Conceptual Framework Model Research Articles

Revealing the pattern of causality between tourist experience and the perception of sacredness at shamanic heritage destinations in Northeast China

For religious heritage tourism, the key to a destination’s reputation lies in enabling visitors to fully experience the sacredness or a unique spiritual experience offered by the site. The authenticity of the tourism experience and perception is the most significant factor influencing visitors’ perception of the sacredness of religious or holy sites. However, there is currently a lack of sufficient references and evidence to explore the relationship between tourists’ authentic experiences and their perception of sacredness in religious heritage tourism. The aim of this study is to elucidate the causal relationship between the characteristics or attributes of tourists’ authentic experiences and their perception of the sacredness of the destination. Furthermore, it seeks to explore resource development and site creation strategies for religious tourism destinations to continuously enhance the sense of sacredness of these places. The Shamanic cultural traditions in the traditional settlements of Northeast China provide a subtly different context for this study. However, the topics discussed have broad applicability in constructing the network of relationships between the characteristics of tourists’ experiences and their perception of sacredness in religious heritage tourism. This study applied the causal decision analysis model based on data mining (RSA-DEMATEL) and established a causal network diagram between core attributes based on clarifying the behavioral rule knowledge (i.e., If…Then… rules) between tourists’ travel experience (conditional attributes) and the perception of place sacredness (decision-making attributes). The study finds that enhancing tourists’ perception of the sacredness of a destination is related to authentic tourism experiences, the ability to observe believers and participate in the religious activities of local residents, landscapes that reflect local traditions and historical culture, as well as the number of tourists and the extent of commercial activities. This research offers further insights into the sustainable development of religious tourism, providing a critical conceptual framework and data analysis model for subsequent related studies, contributing significantly to both theory and practice.

Analysis of students’ conceptual change in learning Newton’s third law with an integrated framework of model analysis and knowledge integration

The purpose of this study is to examine how students may hold coexisting and competing conceptual ideas and how students’ uses of such ideas may evolve during the process of conceptual change by combining two complementary methods including model analysis and the conceptual framework model of knowledge integration. Conceptual change is fundamental to science learning, highlighting the processes of students’ transitions from predominantly relying on alternative views to using scientific ones. Recent studies suggest a growing consensus that alternative views and scientific conceptions coexist and compete in students’ learning. However, explicit research on how the states of coexistence and competition evolve during the process of conceptual change is underdeveloped. Building on existing research, the model analysis provides a quantitative framework to represent the different consistent and coexisting/competing states through probabilities of consistent and/or mixed (coexisting) use of incorrect and scientific ideas. Meanwhile, the conceptual framework model of knowledge integration provides content-specific, cognitive explanations for the developmental levels and processes of conceptual change from novice to expert. By combining these two methods, researchers can gain insights into how the coexistence and competition among different conceptual ideas may evolve as conceptual change progresses. To target the research goal, a model-based knowledge integration assessment of Newton’s third law is developed to measure students’ levels of knowledge integration and model states in a single test. Quantitative data were collected from Chinese high school students, supplemented by interviews with a subgroup from the same population. The model analysis results show the heterogeneity of conceptual development and the evolving competition across novice, intermediate, and expert students, as well as across different concept dimensions. The interviews provide cognitive explanations for the observed model states, framed from the lens of knowledge integration. These insights can inform the development of effective assessments and instructional strategies to facilitate favorable conceptual change in student learning. Published by the American Physical Society 2024

Assessment of knowledge integration in student learning of galvanic cell: An interdisciplinary approach connecting physics and chemistry

