A Cognitive Study on Politeness Intention Processing and Its Association with Pragmatic Failure in Cross-Cultural Communication

Although a large number of studies have focused on various aspects of politeness,very little is known about how politeness intention is activated cognitively during verbal communication.The present study aims to explore the cognitive mechanism of politeness intention processing,and how it is related to pragmatic failure during cross-cultural communication.Using 30 Chinese EFL university students who were instructed to finish a probe word judgment task with 96 virtual scenarios,the results indicate that within both mono-and cross-cultural contexts,the response time in the experimental scenarios was significantly slower than that of the filler scenarios.This suggests that politeness intention was activated while understanding the surface meaning of the conversation;however,the EFL learners could not completely avoid the negative transfer of their native politeness conventions when they were comprehending the conversational intention of the target language.Furthermore,no significant differences in response time were found between the groups with high and low English pragmatic competence,illustrating that transferring the pragmatic rules and principles into cross-cultural communication skills was more cognitively demanding.Overall,this study adds to the literature on politeness research and provides some implications for foreign language pragmatic instructions.

The Research on the Impact Factors of the Comprehensive Evaluation of Communication Unit Camps Based on Analytic Hierarchy Process

Currently, the comprehensive assessment of the communication troops’ camp planning project is primarily qualitative, with limited quantitative evaluation. Drawing upon the relevant spirit of the Military Commission’s documents and leveraging the author’s own work experience in branch offices, this article thoroughly explores the factors influencing the comprehensive assessment of the project and proposes quantitative representation methods for these factors. Utilizing the Analytic Hierarchy Process (AHP), a hierarchical structure model and judgment matrix for the evaluation factors of the communication troops’ camp construction planning project are constructed, enabling the determination of the weightage of each factor. This provides a certain level of support and reference for the project approval and management by branch offices, while also offering valuable insights for the approval and management of camp planning and construction projects in other types of troops and battlefield projects.

Efficient stochastic parallel gradient descent training for on-chip optical processor

In recent years,space-division multiplexing(SDM)technology,which involves transmitting data information on multiple parallel channels for efficient capacity scaling,has been widely used in fiber and free-space optical communication sys-tems.To enable flexible data management and cope with the mixing between different channels,the integrated reconfig-urable optical processor is used for optical switching and mitigating the channel crosstalk.However,efficient online train-ing becomes intricate and challenging,particularly when dealing with a significant number of channels.Here we use the stochastic parallel gradient descent(SPGD)algorithm to configure the integrated optical processor,which has less com-putation than the traditional gradient descent(GD)algorithm.We design and fabricate a 6×6 on-chip optical processor on silicon platform to implement optical switching and descrambling assisted by the online training with the SPDG algorithm.Moreover,we apply the on-chip processor configured by the SPGD algorithm to optical communications for optical switching and efficiently mitigating the channel crosstalk in SDM systems.In comparison with the traditional GD al-gorithm,it is found that the SPGD algorithm features better performance especially when the scale of matrix is large,which means it has the potential to optimize large-scale optical matrix computation acceleration chips.

A Computing Resource Adjustment Mechanism for Communication Protocol Processing in Centralized Radio Access Networks

The centralized radio access cellular network infrastructure based on centralized Super Base Station(CSBS) is a promising solution to reduce the high construction cost and energy consumption of conventional cellular networks. With CSBS, the computing resource for communication protocol processing could be managed flexibly according the protocol load to improve the resource efficiency. Since the protocol load changes frequently and may exceed the capacity of processors, load balancing is needed. However, existing load balancing mechanisms used in data centers cannot satisfy the real-time requirement of the communication protocol processing. Therefore, a new computing resource adjustment scheme is proposed for communication protocol processing in the CSBS architecture. First of all, the main principles of protocol processing resource adjustment is concluded, followed by the analysis on the processing resource outage probability that the computing resource becomes inadequate for protocol processing as load changes. Following the adjustment principles, the proposed scheme is designed to reduce the processing resource outage probability based onthe optimized connected graph which is constructed by the approximate Kruskal algorithm. Simulation re-sults show that compared with the conventional load balancing mechanisms, the proposed scheme can reduce the occurrence number of inadequate processing resource and the additional resource consumption of adjustment greatly.

Application of Windows Socket Technique to Communication Process of the Train Diagram Network System Based on Client/Server Structure

This paper is focused on the technique for de si gn and realization of the process communications about the computer-aided train diagram network system. The Windows Socket technique is adopted to program for the client and the server to create system applications and solve the problems o f data transfer and data sharing in the system.

Striding Networks of Inter-Process Communication Based on TCP/IP Protocol

A mode of process/thread communication between QNX and WINDOWS operating systems in isomerous computers is described. It is proved in practice to be an entirely feasible mode with high efficiency and reliability. A socket created by Socket API is used to communicate between two operating systems.

