Specific Frame Research Articles

Precursor of privacy leakage detection for individual user

The pursuit of dividends from the burgeoning realm of data traffic has emerged as a prevailing trend. Given this current state of affairs, the safeguarding of personal information has become an urgent task. Current methods for personal privacy protection primarily offer alerts when information breaches occur, but at that stage, irreversible breaches have already transpired. Thus, the study of preemptive privacy breach prediction is a task of significant importance within the realm of privacy protection. However, the endeavor to predict privacy breaches in advance remains exceedingly challenging, owing to several factors: (i) The complexity of social networks gives rise to high-dimensional features. (ii) Concerning the comprehensive and precise capture of pathways leading to information leakage. (iii) How to employ time series data effectively to realize early predictions.This study proposes a novel approach for constructing graph neural networks and forecasting privacy breaches, centered on the context of user-generated content within specific time frames, integrates spatial graph structures with temporal series information. The integration can entirely achieve the advance prediction of users' privacy status, thereby preventing information leakage. Empirical tests on real-world datasets demonstrate that our approach surpasses traditional time series forecasting methods in privacy breach predictions, achieving a notable average improvement of 2% in F1 score, Recall, and Precision metrics.

Coinciding storm surge and wave setup: A regional assessment of sea level rise impact

Coastal locations around the world face the multifaceted challenge of rising sea levels, posing threats to coastal communities, particularly during storm surges and high wave conditions. We have examined the dynamics of sea-level fluctuations along Denmark’s coastline, with focus on wave-induced phenomena, such as wave setup. We analysed wave data from DMI’s operational model spanning from 2006 to 2022, as well as climate projections that extend until the middle of the 21st century. We conducted an analysis of the 2% exceedance of the significant wave height maxima during specific time frames (denoted “storm days”) and “storm surge conditions” (the maximum sea level within a 30-year period). We found that the impact of climate change on extreme wave events was insignificant when focusing solely on the wave component, but heightened wave setup during “storm surge conditions” along the north-western coasts of Jutland. In this area, there is a notable increase in wave setup due to longer swells, ranging from 5 to 10 cm, by the mid-century, which is double the current wave setup in the region. Interestingly, other parts of the country did not show significant changes in wave setup. This regional variation highlights the nuanced impact of wave-induced processes on sea level dynamics and underscores the need for tailored adaptation strategies targeting specific vulnerable zones.

Predicting Airline Ticket Prices Using Machine Learning Predicting Airline Ticket Prices Using Machine Learning

Airfare prices are constantly changing due to various factors like the time of flight, destination, and length of the trip. To help people figure out the best time to buy tickets, we are working on a system that will use machine learning to predict prices. By studying past flight data in India, we want to uncover pricing patterns and suggest the ideal time to purchase tickets. This project aims to confirm or dispel common beliefs about airlines by comparing prediction models and finding ways to save money on ticket purchases. Price trends can vary significantly based on various factors such as the route, month, day, time of departure, holidays, and the airline carrier. Competitive routes like major business destinations (Mumbai-Delhi) tend to see price increases closer to the departure date. On the other hand, routes like tier 1 to tier 2 cities (Delhi-Guwahati) have specific time frames when prices are lower. The data also shows that there are two main categories of airline carriers in India: economical and luxurious. Generally, the lowest-priced flights fall under the economical group. Moreover, the data confirms that specific times of the day tend to have higher prices. By including different routes in this project, there is a potential for substantial savings when buying domestic flight tickets in India. Key Words: Airline Ticket, Pricing strategies, Fare fluctuations, Competitor analysis, Market trends

Characterising Modal Formulas with Examples

We study the existence of finite characterisations for modal formulas. A finite characterisation of a modal formula φ is a finite collection of positive and negative examples that distinguishes φ from every other, non-equivalent modal formula, where an example is a finite pointed Kripke structure. This definition can be restricted to specific frame classes and to fragments of the modal language: a modal fragment ℒ admits finite characterisations with respect to a frame class ℱ if every formula φ ∈ ℒ has a finite characterisation with respect to ℒ consisting of examples that are based on frames in ℱ. Finite characterisations are useful for illustration, interactive specification and debugging of formal specifications, and their existence is a precondition for exact learnability with membership queries. We show that the full modal language admits finite characterisations with respect to a frame class ℱ only when the modal logic of ℱ is locally tabular. We then study which modal fragments, freely generated by some set of connectives, admit finite characterisations. Our main result is that the positive modal language without the truth-constants ⊤ and ⊥ admits finite characterisations w.r.t. the class of all frames. This result is essentially optimal: finite characterisability fails when the language is extended with the truth constant ⊤ or ⊥ or with all but very limited forms of negation.

