Research on Intelligent Application of Construction Project Management Method in the New Era

Intelligence has penetrated all walks of life with the rapid development of information technology.In the field of construction management,the application of intelligent technology is also increasingly extensive.Intelligent management methods can not only improve the efficiency and quality of construction projects but also reduce costs and waste of resources.This paper focuses on the intelligent application of construction project management methods in the new era.By analyzing the problems existing in the current construction management,the application of intelligent technology in every link of project management is expounded,including construction site management,material and equipment management,schedule control,quality supervision,and so on.At the same time,the paper also puts forward relevant suggestions on the popularization and application of intelligent management methods,which provides a reference for the innovative development of construction project management.

A Meta-analysis of the spirit turtle eight method Acupuncture Therapy for Insomnia

Objective:To systematically evaluate the efficacy and safety of the spirit turtle eight method acupuncture therapy in the treatment of insomnia,to better serve the clinic and provide reference ideas for the treatment of insomnia.Methods:Search CNKI,CBM,Wanfang,Weipu,China Clinical Trial Registry databases on the use of the spirit turtle eight method compared with others interventions to treat insomnia.The search period is from the library until August 1,2021,two researchers will conduct independent quality evaluation and effect size extraction on the literature,and use STATA16.0 and Review5.3 to conduct Meta analysis and quality evaluation on the literature.Through screening,a total of 18 eligible documents participated in the meta-analysis,with a total of 1583 cases.Results:①The effective rate of the spirit turtle eight method in the treatment of insomnia is higher than the control group[RR=1.213,95%CI(1.155,1.274),Z=7.71,P<0.01];②The Pittsburgh Sleep Quality Index(PSQI)score is lower than other acupuncture treatments[WMD=-2.33,95%CI(-2.75,-1.91),Z=10.97,P<0.01];③The one-month follow-up PSQI score after the treatment of insomnia by the spirit turtle eight method is lower than the control group[WMD=-3.263,95%CI(-3.446,-3.080),Z=34.96,P<0.01];④No studies have reported serious adverse reactions in the treatment group and control group.Conclusion:Based on the current research,the spirit turtle eight method are better than the control group in the treatment of insomnia,and are suitable for clinical application.However,more high-quality clinical studies are still needed to prove its efficacy.

Research on the College English Teaching Innovation Methods based on the Theory of Multiple Intelligence and Language Cognitive

In this paper, we conduct research on the college English teaching innovation methods based on the theory of multiple intelligence and language cognitive. Gardner Suggestions to teaching points out: “the relevant content can be shown by a variety of ways, such as teachers, books, software, hardware, or other media. In many cases, the choice of the above shows patterns, lead to the success of education experience. History can have language, logic, space, or the general pattern of personal understanding to teaching, and even can also use the space geometry teaching classroom, logic, the language and digital methods such as ability to implement teaching.” This paper combines primary theories of the corresponding issues to propose the novel understanding of the modern college English education mode that will be benefi cial for the education mode optimization.

Investigation on behavior of crack penetration/deflection at interfaces in intelligent coating system

Based on the three-phase model, the propagation behavior of a matrix crack in an intelligent coating system is investigated by an energy criterion. The effect of the elastic mismatch parameters and the thickness of the interface layer on the ratio of the energy release rate for infinitesimal deflected and penetrated crack is evaluated with the finite element method. The results show that the ratio of the energy release rates strongly depends on the elastic mismatch al between the substrate and the driving layer. It also strongly depends on the elastic mismatch a2 between the driving layer and the sensing layer for a thinner driving layer when a primary crack reaches an interface between the substrate and the driving layer. Moreover, with the increase in the thickness of the driving layer, the dependence on a2 gradually decreases. The experimental observation on aluminum alloys monitored with intelligent coating shows that the established model can better explain the behavior of matrix crack penetration and can be used in optimization design of intelligent coating.

Prediction of landslide displacement with dynamic features using intelligent approaches

Landslide displacement prediction can enhance the efficacy of landslide monitoring system,and the prediction of the periodic displacement is particularly challenging.In the previous studies,static regression models(e.g.,support vector machine(SVM))were mostly used for predicting the periodic displacement.These models may have bad performances,when the dynamic features of landslide triggers are incorporated.This paper proposes a method for predicting the landslide displacement in a dynamic manner,based on the gated recurrent unit(GRU)neural network and complete ensemble empirical decomposition with adaptive noise(CEEMDAN).The CEEMDAN is used to decompose the training data,and the GRU is subsequently used for predicting the periodic displacement.Implementation procedures of the proposed method were illustrated by a case study in the Caojiatuo landslide area,and SVM was also adopted for the periodic displacement prediction.This case study shows that the predictors obtained by SVM are inaccurate,as the landslide displacement is in a pronouncedly step-wise manner.By contrast,the accuracy can be significantly improved using the dynamic predictive method.This paper reveals the significance of capturing the dynamic features of the inputs in the training process,when the machine learning models are adopted to predict the landslide displacement.

