative descriptive analysis method, namely how to compare labor costs that actually occur (actual). The results of the analysis will show whether direct labor costs are used efficiently to produce a product. This shows that Direct Labor Cost Control is in the efficient and stable category (in control).

Film Policy and Film Distribution: The Case of the Baltic Film Industries

Abstract The aim of the study is to analyse the development of the Baltic film distribution markets and to provide new recommendations for its potential growth based on mission economy approach and bigger role of the states in co-creating and co-shaping the markets especially for the Baltic co-production of films and their distribution. The study used both qualitative and quantitative methods for data extraction and analysis. Firstly, descriptive statistics as a method was used to analyse the market shares of the main film distribution companies in Lithuanian, Latvian and Estonian film industries. Furthermore, 5 semi-structured interviews with experts from the Baltic film industries were conducted. As a result of the research, the author concludes that there is a potential in family genre films that are produced in the Baltic States, but in general the Baltic co-production films lack quality, storytelling that would arouse the interest of the audience and potentially new regional film fund “Baltic Film and TV Fund” would have to focus not only on increased financing for co-productions, but also on other measures that would help to produce better quality genre films including co-productions and their distribution.

Negative and Positive Experiences During the COVID-19 Pandemic in Canadians With Developmental Disabilities: AOne-Year Ontario-Based Survey.

Understanding the experiences of people with developmental disabilities during the initial period of COVID-19 pandemic. Individuals with developmental disabilities and their caregivers completed baseline and up to five follow-up online surveys using the CRISIS-AFAR measures, between July 2020 and September 2021. We used qualitative (thematic analysis) and quantitative (MANOVA) analytic methods. One hundred and eighteen participants (64 caregivers on individuals 6-62 years, 54 self-reporting individuals aged 17-55 years) completed baseline survey; 46 participants (23 caregivers, 23 self-reporting adults) completed ≥1 follow-up. Qualitative themes included uncertainty, and negative and positive influences on behaviours and routines, daily life and mental wellness. Those experiencing positive impacts did not stably perceive so longitudinally. Despite both negative and positive influences on individuals with developmental disabilities and their families, the prolonged pandemic had wide-ranging repercussions. Emergency preparedness planning should consider the disruptive effects of public health measures on routine and support for this vulnerable population.

Quantitative Decoupling Analysis for Assessing the Meteorological, Emission, and Chemical Influences on Fine Particle Pollution

AbstractA comprehensive understanding of meteorological, emission and chemical influences on severe haze is essential for air pollution mitigation. However, the nonlinearity of the atmospheric system greatly hinders this understanding. In this study, we developed the quantitative decoupling analysis (QDA) method by applying the Factor Separation (FS) method into the model processes to quantify the effects of emissions (E), meteorology (M), chemical reactions (C), and their nonlinear interactions and impact on fine particulate matter (PM2.5) pollution. Taking a heavy‐haze episode in Beijing as an example, we show that different from the integrated process rate (IPR) and the scenario analysis approach (SAA) in previous studies, the QDA method explicitly demonstrate the nonlinear effects by decomposing the variation of PM2.5 concentration into individual contributions of E, M and C terms as well as the contributions from interactions among these processes. Results showed that M dominated the hourly fluctuation of the PM2.5 concentration. The C terms increase with increasing the level of haze, reaching maximum (0.37 μg m−3 h−1) at the maintenance stage. Moreover, our method reveals that there are non‐negligible non‐linear effects of meteorological, emission, and chemical processes during pollution stage, with the mean accounting for 50% of the increase in PM2.5 concentrations, which is often ignored in the current air pollution control strategies. This study highlights that the QDA approach can be used to gain insight into the formation of heavy pollution, and to identify uncertainty in numerical models.

MQGA: A quantitative analysis of brain network hubs using multi-graph theoretical indices

Recent advancements in large-scale network studies have shown that connector hubs and provincial hubs are vital for coordinating complex cognitive tasks by facilitating information transfer between and within specialized modules. However, current methods for identifying these hubs often lack standardized measurement criteria, hindering quantitative analysis. This study proposes a novel computational method utilizing multi-graph theoretical index calculations to quantitatively analyze hub attributes in brain networks. Using benchmark network, random simulation network (N = 100), resting fMRI data from the ADHD-200 NYU dataset (HC = 110, ADHD = 146), and the Peking dataset (HC = 120, ADHD = 83), we introduce the Multi-criteria Quantitative Graph Analysis (MQGA) method, which employs betweenness centrality, degree centrality, and participation coefficient to determine the connector (con) hub index and provincial (pro) hub index. The method's accuracy, reliability, and stability were validated through correlation analysis of hub indices and labels, vulnerability tests, and consistency analysis across subjects. Results indicate that as network sparsity increases, the con hub index increases while the pro hub index decreases, with the optimal hub node index at 4 % sparsity. Vulnerability tests revealed that removing con nodes had a greater impact on network integrity than removing pro nodes. Both con and pro exhibited stability in consistency analyses, but con was more stable. The stability of hub scores in disease groups was significantly lower than in the healthy control group. High con values were found in the precuneus, postcentral gyrus, and precentral gyrus, whereas high pro values were identified in the precentral gyrus, postcentral gyrus, superior parietal lobule, precuneus, and superior temporal gyrus. This approach enhances the accuracy and sensitivity of hub node identification, facilitating precise comparisons and producing consistent, replicable results, advancing our understanding of brain network hub nodes, their roles in cognitive processes, and their implications for brain disease research.

