China Communications Editorial Board Meeting 2017 Held in Qingdao

On October 22 and 23,2017,the China Communications Editorial Board Meeting and the China Communications Best Paper Awards Ceremony were held in Qingdao,Shandong,where more than 50 editorial board members attended the meeting.Editorial governors delivered speeches,including Prof.Jianhua Lu,Editor-in-Chief（EiC）,Prof.Zhisheng Niu,Chairman of Editorial Council,and Prof.

Editorial Council Meeting of China Communications Held in Shanghai

The 2014 Editorial Council Meeting of China Communications jounal was held in Radisson Plaza Xing Guo Hotel Shanghai on October 15,2014.Present in the meeting were Stephen Weinstein,Chairman of the Council,Zhang Xinsheng,Vice Chairman and Secretary General of China Institute of Communications,Chen Junliang,Editor in Chief,Yang Qianli,Nim Cheung,Hao Weimin.Niu Zhisheng,Zhang Honggang,Andrzej Jajszczy,and the editorial staff.

INITIATING CHINA COMMUNICATIONS AS A JOINT CIC-IEEE PUBLICATION

The IEEE Communications So- ciety （ComSoc） is happy to bejoining with the China Institute of Communications （CIC） to announce that beginning with this January, 2013 issue, China Communications is fully co-sponsored by our two societies. Professor Junliang Chen, an outstanding editorial leader, will continue to serve as Editor in Chief, aided by three distinguished Associ-ate EICs： Prof. Zhisheng Niu who is an Editor of IEEE Wireless Communications Magazine and a Guest Editor oJ this issue, Prof. Weimin Hao who is a senior advisor of Ad- visory Committee in CIC with over 50 years experiences in telecommunications engineering, research and management, and Prof. Andrzej Jajszczyk, past Editor in Chief of IEEE Communications Magazine and ComSoc Director of Maga- zines. Professor Chen and the three Associate EICs will oversee a strong international editorial staff, growing with the publication as it becomes a leading magazine for infor- mation and communication technologies （ICT） professionals around the world, with authors from many countries but with special emphasis on technology created in China. Manu- scripts will be reviewed with the same quality criteria re- quired in IEEE publications, and published articles will be archived in IEEE Xplore as with all IEEE publications. CIC will produce the magazine, with oversight of operations and editorial quality from an Editorial Council （steering com- mittee） consisting of representatives from both Societies. The chair of the Editorial Council, beginning with one of us （Stephen Weinstein） in 2013-2015, will alternate between the two Societies at three-year intervals.

Deep Learning and Tensor-Based Multiple Clustering Approaches for Cyber-Physical-Social Applications

The study delves into the expanding role of network platforms in our daily lives, encompassing various mediums like blogs, forums, online chats, and prominent social media platforms such as Facebook, Twitter, and Instagram. While these platforms offer avenues for self-expression and community support, they concurrently harbor negative impacts, fostering antisocial behaviors like phishing, impersonation, hate speech, cyberbullying, cyberstalking, cyberterrorism, fake news propagation, spamming, and fraud. Notably, individuals also leverage these platforms to connect with authorities and seek aid during disasters. The overarching objective of this research is to address the dual nature of network platforms by proposing innovative methodologies aimed at enhancing their positive aspects and mitigating their negative repercussions. To achieve this, the study introduces a weight learning method grounded in multi-linear attribute ranking. This approach serves to evaluate the significance of attribute combinations across all feature spaces. Additionally, a novel clustering method based on tensors is proposed to elevate the quality of clustering while effectively distinguishing selected features. The methodology incorporates a weighted average similarity matrix and optionally integrates weighted Euclidean distance, contributing to a more nuanced understanding of attribute importance. The analysis of the proposed methods yields significant findings. The weight learning method proves instrumental in discerning the importance of attribute combinations, shedding light on key aspects within feature spaces. Simultaneously, the clustering method based on tensors exhibits improved efficacy in enhancing clustering quality and feature distinction. This not only advances our understanding of attribute importance but also paves the way for more nuanced data analysis methodologies. In conclusion, this research underscores the pivotal role of network platforms in contemporary society, emphasizing their potential for both positive contributions and adverse consequences. The proposed methodologies offer novel approaches to address these dualities, providing a foundation for future research and practical applications. Ultimately, this study contributes to the ongoing discourse on optimizing the utility of network platforms while minimizing their negative impacts.