The galvanic cell is a typical interdisciplinary topic, which is primarily taught in chemistry but its underpinning is closely related to physics. Student learning in galvanic cell has been extensively studied in chemistry education, which has revealed a large number of misconceptions that are difficult to change through traditional instruction. A source of the learning difficulties is that most students lack an explanatory framework to integrate the many complex phenomena and processes into a coherent knowledge system. As a result, students often rely on memorization of terms, laws, and equations in solving problems but without a meaningful understanding of their reasoning. To address the deficit in learning, this study aims to help students develop an explanatory framework for supporting an integrated knowledge structure. Specifically, a conceptual framework model for galvanic cell is developed based on the central idea from physics, which is used as the core concept for mechanistic explanations of the related chemistry concepts. Guided by the conceptual framework, an instrument is developed to assess the knowledge integration in student learning of galvanic cell. A combination of qualitative and quantitative measures was used to assess the levels of knowledge integration in learning galvanic cell with a large number of Chinese high school and college students. The assessment results show that the conceptual framework model can effectively represent the knowledge structures of students at different levels of knowledge integration. The galvanic cell conceptual framework and assessment results can provide useful resources for teachers to develop instruction for promoting knowledge integration. Published by the American Physical Society 2024

Conceptual Business Model Framework for AI-based Private 5G-IoT Networks

Conceptual Business Model Framework for AI-based Private 5G-IoT Networks

A conceptual data modeling framework with four levels of abstraction for environmental information

Environmental data generated by observation infrastructures and models is widely heterogeneous in both structure and semantics. The design and implementation of an ad hoc data model for each new dataset is costly and creates barriers for data integration. On the other hand, designing a single data model that supports any kind of environmental data has shown to be a complex task, and the resulting tools do not provide the required efficiency. In this paper, a new data modeling framework is proposed that enables the reuse of generic structures among different application domains and specific applications. The framework considers four levels of abstraction for the data models. Levels 1 and 2 provide general data model structures for environmental data, based on those defined by the Observations and Measurements (O&M) standard of the Open Geospatial Consortium (OGC). Level 3 incorporates generic data models for different application areas, whereas specific application models are designed at Level 4, reusing structures of the previous levels. Various use cases were implemented to illustrate the capabilities of the framework. A performance evaluation using six datasets of three different use cases has shown that the query response times achieved over the structures of Level 4 are very good compared to both ad hoc models and to a direct implementation of O&M in a Sensor Observation Service (SOS) tool. A qualitative evaluation shows that the framework fulfills a collection of general requirements not supported by any other existing solution.

Influence from highways on regional economic growth – based on the trade potential in China

The question of whether the construction of the highway network is economical and can produce positive economic benefits has been a hot topic of discussion in recent years. Previous scholars have explored the impact from multiple perspectives. Our paper draws the “trade potential” model proposed by Armstrong, based on the universal gravity model and the principle of space interaction, which is different from the traffic accessibility, market potential, and market access used in most of the literature. We argue that it is more appropriate to consider both the size impact and the time distance or trade cost impact of the two cities. The paper constructs a conceptual framework and theoretical model for the impact of highways on regional economic growth, measures the “minimum transit time” of highways between prefecture-level cities in China, and calculates the trade potential of prefecture-level cities. Through corresponding empirical model testing, we have obtained some meaningful conclusions.

Effectiveness of conceptual-framework-based instruction on promoting knowledge integration in learning simple electric circuit

Student learning in simple electric circuits has been an important area in physics education research. This study builds off a previous investigation that applied the conceptual framework model to examine knowledge integration in student learning of simple electric circuits and developed a multiple-choice concept test for assessing knowledge integration in simple electric circuits. In this study, a conceptual-framework-based teaching intervention was developed and implemented in a controlled study with high school students in China to evaluate the effectiveness of the new instruction. Using the instrument developed in the previous study, a pretest, a post-test, and a delayed post-test were conducted with both groups of students. The delayed post-test was included to further evaluate knowledge retention as evidence of knowledge integration. The results suggest that the conceptual-framework-based teaching intervention was effective in promoting knowledge integration compared to the existing instruction. Published by the American Physical Society 2024

Consistent solutions for simultaneous dynamic water, solute, stable isotope and radon balances to estimate average exchange fluxes between surface water bodies and groundwater