Rockburst early warning based on microseism and critical point theory

During the tunnel construction, rockbursts occurred, posing a risk to safety. To mitigate this risk, a microseismic monitoring system was installed in the tunnel to provide early warning of rockbursts. After conducting research on the evolution of microseismic events in terms of number, moment magnitude, and energy within a specific time frame, an approach for rockbursts risk assessment based on microseismic moment magnitude was proposed. The critical point theory was utilized to quantitatively analyze the energy release process of the surrounding rock before intense rockbursts. This analysis revealed that the energy release of the surrounding rock before rockbursts can be divided into three stages: stable energy release stage, transitional energy release stage and accelerated energy release stage. The obtained process, derived from the critical point theory, was compared and analyzed alongside the evolution process of value of b, cumulative apparent volume, and energy index.

Impact of detraining on the health of individuals with spinal cord injury: a systematic review

Introduction: Spinal cord injury (SCI) is a debilitating condition that causes motor, physiological, and sensory impairments, potentially leading to permanent disability, increased morbidity, and mortality, ultimately impacting an individual's quality of life (QoL). Physical exercise emerges as an effective alternative to mitigate these consequences and uphold the autonomy and QoL for this population. Detraining (DT), defined as the partial or total loss of adaptations induced by physical training in response to its complete interruption or insufficient stimulus, represents a significant concern. The objective of this systematic review was to conduct a comprehensive literature review regarding the current state of knowledge on the potential impacts of DT on the health of individuals with SCI. Method: The search was conducted on PubMed, Web of Science, Embase, SPORTDiscus, and Cochrane databases using relevant English terms (("Detraining") AND ("Spinal Cord Injury")) and their synonyms. Due to the limited number of studies addressing this topic, no specific time frame was set for study eligibility. Results: The literature search was performed in November 2023, yielding 42 results, from which 15 remained after removing duplicates. Two articles were excluded following title analysis. Thirteen abstracts were reviewed, and 7 were excluded, leaving 6 articles for full analysis. Due to the nature of the studies, a meta-analysis was not conducted. Conclusion: DT resulted in alterations in body composition (BC), including increased body fat and reduced muscle mass, especially following the interruption of testosterone-associated training. Additionally, the cessation of training impacted the metabolic profile, leading to changes in glucose, lipids, and insulin sensitivity. Furthermore, hemodynamic variables, such as blood pressure (BP) and heart rate (HR), underwent changes, elevating the risk of cardiovascular complications. Regarding cardiorespiratory components, there was a decline in peak oxygen consumption (VO2peak) following the DT period. Halting exercise can lead to detrimental health consequences, underscoring the imperative of maintaining consistent physical training for these individuals.

Cognitive Performance in the Digital Era

Generational categories classify individuals born in specific time frames, known for unique traits and tech adaptability. Some research indicates that the digital-native generation is more prone to distractions than other groups. However, the underlying mechanism is unclear and influenced by many factors, such as stress. In the current study (n=299), the authors leveraged the mobile monitoring of cognitive change (M2C2) symbol search task to measure processing speed. This study examines the relationships between generational categories (Gen X, Millennials, and Gen Z), perceived stress, subjective age (considered to predict important aspects of well-being beyond chronological age), and distraction cost. These results emphasize the significant influence of age-related variables and stress in shaping susceptibility to distractions. Future research can expand participant numbers, conduct longitudinal studies to track cognitive changes in digital-era generational cohorts, and explore neurocognitive mechanisms and technological fluency's role in distraction susceptibility.

Efficient removal of methylene blue and methyl red dyes using a novel adsorbent derived from Saponaria officinalis Root via H3PO4, H2SO4, and KOH-activation: Optimization, kinetics, and isotherm study

This study focuses on the optimization, kinetics, and isotherms of a novel adsorbent derived from Saponaria officinalis root for efficient removal of methylene blue and methyl red dyes. The preparation of the activated carbon involved specific parameters such as activating agents, impregnation time, and activation temperature. Results indicated a robust adsorption capacity, with the Langmuir isotherm model fitting well to the experimental data. The pseudo-second-order kinetic model demonstrated high applicability, highlighting the potential of the developed adsorbent for wastewater treatment applications. The adsorbent exhibited impressive iodine adsorption capacities ranging from 336.42 to 1250.09 mg/g, with efficient removal rates of over 95% for methylene blue and 75% for methyl red dyes within specific time frames.

