Research on the Optimization of Green Building Performance Based on BIM Technology

With the acceleration of urbanization,the construction industry has developed rapidly worldwide but has also brought serious environmental problems.Traditional architectural design methods often only focus on the function and beauty of the building while ignoring its impact on the environment.In addition,the lack of effective design and construction management methods also led to high resource and energy consumption.To overcome this challenge,the concept of green building came into being.Green buildings emphasize reducing the negative impact of buildings on the environment and improving resource utilization efficiency throughout the entire life cycle.BIM technology provides strong support for achieving this goal.Based on this,starting from the role of BIM technology in green building performance optimization,this article analyzes the optimization of green building performance solutions based on BIM technology in detail to promote the sustainable development of buildings.

Computer Network and Database Security Technology Optimization

With the continuous development of computer network technology, its applications in daily life and work have become increasingly widespread, greatly improving efficiency. However, certain security risks remain. To ensure the security of computer networks and databases, it is essential to enhance the security of both through optimization of technology. This includes improving management practices, optimizing data processing methods, and establishing comprehensive laws and regulations. This paper analyzes the current security risks in computer networks and databases and proposes corresponding solutions, offering reference points for relevant personnel.

Leveraging Geospatial Technologies for Resource Optimization in Livestock Management

Geospatial technologies can be leveraged to optimize the available resources for better productivity and sustainability. The resources can be human, software and hardware equipment and their effective management can enhance operational efficiency through better and informed decision making. This review article examines the application of geospatial technologies, including GPS, GIS, and remote sensing, for optimizing resource utilization in livestock management. It compares these technologies to traditional livestock management practices and highlights their potential to improve animal tracking, feed intake monitoring, disease monitoring, pasture selection, and rangeland management. Previously, animal management practices were labor-intensive, time-consuming, and required more precision for optimal animal health and productivity. Digital technologies, including Artificial Intelligence (AI) and Machine Learning (ML) have transformed the livestock sector through precision livestock management. However, major challenges such as high cost, availability and accessibility to these technologies have deterred their implementation. To fully realize the benefits and tremendous contribution of these digital technologies and to address the challenges associated with their widespread adoption, the review proposes a collaborative approach between different stakeholders in the livestock sector including livestock farmers, researchers, veterinarians, industry professionals, technology developers, the private sector, financial institutions and government to share knowledge and expertise. The collaboration would facilitate the integration of various strategies to ensure the effective and wide adoption of digital technologies in livestock management by supporting the development of user-friendly and accessible tools tailored to specific livestock management and production systems.

Advancing approach and toolbox in optimization of chloroplast genetic transformation technology

Chloroplast is a discrete,highly structured,and semi-autonomous cellular organelle.The small genome of chloroplast makes it an up-and-coming platform for synthetic biology.As a special means of synthetic biology,chloroplast genetic engineering shows excellent potential in reconstructing various sophisticated metabolic pathways within the plants for specific purposes,such as improving crop photosynthetic capacity,enhancing plant stress resistance,and synthesizing new drugs and vaccines.However,many plant species exhibit limited efficiency or inability in chloroplast genetic transformation.Hence,new transformation technologies and tools are being constantly developed.In order to further expand and facilitate the application of chloroplast genetic engineering,this review summarizes the new technologies in chloroplast genetic transformation in recent years and discusses the choice of appropriate synthetic biological elements for the construction of efficient chloroplast transformation vectors.

Discussion on Optimization Measures of Building Construction Management Technology

Building construction needs have expanded in line with people's demands and the quality of life in today’s society.Therefore,the traditional construction management technology can no longer meet the current management and construction requirements,so it is necessary to further optimize the construction management technology.Therefore,this paper focuses on exploring measures regarding building construction technology optimization.Firstly,the paper briefly expounds its optimization value,then systematically analyzes some problems faced by the current housing construction management,and finally puts forward some targeted management optimization measures for future reference.

