Comprehensive Efficiency Research Articles

Research on the Evaluation of the Effectiveness of Industry-Teaching Integration Construction of Higher Vocational Excellence Courses--Based on Network DEA Model Analysis

Abstract The integration of industry and education is an important model for building high-level higher vocational colleges and universities, and it is also a necessary way to promote the modernization and development of higher vocational education. Based on Hall’s three-dimensional structural model, this paper explores the specific process of the construction of industry-teaching integration of high-level, high-quality courses and evaluates the effectiveness of the construction of industry-teaching integration of high-level, high-quality courses using the network SBM-DEA model. The evaluation index system was first constructed according to the questionnaire survey method, Delphi method, and hierarchical analysis method, and then the indexes were screened and applied to the empirical analysis of the effectiveness of the construction of industry-teaching fusion of higher vocational boutique courses. The average overall operational efficiency of the industry-teaching fusion of boutique courses at 45 higher vocational colleges and universities is 0.547, which is the average level. However, the efficiency of the two phases still has some differences between the average efficiency value of the resource construction phase and the outcome output phase. The correlation coefficient between the efficiency of the outcome output stage and the overall operational efficiency is 0.885, which is highly correlated. Most institutions pay more attention to the operation of the outcome output stage. The R² of the fit between pure technical efficiency and comprehensive efficiency is 0.731, and the R² of the fit between scale efficiency and comprehensive efficiency is 0.264, indicating that pure technical efficiency is the dominant factor affecting the comprehensive efficiency of institutions. In the two stages of resource construction and output of results, the output side shows insufficient output, while the input side shows input redundancy, indicating that the input resources are not effectively utilized. This paper provides a direction of action to strengthen the deep integration of industry and education in higher vocational boutique courses and to promote complementary resources and a benign interaction between schools and enterprises.

Research on English Reading Comprehension Strategies Based on Natural Language Processing

Abstract This study investigates strategies based on natural language processing to improve the efficiency and effectiveness of English reading comprehension by analyzing and optimizing reading comprehension models. We introduce the main framework of the English reading comprehension task, including the word embedding representation layer, the context encoding layer, the information interaction layer, and the output layer. The article utilizes the Word2vec model and decision tree ID3 algorithm to enhance the efficiency and accuracy of reading comprehension. The research data comprised 800 English articles, with 60% used for training and 40% used for testing. The articles were graded for difficulty and resources were pushed. It was found that the model proposed in this study performs better in difficulty grading (with a rating range of 0.797-0.926) and is more efficient in terms of time overhead (feature extraction time of about 10 milliseconds, and grading time of 1.7-2.6 seconds), compared to the traditional models such as BiLSTM and RNN. The pushed resources significantly correlate with learners’ self-assessed difficulty and actual performance. The NLP-based strategy proposed in the paper shows significant advantages in both efficiency and accuracy, and helps to improve English learners’ reading comprehension.

Effective paths and model innovations for social work-driven child protection in the context of the Internet

Abstract Children are the hope and future of the country, and doing an excellent job for children is of great importance to social development. Social work program efficiency assessment, can help service providers and program implementers understand the effectiveness of program implementation. For this reason, this study uses data envelopment analysis and the Tobit regression model to construct a child protection social work program efficiency assessment model. The input-output indicators of child protection program efficiency are selected. The model is used to analyze the input-output efficiency of social work child protection programs in City H from 2018-2021 as an example. The variables that affect the efficiency of child protection programs are explored in depth to explore the effective ways of child protection. The results show that the comprehensive technical efficiency, pure technical efficiency, and scale efficiency of the child protection program in 2018-2021 are all less than 1 and have not reached DEA efficiency. The comprehensive technical efficiency of the program is significantly affected by the scale efficiency, which necessitates an increase in resource investment in the child protection program. In addition, the six selected influencing factors are significant, at least at the 10% level, all of which positively affect the efficiency of child protection programs and need to be focused on to better improve the efficiency of social work services.

