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中国邮电高校学报：英文版

中国邮电高校学报：英文版

《中国邮电高校学报》(英文)是由六所高校（北京邮电大学，南京邮电大学，吉林大学、重庆邮电大学，西安邮电学院，及石家庄邮电职业技术学院）于1994年联合创办, 北京邮电大学主办的国内外公开发行，以“信息学科”为特色的学术性科技核心期刊。现为双月刊，大16开。主要刊载通信与信息系统、信号与信息处理、自然语言处理、高等智能、计算机软件与理论、计算机应用技术、电磁场与微波技术、微电子学与固体电子学、控制理论与控制工程等相关基础技术领域的学术论文、研究报告、综述以及学位论文等。它是以促进学术交流，推动技术创新，实现通信现代化和科学技术进步为宗旨。读者对象主要为高等院校师生，科研院(所)的科研人员，企事业的工程技术及管理人员等。
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  • 发文量：2076
  • 被引量：1104
  • H指数：7
  • 开始收录时间：1994,1(1)
  • CNKI综合因子：0.273
  • 维普期刊影响因子： 0.263
  • 万方期刊影响因子：0.34
  • 创刊时间：1994
  • 国内刊号/CN：11-3486/TN
    国际刊号/ISSN：1005-8885
  • 发行周期：双月刊
    邮发代号：2-629
  • 主管单位：中华人民共和国教育部
    主办单位：北京邮电大学
中国邮电高校学报：英文版-联系信息
  • 主编：张平
  • 电话：010-62282493
  • 邮箱：jchupt@bupt.edu.cn
  • 地址：北京邮电大学231信箱
  • 邮编：100876
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中国邮电高校学报：英文版 >2023年第6期
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  • 摘要：In order to meet the emerging requirements for high computational complexity, low delay and energy consumption of the 5 th generation wireless systems(5 G) network, ultra-dense networks(UDNs) combined with multi-access edge computing(MEC) can further improve network capacity and computing capability. In addition, the integration of green energy can effectively reduce the on-grid energy consumption of system and realize green computation. This paper studies the joint optimization of user association(UA) and resource allocation(RA) in MEC enabled UDNs under the green energy supply pattern, users need to perceive the green energy status of base stations(BSs) and choose the one with abundant resources to associate. To minimize the computation cost for all users, the optimization problem is formulated as a mixed integer nonlinear programming(MINLP) which is NP-hard. In order to solve the problem, a deep reinforcement learning(DRL)-based association and optimized allocation(DAOA) scheme is designed to solve it in two stages. The simulation results show that the proposed scheme has good performance in terms of computation cost and time out ratio, as well achieve load balancing potentially.
  • 摘要：Unmanned aerial vehicle base stations(UAV-BSs)can provide a fast network deployment scheme for heterogeneous networks.However,unmanned aerial vehicle(UAV)has limited capability and cannot assist the base station(BS)well.The ability of a UAV to assist the BSs is limited,and the cluster deployment relies on the leading UAV.The dispersive deployment of multiple UAVs(multi-UAVs)need a macro base station(MBS)to determine their positions to prevent collisions or interference.Therefore,a distributed cooperative deployment scheme is proposed for UAVs to solve this problem.The scheme can increase the ability of UAVs to assist users and reduce the pressure on BSs to deploy UAVs.Firstly,the randomly distributed users are pre-clustered.Then the placement problem was modeled as a circle expansion problem and a pre-clustering radius expansion algorithm was proposed.Under the constraint of users'data rates,it provides services for more users.Finally,the proposed algorithm was compared with the density-aware placement algorithm.The simulation results show that the proposed algorithm can provide services for more users and improve the coverage rate of users while ensuring the data rates.
  • 摘要：A downlink covert communication model that consists of a base station and two legitimate users was considered. In addition to the general signals shared by the two users, the base station will send the covert signals only to one user in a certain time without wanting the other to detect this covert communication behavior. In order to achieve covert communication, two information transmission schemes are designed based on transmission antenna selection(TAS) with the help of artificial noise(AN) transmitted by the user receiving the covert signals, denoted as TAS-Ⅰ and TAS-Ⅱ respectively. Considering the best detection performance of the user only receiving the general signals, under the two schemes, the detection error probabilities and their average values, the connection probabilities, the system covert throughputs are separately calculated. In addition, on the premise of meeting the system's covert conditions, an optimization scheme is proposed to maximize the covert system throughput. Finally, the simulation results show that the proposed system can realize covert communication successfully, and the system covert performance under TAS-Ⅰ is better than that under TAS-Ⅱ.
