Research Outcomes Research Articles

The tea buds detection and yield estimation method based on optimized YOLOv8

The existing methodology for detecting and estimating tea bud yields heavily relies on cultivation experience, resulting in a delay in obtaining accurate information regarding tea bud yields. This delay poses challenges in providing timely data support for tea leaf growth management during the early stages of tea production. To address this issue, we propose a novel approach for tea bud detection and yield estimation. Initially, image data is gathered from the tea plantation area to train an optimized YOLOv8 model, enabling precise detection and enumeration of tea buds within the specified region. Ablation experiment is conducted to validate the effectiveness of the model improvements. Subsequently, data associating tea bud quantities with yields are collected, and a yield estimation mathematical model is derived through the partial least squares (PLS) method. Finally, the target detection model is integrated with the yield estimation model. By leveraging data such as the tea bud count within the target area, estimated area, and total planting area, the system accomplishes the estimation of tea bud yields. The outcomes of research are as follows: 1) The optimized YOLOv8 model achieves a recognition accuracy of 95.9 % for tea buds, boasting a recall rate of 85.5 % and an average precision of 91.7 %. 2) The relative error between the estimated yield and actual yield, as determined by the proposed method in this study, stands at 10.28 %. The tea bud detection and yield estimation methodology introduced in this research offer a convenient and expeditious means to estimate tea bud yields. It provides valuable data support to tea growers, facilitating pertinent production planning within the tea industry.

The Romanian Translation and Cultural Adaptation of the Early Arthritis for Psoriatic Patients (EARP) Questionnaire, Psoriasis Epidemiology Screening Tool (PEST), and Toronto Psoriatic Arthritis Screen 2 (ToPAS 2).

Psoriasis is a chronic inflammatory condition mediated by the immune system with various manifestations. The increased prevalence of subclinical joint involvement has led to the development of early diagnostic methods for psoriatic arthritis, including several instruments that have been validated and used in clinical practice. The aim of this study was to perform the Romanian translation, cultural adaptation, and validation of three assessment tools: the Early Arthritis for Psoriatic Patients (EARP) Questionnaire, Psoriasis Epidemiology Screening Tool (PEST), and Toronto Psoriatic Arthritis Screen 2 (TOPAS 2), which are designed to evaluate early-stage arthritis in patients with psoriasis. All the activities were carried out in accordance with the internationally recognized methodology recommended by the International Society for Pharmacoeconomics and Outcome Research (ISPOR), the recommendations of the World Health Organization (WHO) regarding the translation process and the validation of instruments, and data from the international literature. These three questionnaires were administered to 29 patients with psoriasis diagnosed by biopsy. A descriptive study was conducted and the data were analyzed with appropriate statistical tests using the PSPP program. A reliability test was assessed using Cronbach's alpha coefficient. The obtained values were significant for the first two questionnaires, with a value of 0.89 for the EARP and 0.63 for the PEST, but the value was not as significant for ToPAS2, at 0.40. This pilot study revealed that the Romanian and original versions of the three questionnaires are similar.

An introduction to the collection ‘Environmental flows in northern Murray–Darling Basin: what we know about the science and management after a decade of practice’

This paper is the foreword to a collection on monitoring and research outcomes related to water management in the northern Murray–Darling Basin (MDB), Australia. It provides background on the northern MDB, along with a summary of papers presented in the collection. This article belongs to the collection Environmental flows in northern Murray–Darling Basin: what we know about the science and management after a decade of practice.

Reflecting the voices of EFL teachers in the world of Intelligent Computer-Assisted Language Assessment (ICALA): an insight into teacher immunity, reflective teaching, job satisfaction, and L2-teacher grit

Artificial intelligence (AI) and Intelligent Computer-Assisted Language Assessment (ICALA) are transforming the educational landscape by radically changing how lessons are taught and students are evaluated. As the masterminds behind the curriculum, it is critical to consider the emotional and mental health of teachers who applied ICALA as part of their language instruction. To this end, this study’s primary objective was to examine the connections between ICALA, teacher immunity, reflective teaching, job satisfaction, and l2-teacher grit. To achieve this goal, 221 English as a foreign language (EFL) university teachers from Afghanistan participated in the current research. The research outcomes identified and quantified the influences of teacher immunity and reflective teaching on job satisfaction and L2 teacher grit by data screening utilizing confirmatory factor analysis (CFA) and structural equation modeling (SEM). According to the results, TI and RT are vital in implementing AI into language assessment by maintaining an uninterrupted JS and L2TG. The study’s ramifications are further elaborated upon.