Quantifying pigment features of Thangka Five Buddhas using hyperspectral imaging

Thangka, a masterpiece of Tibetan painting, is renowned for its adept use of natural mineral pigments such as gold, turquoise, and cinnabar, which imbue it with profound artistic and historical significance. Presently, chemical analysis methods relying on microscopic perspectives are prevalent in researching the pigment components of cultural artifacts. However, these methods suffer from quantization gaps and carry the risk of damaging the relics. Hence, in this study, we focus on Thangka Five Buddha as our experimental sample and propose a novel approach utilizing Linear Spectral Mixed Analysis (LSMA) based on Hyperspectral Imaging (HSI) technology to perform quantitative analysis of pigment components at a sub-pixel level. The results indicate the following. 1) A database of spectral curves for 25 representative Thangka pigments was established, covering 196 bands from 393 to 800 nm VIR-NIR range. 2) The LSMA model successfully separated the 13 pigment components of the Thangka at the sub-pixel level, achieving a Root Mean Square Error (RMSE) of 0.0186, which indicates high classification accuracy. 3) The quantitative analysis reveals that 33.07 % of the area is painted using a single pigment, while 56.01 % is painted using a combination of two pigments. Verdigris (18.56 %), malachite (17.52 %), and cinnabar (10.91 %) are the pigment types with the highest proportions among them. Out of the 521 pigment combinations, verdigris and turquoise (4.55 %), malachite and calcite (4.02 %), minium and cinnabar (2.87 %), and turquoise and malachite (2.82 %) are more commonly used. 4) The application of quantitative analysis methods demonstrates significant potential in painting techniques, authentication processes, and establishing historical dating, among other areas of study.

Rockery morphology based on quantitative analysis of shading

The rockeries of classical Chinese gardens are masterpieces of classical Chinese garden art and form a key element of garden heritage. Consequently, a quantitative study of “rockery shadows” is of considerable importance to the study of “rockery forms.” In this study, we selected the representative North Rockery in Zhanyuan Garden of Nanjing and Ruiyunfeng, Guanyunfeng, and Yulinglong as the objects of the study. This study aims to explore the shadow images of rockeries using image extraction and targeted quantitative analysis methods. Macroscopically, the overall shape of rockery shadows was described using fractal dimensions; microscopically, the aspect ratio, angle, and refinement indexes of each shadow based on each observation angle of the rockery were measured using the PAT-GEOM plug-in in ImageJ software. SPSS Statistics was used for the normal distribution test of the angular distribution data. Consequently, the shadow data of the North Rockery in Zhanyuan Garden and Ruiyunfeng, Guanyunfeng, and Yulinglong, respectively, were analyzed and compared, and four rockery-shadow laws were derived. Finally, the results were applied to the design of the rockery morphological translation based on quantitative analysis of the shadows. The approach presented here will enhance landscape design, support environmental planning, and preserve cultural heritage.

Analysis of Chemistry Interest Level in Merdeka Curriculum Implementation at SMA Negeri 8 Pontianak

Elective subject is the flagship program of Merdeka Curriculum..The elective subject program is based on students’ interest, talents, and aspirations. Therefore, students’ interest level in chemistry, as one of the options for elective subject program is a necessary to determined. This study aims to determine the level of student interest in choosing chemistry as an elective subject, so that teachers could find the best alternatives to increase students’ interest. The research was conducted with quantitative analysis methods and descriptive statistical approaches, using 139 students of grade 11th who have chosen chemistry as the elective subject. The level of students’ interest in chemistry is measured by students’ interest questionnaire. The questionnaire was adopted and developed by aspects of students’ interest: teachers’ role, students’ perception, students’ intrinsic motivation in learning, and meaningful learning of lesson. Content validation test using Aiken formula showed the questionnaire validity is very high, as value 1. Based on the analysis, the result stated that the level of students’ interest was included as high category with 76,11%. All aspects are categorized as high, aspects of the teacher's role in learning with 77.44%, students’ perceptions with 73.63%, students’ intrinsic motivation 78.99% and the meaningfulness of learning lesson with 74.37%.