Professional Cognitive Education Model for Agricultural Water Conservancy Engineering under the Background of New Agricultural Science

The construction of new agricultural science requires the use of modern scientific and technological means to transform and enhance current agricultural related majors.The agricultural water conservancy engineering major,with its inherent disciplinary advantages,plays an indispensable and important role in the construction of new agricultural science.In recent years,the lack of professional cognitive education has gradually become a significant problem in the training of talents in agricultural water conservancy engineering.Therefore,this paper deeply analyzes the problems and reasons faced by professional cognitive education,and proposes specific educational strategies for several key aspects such as enrollment promotion,freshman enrollment education,construction of teacher team,combination of scientific research and teaching,and strengthening professional cognition through competition activities.It aims to provide reference for improving the quality of professional cognitive education and exploring effective ways.

Cognitive Software Engineering: A Research Framework and Roadmap

The work of software engineers is inherently cognitive. Integral to their duties is understanding and developing several artifacts. Each one is based on a specific model and a given level of abstraction. What distinguishes Software Engineering is the logical complexity of some artifacts (especially programs), the high dependency among them, and the fact that the success of the software project also depends on the human and social factors, which characterize the engineers as individuals and as a group. The complexity of the daily tasks within a software development team motivates the investigation on the relevance of automating the software professionals’ cognitive processes in order to make their work easier and more efficient. The success of this endeavor is expected to emerge as Cognitive Software Engineering. For this aim, the present article suggests a research framework and roadmap, which build on the current state of the art. Some future directions in the Cognitive Software Engineering are presented.

Cognitive Engine Technology

Cognitive Radio (CR) is an intelligent radio communication system, whose intelligence mostly comes from the Cognitive Engine (CE). Based on the techniques of software-defined radio and with the support of machine reasoning and learning in artificial intelligence, cognitive engine implements the cognitive loop to realize the abilities of sensing, adaptation and learning in CR. Cognitive engine consists of the modeling system, knowledge base, reasoning engine, learning engine and interfaces. The key techniques are knowledge representation, machine reasoning and machine learning.

A numerical study of two-and three-dimensional detonation dynamics of pulse detonation engine by the CE/SE method

In this paper, the CE/SE method is developed to simulate the two- and three-dimensional flow-field of Pulse Detonation Engine (PDE). The conservation equations with stiff source terms for chemical reaction are solved in two steps. The detailed analysis of computational results of a PDE with a single detonation tube and a PDE with five detonation tubes are given in this paper. Complex wave systems are observed inside and outside a PDE. For a PDE with 5 detonation tubes, there is a big bow shock produced from a number of little shocks near the open ends of tubes. A lot of vortexes interact with shocks and a large expansion wave propagates forward and backward with respect to the PDE in a semi-oval shape.

Application of Space-time Conservation Element and Solution Element Method in Intake and Exhaust Flows of High Power Density Diesel Engine

A one-dimensional pipe flow model of single-cylinder diesel engine is established to investigate the intake and exhaust flow characteristics of diesel engine in the condition of high power density(HPD).A space-lime conservation element and solution element(CE/SE)method is used to derive the discrete equations of the partial differential equation for the intake and exhaust systems.The performance parameters of diesel engine with speed of 2100 r/min are simulated.The simulated results are in accordance with the experimental data.The effect of increased power density on charging coefficient is analyzed using a validated model.The results show that the charging coefficient is slowly improved with the increase in intake pressure,and is obviously reduced with the increase in engine speed.

A Cognitive Science Framework for the Analysis of Knowledge-Based Systems

The paper presents a cognitive science framework for the analysis of knowledge-based systems,including people, media. simulation and expert systems, resulting in a practical model for the procedures ofknowledge engineering. Starting with the construct of a social organization model driven by anticipationand thed differentiating this into pesonal scientists with diverse relations to people and their internal andexternal communication, it provides powerful and general model of society. people, and the roles of peoplein society. This model extends naturally ic the role of conventional media in the knowledge processes ofsociety and the new roles of computer-based simulation and expert systems. In particular it provides amodel of knowledge transfer that enables the processes of knowledge engineering to be analyzed andautomated.