  • 摘要：Joint user pairing and power allocation approach is investigated to meet the rate requirement of enhanced mobile broadband(eMBB)slicing and delay constraint of ultra-reliable low-latency communication(URLLC)slicing simultaneously in downlink non-orthogonal multiple access(NOMA)system.For maximizing the proportional fairness among mobile terminals,a two-step algorithm is proposed.For a given user sets,the optimal user pairing sets and the factor of the power allocation in a group were obtained to ensure the quality of service(QoS)and the isolation between different types of slicings.Simulation results show that the proposed joint algorithm can provide better throughput than orthogonal multiple access(OMA).
  • 摘要：In heterogeneous wireless networks with time-varying channels,the video rate is usually adjusted based on the network bandwidth to guarantee ultra-low latency video transmission under an end-to-end target delay constraint.However,the target delay with a fixed value according to historical experience cannot guarantee the quality of video continuously since wireless network bandwidth changes rapidly,especially when the network deteriorates.An alternative scheme is to dynamically set the target delay according to the network status within an acceptable delay range.However,this scheme cannot be ensured in heterogeneous wireless networks with time-varying channels.Thus,to address this issue,a multi-objective optimization algorithm for joint optimization of rate control and target delay is proposed,where the target delay and video rate are jointly adjusted dynamically.Second,to reduce the optimization complexity due to the multi-objective and multi-parameter characteristics,multi-objective optimization algorithm be decomposed and solved by optimizing each independent sub-problem.Finally,the proposed algorithm is verified on a semi-physical simulation platform.Experiments show that the frame loss rate is reduced from 6.65%to 2.06%,and a peak signal-to-noise ratio(PSNR)gain of 18.32%is obtained when the network performance is low.
  • 摘要：In order to solve the sensing and motion uncertainty problem of motion planning in narrow passage environment,a partition sampling strategy based on partially observable Markov decision process(POMDP)was proposed.The method combines partition sampling strategy and can improve the success rate of the robot motion planning in the narrow passage.Firstly,the environment is divided into open area and narrow area by using a partition sampling strategy,and generates the initial trajectory of the robot with fewer sampling points.Secondly,the method can calculate a local optimal solution of the initial nominal trajectory by solving POMDP problem,and iterates an overall optimal trajectory of robot motion.The proposed method follows the general POMDP solution framework,in which the belief dynamics is approximated by an extended Kalman filter(EKF),and the value function is represented by an effective quadratic function in the belief space near the nominal trajectory.Using a belief space variant of iterative linear quadratic Gaussian(iLQG)to perform the value iteration,which results in a linear control policy over the belief space that is locally optimal around the nominal trajectory.A new nominal trajectory is generated by executing the control strategy iteration,and the process is repeated until it converges to a locally optimal solution.Finally,the robot gets the optimal trajectory to safely pass through a narrow passage.The experimental results show that the proposed method can efficiently improves the performance of motion planning under uncertainty.
  • 摘要：Vehicle trajectory modeling is an important foundation for urban intelligent services. Trajectory prediction of cars is a hot topic. A model including convolutional neural network(CNN) and long short-term memory(LSTM) was proposed, which is named trajectory-CNN-LSTM(TCL). CNN can extract the spatial features of the trajectory in the input image. Besides, LSTM can extract the time-series features of the input trajectory. After that, the model uses fully connected layers to merge the two features for the final predicting. The experiments on the Porto dataset of The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases(ECML-PKDD) show that the average prediction error of TCL is reduced by 0.15 km, 0.42 km, and 0.39 km compared to the trajectory-convolution(T-CONV), multi-layer perceptron(MLP), and recurrent neural network(RNN) model, respectively.
  • 摘要：Human motion prediction is a critical issue in human-robot collaboration(HRC)tasks.In order to reduce the local error caused by the limitation of the capture range and sampling frequency of the depth sensor,a hybrid human motion prediction algorithm,optimized sliding window polynomial fitting and recursive least squares(OSWPF-RLS)was proposed.The OSWPF-RLS algorithm uses the human body joint data obtained under the HRC task as input,and uses recursive least squares(RLS)to predict the human movement trajectories within the time window.Then,the optimized sliding window polynomial fitting(OSWPF)is used to calculate the multi-step prediction value,and the increment of multi-step prediction value was appropriately constrained.Experimental results show that compared with the existing benchmark algorithms,the OSWPF-RLS algorithm improved the multi-step prediction accuracy of human motion and enhanced the ability to respond to different human movements.