Assessment of the Influence of Tunnel Settlement on Operational Performance of Subway Vehicles

In the realm of subway shield tunnel operations,the impact of tunnel settlement on the operational performance of subway vehicles is a crucial concern.This study introduces an advanced analytical model to investigate rail geometric deformations caused by settlement within a vehicle-track-tunnel coupled system.The model integrates the geometric deformations of the track,attributed to settlement,as track irregularities.A novel“cyclic model”algorithm was employed to enhance computational efficiency without compromising on precision,a claim that was rigorously validated.The model’s capability extends to analyzing the time-history responses of vehicles traversing settlement-affected areas.The research primarily focuses on how settlement wavelength,amplitude,and vehicle speed influence operational performance.Key findings indicate that an increase in settlement wavelength can improve vehicle performance,whereas a rise in amplitude can degrade it.The study also establishes settlement thresholds,based on vehicle operation comfort and safety.These insights are pivotal for maintaining and enhancing the safety and efficiency of subway systems,providing a valuable framework for urban infrastructure management and long-term maintenance strategies in metropolitan transit systems.

Investigation of FRP and SFRC Technologies for Efficient Tunnel Reinforcement Using the Cohesive Zone Model

Amid urbanization and the continuous expansion of transportation networks,the necessity for tunnel construction and maintenance has become paramount.Addressing this need requires the investigation of efficient,economical,and robust tunnel reinforcement techniques.This paper explores fiber reinforced polymer(FRP)and steel fiber reinforced concrete(SFRC)technologies,which have emerged as viable solutions for enhancing tunnel structures.FRP is celebrated for its lightweight and high-strength attributes,effectively augmenting load-bearing capacity and seismic resistance,while SFRC’s notable crack resistance and longevity potentially enhance the performance of tunnel segments.Nonetheless,current research predominantly focuses on experimental analysis,lacking comprehensive theoretical models.To bridge this gap,the cohesive zone model(CZM),which utilizes cohesive elements to characterize the potential fracture surfaces of concrete/SFRC,the rebar-concrete interface,and the FRP-concrete interface,was employed.A modeling approach was subsequently proposed to construct a tunnel segment model reinforced with either SFRC or FRP.Moreover,the corresponding mixed-mode constitutive models,considering interfacial friction,were integrated into the proposed model.Experimental validation and numerical simulations corroborated the accuracy of the proposed model.Additionally,this study examined the reinforcement design of tunnel segments.Through a numerical evaluation,the effectiveness of innovative reinforcement schemes,such as substituting concrete with SFRC and externally bonding FRP sheets,was assessed utilizing a case study from the Fuzhou Metro Shield Tunnel Construction Project.

Numerical Analysis of Fiber Reinforced Polymer-Confined Concrete under Cyclic Compression Using Cohesive Zone Models

This paper examines the mechanical behavior offiber reinforced polymer(FRP)-confined concrete under cyclic compression using the 3D cohesive zone model(CZM).A numerical modeling method was developed,employing zero-thickness cohesive elements to represent the stress-displacement relationship of concrete potential fracture surfaces and FRP-concrete interfaces.Additionally,mixed-mode damage plastic constitutive models were pro-posed for the concrete potential fracture surfaces and FRP-concrete interface,considering interfacial friction.Furthermore,an anisotropic plastic constitutive model was developed for the FRP composite jacket.The CZM model proposed in this study was validated using experimental data from plain concrete and large rupture strain(LRS)FRP-confined concrete subjected to cyclic compression.The simulation results demonstrate that the pro-posed model accurately predicts the mechanical response of both concrete and FRP-confined concrete under cyc-lic compression.Lastly,various parametric studies were conducted to investigate the internal failure mechanism of FRP-confined concrete under cyclic loading to analyze the influence of the inner friction plasticity of different components.