A Study on the Development Trend and Mechanism Perfection of Cultural Industry in Western China Based on Variable Model

Abstract As an emerging industry with high growth, the cultural industry plays an increasingly prominent role in boosting national economic construction and enriching people’s lives. This paper utilizes the relevant statistical data of the culture industry in 2022, selects the indicators of input-output variables, and adopts the three-stage DEA method to measure the efficiency level of the culture industry in Western China and explore the development trend of the culture industry in western China after eliminating the influence of external environment and random variables on the analysis results. In addition, the level of cultural industry efficiency in West China is taken as an explanatory variable. Relevant explanatory variables are selected to derive the influence of each variable on cultural industry efficiency by the partial least squares method, and regional heterogeneity is detected. The overall cultural industry efficiency in the western region is low; more than 30% of the inputs do not create value, and 50% of the provinces and municipalities have a low level of cultural industry operation and management and low development of industry scale. Except for Chongqing and Shaanxi, all other provinces and cities are in the stage of increasing returns to scale. The selected explanatory variables all positively contribute to the comprehensive technical efficiency of the cultural industry, with the most significant effect of the urbanization level, with a regression effect of 0.387. Focusing on improving the operation and management levels and the scale of the cultural industry is the key to enhancing the efficiency of the overall cultural industry in the West.

Research on the Comprehensive Noise Reduction Efficiency of Urban Green Space Plant Communities $lt;BR$gt;—Taking the Plant Communities of Suzhou River Waterfront Green Space in Shanghai as an Example

Research on the Comprehensive Noise Reduction Efficiency of Urban Green Space Plant Communities $lt;BR$gt;—Taking the Plant Communities of Suzhou River Waterfront Green Space in Shanghai as an Example

An Initial Exploration of an Intercollegiate Collaborative Innovation Path for Aviation Equipment Primary Training Based on ANT

Talent cultivation for primary training of aviation equipment majors has many modules, many categories, long class hours and cross-fields, and there are realistic difficulties in improving the teaching effect. After a number of training practices and explorations, it is found that collaborative training based on inter-college innovation has obvious advantages. In view of the real problems of aviation equipment professional primary training personnel training, based on the perspective of the advanced theory widely recognized in the education sector -actor network theory (ANT), we have explored the intercollegiate synergistic path with military colleges as the main body, which is of certain practical significance for further improving the comprehensive quality and efficiency of aviation security primary training personnel training.

Fine-Grained Learning Behavior-Oriented Knowledge Distillation for Graph Neural Networks.

Knowledge distillation (KD), as an effective compression technology, is used to reduce the resource consumption of graph neural networks (GNNs) and facilitate their deployment on resource-constrained devices. Numerous studies exist on GNN distillation, and however, the impacts of knowledge complexity and differences in learning behavior between teachers and students on distillation efficiency remain underexplored. We propose a KD method for fine-grained learning behavior (FLB), comprising two main components: feature knowledge decoupling (FKD) and teacher learning behavior guidance (TLBG). Specifically, FKD decouples the intermediate-layer features of the student network into two types: teacher-related features (TRFs) and downstream features (DFs), enhancing knowledge comprehension and learning efficiency by guiding the student to simultaneously focus on these features. TLBG maps the teacher model's learning behaviors to provide reliable guidance for correcting deviations in student learning. Extensive experiments across eight datasets and 12 baseline frameworks demonstrate that FLB significantly enhances the performance and robustness of student GNNs within the original framework.

FEVERLESS: Fast and Secure Vertical Federated Learning based on XGBoost for Decentralized Labels

Vertical Federated Learning (VFL) enables multiple clients to collaboratively train a global model over vertically partitioned data without leaking private local information. Tree-based models, like XGBoost and LightGBM, have been widely used in VFL to enhance the interpretation and efficiency of training. However, there is a fundamental lack of research on how to conduct VFL securely over distributed labels. This work is the first to fill this gap by designing a novel protocol, called FEVERLESS, based on XGBoost. FEVERLESS leverages secure aggregation via information masking technique and global differential privacy provided by a fairly and randomly selected noise leader to prevent private information from being leaked in the training process. Furthermore, it provides label and data privacy against honest-but-curious adversaries even in the case of collusion of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$n - 2$</tex-math></inline-formula> out of n clients. We present a comprehensive security and efficiency analysis for our design, and the empirical results from our experiments demonstrate that FEVERLESS is fast and secure. In particular, it outperforms the solution based on additive homomorphic encryption in runtime cost and provides better accuracy than the local differential privacy approach.