5G Resource Allocation Using Feature Selection and Greylag Goose Optimization Algorithm

In the contemporary world of highly efficient technological development,fifth-generation technology(5G)is seen as a vital step forward with theoretical maximum download speeds of up to twenty gigabits per second(Gbps).As far as the current implementations are concerned,they are at the level of slightly below 1 Gbps,but this allowed a great leap forward from fourth generation technology(4G),as well as enabling significantly reduced latency,making 5G an absolute necessity for applications such as gaming,virtual conferencing,and other interactive electronic processes.Prospects of this change are not limited to connectivity alone;it urges operators to refine their business strategies and offers users better and improved digital solutions.An essential factor is optimization and the application of artificial intelligence throughout the general arrangement of intricate and detailed 5G lines.Integrating Binary Greylag Goose Optimization(bGGO)to achieve a significant reduction in the feature set while maintaining or improving model performance,leading to more efficient and effective 5G network management,and Greylag Goose Optimization(GGO)increases the efficiency of the machine learningmodels.Thus,the model performs and yields more accurate results.This work proposes a new method to schedule the resources in the next generation,5G,based on a feature selection using GGO and a regression model that is an ensemble of K-Nearest Neighbors(KNN),Gradient Boosting,and Extra Trees algorithms.The ensemble model shows better prediction performance with the coefficient of determination R squared value equal to.99348.The proposed framework is supported by several Statistical analyses,such as theWilcoxon signed-rank test.Some of the benefits of this study are the introduction of new efficient optimization algorithms,the selection of features and more reliable ensemble models which improve the efficiency of 5G technology.

Optimization and Performance Analysis of Intelligent Video AI Dynamic

In today’s information age,video data,as an important carrier of information,is growing explosively in terms of production volume.The quick and accurate extraction of useful information from massive video data has become a focus of research in the field of computer vision.AI dynamic recognition technology has become one of the key technologies to address this issue due to its powerful data processing capabilities and intelligent recognition functions.Based on this,this paper first elaborates on the development of intelligent video AI dynamic recognition technology,then proposes several optimization strategies for intelligent video AI dynamic recognition technology,and finally analyzes the performance of intelligent video AI dynamic recognition technology for reference.

Temperature-Based Fan Speed Optimization Strategy

As energy efficiency and indoor comfort increasingly become key standards in modern residential and office environments,research on intelligent fan speed control systems has become particularly important.This study aims to develop a temperature-feedback-based fan speed optimization strategy to achieve higher energy efficiency and user comfort.Firstly,by analyzing existing fan speed control technologies,their main limitations are identified,such as the inability to achieve smooth speed transitions.To address this issue,a BP-PID speed control algorithm is designed,which dynamically adjusts fan speed based on indoor temperature changes.Experimental validation demonstrates that the designed system can achieve smooth speed transitions compared to traditional fan systems while maintaining stable indoor temperatures.Furthermore,the real-time responsiveness of the system is crucial for enhancing user comfort.Our research not only demonstrates the feasibility of temperature-based fan speed optimization strategies in both theory and practice but also provides valuable insights for energy management in future smart home environments.Ultimately,this research outcome will facilitate the development of smart home systems and have a positive impact on environmental sustainability.

E-Commerce Supply Chain Process Optimization Based on Whole-Process Sharing of Internet of Things Identification Technology

With in-depth development of the Internet of Things(IoT)in various industries,the informatization process of various industries has also entered the fast lane.This article aims to solve the supply chain process problem in e-commerce,focusing on the specific application of Internet of Things technology in e-commerce.Warehousing logistics is an important link in today’s e-commerce transactions.This article proposes a distributed analysis method for RFID-based e-commerce warehousing process optimization and an e-commerce supply chain management process based on Internet of Things technology.This article first introduces the advantages and disadvantages of shared IoT identification technology and the IoT resource sharing platform based on the three-layer abstract data model and representational state transfer(REST)style.Combining actual IoT applications and the characteristics of an existing platform,a REST-based IoT resource sharing platform is proposed.Combined with actual projects,a REST-based IoT resource sharing platform was built,and key technology experiments were conducted for verification.Finally,optimizing the e-commerce supply chain management process under Internet of Things technology and explaining the advantages of optimized e-commerce supply chain management are discussed.Research on this subject provides a theoretical basis for the application of the Internet of Things in e-commerce and has practical significance and practical value for managing service capabilities and service levels in e-commerce.