Real-time determination of sandy soil stiffness during vibratory compaction incorporating machine learning method for intelligent compaction

An emerging real-time ground compaction and quality control, known as intelligent compaction(IC), has been applied for efficiently optimising the full-area compaction. Although IC technology can provide real-time assessment of uniformity of the compacted area, accurate determination of the soil stiffness required for quality control and design remains challenging. In this paper, a novel and advanced numerical model simulating the interaction of vibratory drum and soil beneath is developed. The model is capable of evaluating the nonlinear behaviour of underlying soil subjected to dynamic loading by capturing the variations of damping with the cyclic shear strains and degradation of soil modulus. The interaction of the drum and the soil is simulated via the finite element method to develop a comprehensive dataset capturing the dynamic responses of the drum and the soil. Indeed, more than a thousand three-dimensional(3D) numerical models covering various soil characteristics, roller weights, vibration amplitudes and frequencies were adopted. The developed dataset is then used to train the inverse solver using an innovative machine learning approach, i.e. the extended support vector regression, to simulate the stiffness of the compacted soil by adopting drum acceleration records. Furthermore, the impacts of the amplitude and frequency of the vibration on the level of underlying soil compaction are discussed.The proposed machine learning approach is promising for real-time extraction of actual soil stiffness during compaction. Results of the study can be employed by practising engineers to interpret roller drum acceleration data to estimate the level of compaction and ground stiffness during compaction.

Global Inverse Optimal Tracking Control of Underactuated Omni-directional Intelligent Navigators （ODINs）

This paper presents a design of optimal controllers with respect to a meaningful cost function to force an underactuated omni-directional intelligent navigator （ODIN） under unknown constant environmental loads to track a reference trajectory in two-dimensional space. Motivated by the vehicle＇s steering practice, the yaw angle regarded as a virtual control plus the surge thrust force are used to force the position of the vehicle to globally track its reference trajectory. The control design is based on several recent results developed for inverse optimal control and stability analysis of nonlinear systems, a new design of bounded disturbance observers, and backstepping and Lyapunov＇s direct methods. Both state- and output-feedback control designs are addressed. Simulations are included to illustrate the effectiveness of the proposed results.

Clinical Intelligent Diagnosis Path Based on the Chief Complaint

Goals of traditional Chinese medicine(TCM)include precision,accuracy,and recognition by clinical practice.Establishment of a diagnosis and treatment system that closely conforms to the principle-method-recipe-medicines system and derivation of an accurate diagnosis and treatment plan should be considerations of TCM.Artificial intelligence research based on computer technology is one of the effective ways to solve this problem.In the research of intelligent diagnosis path,reflecting the characteristics of the overall view and dialectical treatment of TCM such as"Combination of four diagnostic methods""overall examination""combination of disease and syndrome"and"treatment individualized to patient,season and locality"are key for successful research of artificial intelligence in TCM diagnosis or recognition by clinical practice.

Strategic information perception methods and practices in the open source intelligence

Open source intelligence is one of the most important public data sources for strategic information analysis. One of the primary and core issues of strategic information research is information perception,so this paper mainly expounds the perception method for strategic information perception in the open source intelligence environment as well as the framework and basic process of information perception. This paper argues that in order to match the information perception result with the information depiction result,it conducts practical exploration for the results of information acquisition,perception,depiction and analysis. This paper introduces and develops a monitoring platform for information perception. The results show that the method proposed in this paper is feasible.

THE DEVELOPING METHOD OF AI SOFTWARE FOR APPLICATION OF AERIAL PHOTOGRAPH(AIAAP)

This paper put forward a framework of artificial intelligence (AI) for app;ication of aerial photograph. The framwork contains structures of knowledge base and inference mechanism.The functions of framework about how to convert expert’s knowledge into logical rules and how to inference using the rules wer discussed. The regeneraion pltring of fired land in Dwi’an Mountains area was taken as an example to have a ditail discuss on the contation of knowledge base and the steps of inference mechaism. the program was written using the basic langUae and the running result proyed tha the software can take the place of expert’s work with high efficiellcy.

Deciphering gastric inflammation-induced tumorigenesis through multi-omics data and AI methods

Gastric cancer(GC), the fifth most common cancer globally, remains the leading cause of cancer deaths worldwide. Inflammation-induced tumorigenesis is the predominant process in GC development;therefore, systematic research in this area should improve understanding of the biological mechanisms that initiate GC development and promote cancer hallmarks. Here, we summarize biological knowledge regarding gastric inflammation-induced tumorigenesis, and characterize the multi-omics data and systems biology methods for investigating GC development. Of note, we highlight pioneering studies in multi-omics data and state-of-the-art network-based algorithms used for dissecting the features of gastric inflammation-induced tumorigenesis, and we propose translational applications in early GC warning biomarkers and precise treatment strategies. This review offers integrative insights for GC research, with the goal of paving the way to novel paradigms for GC precision oncology and prevention.