  • 摘要：Aiming at the shortcomings of current gesture tracking methods in accuracy and speed, based on deep learning You Only Look Once version 4(YOLOv4) model, a new YOLOv4 model combined with Kalman filter real-time hand tracking method was proposed. The new algorithm can address some problems existing in hand tracking technology such as detection speed, accuracy and stability. The convolutional neural network(CNN) model YOLOv4 is used to detect the target of current frame tracking and Kalman filter is applied to predict the next position and bounding box size of the target according to its current position. The detected target is tracked by comparing the estimated result with the detected target in the next frame and, finally, the real-time hand movement track is displayed. The experimental results validate the proposed algorithm with the overall success rate of 99.43% at speed of 41.822 frame/s, achieving superior results than other algorithms.
  • 摘要：An on-chip debug circuit based on Joint Test Action Group(JTAG)interface for L-digital signal processor(L-DSP)is proposed,which has debug functions such as storage resource access,central processing unit(CPU)pipeline control,hardware breakpoint/observation point,and parameter statistics.Compared with traditional debug mode,the proposed debug circuit completes direct transmission of data between peripherals and memory by adding data test-direct memory access(DT-DMA)module,which improves debug efficiency greatly.The proposed circuit was designed in a 0.18μm complementary metal-oxide-semiconductor(CMOS)process with an area of 167234.76μm~2 and a power consumption of 8.89 mW.And the proposed debug circuit and L-DSP were verified under a field programmable gate array(FPGA).Experimental results show that the proposed circuit has complete debug functions and the rate of DT-DMA for transferring debug data is three times faster than the CPU.
  • 摘要：In order to specify brain temporal dynamics difference between two representative puns, homonymic and semantic puns, alternate presentation of words and phrase(APWP) paradigm was proposed. The highlight of APWP paradigm is to make sentences strictly presented in word-phrase-word-phrase-word forms, which helps relieve visual fatigue of the monotonous presentation form and prevent disturbance by the settled position of the ending word. Following the APWP paradigm, participants are invited to read puns presenting in word-phrase-word-phrase-word forms. Meanwhile, event-related potential(ERP) was adopted to record their electroencephalogram(EEG) data. By observing two linguistic cognitive indexes of EEG data, N400 and P600 caused by puns, it was found that there were significant difference of logical mechanisms between homonymic and semantic puns. For homonymic puns, a significant P600 effect without any obvious N400 amplitude was elicited for the pronunciation of heterograph. For semantic puns, an apparent N400 amplitude might reflect ambiguities and comprehensive difficulty of a homonym into its discourse context. This study also conveyed that the APWP paradigm proved to be a good model for sentences research, which can be applied to other linguistic phenomena of complete context, such as metaphor, irony and jokes, sentence pattern and syntactic research.
  • 摘要：Facial recognition has become the most common identity authentication technologies. However, problems such as uneven light and occluded faces have increased the hardness of liveness detection. Nevertheless, there are a few pieces of research on face liveness detection under occlusion conditions. This paper designs a face recognition technique suitable for different degrees of facial occlusion, which employs the facial datasets of near-infrared(NIR) images and visible(VIS) light images to examine the single-modality detection accuracy rate(experimental control group) and the corresponding high-dimensional features through the residual network(ResNet). Based on the idea of data fusion, we propose two feature fusion methods. The two methods extract and fuse the data of one and two convolutional layers from two single-modality detectors respectively. The fusion of high-dimensional features apply a new ResNet to get the dual-modality detection accuracy. And then, a new ResNet is applied to test the accuracy of dual-modality detection. The experimental results show that the dual-modality face liveness detection model improves face live detection accuracy and robustness compared with the single-modality. The fusion of two-layer features from the single-modality detector can also improve face detection accuracy by utilizing the above-mentioned dual-modality detector, and it doesn’t increase the algorithm’s complexity.
  • 摘要：Predicting user states in future and rendering visual feedbacks accordingly can effectively reduce the visual experienced delay in the tactile Internet(TI). However, most works omit the fact that different parts in an image may have distinct prediction requirements, based on which different prediction models can be used in the predicting process, and then it can further improve predicting quality especially under resources-limited environment. In this paper, a hybrid prediction scheme is proposed for the visual feedbacks in a typical TI scenario with mixed visuo-haptic interactions, in which haptic traffic needs sufficient wireless resources to meet its stringent communication requirement, leaving less radio resources for the visual feedback. First, the minimum required number of radio resources for haptic traffic is derived based on the haptic communication requirements, and wireless resources are allocated to the haptic and visual traffics afterwards. Then, a grouping strategy is designed based on the deep neural network(DNN) to allocate different parts from an image feedback into two groups to use different prediction models, which jointly considers the prediction deviation thresholds, latency and reliability requirements, and the bit sizes of different image parts. Simulations show that, the hybrid prediction scheme can further reduce the visual experienced delay under haptic traffic requirements compared with existing strategies.