Many papers show that water, conservative solute, stable isotope and radon balances can be applied to the study of surface water – groundwater interaction. When undertaken simultaneously, such analysis provides an even more powerful method for estimating groundwater inflows and outflows, i.e. the exchange fluxes that for most people are hardest to estimate. The overarching objective of this paper is to provide practitioners with a consistent conceptual and simulation modelling framework with which to achieve a rapid initial understanding of surface water – groundwater interaction, as well as to guide the efficient and targeted acquisition of field data. This paper makes several important contributions. First, after an introduction that explains the complexities of groundwater flow patterns near surface water bodies, a set of general balance equations is developed using consistent terminology and notation. Second, after focusing on a simple conceptual model with steady groundwater inflow I, groundwater outflow O, precipitation P and ever-present evaporation E, analytical solutions are developed for transient and steady state conditions: one water balance solution is found to apply in all situations; solutions for the solute balance equation are developed for 23 different subcases; a transient balance equation for stable isotopes written in terms of 1+δ is found to apply in all situations; and a new transient solution for radon is found in terms of the upper incomplete gamma function. On the path towards developing the isotope balance equation, we present a rigorous approach, based on coupled nonlinear balance equations for abundant and rare isotope pairs (1H and 2H, then 16O and 18O), using isotope ratios and the fractions of each isotope. Third, we describe a Lake Water Balance Calculator (LWBC) written using GoldSim simulation software, a tool to help others to conduct the simultaneous analyses that we promote; we use GoldSim’s numerical methods to solve the general balance equations, we implement the analytical solutions to demonstrate that both GoldSim’s numerical methods and the analytical solutions are correct, and we also show that the 1+δ approximation is equivalent to the rigorous coupled equations, at least for heavy stable isotopes with very low abundance. Fourth, we describe field studies: we provide three examples of applications of LWBC to short-term studies of Perry Lakes East, Lake Jasper and Georgetown Billabong in Australia; we then describe WSIBal, a simulation model based on the same balance equations and describe its application to Lake Jasper over a 19-year period; finally, we describe R-WSIBal, which evolved from WSIBal, and explain its application to 2500 km of the Murray River in Australia.

Visual Representation of Cross-Cultural Adaptation through Lifestyles in Georgette Chen's Paintings

This study aims to analyse, understand and interpret the visual representation of cross-cultural adaptation and its symbolic information in Georgette Chen's paintings. Based on the conceptual framework model created in this study, the target is deeply studied using relevant concepts combined with the qualitative research case study method. The analysis results show that cross-cultural adaptation in Georgette Chen's paintings is a symbol that expresses the desire for a new identity and nostalgia for the old culture, which also reflects the characteristics of different stages in the process of cross-cultural adaptation. The study concluded that the oeuvre of Georgette Chen provides a profound insight into the intricate process of cross-cultural adaptation, vividly embodied through incorporating various cultural elements. This study contributes to the broader discourse on the intersection of Visual Arts and Cross-Cultural Adaptation. It will benefit artists, researchers, and scholars interested in studying this area.

Influence of crop development and fruit retention on the timing of crop maturity in Ultra-narrow row cotton

Ultra-narrow row (UNR) cotton, a production system with rows spaced less than 40 cm apart, has been proposed as a system for earlier maturity without substantial yield loss. However, trials in the U.S.A. and Australia have found maturity benefits difficult to achieve consistently. Studies undertaken in high input cotton systems that compared UNR to conventionally (1 m) spaced cotton found yield differences but failed to demonstrate differences in crop maturity. This paper examines crop development and fruiting dynamics of the two systems in more detail to understand why there were no differences in maturity. Results showed that lack of difference in maturity between the row spacings was not influenced by differences in the time to reach crop development stages nor by lower fruit retention of early bolls in the UNR plants. Node production and fruiting site production on a per plant basis were significantly slower in the UNR plants from early in the growing season. Slower node and fruiting site production delayed maturity in the UNR plants as they set fewer fruit within the same period of time compared to plants grown in conventional spaced rows. The number of fruiting sites produced per plant was highly dependent on the amount of dry matter per plant. Fruiting site production was reduced in the UNR crop because each plant produced less total dry matter, and hence plant development was slower. To further help understand the reasons for outcomes generated in these studies, and how UNR could possibly mature earlier without impacting yield, a conceptual modelling framework was developed to integrate seasonal patterns in fruiting site production, retention, and boll growth. A key component of this framework is translating from a per plant basis to an area basis. The analysis showed that for individual UNR plants to mature earlier and maintain yield on an area basis, early node production and fruiting site production must proceed at a similar rate to conventionally spaced crops. In this scenario 90 % of final yield would be present 14 days earlier in the UNR crop compared to conventionally spaced crops. To realise any benefits of potential earlier maturity further research is needed to explore genetic or management interventions that might avoid the early competitive stress response that slows node development in UNR.