The Influence of ZIS, Islamic Human Development Index, and Investment on Indonesia's Economic Growth: An ECM Model Analysis

Economic growth refers to the generation of additional income for a society within a specific time frame through economic activities. This is often measured by GDP. However, despite an increase in GDP, Indonesia's economic growth as a developing country is still considered unoptimal. Therefore, the purpose of this research is to analyze the impact of ZIS, I-HDI, FDI, and Domestic Investment on Indonesia's economic growth from 2013 to 2022, spanning ten years. This study adopts a quantitative approach and uses an ECM model. The findings indicate that ZIS, I-HDI, and Domestic Investment have a significant positive long-term effect on economic growth, but their impact is not significant in the short term. Conversely, FDI has an insignificant negative effect on both long-term and short-term economic growth. When analyzing all the factors simultaneously, the results demonstrate that ZIS, I-HDI, FDI, and Domestic Investment collectively have a significant effect on economic growth in both the long and short term. Building on these findings, policymakers should delve deeper into the specific mechanisms through which ZIS, the Islamic Human Development Index, FDI, and Domestic Investment influence economic growth in both the short and long term. By understanding the intricate connections between these factors and economic growth, policymakers can develop more targeted and effective strategies to promote sustainable and balanced economic development.

Developing an Assessment Battery to Measure Exposure to Police Brutality on Social Media Among Black Adolescents

This study aims to investigate the impact of police brutality exposure on social media among Black adolescents, recognizing its profound influence on attitudes and perceptions. The research developed the PBE-SM self-report assessment battery through an iterative process, involving qualitative interviews and cognitive assessments with Black first-year college students. The battery comprises five instruments, each probing specific time frames to capture the dynamic nature of social media exposure. For each instrument, all ten items were submitted to an exploratory factor analysis, revealing distinct structures, and providing psychometric evidence of construct validity and the utility of a multifaceted approach in understanding how perceptions evolve over time. The study emphasizes the practical applications of PBE-SM for researchers, educators, and counselors. It facilitates real-time monitoring of Black adolescents' exposure, aiding counselors in recognizing periods of heightened exposure and guiding stress management. Educators can use the tool for positive social media integration in academic settings. While limited to Black college undergraduates, future research aims to establish external validity across diverse demographics. In conclusion, PBE-SM represents an innovative tool for comprehending and addressing the psychological well-being of Black adolescents amidst prevalent exposure to police brutality on social media.

If you were happy and you know it, clap your hands! Testing the peak-end rule for retrospective judgments of well-being in everyday life

The experience sampling method (ESM) and comparable assessment approaches are increasingly becoming popular tools for well-being research. In part, they are so popular because they represent more direct approaches for assessing individuals’ experienced well-being during a specified period, whereas one-time, retrospective evaluations of that episode are believed to introduce systematic biases. Along these lines, the peak-end rule states that the most extreme and recent sensations of an episode disproportionally influence retrospective well-being judgments. However, it has yet to be determined whether such systematic effects found in experimental laboratory studies generalize to retrospective judgments of well-being in everyday life as captured in ESM studies. Across four ESM samples (overall N = 1,889, total measurements = 131,575), we found that retrospective well-being judgments were disproportionately influenced by the peak and end experiences from the assessment period. However, these effects depended on the item framing of the retrospective judgment (global vs. more specific framings) and broad versus narrow conceptualizations of peaks and ends (states, days, and weeks), pointing toward potential ways to mitigate peak/end effects. Our findings emphasize the importance of differentiating between momentary and retrospective well-being assessments and selecting an appropriate measurement approach on the basis of these conceptual considerations.