Optimization of Extraction Technology for Rice Bran Oil

[ Objective ] This study aimed to optimize the extraction technology for rice bran oil. [ Method ] Using rice bran as raw material, effects of ultrasonicassisted extraction technology and different organic solvents, extraction durations, solid-liquid ratios and extraction temperatures on extraction results of rice bran oil were investigated. Based on the results of single-factor experiment, L9 （34 ） orthngonal experiment with three factors at three levels was conducted to optimize the extraction technological parameters, thus obtaining the optimal technological conditions for extracting rice bran oil. [ Result] Anhydrous ethanol led to the best extraction result; after ultrasonic treatment, the extraction rate of rice bran oil from raw material was not enhanced. The optimized technological parameters were ： extraction temperature of 80 ℃, extraction duration of 20 rain and solid-liquid ratio of 1：24 （ g： ml）. Under the optimized technological conditions, the extraction rate of rice bran oil reached 19.33%. [ Conclusion] This study laid solid foundation for further investigation and development of rice bran oil.

Process Optimization of RTS Technology for Ultra-Low Sulfur Diesel

The RTS technology can produce ultra-low sulfur diesel at lower costs using available hydrogenation catalyst and device.However,with the increase of the mixing proportion of secondary processed diesel fuel in the feed,the content of nitrogen compounds and polycyclic aromatic hydrocarbons in the feed increased,leading to the acceleration of the deactivation rate of the primary catalyst and the shortening of the service cycle.In order to fully understand the reason of catalyst deactivation,the effect of mixing secondary processed diesel fuel oil on the operating stability of the catalyst in the first reactor was investigated in a medium-sized fixed-bed hydrogenation unit.The results showed that the nitrogen compounds mainly affected the initial activity of the catalyst,but had little effect on the stability of the catalyst.The PAHs had little effect on the initial activity of the catalyst,but could significantly accelerate the deactivation of the catalyst.Combined with the analysis of the reason of catalyst deactivation and the study of RTS technology,the direction of RTS technology process optimization was put forward,and the stability of catalyst was improved obviously after process optimization.

Optimization Design System for Composite Structures Based on Grid Technology

To solve the topology optimization of complicated multi-objective continuous/discrete design variables in aircmit structure design, a Parallel Pareto Genetic Algorithm （PPGA） is presented based on grid platform in this paper. In the algorithm, the commercial finite element analysis （FEA） software is integrated as the calculating tool for analyzing the objective functions and the filter of Pareto solution set based on weight information is introduced to deal with the relationships among all objectives. Grid technology is utilized in PPGA to realize the distributed computations and the user interface is developed to realize the job submission and job management locally/remotely. Taking the aero-elastic tailoring of a composite wing for optimization as an example, a set of Pareto solutions are obtained for the decision-maker. The numerical results show that the aileron reversal problem can be solved by adding the limited skin weight in this system. The algorithm can be used to solve complicated topology optimization for composite structures in engineering and the computation efficiency can be improved greatly by using the grid platform that aggregates numerous idle resources.

Saponins Content in Fibrous Roots of Pseudostellaria heterophylla and Optimization of the SEP Extraction Technology

[Objectives]To explore the saponins resources in fibrous roots of Pseudostellaria heterophylla and optimize the SEP technology for extracting saponins.[Methods]Saponins contents in fibrous roots and root tubers of P.heterophylla were compared;with the fibrous roots as host materials,this experiment applied Box-Behnken design to analyze the influence of steam pressure,maintenance pressure time,moisture content of host materials on the content of saponins extracts.[Results]Saponins content was higher in fibrous roots than in tuberous roots of P.heterophylla;the response surface optimization showed that SEP(steam explosion pretreatment)promoted the contents of saponins and extracts in fibrous roots,and the optimal extracting conditions were stream pressure 1.50 Mpa,maintenance pressure time 54 s,and moisture content of host materials 30%.Under this extracting conditions,the verification value of saponins content experiment was 0.441%,36.53%higher than the untreated control group.[Conclusions]This research offered a new method of exploring saponins resources from fibrous roots of P.heterophylla,and provided a reference for developing new medicinal parts of P.heterophylla.