Enhanced calendar support for temporal datacube queries

AbstractA significant share of our data are timeseries. Time can occur as the single dimension, or further (such as spatial) dimensions can be present as well, leading to multidimensional data such as 3D x/y/t satellite image timeseries or 4D x/y/z/t atmospheric simulations like weather forecasts. However, no user would like to count “seconds since epoch,” rather we all prefer calendar notation. Libraries, SQL, etc. support calendar arithmetics, yet more advanced functionality is needed. Instead of demoting advanced calendar functionality to low‐level coding, it seems desirable to have semantic support for calendars at high‐level, declarative query level. We present a conceptual framework for temporal modeling which allows the expression of a wide range of temporal queries. It smoothly enhances existing calendar handling by adding two new data and query description parameters, period of validity, and granularity. While our work is embedded in spatio‐temporal geo services, it can be incorporated in a non‐breaking manner in any environment needing calendar addressing. The concepts are implemented in an Array DBMS operational on several Petabytes of Earth datacubes.

Rethinking entrepreneurship and management education for engineering students: The appropriateness of design thinking

The study argues that the educational needs of engineering students for entrepreneurship and managerial education are specific and evolving over time toward a set of skills and knowledge needed in digital and dynamic world. Existing research largely ignored the distinct and evolving nature of these educational needs and their implications for entrepreneurship and managerial education of engineering students. Using design thinking and teaching model literature, we proposed teaching model framework and derived propositions from conceptual arguments to address these educational needs effectively. The proposed conceptual teaching model framework elaborates on the incorporation of cognitive acts of design in various aspects at ontological, didactical, and contextual levels. The framework views education as a process of co-construction, centered on students, where the role of the teacher is similar to that of a coach. Students work in teams and practice the cognitive acts of design that lead to the development of interpersonal, entrepreneurial, and managerial skills. For this purpose, open-ended questioning, real-life customer problems, design thinking methodology, and lean methodology are proposed as effective content and pedagogies to promote the entrepreneurial behaviors required in the current industrial scenario.

Assessing and enhancing university students’ knowledge integration in learning electromagnetic induction

ABSTRACT Electromagnetic induction stands as a fundamental concept in electromagnetism and has been extensively studied in physics education. In this research, a conceptual framework model is developed to explore university students’ understanding of electromagnetic induction through the lens of knowledge integration. Building upon the experts’ viewpoints and a comprehensive literature review on students’ challenges and misconceptions, a conceptual framework for electromagnetic induction is established, serving as the guidance for developing a concept test to assess levels of knowledge integration in student learning. According to both quantitative and qualitative analyses, the findings confirm that the conceptual framework can proficiently depict the different integration levels of students’ knowledge structures, while also revealing the intricate pathways that underlie their reasoning processes. Drawing from the conceptual framework and insights gained through assessment, an instructional intervention is designed with the specific goal of promoting knowledge integration by highlighting the central idea of electromagnetic induction and connecting it to other knowledge components. The score changes of pre–post testing indicate that the modified instruction has achieved success in improving knowledge integration and deep learning of electromagnetic induction.

Exploring ICT-based learning adoption in higher education: An extended perspective of the technology acceptance model