A comprehensive Exdia TRF-LFIA for simultaneous quantification of GFAP and NT-proBNP in distinguishing ischemic and hemorrhagic stroke

The goal of this study is to create a highly sensitive time-resolved fluorescence lateral flow immunoassay (TRF-LFIA) capable of concurrently measuring glial fibrillary acidic protein (GFAP) and the N-terminal fragment of B-type natriuretic peptide precursor (NT-proBNP). This assay is designed as a diagnostic tool and aims to provide an algorithm for stroke management, specifically for distinguishing between Ischemic stroke (IS) and Hemorrhagic stroke (HS). However, LFIA to quantify simultaneous serum NT-proBNP and GFAP are not yet available.We have developed and validated a novel TRF-LFIA for the simultaneous quantitative detection of NT-proBNP and GFAP. The sensitivity and reproducibility of the immunoassay were significantly improved by employing specific monoclonal antibodies linked to europium nanoparticles (EuNPs) that specifically target NT-proBNP and GFAP. The detection area on the nitrocellulose membrane featured sandwich-style complexes containing two test lines for NT-proBNP and GFAP, and one Control line. The fluorescence intensity of these test lines and control line was measured using an in-house developed Exdia TRF-Plus analyzer. As proof-of-concept, we enrolled patients suspected of having a stroke who were admitted within a specific time frame (6 h). A small amount of clinical specimen (serum) was used.To optimize the LFIA, an EuNPs conjugated antibodies were investigated to improve the detection sensitivity and decrease the background signal as well shorten the detection time. The Exdia TRF-LFIA cartridge offers a wide linear dynamic detection range, rapid detection, high sensitivity, and specificity. The limit of detection was determined to be 98 pg/mL for NT-proBNP and 68 pg/mL for GFAP, with minimal cross-reactivity. There were 200 clinical human serum samples that were used to evaluate this platform with high correlation. By combining the results of NT-proBNP and GFAP, we formulated an algorithm for the clinical assessment of Ischemic Stroke (IS) and Hemorrhagic Stroke (HS). According to our proposed algorithm, the combination of GFAP and NT-proBNP emerged as the most effective biomarker combination for distinguishing between IS and HS.Exdia TRF-LFIA shows great potential as a supplemental method for in vitro diagnostics in the laboratory or in other point-of-care testing (POCT) applications. Its development substantially decreases the diagnosis time for IS and HS. The proposed algorithm not only minimizes treatment delays but also lowers medical costs for patients.

Effects of Scanning Health News Headlines on Trust in Science: An Emotional Framing Perspective

ABSTRACT Rooted in the emotions-as-frames model (EFM), this research examines how hope, fear, and annoyance are evoked through health news headline scanning, and how these emotions influence perceptions of news and medical science institutions as well as health behavioral intentions. A sample of U.S. adults (N = 327) were assigned to one of four headline framing conditions expected to associate with different emotions (positive future frame-hope; threat frame-fear/anxiety; reversal frame-annoyance; and control-neutral) and then asked about their emotional states, trust in science and news, and health-related behavioral intentions. Overall, health news headlines generated more hope than any other emotion across all conditions, and positive future-framed headlines evoked more hope than other framed headlines. Felt hope, in turn, generated greater trust in news and science, higher expectations of medical breakthroughs and cures, and greater intention to engage in preventative health behaviors. Felt anxiety had marginal positive benefits whereas felt annoyance negatively impacted the outcomes of interest. Notably, felt emotion mediated the headline frame-outcome relationships in the positive future/hope condition. These findings offer some support for the EFM and demonstrate that scanning headlines imbued with specific emotional frames can influence important health-related outcomes through the emotions they evoke. We discuss both the theoretical and practical implication of these findings.

Kants »Über Pädagogik« in englisch- und deutschsprachigen Editionen. Ein Beitrag zur erziehungswissenschaftlichen Komparatistik

Abstract Kant’s »Lectures On Pedagogy« in English- and German-language Editions. A Contribution to Comparative Educational Studies By means of a content analysis, the article examines the introductions to Kant’s »Lectures on Pedagogy« in a comparison of English- and German-language editions. The objects of investigation are the editors’ prefaces, which, as paratexts, provide a specific framing for the main text and are thus particularly suitable for closer inspection. The aim is to open up perspectives with which the pedagogical significance of Kant’s writing can be dealt with in an international comparison.