Recent Advances in Data-Driven Wireless Communication Using Gaussian Processes: A Comprehensive Survey

Data-driven paradigms are well-known and salient demands of future wireless communication. Empowered by big data and machine learning techniques,next-generation data-driven communication systems will be intelligent with unique characteristics of expressiveness, scalability, interpretability, and uncertainty awareness, which can confidently involve diversified latent demands and personalized services in the foreseeable future. In this paper, we review a promising family of nonparametric Bayesian machine learning models,i.e., Gaussian processes(GPs), and their applications in wireless communication. Since GP models demonstrate outstanding expressive and interpretable learning ability with uncertainty, they are particularly suitable for wireless communication. Moreover, they provide a natural framework for collaborating data and empirical models(DEM). Specifically, we first envision three-level motivations of data-driven wireless communication using GP models. Then, we present the background of the GPs in terms of covariance structure and model inference. The expressiveness of the GP model using various interpretable kernels, including stationary, non-stationary, deep and multi-task kernels,is showcased. Furthermore, we review the distributed GP models with promising scalability, which is suitable for applications in wireless networks with a large number of distributed edge devices. Finally, we list representative solutions and promising techniques that adopt GP models in various wireless communication applications.

Finite family trees of continuous time birth and death processes for evaluating the transmitting speed of information on communication networks

A finite random graph generated by continuous time birth and death processes with exponentially distributed waiting times was investigated, which is similar to a communication network in daily life. The vertices are the living particles, and directed edges go from mothers to daughters. The size of the communication network was studied. Furthermore, the probability of successfully connecting senders with receivers and the transmitting speed of information were obtained.

FUNDAMENTAL COMMUNICATIONS THEORIES AND SIGNAL PROCESSING TECHNIQUES FOR AMORPHOUS CELLULAR SYSTEMS

The rapid developing of the fourth generation(4G)wireless communications has aroused tremendous demands for high speed data transmission due to the dissemination of various types of the intelligent user terminals as well as the wireless multi-media services.It is predicted that the network throughput will increase

A Study on Doctor-patient Communication under Defler Interaction Process Model

At present,doctor-patient relationship has become a sensitive topic in society,and frequent doctor-patient communication problems have become an important factor affecting the tension of the relationship.From the perspective of communication,this paper analyzes the causes of doctor-patient communication barriers based on the communication mode of interaction process proposed by Deffler and puts forward relevant solutions.

Predictive Tracking Implementation for Mobile Communication Using Programmable Metasurface

The programmable metasurface(PM)is an antenna array architecture that realizes flexible beam steering.This functionality is achieved by controlling the unit cells designed with micro components such as positive-intrinsic-negative(PIN)diodes,which offers potential cost reductions in the next generation wireless communication systems.Although PM has been a popular topic in antenna design,its implementations in real-time systems accompanied by signal processing algorithms are challenging.In this paper,novel predictive tracking algorithms for mobile communication scenarios using a PM are created and implemented in a real-time system operating at 28 GHz.An angular speed prediction(ASP)algorithm is proposed to compute the position of user equipment(UE)based on the previously recorded beam directions.As another solution,an angle correction(AC)algorithm is proposed to further improve the prediction and tracking accuracy.As a benchmark,the comparisons to a previous PM tracking algorithm without prediction are presented.Both simulation and measurement results show that the prediction algorithms successfully improve the tracking performance,which also prove the feasibilities of PM-based systems to solve complex real-time signal processing problems.

Partial Iterative Decode of Turbo Codes for On-Board Processing Satellite Platform

There is a contradiction between high processing complexity and limited processing resources when turbo codes are used on the on-board processing(OBP)satellite platform.To solve this problem,this paper proposes a partial iterative decode method for on-board application,in which satellite only carries out limited number of iteration according to the on-board processing resource limitation and the throughput capacity requirements.In this method,the soft information of parity bits,which is not obtained individually in conventional turbo decoder,is encoded and forwarded along with those of information bits.To save downlink transmit power,the soft information is limited and normalized before forwarding.The iteration number and limiter parameters are optimized with the help of EXIT chart and numerical analysis,respectively.Simulation results show that the proposed method can effectively decrease the complexity of onboard processing while achieve most of the decoding gain..

Distributed cooperative task planning algorithm for multiple satellites in delayed communication environment

Multiple earth observing satellites need to communicate with each other to observe plenty of targets on the Earth together. The factors, such as external interference, result in satellite information interaction delays, which is unable to ensure the integrity and timeliness of the information on decision making for satellites. And the optimization of the planning result is affected. Therefore, the effect of communication delay is considered during the multi-satel ite coordinating process. For this problem, firstly, a distributed cooperative optimization problem for multiple satellites in the delayed communication environment is formulized. Secondly, based on both the analysis of the temporal sequence of tasks in a single satellite and the dynamically decoupled characteristics of the multi-satellite system, the environment information of multi-satellite distributed cooperative optimization is constructed on the basis of the directed acyclic graph（DAG）. Then, both a cooperative optimization decision making framework and a model are built according to the decentralized partial observable Markov decision process（DEC-POMDP）. After that, a satellite coordinating strategy aimed at different conditions of communication delay is mainly analyzed, and a unified processing strategy on communication delay is designed. An approximate cooperative optimization algorithm based on simulated annealing is proposed. Finally, the effectiveness and robustness of the method presented in this paper are verified via the simulation.