Energy efficiency and energy-saving evaluation methods for public building energy systems under the dual carbon background

The energy consumption characteristics and energy system structure of each type of building are different, so the evaluation methods and indicators need to be customized for different types of buildings, which increases the complexity of the evaluation. Therefore, a method for evaluating the energy efficiency and energy conservation of public building energy systems under the dual carbon background is proposed. Analyze the coupling coefficient data of energy quality, energy and flow, obtain the base of energy efficiency optimization coefficients, and use twin technology to establish a comprehensive energy efficiency model. Introduce matter element analysis and use matter element extension models to evaluate the energy efficiency and energy-saving effects of public building energy systems. The experimental test results show that the research method can accurately evaluate the energy consumption of public buildings and has an effective evaluation effect on different types of buildings.

Innovative Research on Cultivation Mechanism and Introduction Mechanism of Top Talents in Colleges and Universities under the Background of Big Data

Abstract In the context of fierce competition for talents in colleges and universities, cultivating and introducing outstanding young talents are crucial to the construction and sustainable development of talents in colleges and universities. The article utilizes the IPO model to construct an evaluation system for the quality of cultivation of top talents and the implementation effect of talent introduction policy in colleges and universities. The study takes eight colleges and universities in the university city of Province P as examples, uses the EWM method to determine the weights of the indicators, and carries out a comprehensive evaluation through the improved TOPSIS method and the Data Envelopment Analysis Model (DEA). The results show that in talent cultivation, the weight of the result quality is 18.09% higher than the essential quality. In contrast, in implementing the talent introduction policy, the maximum difference of each weight value is only 1.24%.The effective decision-making unit of the DEA reaches the optimal value of 1.00 in the comprehensive technical efficiency, pure technical efficiency and scale efficiency. The study reveals the shortcomings of implementing talent cultivation and introduction policy in universities. It guides the universities to improve the mechanism of cultivation and introduction of top talents, to enhance the core competitiveness.

Study on the transformation model of old neighborhoods oriented towards sustainable community economic development

Abstract Urban renewal now dominates the strategic stage of urbanization, shifting from the previous focus on “whether there is” to the pursuit of “good.” In the context of urban renewal, the transformation of old neighborhoods should be carried out reasonably. In this regard, this study focuses on exploring design ideas for the transformation of old neighborhoods in the context of sustainable community economic development, with the aim of proposing a set of comprehensive transformation programs. Then, based on the three perspectives of residents, community, and city, the evaluation indexes for the transformation of old neighborhoods are selected from two perspectives of input-output, and the transformation efficiency evaluation model is constructed by combining the model of DEA-BCC and the model of DEA-Malmquist index. Finally, taking 19 old neighborhoods in QD city as samples, we analyze the citizens’ satisfaction with the transformation effect of the neighborhoods, analyze the efficiency of the transformation investment in the old neighborhoods from the two perspectives of comprehensive efficiency value and scale efficiency value, and analyze the problems and the direction of improvement of the transformation of the old neighborhoods from the redundancy of the slack variables. The results show that the average investment efficiency of the old neighborhood transformation is 0.9185, and the pure technical efficiency and scale efficiency are 0.9239 and 0.9651, respectively.

Value, Dilemmas and Innovative Strategies of Educational Management Clustering in the Internet Era

Abstract With the continuous improvement of the national education system, the Internet brings new opportunities for educational development but also brings specific challenges to the educational management of colleges and universities. This paper aims to analyze the current situation of education management in colleges and universities and construct an innovation model for education management clustering based on PDCA, which will be explored for its development value and power. And then, using the partial least squares regression algorithm and its modeling steps, to construct the educational management clustering regression model. The influencing factors of the educational management clustering model are analyzed with 12 “double first-class” colleges and universities in five provinces in Northwest China as research objects. The results show that the average comprehensive efficiency and pure technical efficiency of the universities in Northwest China range from 0.6585 to 0.9987 and from 0.773 to 0.994, respectively, indicating that the efficiency of higher education resource allocation in Northwest China is constantly improving. Compared with the traditional education management model, the colleges and universities applying the education management clustering model constructed in this paper in 2022–2023 show a scale-invariant trend, indicating that the colleges and universities have sufficiently invested in education resources and realized the scale efficiency. Educational management clustering can improve the efficiency of school educational resource allocation, thus improving the level of educational management and providing a theoretical basis for the study of innovative strategies in educational management.