Programmable intratumoral drug delivery to breast cancer using wireless bioelectronic device with electrochemical actuation

ABSTRACT Objective Breast cancer is a global health concern that demands attention. In our contribution to addressing this disease, our study focuses on investigating a wireless micro-device for intratumoral drug delivery, utilizing electrochemical actuation. Microdevices have emerged as a promising approach in this field due to their ability to enable controlled injections in various applications. Methods Our study is conducted within a computational framework, employing models that simulate the behavior of the microdevice and drug discharge based on the principles of the ideal gas law. Furthermore, the distribution of the drug within the tissue is simulated, considering both diffusion and convection mechanisms. To predict the therapeutic response, a pharmacodynamic model is utilized, considering the chemotherapeutic effects and cell proliferation. Results The findings demonstrate that an effective current of 3 mA, along with an initial gas volume equal to the drug volume in the microdevice, optimizes drug delivery. Microdevices with multiple injection capabilities exhibit enhanced therapeutic efficacy, effectively suppressing cell proliferation. Additionally, tumors with lower microvascular density experience higher drug concentrations in the extracellular space, resulting in significant cell death in hypoxic regions. Conclusions Achieving an efficient therapeutic response involves considering both the characteristics of the tumor microenvironment and the frequency of injections within a specific time frame.

Three-dimensional coherence beamforming using row-column arrays and matrix arrays

Much advancement in 3D ultrasound imaging has been achieved in recent years, allowing for its implementation in many research capacities. Translation of 3D imaging to a clinical setting has been hindered by small fields of view, expensive equipment and poor image quality. For ultrafast imaging, these challenges are accentuated by the need for a small number of transmission events. The row-column array is an emerging technology which can produce large field-of-view 3D ultrasound images, however, they can produce major artefacts when operated at high frame rates. Here we present some techniques which have been developed to improve the image quality and reduce the artifact level of row-column arrays by exploiting the incoherence of the transmission schemes. Presented will be the Row-Column specific Frame Multiply and Sum beamforming along with a technique for implementing Acoustic Sub-Aperture Processing which improves signal-to-noise ratio whilst also increasing the effective frame rate. Additional coherence-based algorithms, which have previously been developed for 2D imaging, are implemented and presented here for 3D imaging using a matrix array probe. All of the above algorithms have been optimised for super-resolution but should improve all types of 3D ultrasound imaging.

Emotional wage, happiness at work and organisational justice as triggers for happiness management

PurposeThis study analyses the concept of happiness management based on the empirical validation of the interactions between emotional wage, organisational justice and happiness at work. It complements a holistic view of the management models used in recent corporate governance. This perspective explores the dimension’s emotional wage mediating role and influences on organisational justice and happiness at work. The effect of organisational justice on happiness at work is also analysed.Design/methodology/approachA quantitative, cross-sectional, descriptive and correlational study is proposed. A sample of 502 workers in the education sector in Costa Rica was selected. A structural equation model (PLS-SEM) was developed to test the proposed theoretical model. The SPSS-AMOS 23 and SmartPLS 4 computer programs are used for this purpose.FindingsThe results show that emotional wage has a positive impact on happiness at work and that it mediates positively between organisational justice and happiness at work. Developing organisational policies to include these variables as necessary resources for corporate governance is recommended.Research limitations/implicationsThe first limitation of this study is due to the type of sampling, which was purposive. The kind of population and the time of execution of this study were determining factors when deciding on the mode of application of the instrument. However, an attempt to reduce the bias associated with this element could be made by expanding the sample to as many respondents as possible. The second limitation was that the data were collected within a specific time frame. Longitudinal studies address Thcould. The third limitation stems from the scarcity of literature on happiness management. In this regard, this type of research currently needs to be explored in emerging economies. It makes it difficult to determine whether the empirical results obtained in this paper can be generalised to other territories in the global village. Moreover, the last limitation is that the authors of this research have only explored the moderating role of emotional pay in the relationship between the dimensions of organisational justice and happiness at work. It would be interesting to consider other mediating variables to have a clearer picture of the organisational justice–happiness at work construct from the happiness management approach.Practical implicationsAs already indicated throughout this research, emotional wage, organisational justice and happiness at work are constructs that positively drive employee satisfaction, motivation and well-being. Human talent management strategies undertaken by organisations should encourage the adaptation of actions that stimulate employees' quality of life, corporate social responsibility and ethical management practices to be more competitive in today’s markets. It requires implementing the dynamic management models that provide internal customers with a high sense of belonging, job satisfaction and commitment to their professional performance. In other words, this will require robust leadership styles and corporate cultures that stimulate employee creativity, loyalty and innovation. For this reason, management of organisations must implement human resources policies to attract and retain creative talent through happy leadership. It requires, among other things that the philosophy of happiness management becomes a critical strategic resource for companies to promote nonfinancial benefits for employees, including emotional wage (Ruiz-Rodríguez et al., 2023).Social implicationsIn the current business environment, there has been a transformation in leadership styles, motivation and the development of a sense of belonging in organisations' human capital. Based on this trend, the study of happiness management becomes a social strategy to improve the conditions, in which the organisations compete to attract highly demanded human capital. It is why this research contributes elements that have an impact on citizenship by proposing the management models based on happiness at work and quality of life.Originality/valueThis study adds to the happiness management literature by including emotional wage, organisational justice and happiness at work in human resources and strategic management. It also contributes to the academic debate on the need to formulate organisational cultures that empower workers in their professional performance based on happiness and positive emotions.