Indigenizing research methods: making research outcomes better for all

In the context of Indigenizing academic practices and promoting cultural inclusivity within library and information institutions, this paper explores the significance of incorporating Indigenous approaches to research within LIS research methods courses. It argues that Indigenous research methods can be adapted and applied to other contexts, especially where research is being done in Diversity Equity and Inclusion (DEI) communities, who also have a history of being marginalized in research. This paper advocates for research methods to be transformed by incorporating Indigenous approaches into research methods education and empowering students to become culturally competent researchers. The paper will demonstrate how the use of Indigenous methodologies provides students with an understanding of alternative paradigms informed by indigenous ways of knowing.

Building and Sustaining Public Trust in Health Data Sharing for Musculoskeletal Research: Semistructured Interview and Focus Group Study.

Although many people are supportive of their deidentified health care data being used for research, concerns about privacy, safety, and security of health care data remain. There is low awareness about how data are used for research and related governance. Transparency about how health data are used for research is crucial for building public trust. One proposed solution is to ensure that affected communities are notified, particularly marginalized communities where there has previously been a lack of engagement and mistrust. This study aims to explore patient and public perspectives on the use of deidentified data from electronic health records for musculoskeletal research and to explore ways to build and sustain public trust in health data sharing for a research program (known as "the Data Jigsaw") piloting new ways of using and analyzing electronic health data. Views and perspectives about how best to engage with local communities informed the development of a public notification campaign about the research. Qualitative methods data were generated from 20 semistructured interviews and 8 focus groups, comprising 48 participants in total with musculoskeletal conditions or symptoms, including 3 carers. A presentation about the use of health data for research and examples from the specific research projects within the program were used to trigger discussion. We worked in partnership with a patient and public involvement group throughout the research and cofacilitated wider community engagement. Respondents were supportive of their health care data being shared for research purposes, but there was low awareness about how electronic health records are used for research. Security and governance concerns about data sharing were noted, including collaborations with external companies and accessing social care records. Project examples from the Data Jigsaw program were viewed positively after respondents knew more about how their data were being used to improve patient care. A range of different methods to build and sustain trust were deemed necessary by participants. Information was requested about: data management; individuals with access to the data (including any collaboration with external companies); the National Health Service's national data opt-out; and research outcomes. It was considered important to enable in-person dialogue with affected communities in addition to other forms of information. The findings have emphasized the need for transparency and awareness about health data sharing for research, and the value of tailoring this to reflect current and local research where residents might feel more invested in the focus of research and the use of local records. Thus, the provision for targeted information within affected communities with accessible messages and community-based dialogue could help to build and sustain public trust. These findings can also be extrapolated to other conditions beyond musculoskeletal conditions, making the findings relevant to a much wider community.

IoT-based framework for optimizing energy efficiency and reliability in acoustic sensor networks using mobile sinks

In today’s world, there is an increasing demand for environmental monitoring, surveillance, and oceanographic research, which poses challenges in improving energy efficiency and data transfer reliability in Acoustic Sensor Networks. Existing methods face hurdles due to limited energy resources and unreliable data transmission. We propose a Reliable and Energy-Efficient Framework with Sink Mobility (REEFSM) to address these issues. This framework optimizes energy consumption and enhances data reliability by incorporating advanced energy management strategies such as adaptive duty cycling and efficient data transmission mechanisms by minimizing forwarding nodes. Simulation results demonstrate that REEFSM reduces energy consumption by up to 43% and increases data reliability by 35% compared to protocols like EERBCR and DEADS. REEFSM ensures zero dead nodes, minimizes packet drops, and maintains high data accuracy throughout the simulation. This research outcome provides a sustainable and reliable solution for energy-efficient data collection in underwater environments. The future research directions, including integrating autonomous path planning, energy harvesting, and machine learning techniques, hold great potential for further advancements in the field.