  • 摘要：With the rapid development of vehicle-based applications, entertainment videos have gained popularity for passengers on public vehicles. Therefore, how to provide high quality video service for passengers in typical public transportation scenarios is an essential problem. This paper proposes a quality of experience(QoE)-based video segments caching(QoE-VSC) strategy to guarantee the smooth watching experience of passengers. Consequently, this paper considers a jointly caching scenario where the bus provides the beginning segments of a video, and the road side unit(RSU) offers the remaining for passengers. To evaluate the effectiveness, QoE hit ratio is defined to represent the probability that the bus and RSUs jointly provide passengers with desirable video segments successfully. Furthermore, since passenger volume change will lead to different video preferences, a deep reinforcement learning(DRL) network is trained to generate the segment replacing policy on the video segments cached by the bus server. And the training target of DRL is to maximize the QoE hit ratio, thus enabling more passengers to get the required video. The simulation results prove that the proposed method has a better performance than baseline methods in terms of QoE hit ratio and cache costs.
  • 摘要：Robust minimum class variance twin support vector machine(RMCV-TWSVM) presented previously gets better classification performance than the classical TWSVM. The RMCV-TWSVM introduces the class variance matrix of positive and negative samples into the construction of two hyperplanes. However, it does not consider the total structure information of all the samples, which can substantially reduce its classification accuracy. In this paper, a new algorithm named structural regularized TWSVM based on within-class scatter and between-class scatter(WSBS-STWSVM) is put forward. The WSBS-STWSVM can make full use of the total within-class distribution information and between-class structure information of all the samples. The experimental results illustrate high classification accuracy and strong generalization ability of the proposed algorithm.
  • 摘要：Aiming at the sensor faults of near-space hypersonic vehicles(NSHV), a fault identification method based on the extended state observer and kernel extreme learning machine(ESO-KELM) is proposed in this paper. The method is generated by a combination of the model-based method and the data-driven method. As the source of the fault diagnosis, the residual signals represent the difference between the ESO output and the result measured by the sensor in particular. The energy of the residual signals is distributed in both low frequency bands and high frequency bands. However, the energy of the sensor concentrates on the low-frequency bands. Combined with more different features detected by KELM, the proposed method devotes to improving the accuracy. Meanwhile, it is competent to calculate the magnitude of minor faults based on time-frequency analysis. Finally, the simulation is performed on the longitudinal channel of the Winged-Cone model published by the national aeronautics and space administration(NASA). Results show the validity and the accuracy in calculating the magnitude of the minor faults.
  • 摘要：A tracking structure suitable for L6 signal of quasi-zenith satellite system(QZSS) was proposed in order to track the L6 signal without other frequency assistance. Moreover, the tracking structure does not change the receiver’s hardware structure. The main difference between the proposed and the traditional tracking structure lies in the generation of local codes of E,P and L branches. The method of local code generation is designed in a two-stage manner. The first stage is the generation of the P branch local code with fast fouriertransform(FFT). In the second stage, the local codes of the E and L branches are obtained with the code-chip interval. The tracking structure can track and decode L6 signal separately, and track code shift keying(CSK)modulated signal as well. The structure was verified using both simulation data, generated in different conditions, and actual data obtained from QZSS satellites respectively. The results show that the improved tracking loop is able to track L6 signal without other frequency assitance. Furthermore, the biterror ratio(BER) of L6 tracking algorithm is lower than that of L1C/A assist L6 algorithm, when the Doppler remains a constant and reed solomn(RS)encode are applied. To be more specific, with the proposed structure the BER decreased by 11.40%, 17.07%, 15.00%, 11.15%, 5.19% when carrier to noise ratio(CNR) is 36-40 dB·Hz.