Determinants for positive and negative experiences of interpersonal touch: context matters

ABSTRACT The goal of the study was to determine which aspects of interpersonal touch interactions lead to a positive or negative experience. Previous research has focused primarily on physical characteristics. We suggest that this may not be sufficient to fully capture the complexity of the experience. Specifically, we examined how fulfilment of psychological needs influences touch experiences and how this relates to physical touch characteristics and situational factors. In two mixed-method studies, participants described their most positive and most negative interpersonal touch experience within a specific time frame. They reported fulfilment of nine needs, affect, intention, and reason for positivity/negativity, as well as the body part(s) touched, location, type of touch, interaction partner, and particular touch characteristics (e.g. humidity). Positive and negative touch experiences shared similar touch types, locations, and body parts touched, but differed in intended purpose and reasons. Overall, the valence of a touch experience could be predicted from fulfilment of relatedness, the interaction partner and initiator, and physical touch characteristics. Positive affect increased with need fulfilment, and negative affect decreased. The results highlight the importance of relatedness and reciprocity for the valence of touch, and emphasise the need to incorporate psychological needs in touch research.

Corporate Governance Mechanisms on Earnings management in the Indonesian Banking Sector

Research Aims: This research aims to examine the influence of corporate governance on earnings management. The corporate governance variable is proxied by independent commissioners, audit committees, and audit quality. The data in this research is secondary data originating from the financial reports of banking companies listed on the Indonesia Stock Exchange in 2019-2022. 
 Design/methodology/approach: The analytical techniques used to test the hypothesis in this research are descriptive statistics, classical assumption tests, and multiple linear regression analysis. The type of data used in this research is quantitative data. The sample for this research was obtained using a purposive sampling method, and a sample of 116 banking companies was obtained.
 Research Findings: Test results using multiple linear regression show that the independent commissioner variable does not affect earnings management. the audit committee variable has negative impact on earnings management while audit quality variable have a significant positive effect. Test results also show that the control variable ROA has a significant negative influence on earnings management (EM). However, the leverage control variable does not influence management (EM).
 Theoretical Contribution/Originality: This research contributes by providing nuanced insights into the specific impact of corporate governance components on earnings management within Indonesian banking companies. The findings offer a deeper understanding of the intricate relationships between governance mechanisms and financial practices.
 Research limitation and implication: Limitations include the focus on banking companies and the specific time frame. Future research may explore diverse sectors and extend the study period. The results imply the need for policymakers and practitioners to recognize the varying impacts of different corporate governance components on earnings management for effective financial oversight.

Study on the Influence and Optimization Design of Viscous Damper Parameters on the Damping Efficiency of Frame Shear Wall Structure

This study investigates the influence of viscous damper parameters on the damping efficiency of frame shear wall structures. Taking a specific frame shear wall structure as the background, a three-dimensional finite element model is established using a nonlinear dynamic time–history analysis method. The damping ratio, reduction in vertex displacement, reduction in base shear, and inter-story drift utilization rate are selected as the damping performance indicators. Firstly, a sensitivity analysis is conducted to study the influence of different viscous damper parameters on these indicators. Then, the relationship models between the viscous damper parameters and the indicators are fitted using the response surface method, and the fitting effect is evaluated through an F-test and determination coefficient R2. Finally, an objective function based on key damping performance indicators is established to solve for the optimal parameters. The results show that the traditional sensitivity analysis method is unable to comprehensively consider the combined effects of different damping efficiency indicators. The response surface method has high fitting accuracy and good predictability and can serve as an optimization model. Considering the stiffness of supporting components matched with the viscous damper parameters, the feasibility of the optimal damping parameters is demonstrated from an engineering application perspective. A simple and easy-to-operate damping design flowchart is proposed, providing important guidance and reference for designers in frame shear wall structure damping design in the future.