ARCHIVES COMMUNICATION: MUTATIONS OF A FUNCTION

Objective: The objective of this article is to examine the evolving communication function of archives in the context of new information and communication technologies. It aims to identify the impact of digitalization on archival practices, focusing on how these changes enhance the accessibility and usability of archival materials for the public and researchers. By exploring the emerging practices of archivists and their role in facilitating effective communication, this article seeks to highlight the significance of communication in the archival profession and to provide insights into the best practices for ensuring a positive user experience in the consultation of archival documents. Theoretical Framework: This article explores the communication of archives in the digital age, focusing on communication theory, digital archive science, user-centered design, social constructivism, and information behavior. It emphasizes the importance of understanding historical and cultural contexts, user needs, and information behavior to design effective communication strategies. Method: This article uses a qualitative research approach to examine the evolving communication function of archives in the context of digital technologies. It uses literature review, case studies, interviews with archivists, user surveys, and content analysis to understand the impact of digitalization on archives and identify best practices for archivists. Results and Discussion: The literature review, case studies, interviews, user surveys, and content analysis reveal a significant shift in archival practices towards digital communication. Key themes include accessibility, user engagement, and the role of digital technologies in transforming traditional functions. Successful examples include digitization of collections, innovative outreach strategies, and collaborations between archivists and technology experts. Key themes include a user-centered approach, balancing digital and traditional practices, ongoing training, and collaboration between archivists, technology professionals, and user communities. Research Implications: This study highlights the need for further research in archival science and communication to explore digital practices, user experience, collaboration models, social media's impact, training for archivists, ethical considerations, and long-term impact on research outcomes. It emphasizes the need for in-depth studies on user experience, collaboration models, social media's role, and the impact of training on professional development and broader societal impact. Originality/Value: This article explores the evolving communication function of archives in response to digital advancements. It integrates theoretical frameworks with practical insights from case studies, interviews, and user surveys. The research emphasizes user-centered approaches, empirical evidence, and best practices for archivists. It contributes to ongoing discourse on the future of archives and raises ethical considerations, addressing challenges faced by archivists.

The long arc of learning: Perspectives and innovations from 20 years of U.S. National Professional Development Program projects

AbstractU.S. National Professional Development (NPD) grants can afford a longitudinal understanding of how teachers learn to support English learners. When NPD projects are completed successively and successfully, they can provide an even greater longitudinal arc of understanding. This article chronicles the designs and lessons learned across five NPD grants between 2002 and 2023. Each grant represents a snapshot in time, presenting a set of assumptions from the field, programmatic innovations, and insights from research outcomes. From highlighting the difference between incremental and radical pedagogical change and what it takes to move beyond individual teacher change to systemic change benefiting multilingual learners, the article outlines the succession of aspirations (capacity building, sustainability, and scalability), experiences, changing conditions, and data points framing lessons learned and new cycles of praxis. This article offers implications for theory, practice, and research. It stands as an argument for adapting, innovating, and moving beyond the status quo to inspire more innovation in teacher preparation for multilingual learners.

An exploratory factor analysis on technological-related barriers to the construction of zero-energy buildings in Nigeria

PurposeZero-energy building (ZEB) has been considered as an innovative approach to reducing building carbon emissions (CEs) and improving building energy performance. Despite huge benefits of ZEBs, there are still challenges limiting the construction of ZEBs in the construction sector. This study seeks to assess and determine the principal component of technological-related barriers to the construction of ZEBs in Nigeria.Design/methodology/approachThe study designed a questionnaire to examine the technological-related barriers to the construction of ZEBs in Nigeria. Questionnaires were administered, and 272 valid responses were elicited. Thereafter, data were analysed using descriptive and inferential statistics.FindingsThe results from the exploratory factors analysis show that the principal components of technological-related barriers to the construction of ZEBs in Nigeria are categorised into five principal components: access and awareness for technological integration and innovation; knowledge on renewable technology integration; space and complexity of sustainable energy technologies; cost and readiness for ZEB technologies; and research outcomes with practical implementation in sustainable building technologies.Originality/valueThis study contributed to more effective ZEB studies by highlighting technological-related barriers to the construction of ZEBs in construction industry. An understanding of these barriers can aid construction stakeholders, organisations, policy-makers and governments in devising strategies targeted at reducing these technological-related barriers and fostering the construction of ZEBs in construction sector. Recommendations for further study on ZEBs were also made.