Design and Application of an Intelligent Agent for Web Information Discovery

With the propagation of applications on the internet, the internet has become a great information source which supplies users with valuable information. But it is hard for users to quickly acquire the right information on the web. This paper an intelligent agent for internet applications to retrieve and extract web information under user's guidance. The intelligent agent is made up of a retrieval script to identify web sources, an extraction script based on the document object model to express extraction process, a data translator to export the extracted information into knowledge bases with frame structures, and a data reasoning to reply users' questions. A GUI tool named Script Writer helps to generate the extraction script visually, and knowledge rule databases help to extract wanted information and to generate the answer to questions.

IMPROVED EXECUTION METHOD OF TENTACLE ALGORITHM FOR INTELLIGENT VEHICLE

In order to solve some deficiencies in tentacle execution, an improved execution method of tentacle algo- rithm is presented. The method uses a short trajectory to match the curvature between the path of vehicle and ten- tacle, rather than computing a whole steady state. To control vehicle motion via wheel force and steering angle, two parameters should be discretized under certain area and these discrete values can form 18 5〈 20 groups. Then the curvature between the trajectory and tentacle should be matched, and the corresponding group of wheel force and steering angle can be found. The flow chart of the improved execution method is given, and simulation is per- formed on a platform named ＂pro-sivic＂. The simulation results show that the improved method can maintain the advantage of the tentacle algorithm in terms of computation speed, and avoid the errors such as endless loop and data overflow, which proves the method more efficient.

Key problems in validation of intelligent models

To provide a realistic simulation environment for users,intelligent models have become key components in military simulations. After the analysis of modeling nature of intelligent models,the validation criteria for defining the validation points and validation metrics for measuring the agreements between human experts and intelligent models were presented. Further,such methods as graphical comparison,feature analysis and face validation were discussed according to the characteristics of intelligent models. Based on the validation criteria,validation metrics and validation methods,the intelligent models can be effectively validated,which has been proved in current developed intelligent models.

Distributed Intelligent Lighting System by Performing New Model for Illuminance and Color Temperature in the Workplace

A new approach has been proposed to improve the performance of the in-telligent lighting system by estimating personal illuminance and desired color temperature at the workplace. We are considering the problem of using the sensing devices manually for the intelligent lighting system. The lighting control system has not become useful without sensing devices to measure the provided illuminance and color temperature. In this paper, we have used the property of light for the color temperature to estimate the level of color temperature for each user at the workplace. The new method will give personal illuminance for each user at the workplace and decrease the power consumption of the environment as well. As a result, the proposed method of the intelligent lighting system has realized the target of illuminance and color temperature for each user at the workplace by adapting dimming levels using illuminance sensing information for each user. Thus, the energy of the workplace has reduced by using a distributed luminance to realize the target for each user.

Comparative Analysis for Evaluating Wind Energy Resources Using Intelligent Optimization Algorithms and Numerical Methods

Statistical distributions are used to model wind speed,and the twoparameters Weibull distribution has proven its effectiveness at characterizing wind speed.Accurate estimation of Weibull parameters,the scale(c)and shape(k),is crucial in describing the actual wind speed data and evaluating the wind energy potential.Therefore,this study compares the most common conventional numerical(CN)estimation methods and the recent intelligent optimization algorithms(IOA)to show how precise estimation of c and k affects the wind energy resource assessments.In addition,this study conducts technical and economic feasibility studies for five sites in the northern part of Saudi Arabia,namely Aljouf,Rafha,Tabuk,Turaif,and Yanbo.Results exhibit that IOAs have better performance in attaining optimal Weibull parameters and provided an adequate description of the observed wind speed data.Also,with six wind turbine technologies rating between 1 and 3MW,the technical and economic assessment results reveal that the CN methods tend to overestimate the energy output and underestimate the cost of energy($/kWh)compared to the assessments by IOAs.The energy cost analyses show that Turaif is the windiest site,with an electricity cost of$0.016906/kWh.The highest wind energy output is obtained with the wind turbine having a rated power of 2.5 MW at all considered sites with electricity costs not exceeding$0.02739/kWh.Finally,the outcomes of this study exhibit the potential of wind energy in Saudi Arabia,and its environmental goals can be acquired by harvesting wind energy.