Artificial Intelligence Based Model for Channel Status Prediction: A New Spectrum Sensing Technique for Cognitive Radio

The recent phenomena of tremendous growth in wireless communication application urge increasing need of radio spectrum, albeit it being a precious but natural resource. The recent technology under development to overview the situation is the concept of Cognitive Radio (CR). Recently the Artificial Intelligence (AI) tools are being considered for the topic. AI is the core of the cognitive engine that examines the external and internal environment parameters that leads to some postulations for QoS improvement. In this article, we propose a new Artificial Neural Network (ANN) model for detection of a spectrum hole. The model is trained with some pertinent features over a channel like SNR, channel capacity, bandwidth efficiency etc. The channel capacity status could be identified in a quantized index form . Some simulation results are presented.

Performance Analysis of Hybrid MAC Protocol for Cognitive Radio Networks

The rapid growth in demand for broadband wireless services coupled with the recent developmental work on wireless communications technology and the static allocation of the spectrum have led to the artificial scarcity of the radio spectrum. The traditional command and control model (Static allocation) of spectrum allocation policy allows for severe spectrum underutilization. Spectrum allocated to TV operators can potentially be shared by wireless data services, either when the primary service is switched off or by exploiting spatial reuse opportunities. This paper describes a hybrid access scheme based on CSMA/CA and TDMA MAC protocols for use in the TV bands. The approach allows secondary users (SU) to operate in the presence of the primary users (PU) and the OPNET simulation and modelling software has been used to model the performance of the scheme. An analysis of the results shows that, the proposed schemes protect the primary user from harmful Interference from the secondary user. In terms of delay, it was found that packet arrival rates, data rates and the number of secondary users have significant effects on delay.

Interference Mitigation MAC Protocol for Cognitive Radio Networks

The growing demand for wireless services coupled with the limited availability of suitable electromagnetic spectrum is increasing the need for more efficient RF spectrum utilization. Spectrum allocated to TV operators can potentially be shared by wireless data services, either when the primary service is switched off or by exploiting spatial reuse opportunities. This paper describes a dynamic spectrum access scheme for use in the TV bands which uses cognitive radio techniques to determine the spectrum availability. The approach allows secondary users (SU) to operate in the presence of the primary users (PU) and the OPNET simulation and modelling software has been used to model the performance of the scheme. An analysis of the results shows that the proposed scheme protects the primary users from harmful interference from the secondary users. In comparison with the 802.11 MAC protocol, the scheme improves spectrum utilization by about 27% while limiting the interference imposed on the primary receiver.

Membrane-inspired quantum bee colony optimization and its applications for decision engine

In order to effectively solve combinatorial optimization problems,a membrane-inspired quantum bee colony optimization(MQBCO)is proposed for scientific computing and engineering applications.The proposed MQBCO algorithm applies the membrane computing theory to quantum bee colony optimization(QBCO),which is an effective discrete optimization algorithm.The global convergence performance of MQBCO is proved by Markov theory,and the validity of MQBCO is verified by testing the classical benchmark functions.Then the proposed MQBCO algorithm is used to solve decision engine problems of cognitive radio system.By hybridizing the QBCO and membrane computing theory,the quantum state and observation state of the quantum bees can be well evolved within the membrane structure.Simulation results for cognitive radio system show that the proposed decision engine method is superior to the traditional intelligent decision engine algorithms in terms of convergence,precision and stability.Simulation experiments under different communication scenarios illustrate that the balance between three objective functions and the adapted parameter configuration is consistent with the weights of three normalized objective functions.