An Improved JSO and Its Application in Spreader Optimization of Large Span Corridor Bridge

In this paper,given the shortcomings of jellyfish search algorithmwith low search ability in the early stage and easy to fall into local optimal solution,this paper introduces adaptive weight function and elite strategy,improving the global search scope in the early stage and the ability to refine the local development in the later stage.In the numerical study,the benchmark problem of dimensional optimization with a 10-bar truss structure and simultaneous dimensional shape optimization with a 15-bar truss structure is adopted,and the corresponding penalty method is used for constraint treatment.The test results show that the improved jellyfish search algorithm can provide better truss sections as well as weights.Because when the steel main truss of the large-span covered bridge is lifted,the site is limited and the large lifting equipment cannot enter the site,and the original structure does not meet the problem of stress concentration and large deformation of the bolt group,so the spreader is used to lift,and the improved jellyfish search algorithm is introduced into the design optimization of the spreader.The results show that the improved jellyfish algorithm can efficiently and accurately find out the optimal shape and weight of the spreader,and throughMidas Civil simulation,the spreader used canmeet the requirements of weight and safety.

Design Framework of Unsourced Multiple Access for 6G Massive IoT

In this paper,ambient IoT is used as a typical use case of massive connections for the sixth generation(6G)mobile communications where we derive the performance requirements to facilitate the evaluation of technical solutions.A rather complete design of unsourced multiple access is proposed in which two key parts:a compressed sensing module for active user detection,and a sparse interleaver-division multiple access(SIDMA)module are simulated side by side on a same platform at balanced signal to noise ratio(SNR)operating points.With a proper combination of compressed sensing matrix,a convolutional encoder,receiver algorithms,the simulated performance results appear superior to the state-of-the-art benchmark,yet with relatively less complicated processing.

Guest Editorial

IEEE International Conference on Communication Technology(ICCT)was jointly initiated and organized by IEEE Beijing Section and IEEE Com Soc in 1986.It is one of the highest-level academic events in the field of communication technology in China.It is also an international gathering for research for information and communication technology.

Research on Tensor Multi-Clustering Distributed Incremental Updating Method for Big Data

The scale and complexity of big data are growing continuously,posing severe challenges to traditional data processing methods,especially in the field of clustering analysis.To address this issue,this paper introduces a new method named Big Data Tensor Multi-Cluster Distributed Incremental Update(BDTMCDIncreUpdate),which combines distributed computing,storage technology,and incremental update techniques to provide an efficient and effective means for clustering analysis.Firstly,the original dataset is divided into multiple subblocks,and distributed computing resources are utilized to process the sub-blocks in parallel,enhancing efficiency.Then,initial clustering is performed on each sub-block using tensor-based multi-clustering techniques to obtain preliminary results.When new data arrives,incremental update technology is employed to update the core tensor and factor matrix,ensuring that the clustering model can adapt to changes in data.Finally,by combining the updated core tensor and factor matrix with historical computational results,refined clustering results are obtained,achieving real-time adaptation to dynamic data.Through experimental simulation on the Aminer dataset,the BDTMCDIncreUpdate method has demonstrated outstanding performance in terms of accuracy(ACC)and normalized mutual information(NMI)metrics,achieving an accuracy rate of 90%and an NMI score of 0.85,which outperforms existing methods such as TClusInitUpdate and TKLClusUpdate in most scenarios.Therefore,the BDTMCDIncreUpdate method offers an innovative solution to the field of big data analysis,integrating distributed computing,incremental updates,and tensor-based multi-clustering techniques.It not only improves the efficiency and scalability in processing large-scale high-dimensional datasets but also has been validated for its effectiveness and accuracy through experiments.This method shows great potential in real-world applications where dynamic data growth is common,and it is of significant importance for advancing the development of data analysis technology.