MANAGING RECRUITMENT AND DATA COLLECTION: ONLINE FOCUS GROUPS BEST PRACTICES AND STRATEGIES TO ADDRESS SCAMMERS

Common methods to collect data include quantitative, qualitative, and mixed method approaches. Although it is common to complete data collection in-person, the onset of COVID-19 has resulted in the increased use of online modalities. Qualitative research is commonly gathered through individual or focus group interviews. However, best practices outlining strategies when conducting online focus groups and approaches to address issues specific to online research (i.e., scammers) are limited. Due to the growing use of data collection through such means, it is imperative to draw out specific strategies that could regulate data quality and reduce the chances of scamming. The current article addresses this practical gap by providing a synthesis of the available literature on online focus groups that document best practices and suggestions to deal with scammers which is currently missing from the literature. The goal was to provide initial suggestions to improve data quality of online focus groups by examining the available literature that outlines best practices, addresses the issues of scammers, and to provide a concise and comprehensive overview of identified literature The article is organized beginning with a review of the literature. The research is then synthesized including an outline of best practices and strategies to address scammers when engaging in online focus groups. The article closes with a discussion of the significance of the review, limitations, and article summary. Scammers are prevalent in online spaces. Although this article provides a preliminary outline of suggestions from the literature, more research is necessary that provides specific examples of how challenges have been addressed and the impact of including the recommended strategies on the research process and outcomes.

Development of lateral acceleration prediction models and consistency evaluation criteria for horizontal curves with gradient on two lane rural highways

Objectives The challenge of combined horizontal and vertical highway alignments continues to be a concern in transportation design, particularly regarding truck stability. This study analyses the stability of trucks on horizontal curves combined with ascending or descending gradients using center of gravity (CoG) height and curve geometry as parameters. It also develops models that predict lateral stability of trucks and criteria for evaluating geometric design consistency based on vehicle stability. Method A smartphone application was used to collect real-time data on lateral acceleration experienced by two-axle trucks on curves with gradient. Results Findings show a lower safety margin against rollover on curves with descending gradient compared to ascending ones. Key factors affecting stability are identified as radius and length of horizontal curve, suggesting improvements in rollover stability by increasing these parameters. Geometric design consistency evaluation criteria were developed based on lateral acceleration, categorizing curves with gradient as good, fair, or poor. Predictive models were developed to quantify the impact of CoG height of truck and curve geometry on lateral acceleration, aiding in consistency assessment. Conclusion Outcomes of research will be useful for the design of safer horizontal curves with gradient by prioritizing vehicle stability

Access Pass: Validating The Scale of Barriers to Participation in Recreational Spaces

The importance of parks and recreational spaces in terms of public health has become even more evident after the pandemic period. The increased utilization of these areas by larger populations has imposed different responsibilities on the park and recreational spaces managers. To increase people's participation in parks and recreational spaces, it is important to first identify the barriers that hinder their participation. This study aims to adapt The Scale of Barriers to Participation in Recreational Spaces, developed by Gümüş and Alay, to the United States. In this context the study was conducted in a mid-sized city located in the Midwest in the U.S.A., involving a sample of 412 individuals ranging in age from 18 to 76. The data collection took place over four months, from December 2022 to March 2023. The factor structure obtained in the original scale development study was tested through Confirmatory Factor Analysis (CFA) as part of the validity study. During this analysis, it was necessary to remove one item from the security factor as it increased the Chi-square value in the CFA procedure. According to the analysis, it is evident that the goodness-of-fit indices yielded favorable results. Specifically, the Root Mean Square Error of Approximation (RMSEA) obtained a value of 0.04, while the Incremental Fit Index (IFI) and Comparative Fit Index (CFI) reached values of 0.94 and 0.98, respectively, signifying excellent goodness of fit. Additionally, the Normed Fit Index (NFI) and Goodness-of-Fit Index (GFI) attained values of 0.94, which fall within acceptable limits. Moreover, the chi-square value of χ2(94)=153.693 and a ratio of χ2/sd=1.63<2 indicated a perfect fit for the model. Correlation analyses between dimensions were conducted as part of the validity study. In the reliability study of the scale, Cronbach's alpha reliability coefficient was estimated. According to the findings, the factor structure of the scale was confirmed to be parallel to the original scale development study. Furthermore, Cronbach's alpha values ranged between 0.83 and 0.90. With these conducted studies, the scale has provided the necessary validity and reliability evidence for its use in the USA culture and has been introduced to the field to be utilized in various studies. It is expected that this scale can benefit both park and recreational spaces managers and users by identifying barriers to participation in these spaces and increasing engagement. Concurrently with the research outcomes, recommendations were formulated for park and recreation administrators.

A brief history of antenatal colostrum expression, and where to from here.