Optimization of Cognitive Radio System Using Self-Learning Salp Swarm Algorithm

CognitiveRadio(CR)has been developed as an enabling technology that allows the unused or underused spectrum to be used dynamically to increase spectral efficiency.To improve the overall performance of the CR systemit is extremely important to adapt or reconfigure the systemparameters.The Decision Engine is a major module in the CR-based system that not only includes radio monitoring and cognition functions but also responsible for parameter adaptation.As meta-heuristic algorithms offer numerous advantages compared to traditional mathematical approaches,the performance of these algorithms is investigated in order to design an efficient CR system that is able to adapt the transmitting parameters to effectively reduce power consumption,bit error rate and adjacent interference of the channel,while maximized secondary user throughput.Self-Learning Salp Swarm Algorithm(SLSSA)is a recent meta-heuristic algorithm that is the enhanced version of SSA inspired by the swarming behavior of salps.In this work,the parametric adaption of CR system is performed by SLSSA and the simulation results show that SLSSA has high accuracy,stability and outperforms other competitive algorithms formaximizing the throughput of secondary users.The results obtained with SLSSA are also shown to be extremely satisfactory and need fewer iterations to converge compared to the competitive methods.

IDSS: Designing to Extend the Cognitive Limits

The paper presents the conceptual and operational basis of the creation of IDSS based on our recent research experience. In this paper, an intelligent decision support system, IDSS is defined as: any interactive system that is specially designed to improve the decision making of its user by extending the user's cognitive decision making abilities. As a result, this view of man-machine joint cognitive system stresses the need to use computational technology to aid the user in the decision making process. And the human's role is to achieve total systems's objectives. The paper outlines the designing procedure in successive steps. First, the decision maker's cognitive needs for decision support are identified. Second, the computationally realizable support functions are defined that could be provided by IDSS. Then, the specific techniques that would best fill the decision needs are discussed. And finally, for system implementation the modern computational technology infrastructure is emphasized.

The Monty Hall Problem and beyond: Digital-Mathematical and Cognitive Analysis in Boole’s Algebra, Including an Extension and Generalization to Related Cases

The Monty Hall problem has received its fair share of attention in mathematics. Recently, an entire monograph has been devoted to its history. There has been a multiplicity of approaches to the problem. These approaches are not necessarily mutually exclusive. The design of the present paper is to add one more approach by analyzing the mathematical structure of the Monty Hall problem in digital terms. The structure of the problem is described as much as possible in the tradition and the spirit—and as much as possible by means of the algebraic conventions—of George Boole’s Investigation of the Laws of Thought (1854), the Magna Charta of the digital age, and of John Venn’s Symbolic Logic (second edition, 1894), which is squarely based on Boole’s Investigation and elucidates it in many ways. The focus is not only on the digital-mathematical structure itself but also on its relation to the presumed digital nature of cognition as expressed in rational thought and language. The digital approach is outlined in part 1. In part 2, the Monty Hall problem is analyzed digitally. To ensure the generality of the digital approach and demonstrate its reliability and productivity, the Monty Hall problem is extended and generalized in parts 3 and 4 to related cases in light of the axioms of probability theory. In the full mapping of the mathematical structure of the Monty Hall problem and any extensions thereof, a digital or non-quantitative skeleton is fleshed out by a quantitative component. The pertinent mathematical equations are developed and presented and illustrated by means of examples.

CuCeZr催化乙醇脱氢制备乙酸乙酯

乙醇作为一种重要的低碳平台分子,其下游转化制备高附加值化学品相关研究备受关注,其中乙醇脱氢法制备乙酸乙酯是一条具有竞争力的反应路线。利用共沉淀法合成了系列CuCeZr催化剂,考察共沉淀pH值对乙醇脱氢制备乙酸乙酯催化性能的影响,考察并优化反应温度、反应压力和空速等反应条件。结果表明,当沉淀pH=12时,CuCeZr催化剂的催化性能最优。在最佳条件95%乙醇水溶液为原料、进料速率0.1 mL·min-1、反应温度240℃、反应压力1.0 MPa和无载气时,乙醇转化率与乙酸乙酯选择性分别达45.6%和80.6%。催化剂连续250 h稳定运行,表明该催化剂具有良好的催化稳定性。

An Overview of Concurrent Engineering Research and Its Industrial Implementation in Chinese Enterprises

Concurrent Engineering (CE) is an effective way for enterprises to reengineer the product development processes and to improve the product development abilities. In this paper, the existing status of product development in Chinese manufacturing industry is analyzed, and the requirements of manufacturing technology for them are investigated. An overview of our CE R&D work is introduced, including product modeling, DFA, DFM, QFD, PDM, and other enabling technologies. A case study of the CE pilot project is discussed. The industrial implementation and application in Chinese enterprises are summarized.