  • 摘要：Cross-project defect prediction(CPDP) uses one or more source projects to build a defect prediction model and applies the model to the target project. There is usually a big difference between the data distribution of the source project and the target project, which makes it difficult to construct an effective defect prediction model. In order to alleviate the problem of negative migration between the source project and the target project in CPDP, this paper proposes an integrated transfer adaptive boosting(TrAdaBoost) algorithm based on multi-source data sets(MSITrA). The algorithm uses an existing two-stage data filtering algorithm to obtain source project data related to the target project from multiple source items, and then uses the integrated TrAdaBoost algorithm proposed in the paper to build a CPDP model. The experimental results of Promise’s 15 public data sets show that: 1) The cross-project software defect prediction model proposed in this paper has better performance in all tested CPDP methods;2) In the within-project software defect prediction(WPDP) experiment, the proposed CPDP method has achieved the better experimental results than the tested WPDP method.
  • 摘要：Robot error compensation is a technique for enhancing the positioning accuracy of the system. This paper presented an error measuring technique for serial robots based on the multi-hole measuring method, combined with the intelligent particle swarm optimisation(PSO) to obtain the optimal solution of the robot’s error compensation values, thereby improving the positioning accuracy of the robot. In the experiment, the robot error was measured using self-made multi-hole measuring plates and probes, and the experimental data were combined with PSO for the error comprehensive analysis. The results showed that on this type of serial robot, the multi-hole measuring method and PSO algorithm had obvious error compensation effects, which effectively improved the positioning accuracy of the robot, with the error reduced by 35% after compensation.
  • 摘要：General It mainly publishes academic papers, research reports,surveys,research briefings,and degree theses in the field of communications&information systems, signal&information processing,computer software and computer theory,computer application technology,electromagnetismµwave technology,microelectronics&solid electronics,control theory and control engineering, management science&engineering, and other related basic theories and technologies. The readerships are universities faculties and students, scientists in research institutions,and engineers and managers in enterprises,etc.
  • 摘要：At present, there is an urgent need for blockchain interoperability technology to realize interconnection between various blockchains, data communication and value transfer between blockchains, so as to break the ‘value silo’ phenomenon of each blockchain. Firstly, it lists what people understand about the concept of interoperability. Secondly, it gives the key technical issues of cross-chain, including cross-chain mechanism, interoperability, eventual consistency, and universality. Then, the implementation of each cross-chain key technology is analyzed, including Hash-locking, two-way peg, notary schemes, relay chain scheme, cross-chain protocol, and global identity system. Immediately after that, five typical cross-chain systems are introduced and comparative analysis is made. In addition, two examples of cross-chain programmability and their analysis are given. Finally, the current state of cross-chain technology is summarized from two aspects: key technology implementation and cross-chain application enforcement. The cross-chain technology as a whole has formed a centralized fixed mechanism, as well as a trend of modular design, and some of the solutions to mature applications were established in the relevant standards organizations, and the cross-chain technology architecture tends to be unified, which is expected to accelerate the evolution of the open cross-chain network that supports the real needs of the interconnection of all chains.
  • 摘要：Threshold proxy re-encryption(PRE) authorizes the data access right of data subject to multiple proxies, who authorize the right again to delegatee to accomplish the end-to-end data encryption process from storage to authorization. Based on threshold PRE algorithm, in order to build a complete trusted data storage and authorization system, the four protocols, which are data access protocol, authorization proxy protocol, authorization proxy cancellation protocol and data reading authorization protocol, are defined completely. On that basis, an efficient data searching method is constructed by specifying the data delegatee. At last, to ensure the right to know of data, the audit log is processed with trusted data right confirmation based on distributed ledger technology. Meanwhile, a parallel data right confirmation processing method is defined based on hierarchical derivation algorithm of public and private key. In the end, the performance evaluation analysis of the protocol are given. Trusted data access and authorization protocol is convenient to build a complete data processing system on the premise of protecting data privacy based on public cloud storage system or distributed storage system.
  • 摘要：Delegated proof-of-stake(DPOS) consensus mechanism is widely adopted in blockchain platforms, but problems exist in its current applications. In order to explore the security risks in the voting attack of the DPOS consensus mechanism, an extensive game model between nodes was constructed, and it was concluded that the DPOS consensus mechanism relies too much on tokens, and the possibility of node attacks is very high. In order to solve the problems of frequent changes of DPOS consensus mechanism nodes, inactive node voting, excessive reliance on tokens, and malicious nodes, a dynamic, credible, and attack-evading DPOS consensus mechanism was proposed. In addition, the Python simulation results show that the improved Bayesian voting algorithm is effective in calculating node scores.