This article analyses the self-perception of digital technology learning competence among engineering and science students. The use of information and communication technologies (ICT) is now considered highly essential in higher education. Today's higher education institutions (HEIs) seldom employ traditional methods of instruction; instead, sophisticated ICT is starting to emerge as a feasible paradigm for fundamental change. To this end, Pakistan's Higher Education Commission (HEC) has heavily invested in technology in the education sector and initiated several programs. The ramifications of ICT utilization on the environment, student academic performance, and capabilities remain ambiguous. In delving into how students embrace and utilize ICT systems for learning in HEIs, researchers felt the need to grasp the factors that influence students' acceptance and utilization of ICT skills through the lens of the Extended Technology Acceptance Model (TAM). This study develops an exclusive conceptual model by incorporating TAM with a set of latent variables identified in the available literature: interest, ICT self-efficacy, economic cost, and performance expectancy. The adapted TAM model developed in this study considers the influence of these variables on students’ ICT acceptance and its impact on academic performance in emerging countries. As part of this study, reports on the development of instruments and validation in the research field were managed using a cross-sectional survey method and SPSS-22 and Smart PLS-4 software. In addition, association rule mining applied in demographic data. A sample of 69 students was randomly selected from three universities representing engineering, medical, and general HEIs in the Sindh province. Though the sample size was small, it showcases that the reliability of the scales is within an acceptable range and can be used to test the main study hypotheses. A conceptual framework model is introduced to offer a comprehensive framework derived from the amalgamation of various acceptance and usage models of technology. The results demonstrate that the survey items are appropriate and suitable for further research.

Advancement in ice-jam flood risk management: Integrating dynamic adaptive behavior by an agent-based modeling in Fort McMurray, Canada

Ice-jam flooding is a prevalent extreme event that impacts flood hazard and vulnerability. We introduce a conceptual model framework for Dynamic Ice-jam Flood Risk Assessment (DIFRA). DIFRA integrates ice-jam flood hazard, ice-jam flood risk, and human adaptation. Using agent-based modeling, we captured top-down (artificial breakup) and bottom-up (flood-proofing) adaptive behavior. Our study in Fort McMurray, Canada, shows the complex interaction between micro-level behaviors and macro-level phenomena over time. Our variance-based global sensitivity analysis shows the role of dynamic adaptive behavior in ice-jam flood risk, where the artificial breakage by the government can lead to a regime shift and a decrease in the ice-jam flood risk. However, it can also decrease the number of newly adapted residents to flood-proofing and the role of residents in ice-jam flood risk. DIFRA offers a comprehensive approach to understanding and managing ice-jam flood risk, with potential applications to similar riverine communities in cold regions.

Division of Inheritance and Will: First Marital Children, Second Marital Wife (Literature Legal Review)

The purpose of this article is to make a positive contribution in promoting justice, understanding, and innovative solutions in the context of inheritance and testamentary divisions, particularly in situations involving children from first marriages and wives from second marriages. An in-depth article on the complexities of the division of inheritances and wills, in particular involving children from first marriages and wives from second marriages, qualitative research methods can be used. Qualitative research methods aim to understand phenomena in depth, exploring individual perspectives, values, and experiences related to the topic under study. Literature reviews of related scientific articles to provide reinforcement and ultimately the article offers a conceptual framework model of research results. The division of inheritances and wills is a complex topic, involving various aspects of law and social practice. In diverse societies, the process of inheritance sharing often reflects different cultural and religious values. However, in the context of globalization and modernization, there are challenges in harmonizing traditional practices with more inclusive modern laws. It is important to understand that the division of inheritances and wills is not only a legal issue, but also reflects complex social dynamics. Factors such as cultural norms, religious beliefs, and family structure can influence how inheritances are divided and wills are made.

Conceptual Model of Financial Ratios in Detecting Fraud in Local Government Financial Statement

The preparation of a local government financial statement must be free from fraud, so local governments need to ensure that there are no elements of material misstatement in the preparation of financial statement. This research aims to propose a conceptual model of the influence of financial ratios which includes the quick ratio, current ratio, working capital to total assets ratio, debt-to-equity ratio, and debt to capital assets ratio which have the potential to detect fraud in local government financial statements. The method used in this research combines four concepts in one conceptual model framework. It is hoped that this research's conceptual model can become a method used in local government agencies to detect fraudulent financial statement through financial ratios.