Research on the reform of English writing teaching mode and its system construction under the background of information age

Today’s society has entered the information age, people’s thinking and learning methods have undergone great changes. This brings opportunities and challenges for the College English Writing Teaching. Based on the large background data in order to analyze the main problems of traditional college English teaching of writing based on proposed the idea of the University Teaching of English Writing from teaching objectives, teaching resources, teaching methods, students and life and relationships, and evaluation system. With the development of society and the times, the traditional English teaching model can not meet the needs of students. They urgently need to learn academic English knowledge for the future professional learning and research in the basic culture of academic quality. On the current status of teaching academic English at home and abroad, the author proposes a set of academic English writing class build system, and by way of comparative tests to verify the effectiveness and practicality of the system. We analyzed domestic and composition of the English examination system intelligence related applied research, put forward the theory of Constructivism basis, writing intelligent examination system to practical tools, built on Teaching of English Writing English Writing intelligent examination system so as to promote English writing teaching reform, autonomous learning ability to improve students’ English writing skills

AI-Enhanced Performance Evaluation of Python, MATLAB, and Scilab for Solving Nonlinear Systems of Equations: A Comparative Study Using the Broyden Method

This research extensively evaluates three leading mathematical software packages: Python, MATLAB, and Scilab, in the context of solving nonlinear systems of equations with five unknown variables. The study’s core objectives include comparing software performance using standardized benchmarks, employing key performance metrics for quantitative assessment, and examining the influence of varying hardware specifications on software efficiency across HP ProBook, HP EliteBook, Dell Inspiron, and Dell Latitude laptops. Results from this investigation reveal insights into the capabilities of these software tools in diverse computing environments. On the HP ProBook, Python consistently outperforms MATLAB in terms of computational time. Python also exhibits a lower robustness index for problems 3 and 5 but matches or surpasses MATLAB for problem 1, for some initial guess values. In contrast, on the HP EliteBook, MATLAB consistently exhibits shorter computational times than Python across all benchmark problems. However, Python maintains a lower robustness index for most problems, except for problem 3, where MATLAB performs better. A notable challenge is Python’s failure to converge for problem 4 with certain initial guess values, while MATLAB succeeds in producing results. Analysis on the Dell Inspiron reveals a split in strengths. Python demonstrates superior computational efficiency for some problems, while MATLAB excels in handling others. This pattern extends to the robustness index, with Python showing lower values for some problems, and MATLAB achieving the lowest indices for other problems. In conclusion, this research offers valuable insights into the comparative performance of Python, MATLAB, and Scilab in solving nonlinear systems of equations. It underscores the importance of considering both software and hardware specifications in real-world applications. The choice between Python and MATLAB can yield distinct advantages depending on the specific problem and computational environment, providing guidance for researchers and practitioners in selecting tools for their unique challenges.

Holistic and localized preparation methods for triboelectric sensors:principles,applications and perspectives

With the arrival of intelligent terminals,triboelectric nanogenerators,as a new kind of energy converter,are considered one of the most important technologies for the next generation of intelligent electronics.As a self-powered sensor,it can greatly reduce the power consumption of the entire sensing system by transforming external mechanical energy to electricity.However,the fabrication method of triboelectric sensors largely determines their functionality and performance.This review provides an overview of various methods used to fabricate triboelectric sensors,with a focus on the processes of micro-electro-mechanical systems technology,three-dimensional printing,textile methods,template-assisted methods,and material synthesis methods for manufacturing.The working mechanisms and suitable application scenarios of various methods are outlined.Subsequently,the advantages and disadvantages of various methods are summarized,and reference schemes for the subsequent application of these methods are included.Finally,the opportunities and challenges faced by different methods are discussed,as well as their potential for application in various intelligent systems in the Internet of Things.

Interaction and the Genesis of Experience: A Phenomenological Contribution for Meaningful Embodied Artificial Intelligence

In this article I will address the issue of the meaning of Embodied Artificial Intelligence(EAI)as it is configured today.My starting point is the refined interactive perspective on the semantics of EAI,as was recently suggested by Froese and colleagues.This perspective rests on the assumption that the concept of human bodily subjectivity must be extended to include meaning-making processes,which are enabled by advanced AI systems that may be incorporated in the human biological body.After having clarified the technical background,I will introduce the genetic component of the phenomenological method as a suitable tool to face the aforementioned issue.Towards this end,I will place the genetic method in the context of the so-called New Human-Machine Interaction(New HMI).I will further outline a genetic phenomenology of visual embodiment,suggesting a futuristic application based on the thesis of the“technological supplementation of phenomenological methodology”through the synthetic method.The case at stake is that of patients with a severe clinical picture characterised by the loss of corneal function,who in the near future could be treated with synthetic corneal prosthetic implants produced by a 3D bio-printing process by using an advanced EAI technique.I will conclude this article with a brief review of the main problems that still remain open.