Simulation and optimization for synthetic technology of 2-chloro-4,6-dinitroresorcinol based on back-propagation neural network

Back-propagation neural network was applied to predict and optimize the synthetic technology of 2-chloro-4,6-dinitroresorcinol. A model was established based on back-propagation neural network using the experimental data of homogeneous design as the training sample set and the technological parameters were optimized by it. The optimal technological parameters are as follows： the reaction time is 4h, the reaction temperature is 80℃, the molar ratio of NaOH to 4,6-dinitro-1,2,3-trichlorobenzene is 5.5：1, the molar ratio of methanol to 4,6-dinitro-1,2,3- trichlorobenzene is 11：1, and the molar ratio of water to 4,6-dinitro-1,2,3-trichlorobenzene is 70：1. Under the optimal conditions, three groups of experiments were performed and the average yield of 2-chloro-4,6-dinitroresorcinol is 96.64%, the absolute error of it with the predicted value is -1.07%.

Analysis of Effective Optimization Methods for Building Construction Technology Management

During the construction process of the construction project,the construction technology management work can improve the overall quality of the project construction.In the context of increasingly fierce competition in the construction market,construction enterprises should strengthen the management of construction technology,enhance their technical level and market competitiveness,and promote the development of the construction market[1].The paper mainly analyzes the optimization methods of build-Keywords:ing construction technology management.

Technological Optimization of the Preparation of Imidacloprid

In order to reduce the production cost of imidacloprid, the preparation technology for the direct com-bination of 2-chloro-5-chloromethylpyridine and 2-nitryliminoglyoxaline has been optimized in a 10 L stirred tank reactor with a new solvent, butanone, and a new catalyst, benzyl triethyl-ammonium chloride (BTEAC), which was proved to be more profitable for the production of imidacloprid. Three main affecting factors (the reaction temper-ature, the molar ratio of BTEAC to 2-nitryliminoglyoxaline and the concentration of 2-nitryuminoglyoxaline) for the production of imidacloprid were investigated and the optimum operating conditions were found. Based on the above technological optimization, an industrial process for imidacloprid with a production capacity of 50 tons per year was put in operation using a 2500 L stirred tank reactor under the same operating conditions. Good yield and purity of imidacloprid was also obtained in the industrial production.

Research on the User Information Optimized Retrieval Technology in Distributed Database

The traditional method first classifies the user information and combines the query method to retrieve the interest information, but neglects to calculate the weight of the user interest information, which leads to the low retrieval accuracy. A retrieval method based on the fuzzy proximity classification technology is proposed. Approximation between the fuzzy sets is used to represent the consistency between the user interest information features, and the consistency calculation formula and the skewness confidence matrix between the user interest information features are given. The fuzzy classification of the user interest information can obtain the most consistent confidence data and eliminate the redundant approximation interference data. The probabilistic model of the information word frequency and the user interest information length calculates the weight of the user interest information, and adjusts the weight formula constantly.

Mathematical Apparatus for Selection of Optimal Parameters of Technical, Technological Systems and Materials Based on Vector Optimization

We presented Mathematical apparatus of the choice of optimum parameters of technical, technological systems and materials on the basis of vector optimization. We have considered the formulation and solution of three types of tasks presented below. First, the problem of selecting the optimal parameters of technical systems depending on the functional characteristics of the system. Secondly, the problem of selecting the optimal parameters of the process depending on the technological characteristics of the process. Third, the problem of choosing the optimal structure of the material depending on the functional characteristics of this material. The statement of all problems is made in the form of vector problems of mathematical (nonlinear) programming. The theory and the principle of optimality of the solution of vector tasks it is explained in work of https://rdcu.be/bhZ8i. The implementation of the methodology is shown on a numerical example of the choice of optimum parameters of the technical, technological systems and materials. On the basis of mathematical methods of solution of vector problems we developed the software in the MATLAB system. The numerical example includes: input data (requirement specification) for modeling;transformation of mathematical models with uncertainty to the model under certainty;acceptance of an optimal solution with equivalent criteria (the solution of numerical model);acceptance of an optimal solution with the given priority of criterion.

Optimal Rules to Adopt High Technology under Uncertainty

In the research of choosing the optimal timing for the high technology products, especially IT products to the market, most studies prefer to provide the scope or infnnum of timing. In this paper, an optimal rule is adopted to guild the timing of high technology product to the market, this idea is illustrated through the theory of optimal stopping, and a high approach is developed to theoretical framework for timing decision. On this basis, a random programming model is established, in which the objective function is the expected profit to adopt high technology and the constraint condition is the successful probability over critical value a with all variables beyond the rule, and it is used to find the optimal timing of adopt high technology product.