The practice of antenatal colostrum expression (ACE), or the extraction of colostrum from the breasts during pregnancy, has an interesting history and continues to evolve. This narrative review aims to describe how perception and practices of ACE have changed over time, summarise the evidence on ACE in maternal and infant care, and highlight areas for future research. The literature demonstrates that ACE is safe for low-risk women when done from around 36 weeks' gestation. Women should be reassured that the skill of hand expressing is a valuable tool post-birth, regardless of whether they are able to collect colostrum antenatally or not. The collection and storage of colostrum in pregnancy can help avoid formula use in hospital, which may have follow on effects immune function and other areas. Ideally, colostrum collected during pregnancy would be kept safely frozen during the hospital stay and only defrosted and used during the stay if medically indicated, with parents supported through that process. Although ACE does not appear to improve long-term breastfeeding rates at present, it can increase confidence around breastfeeding. Further research in more diverse population groups, long-term breastfeeding and long-term health outcomes of using frozen antenatally expressed colostrum for babies (as compared to formula or fresh colostrum) would be valuable to gain a better understanding of the importance of ACE in maternity care.

Proactive policies are the key to reversing desertification in the main stream of the Tarim River in the past 30 years

The main stream of the Tarim River is a crucial part of China's ecological security strategy within the "two screens and three belts" framework, serving the "northern sand control belt" and the ecological civilization corridor. Evaluating and understanding desertification dynamics and driving factors is essential for achieving the United Nations Sustainable Development Goals and promoting ecological civilization. This study, based on the United Nations Convention to Combat Desertification, quantified the desertification process of the Tarim River's main stream from 1990 to 2020 using Landsat series satellite imagery from Google Earth Engine. Additionally, we employed panel data models to analyze the driving roles of climate change, socio-economic factors, and policies in desertification.Results indicate that between 1990 and 2020, desertification in the main stream of the Tarim River initially intensified, with 15% of the area experiencing desertification between 1990 and 2000. However, this trend was subsequently reversed, with only 0.6% of the area undergoing desertification over the 30-year period. Extensive economic development (−37.2%) and population growth (−48.7%) were the predominant factors exacerbating desertification in the initial period (1990–2000), whereas positive policies (55.3%) were the key to reversing desertification in the main stream of the Tarim River over the past 30 years.We also explored whether policies necessarily play a positive role in combating and preventing desertification. Based on this, we suggest actively engaging in interdisciplinary research and linking research outcomes with practical situations to formulate scientifically sound policies and measures for desertification prevention and control.

Application and interpretation of linear-regression analysis.

Linear-regression analysis is a well-known statistical technique that serves as a basis for understanding the relationships between variables. Its simplicity and interpretability render it the preferred choice in healthcare research, including vision science, as it enables researchers and practitioners to model and predict outcomes effectively. This article presents the fundamentals of linear-regression modeling and reviews the applications and interpretations of the main linear-regression analysis. The primary objective of linear regression is to fit a linear equation to observed data, thus allowing one to predict and interpret the effects of predictor variables. A simple linear regression involves a single independent variable, whereas multiple linear regression includes multiple predictors. A linear-regression model is used to identify the general underlying pattern connecting independent and dependent variables, prove the relationship between these variables, and predict the dependent variables for a specified value of the independent variables. This review demonstrates the appropriate interpretation of linear-regression results using examples from publications in the field of vision science. Simple and multiple linear regressions are performed, with emphasis on the correct interpretation of standardized and unstandardized regression coefficients, the coefficient of determination, the method for variable selection, assumptions in linear regression, dummy variables, and sample size, along with common mistakes in reporting linear-regression analysis. Finally, a checklist is presented to the editors and peer reviewers for a systematic assessment of submissions that used linear-regression models. Medical practitioners and researchers should acquire basic knowledge of linear-regression such that they can contribute meaningfully to the development of technology by accurately interpreting research outcomes. Incorrect use or interpretation of appropriate linear-regression models may result in inaccurate results. Appointing an expert statistician in an interdisciplinary research team may offer added value to the study design by preventing overstated results.