Enhancing conceptual models with computational capabilities: A methodical approach to executable integrative modeling

AbstractThe lack of a common executable modeling framework that integrates systems engineering, software design, and other engineering domains is a major impediment to seamless product development processes. Our research aims to overcome this system‐software modeling gap by integrating computational, software‐related, and model execution capabilities into OPM‐based conceptual modeling, resulting in a holistic unified executable quantitative‐qualitative modeling framework. The gap is overcome via a Methodical Approach to Executable Integrative Modeling—MAXIM, an extension of OPM ISO 19450:2015, a standardization approvement given on 2015. We present the principles of MAXIM and demonstrate its operation within OPCloud—a web‐based collaborative conceptual OPM modeling framework. As a proof‐of‐concept, a model of an Airbus civil aircraft landing gear braking system is constructed and executed. Using MAXIM, engineers from five domains can collaborate at the very early phase of the system development and jointly construct a unified model that fuses qualitative and quantitative aspects of the various disciplines. This case study illustrates an important first step towards satisfying the critical and growing need to integrate systems engineering with software computations into a unified framework that enables a smooth transition from high‐level architecting to detailed, discipline‐oriented design. Such a framework is a key to agile yet robust future development of software‐intensive systems.

Geostatistical modeling approach for studying total soil nitrogen and phosphorus under various land uses of North-Western Himalayas

The distribution of total soil nitrogen (TSN) and total soil phosphorus (TSP) plays a pivotal role in shaping soil quality, fertility, agricultural practices, and environmental balance, especially in ecologically sensitive regions like the North-Western Himalayas (NWH). The primary objectives of this study were to contribute to clarify the impact and the rationale of various land uses on the spatial variation of TSN and TSP in the corresponding soils. This study aimed to explore the relation of TSN and TSP distribution in NWH soils with various factors like landscape physiography and soil physical and chemical properties using random sampling and geostatistical analyses. Employing random sampling, 300 soil surface samples (at a depth of 0–20 cm) were collected across various 500 m × 500 m grids from agriculture, horticulture, forest and fallow lands in the NWH region. The spatial land heterogeneity of TSN and TSP were systematically analyzed using standard statistical and geostatistical approaches (Gaussian, spherical, exponential, and linear). Results revealed a decreasing order of TSN and TSP levels i.e., horticulture (0.410 and 0.723 mg/kg) > agriculture (0.314 and 0.597 mg/kg) > forest (0.236 and 0.572 mg/kg) > fallow (0.275 and 0.342 mg/kg). Stepwise multiple regression results demonstrated a correlation between TSN and soil organic carbon (SOC), while TSP was correlated with soil organic carbon (SOC) and fine-grained soil particles. Nugget % values indicated the following spatial variability for TSN: agricultural (1.4) > horticultural (3.2) > forest (3.9) > fallow land (4.8) > mixed land (5.8), whereas the spatial variability of TSP showed a similar trend for all land uses. The optimized conceptual framework and isotropy models varied for TSN and TSP on dependence on land use type. The results of this study revealed the spatial patterns and land use-related variations and improved the prediction of nutrient distribution, so contributing an optimized conceptual framework for future studies. Finally, this study provided crucial insights to enhance soil quality, fertility, agricultural sustainability, and environmental equilibrium in the ecologically fragile NWH region, contributing to solve a significant research gap in the global understanding of soil dynamics.

Predicting Soil Quality Index with a Deep Regression Approach

ABSTRACT The detection, preservation and enhancement of soil quality is essential for ecosystem managers to offer the appropriate support after discovering factors that are linked to soil’s functional capability. In this study, soil quality indicators were combined to establish a soil quality index (SQI) by conducting an efficiency analysis for using Convolutional Neural Network (CNN), Gradient Boosting Methods (GBM) and Decision Tree (DT) approaches. For this purpose, soil’s intrinsic parameters, namely indicators, are utilized in case of fitting a deeper regression model. The experiments were carried out with analysis results of 545 soil samples obtained from previously studies conducted on different areas such as watershed, delta, pasture and farmland. The performance of each model is validated by the reported data. Compared to gradient boosting models, the proposed CNN model with mean absolute loss function achieves a lower error rate of 2.71 in Mean Absolute Percentage Error (MAPE) and best average correlation coefficient 0.90 in R2, which proves generalizability of CNN based regression. The findings show that CNNs may be utilized as an effective tool as giving a better prediction accuracy level and reliability in terms the establishing correlations and providing a conceptual framework for modeling of soil quality.