An Evaluation of Human Error Probabilities for Critical Failures in Auxiliary Systems of Marine Diesel Engines

Human error,an important factor,may lead to serious results in various operational fields.The human factor plays a critical role in the risks and hazards of the maritime industry.A ship can achieve safe navigation when all operations in the engine room are conducted vigilantly.This paper presents a systematic evaluation of 20 failures in auxiliary systems of marine diesel engines that may be caused by human error.The Cognitive Reliability Error Analysis Method(CREAM)is used to determine the potentiality of human errors in the failures implied thanks to the answers of experts.Using this method,the probabilities of human error on failures were evaluated and the critical ones were emphasized.The measures to be taken for these results will make significant contributions not only to the seafarers but also to the ship owners.

基于“认识规律”的电化学原理课程教学设计——电子转移步骤动力学

电化学原理课程是化学、化工、材料、环境工程和新能源等专业常开的一门课程,普遍使用的教材常以“学科思维”进行编写,不符合学生的认知规律。笔者基于“认知规律”对电化学原理课程中电子转移步骤动力学章节进行了重构,将有助于学生学习目标的达成,体现了新工科建设的思维和内涵。

改进贝叶斯网络模型在起重作业人机交互差错风险分析中的应用

为量化分析起重作业人机交互差错风险,根据安全工效学原理及安全技术规范将起重作业人、机、环相关影响因素作为根节点,按照事故致因层次关联关系确定子节点,构建起重作业人机交互差错的3层级贝叶斯网络模型(Bayesian Network, BN);基于模糊集理论,采用认知可靠性与失误分析方法(Cognitive Reliability and Error Analysis Method, CREAM),厘定贝叶斯网络父节点失效概率以及中间节点条件概率;利用逆向推理仿真技术分析起重作业人机交互差错发生的因果链,探究起重伤害事故发生的人机交互差错风险。结果表明:起重作业人机交互差错最可能致因链为起重设备安全检查不到位→管理人员失误→人员操作失误→起重伤害事故发生;单因素失效条件下,起重作业人机交互差错风险概率呈线性增长趋势;在多因素失效条件下,一级节点因素失效概率愈大则人机交互差错效应愈显著,且呈现非线性增长态势。

基于驾驶员脑电微状态分析的草原公路交叉口交通设施组合研究

为解决典型草原公路交叉口交通标志组合设置现存问题,针对性优化交叉口交通工程设施组合设置。通过模拟试验,采集40名驾驶员的脑电信号,聚类为5种(MS1—MS5)微状态地形图,并对驾驶员的反应时间和微状态的持续时间、覆盖率、出现频率、转换概率进行统计分析。试验结果表明,在草原公路交叉口交通设施组合的认知过程中,驾驶员脑电微状态中的默认网络和背侧注意网络发挥主要作用;MS4的持续时间和MS1—MS3的转换概率随交通设施增多呈上升趋势,可以作为评估驾驶员认知负荷的直接指标;微状态指标和反应时趋势分析发现在信息量等级C,即4种交通工程设施组合时驾驶员大脑状态具有最佳表现,认知能力最强,负荷较小且反应最快。

认知分心情境下驾驶人应激反应行为研究

选取40名被试,采用2-back任务诱导认知分心,利用驾驶模拟系统构建行人-机动车、非机动车-机动车和机动车-机动车等3种应激场景,开展了不同应激场景正常驾驶及认知分心驾驶2种工况驾驶人的应激反应实验研究;根据采集的被试的眼动、脑电和驾驶行为等数据,分析了认知分心驾驶工况驾驶人的应激反应行为特性;对实验结果进行集对分析(SPA),完成了不同应激场景下驾驶人应激反应行为的安全性评估。结果表明:驾驶人应激反应行为的安全性因受认知分心的影响而降低,其中在行人应激场景下的影响最为显著。