EMPOWERMENT THROUGH UNDERSTANDING: A DEEP DIVE INTO LEARNING DIFFICULTIES

<p>This qualitative study focuses on a detailed investigation into the complexities of learning difficulties, aiming to uncover the underlying causes, identify prevalent symptoms, discern societal attitudes, and evaluate the efficacy of various intervention strategies. By engaging a substantial participant base of 863 individuals, the study leverages qualitative methodologies to shed light on the nuanced experiences of those with learning disabilities, including challenges related to perception, skill acquisition, and social integration. The research outcomes emphasize the critical need for a holistic understanding of learning difficulties, taking into account the intricate interplay between psychological, genetic, environmental, and educational influences. Such comprehensive insights are pivotal for the development of tailored support and intervention programs, with the potential to significantly impact educational policies and practices. This study not only enriches the academic and clinical discourse surrounding learning disabilities but also advocates for enhanced societal support mechanisms, thereby aiming to improve the educational journey and quality of life for individuals facing these challenges.</p><p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0746/a.php" alt="Hit counter" /></p>

Antibacterial bio pores as a river flow filter for the development of "Ndeso Park" water tourism

The realization of the full potential of natural resources in each village for the benefit of the local community has been observed as a significant challenge. The national village-owned enterprises program encourages villages to optimize the utilization of their existing natural and human resources with the objective of fostering their economic independence. The program entails the optimization of the national village-owned enterprises program in the tourism sector, specifically in the context of Taman Ndeso. The objective of this community service activity is to provide technological assistance and address the issue of river water filtration as a pool water source. The impetus for this activity is the declining tourism activities at Taman Ndeso due to the presence of turbid water in the pool, which was deemed unsuitable for use. The activity is realized through the construction of a water purification filtration system to produce clean and healthy water. The antibacterial biopores are applied as filtration technology. This technology is designed to capture bacteria from river water that flow into the pond. This research adopted the direct exploration method, which was divided into a number of stages, including planning and preparation, implementation, evaluation, and reporting. The research outcome manifests into the restoration of the Taman Ndeso water tourism pool, which will be capable of attracting tourists and reviving village income to the maximum extent possible, with the management of the village-owned business entity.

Evolution strategies for collaborative governance of marine microplastic pollution from the industry-research integration perspective

IntroductionMarine microplastics, are widely distributed in the global marine environment, posing a challenging issue that requires the joint efforts of global stakeholders.MethodsTo effectively address the issue of marine microplastic pollution (MMP) governance and analyze the dynamic changes in governance willingness of various participants under different scenarios, this paper meticulously constructs a game theory framework encompassing polluting enterprises, research institutions, and environmental organizations. Results(1) On the political level, the implementation of continuous and strong economic penalty mechanisms is an effective means to deter enterprises from evading MMP governance responsibilities. However, the effective execution of this strategy highly depends on the participation and supervision of environmental organizations. Therefore, it is essential to assign more roles and responsibilities to environmental organizations to ensure the thorough execution of governance measures. (2) On the technical level, the effectiveness of research directly determines the functional status of enterprises and research institutions in the MMP governance decision-making system. Weaker entities tend to make decisions following the behavioral preferences of dominant entities. Thus, deepening the integration of industry and research and fully unleashing the effectiveness of research outcomes in MMP governance is a key path to enhancing overall governance efficiency and effectiveness. (3) On the economic level, high governance costs often become a significant factor limiting the enthusiasm of all parties to participate. However, when innovative cooperation models achieve cost sharing and benefit sharing, the governance willingness of participants significantly increases. It is evident that optimizing resource allocation, improving the efficiency of fund utilization, and establishing a diversified and sustainable funding guarantee mechanism are crucial for advancing the in-depth progress of MMP governance. DiscussionIn summary, this study not only provides profound theoretical insights into the interaction relationships and behavioral choices of multiple stakeholders in MMP governance but also offers practical strategic recommendations for constructing an efficient and collaborative governance system.

Intelligent diagnostic method for beam pumping units based on torque indicator cards

An innovative approach is introduced to the intelligent diagnosis of torque indicator card conditions using electric parameters, effectively addressing the high costs associated with acquiring polished rod indicator cards and the convergence difficulties encountered when converting electrical parameters. The proposed method begins by establishing a library of 15 typical operating conditions, followed by an engineering feature analysis. Key to this approach is the use of the AlexNet model for intelligent recognition training, which successfully enhances model convergence and stability, even with varying sample sizes. This allows for automated recognition and classification of operating conditions through model training. The research outcomes demonstrate that the model achieved a fault diagnosis accuracy of over 95% for beam pumping units. This not only improves the accuracy and efficiency of fault diagnosis in oil well pumping units but also presents a novel and effective approach for intelligent diagnostic applications in oil field extraction, offering substantial practical value.