Network Intrusion Traffic Detection Based on Feature Extraction

With the increasing dimensionality of network traffic,extracting effective traffic features and improving the identification accuracy of different intrusion traffic have become critical in intrusion detection systems(IDS).However,both unsupervised and semisupervised anomalous traffic detection methods suffer from the drawback of ignoring potential correlations between features,resulting in an analysis that is not an optimal set.Therefore,in order to extract more representative traffic features as well as to improve the accuracy of traffic identification,this paper proposes a feature dimensionality reduction method combining principal component analysis and Hotelling’s T^(2) and a multilayer convolutional bidirectional long short-term memory(MSC_BiLSTM)classifier model for network traffic intrusion detection.This method reduces the parameters and redundancy of the model by feature extraction and extracts the dependent features between the data by a bidirectional long short-term memory(BiLSTM)network,which fully considers the influence between the before and after features.The network traffic is first characteristically downscaled by principal component analysis(PCA),and then the downscaled principal components are used as input to Hotelling’s T^(2) to compare the differences between groups.For datasets with outliers,Hotelling’s T^(2) can help identify the groups where the outliers are located and quantitatively measure the extent of the outliers.Finally,a multilayer convolutional neural network and a BiLSTM network are used to extract the spatial and temporal features of network traffic data.The empirical consequences exhibit that the suggested approach in this manuscript attains superior outcomes in precision,recall and F1-score juxtaposed with the prevailing techniques.The results show that the intrusion detection accuracy,precision,and F1-score of the proposed MSC_BiLSTM model for the CIC-IDS 2017 dataset are 98.71%,95.97%,and 90.22%.

An Rapid Assessment Method for Bearing Capacity of RC Girder Bridges Based on Residual Strain

In order to realize the in-situ evaluation of reinforced concrete bridges subjected to fatigue for a long time or after earthquake, an evaluation method for cumulative damage of concrete structures based on unloading elastic modulus was proposed. First, according to the concrete stress-strain curve and the statistical relationship between residual strain and cumulative strain, the calculation method of static equivalent strain and residual strain concrete based on unloading elastic modulus and the method for estimating the strength of concrete after damage were proposed. The detailed steps of field test and analysis and the practical damage indicators of residual strain were given. Then, the evaluation method of existing stress and strain of Reinforced Concrete Bridge under dead load and the concept of “equivalent dead load bending moment” were put forward. On this basis, the paper analyzed the root cause of the decrease of bearing capacity of Reinforced Concrete Bridge after fatigue damage, and pointed out that the equivalent strain or residual strain of reinforced concrete increases under the fatigue effect, which led to the decreasing of actual live moment and deformation performance while the ultimate load-carrying capacity remained constant or very little decrease. The evaluation method of structure residual capacity was given, and through comparative analysis of eight T reinforced concrete beams that had been in service for 35 years with the static failure tests, the effectiveness of the method was verified.

Putting People Above All

With over 200 countries and regions,more than 2,500 ethnic groups,and various religions in existence today,different civilisations have evolved,based on diverse histories,national conditions and customs.People-to-people exchanges and interactions play a crucial role in promoting people-to-people ties and enhancing exchanges and mutual learning.In today’s world,as changes unseen in a century accelerate,exchanges and mutual learning between diverse cultures are more necessary and important than ever.