MULTI-AGENT BASED DISTRIBUTED PROCESS PLANNING MANAGEMENT

A distributed process planning system based on autonomous multi agent system to solve a distributed process plan task in a manufacturing environment was presented. A distributed agent based process plan structure was shown to be a viable alternative to hierarchical systems providing real time response to shop floor condition. An outline was done to show how to structure a distributed process plan and how its management may be achieved among manufacturers of parts that form a product. Communication between the agents involved in a distributed process planning was also shown to be important, with the controlling agent having an overall supervision of the plans. Based on the reference model a software tool was developed to realize it.

New approach for obtaining the time-evolution law of a chaotic light field in a damping gaining-process

A new approach for studying the time-evolution law of a chaotic light field in a damping-gaining coexisting process is presented. The new differential equation for determining the parameter of the density operator p（t） is derived and the solution of f for the damping and gaining processes are studied separately. Our approach is direct and the result is concise since it is not necessary for us to know the Kraus operators in advance.

Optimal Bidirectional LSTM for Modulation Signal Classification in Communication Systems

Modulation signal classification in communication systems can be considered a pattern recognition problem.Earlier works have focused on several feature extraction approaches such as fractal feature,signal constellation reconstruction,etc.The recent advent of deep learning(DL)models makes it possible to proficiently classify the modulation signals.In this view,this study designs a chaotic oppositional satin bowerbird optimization(COSBO)with bidirectional long term memory(BiLSTM)model for modulation signal classification in communication systems.The proposed COSBO-BiLSTM technique aims to classify the different kinds of digitally modulated signals.In addition,the fractal feature extraction process takes place by the use of Sevcik Fractal Dimension(SFD)approach.Moreover,the modulation signal classification process takes place using BiLSTM with fully convolutional network(BiLSTM-FCN).Furthermore,the optimal hyperparameter adjustment of the BiLSTM-FCN technique takes place by the use of COSBO algorithm.In order to ensure the enhanced classification performance of the COSBO-BiLSTM model,a wide range of simulations were carried out.The experimental results highlighted that the COSBO-BiLSTM technique has accomplished improved performance over the existing techniques.

Lexical Processing in Context Interpretation

Elaborate explanations of word definitions and word distinctions are the usual practice in reading class in China. This paper proposes a 3P method in vocabulary learning and teaching which includes vocabulary preview, vocabulary processing, and vocabulary practice, aiming for a better knowledge of vocabulary and a better comprehension of the text.

DVCast:denoising and variable dct for analog visual communications

Recently,analog visual transmission has attracted considerable attention owing to its graceful performance degradation for various wireless channels.In this study,we propose a novel analog visual communications system,named DVCast,in which an image denoising algorithm is used to fully utilize spatial correlation;moreover,the variable block size Discrete Cosine Transform(DCT)is used to preserve more correlation information in an image.Obviously,there is a tradeoff between system performance and computing complexity.Therefore,to improve the real-time performance of the proposed system,implementation of Block Matching with 3D filtering(BM3D)and DCT by Graphics Processing Units(GPUs)is introduced.According to DCT block size,i.e.,88,1616,and 3232,the schemes DVCast8,DVCast16,and DVCast32,respectively,are designed and implemented.Simulations show that DVCast with larger block size achieves better gain and visual quality than reference schemes.Moreover,it requires less computing time.DVCast32 outperforms conventional digital schemes by approximately 3.51 dB and achieves a 1.12 dB gain over state-of-the-art reference schemes.Furthermore,the analysis shows that DVCast can reduce overhead by at least 75%.

Performance Analysis of Cross⁃Site Scripting Based on Natural Language Processing

With the acceleration of network communication in the 5G era,the volume of data communication in cyberspace has increased unprecedentedly.The speed of data transmission will accelerate.Subsequently,the security of network communication data becomes more and more serious.Among them,malicious cross⁃site scripting leading to the leakage of user information is very serious.This article uses URL attribute analysis method and YARA rule to process data for cross⁃site scripting based on the long short⁃term memory(LSTM)characteristics of LSTM model.The results show that the LSTM classification model adopted in this paper has higher recall rate and F1⁃score than other machine learning methods,which proves that the method adopted in this paper is feasible.

Off-line Programming Technology Based on RPC Communication Method and its Application

This paper puts forward a communication programming method between robot and external computer based on RPC (Remote Produce Call) communication method, which realizes robot distributed controlling network system model. And a new Robot off line programming method is built based on this communication method and network model. Further more, as an example, robot auto marking and auto cutting of shipbuilding profile system is developed, which proves the ideas of author’s off line programming and development methods of robot flexible automation system. As a result, this paper presents a new method for developing robot flexible automation system.