Towards a generic framework of OEE monitoring for driving effectiveness in digitalization era

In today's dynamic business environment, achieving and sustaining operational efficiency is paramount for organizations. To remain competitive and meet evolving customer demands, companies strive to optimize their operations and enhance efficiency. Over time, various indicators have been developed to assess efficiency across multiple operational dimensions, aligning with technological advancements and industrial practices. One such indicator is Overall Equipment Effectiveness (OEE), which evaluates equipment efficiency based on availability, performance, and quality. However, with the advent of the digital industry, the management of data for efficiency calculations has become increasingly complex.In this context, this paper proposes a digitized, real-time OEE calculation system that leverages advanced technologies to continuously monitor OEE, enable real-time decision-making, and drive performance improvements. Harnessing the potential of digitalization, the system facilitates seamless data collection, analysis, and reporting while automating manual processes. By focusing on OEE as a comprehensive efficiency indicator, the proposed system aims to enhance organizational performance and establish a foundation for calculating other efficiency measures.

Collaborative Filtering Algorithms in Financial Performance Evaluation Indicators for Intelligent Innovation Dynamic Research

Abstract This study develops a financial performance evaluation system for S Group, employing a collaborative filtering algorithm to address the limitations inherent in traditional financial performance evaluation methodologies. Improvements have been made to the similarity measure method, data imputation technique, and rating prediction approach within the model. Subsequently, the financial status of S Group is scrutinized, with a thorough exploration of the input and output indicators, leading to the calculation of the efficiency values within the financial indicator system. Through sensitivity analysis, this research investigates the impact of input and output indicators on the outcomes derived from collaborative filtering. Based on the study, recommendations are formulated in alignment with the evaluation outcomes. The findings reveal that the average comprehensive efficiency of S Group over the past decade is 0.772, with a median comprehensive efficiency of 0.788, indicative of a robust financial condition. This research provides a valuable reference for the formulation of financial performance evaluation systems and the analysis of financial performance across various industries.

Informatization Exploration of Innovation and Entrepreneurship Education Mode in Vocational Colleges under the View of Industry-Teaching Integration

Abstract Innovation and entrepreneurship are essential for higher vocational students to escape low-end employment and are vital for vocational education to provide diverse products and services, fulfilling the people’s demand for a better life. This study builds on the theory of innovation and entrepreneurship education, integrating information technology to devise the “Four-Drive-One-Guide” model for vocational colleges. Utilizing Province A as a case study, a survey was conducted to gather data on the effectiveness of this education model, analyzed using ANOVA, Pearson’s correlation coefficient, and multiple linear regression. Furthermore, the operational efficiency of innovation and entrepreneurship education across 30 Chinese regions was assessed using the CCR model within the DEA framework. Findings reveal that the “Four-Drive-One-Guide” model significantly boosts students’ innovative and entrepreneurial capabilities, with an average rating of 4.06. The most influential factor in its effectiveness is students’ attitudes, with a coefficient of 0.238. Moreover, vocational colleges in the eastern region exhibit the highest comprehensive efficiency at 0.875. The study suggests that integrating industry teaching and optimizing the curriculum can further enhance students’ innovative and entrepreneurial thinking.

Enhancing Hospital Performance: The Comprehensive Efficiency Index Approach

Enhancing Hospital Performance: The Comprehensive Efficiency Index Approach

Трансформация механизмов обеспечения эффективности в условиях циркулярной экономики

The paper is dedicated to analyzing the process of transformation of efficiency mechanisms in the circular economy. The authors substantiate that a linear economic model with a focus on results in the form of profit does not meet the values of modern society, the main ones of which are the achievement of universal social and environmental wellbeing. Thus, the purpose of this study is to develop mechanisms for ensuring the efficiency of economic activity in the circular economy, a model that meets current values. To achieve the goal, the following research tasks were formulated and solved: to analyze existing generally accepted criteria for assessing efficiency for their relevance to circular economic models; identify the main features of the transformation of the economic system into a circular model; propose an integral indicator of the economic effect of a circular economic system, taking into account all the features of the functioning of such a system; formulate principles of effective interaction within circular ecosystems. As a result of the study, the authors have concluded that it is the economic integration of enterprises within one closed economic system and their interaction that will ensure comprehensive efficiency.