Thoughts on the Development of Bridge Technology in China

In the history of bridge engineering, demand has always been the primary driving force for development. Driven by the huge demand for construction since China’s reform and opening-up, Chinese bridge has leapt forward both quantitatively and qualitatively in three major stages, by completing the transition from “follower” to “competitor,” and nally to “leader.” A new future is emerging for Chinese bridge engi- neering. As an important part of China’s transportation infrastructure, the bridge engineering industry is facing challenges in this new era on how to support the construction of a new form of transportation. This paper provides a summary of the status of bridge technology in China, based on a basic analysis of stock demand, incremental demand, and management demand. It is our belief that the Chinese bridge engi- neering industry must ful ll three outstanding requirements: construction ef ciency, management effec- tiveness, and long-term service. Intelligent technology based on information technology provides a new opportunity for innovation in bridge engineering. As a result, the development path of bridge engineering needs to be changed. This paper puts forward the idea of developing a third-generation bridge project that is characterized by intelligence, and discusses this project’s implications, development focus, and plan. In this way, this work provides a direction for the improvement of the core competitiveness of China’s bridge engineering industry.

Family Development in China Steps into New Level and Enhancement of Interpersonal Harmony and Social Emotion Is Urgently Needed——Survey Report on Family Happiness in China

Family happiness is an important index to gauge national well-being. The demand of a family is the basic need for people's livelihood. To understand the family development situation and the demand and mood of family members in China, the first'Online Survey on Family Happiness in China'was

Report of Survey on Family Happiness in China

The process and characteristics of China's population change are unique in the world. In the past 60 years,China has not only experienced the peaks and busts of the size o births, but also the radical fluctuation of the total number of deaths, and large population migration and movement Especially in the last 30 years

Experimental Studies on Cyclic Shear Behavior of Steel-Clay Interface Under Constant Normal Load

The degradation of the shear stress between pile-clay interface caused by undrained cyclic jacking affects the jacking force.A series of large displacement monotonic shear,cyclic shear and post-cyclic monotonic steel plate-clay interface shear te sts were performed under the constant normal load(CNL)condition to inve stigate the effects of normal stre ss,cyclic amplitude,and number of cycles on a steel plate-clay interface using the GDS multi-function interface shear tester.Based on the experimental results,in monotonic shear tests,change of shear stress took place in the specimen,the shear stress rapidly reached the peak value at shear displacement of 1 mm,and then abruptly decreased to the residual value.In cyclic shear te sts,accumulated displacement was a better parameter to describe the soil degradation characteristics,and the degradation degree of shear stress became greater with the increasing of normal stress and accumulated displacement.Shear stress in post-cyclic monotonic shear tests did not generate a peak value and was lower than that in monotonic shear tests under the same normal stress.The soil was completely disturbed and reached the residual strength when the cumulative displacement approached 6 m.An empirical equation to evaluate shear stress degradation mechanism was formulated and the procedure of parameter identification was presented.

Effects of Water-cement Ratio and Hydration Heat Regulating Materials on Hydration Process of Early-age Cementitious Materials

By means of low-field nuclear magnetic resonance(LF-NMR),the transverse relaxation time(T_(2))signals of physically bound water in cement paste were monitored to indicate water content change and characterize the early-age hydration process.With the curves of the T_(2)signals and hydration time obtained,the hydration process could be divided into four typical periods using the null points of the second derivative curve,and the influences of water-cement ratio(w/c)and hydration heat regulating materials(HHRM)on hydration process were analyzed.The experimental results showed that the hydration rate of pure cement paste in accelerated period presented a positive correlation with w/c.Compared to pure cement paste,the addition of HHRM extended all four periods,and led to a much faster hydration rate in initial period as well as a slower rate in accelerated period.Finally,according to the LFNMR test results,the early-age hydration model of cementitious materials was proposed considering w/c and HHRM content.

The Dual Iconic Features and Key Enabling Technologies of 6G

1.Introduction Since the 1980s,when the first generation(1G)of mobile networks came into being,mobile communications have been developing with the trend of a generational upgrade occurring every decade.At present,the fifth generation(5G)is in the commercial stage and the sixth generation(6G)is in the research stage.It is expected that the standardization for 6G will debut in the year 2025,and the first version for commercialization will be launched in 2030.For the purpose of better understanding 6G.