A Study on Corporate Management Strategies for Downstream Innovation Ecosystems in the Context of Digital Economy

Abstract The rapid development of the digital economy makes the center of gravity of enterprise development accelerate from the consumer field to the production and manufacturing field, penetrating all aspects of the daily operation and management of an enterprise. This paper presents relevant management strategies by exploring the impact of the ecosystem model of enterprise management innovation on the impact of enterprise management in the digital context. In order to measure the comprehensive efficiency value, the efficiency value of capital absorption, and the efficiency value of investment after enterprise management, the theory of antagonistic cross-efficiency is introduced, the antagonistic cross-DEA model is constructed, and the evaluation steps of enterprise management effect are given. Using this model to empirically analyze the management effectiveness of China’s construction industry, enterprise performance=4.563+0.352*digital innovation ecosystem index+0.236* periodic cost+0.362*number of R&amp;D personnel, and the digital innovation ecosystem is significantly related to enterprise performance. Finally, this paper designs a corporate management strategy for the digital innovation ecosystem in the context of the digital economy from three perspectives.

Experimental study on the performance enhancement of PV/T by adding graphene oxide in paraffin phase change material emulsions

Traditional water-based PV/T systems have low heat storage density, high PV backsheet temperatures, and low energy utilization in practical applications. In this work, nanoparticles were applied to improve thermal conductivity and simultaneously emulsions were added to enhance energy storage density of the conventional heat transfer media. Furthermore, the synergistic effect of nanocomposite Phase Change Material Emulsions (PCME) as the heat transfer medium on the thermoelectric efficiency of PV/T was studied in a real system. Specifically, the water-based 30 % paraffin emulsions with graphene oxide (GO) concentration of 0.01, 0.02 and 0.03 wt% were prepared by ultrasonic stirring and their thermophysical properties were characterized. The results show that the 30 wt% paraffin emulsion with addition of 0.02 wt% GO has the phase change temperature of 35 °C, latent heat of 42.93 J/g, thermal conductivity of 0.505 W/(m·K) and viscosity coefficient of 0.91. It shows the thermal efficiency of the paraffin/GO emulsion increased by 92.28 %, the electrical efficiency increased by 8.87 %, the comprehensive efficiency increased by 45.75 %, and 15.8 % increase in heat collection for the heat exchange tank in comparison with the water. It is concluded application of PCME would improves the thermoelectric performance of the system than traditional water-based PV/T systems.

Numerical Simulation and Experimental Research on Heat Transfer Characteristics Based on Internal Meshing Screw

The mixing and processing of high-viscosity materials play a pivotal role in composite material processing. In this context, the internal meshing screw mixer, rooted in volume extensional rheology, offers distinct advantages, including heightened mixing efficiency, exceptional material adaptability, and favorable thermomechanical properties. This research endeavors to advance our understanding of these qualities by presenting an in-depth exploration of internal meshing screw mixing. To facilitate this, an internal meshing screw mixing experimental apparatus was meticulously constructed, accompanied by extensive numerical simulations and experimental investigations into its heat transfer characteristics. Two distinct heat transfer modes are established: Mode 1 entails the transfer of the high temperature from the outer wall of the stator to the interior, while Mode 2 involves the transmission of the high temperature from the inner wall of the rotor to the exterior. The ensuing research yields several notable findings: 1. It is evident that higher rotational speeds lead to enhanced heat transfer efficiency across the board. However, among the three rotational speeds examined, 60 rpm emerges as the optimal parameter for achieving the highest heat transfer efficiency. Furthermore, within this parameter, the heat transfer efficiency is superior in Mode 1 compared to Mode 2. 2. As eccentricity increases, a corresponding decline in comprehensive heat transfer efficiency is observed. Moreover, the impact of eccentricity on heat transfer efficiency becomes increasingly pronounced over time. 3. A lower gap dimension contributes to higher heat transfer within the system. Nevertheless, this heightened heat transfer comes at the expense of reduced stability in the heat transfer process. 4. It is demonstrated that heat transfer in Mode 1 primarily follows a convection heat transfer mechanism, while Mode 2 predominantly exhibits diffusion-based heat transfer. The heat transfer efficiency of Mode 1 significantly surpasses that of Mode 2. This research substantiates its findings with the potential to enhance the heat transfer efficiency of internal meshing screw mixers, thereby making a valuable contribution to the field of polymer engineering and science.