  • 摘要：Data island and information opacity are two major problems in collaborative administration. Blockchain has the potential to provide a trustable and transparent environment encouraging data sharing among administration members. However, the blockchain only stores Hash values and transactions in blocks which makes it unable to store big data and trace their changes. In this paper, a labor arbitration scheme based on blockchain was proposed to share labor arbitration data. In the system, a collaborative administration scheme that provides a big data storage model combined blockchain and interplanetary file system(IPFS) is designed. It can store big data and share these data among different parties. Moreover, a file version control mechanism based on blockchain is designed to manage the data changes in IPFS network. It creates a tracing chain that consists of many IPFS objects to track changes of stored data. The relationship of previous and current IPFS objects recorded by blockchain can describe the changes of administration data and trace the data operations. The proposed platform is used in Rizhao City in China, and the experiment result shows collaborative administration scheme achieves traceability with high throughput and is more efficient than traditional hypertext transfer protocol(HTTP) way to share data.
  • 摘要：Blockchain technology is used in edge computing(EC) systems to solve the security problems caused by single point of failure(SPOF) due to data loss, task execution failure, or control by malicious nodes. However, the disadvantage of blockchain is high latency, which contradicts the strict latency requirements of EC services. The existing single-level sharded blockchain system(SLSBS) cannot provide different quality of service for different tasks. To solve these problems, a multi-level sharded blockchain system(MLSBS) based on genetic algorithm(GA) is proposed. The shards are classified according to the delay of the service, and the parameters such as the shard size of different shards are different. Using the GA, the MLSBS obtains the optimal resource allocation strategy that achieves maximum security. Simulation results show that the proposed scheme outperforms SLSBS.
  • 摘要：The color, shape, and other appearance characteristics of the flame emitted by different flame engines are different. In order to make a preliminary judgment on the category of the device to which it belongs through studying exterior characteristics of the flame, this paper uses the flame of matches, lighters, and candles to simulate different types of flames. It is hoped that the flames can be located and classified by detecting the characteristics of flames using the object detection algorithm. First, different types of fire are collected for the dataset of experiments. The mmDetection toolbox is then used to build several different object detection frameworks, in which the dataset can be trained and tested. The object detection model suitable for this kind of problem is obtained through the evaluation index analysis. The model is ResNet50-based faster-region-convolutional neural network(Faster R-CNN), whose mean average-precision(mAP) is 93.6%. Besides, after clipping the detected flames through object detection, a similarity fusion algorithm is used to aggregate and classify the three types of flames. Finally, the color components are analyzed to obtain the red, green, blue(RGB) color histograms of the three flames.
  • 摘要：In order to solve the impact of image degradation on object detection, an object detection method based on light field super-resolution(LFSR) is proposed. This method takes LFSR as an image enhancement step to provide high-quality images for object detection without using expensive imaging equipment. To evaluate this method, three types of objects: person, bicycle, and car, are chosen and the results are compared from 5 parts: detected object quantity, mean confidence score, detection results in different scenes, error detection, and detection results from different images sizes and detection speed. Experimental results based on the common object in context(COCO) dataset show that the method incorporated LFSR improves performance of object detection models.
  • 摘要：Existing algorithms of news recommendations lack in depth analysis of news texts and timeliness. To address these issues, an algorithm for news recommendations based on time factor and word embedding(TFWE) was proposed to improve the interpretability and precision of news recommendations. First, TFWE used term frequency-inverse document frequency(TF-IDF) to extract news feature words and used the bidirectional encoder representations from transformers(BERT) pre-training model to convert the feature words into vector representations. By calculating the distance between the vectors, TFWE analyzed the semantic similarity to construct a user interest model. Second, considering the timeliness of news, a method of calculating news popularity by integrating time factors into the similarity calculation was proposed. Finally, TFWE combined the similarity of news content with the similarity of collaborative filtering(CF) and recommended some news with higher rankings to users. In addition, results of the experiments on real dataset showed that TFWE significantly improved precision, recall, and F1 score compared to the classic hybrid recommendation algorithm.
  • 摘要：In distributed systems, it is important to adjust load distribution dynamically based on server performance and load information. Meanwhile, gray release and rapid expansion are the basic requirements to ensure reliability and stability for systems with short version iteration cycles. The traditional Hash algorithm performs poorly in gray release, rapid expansion, and load distribution. To solve these problems, a novel Hash-based dynamic mapping(HDM) load balancing algorithm was proposed. On the one hand, this algorithm can adjust the load distribution dynamically based on server performance and load information. On the other hand, it implements gray release by controlling the ratio of requests assigned to the changed nodes. Additionally, HDM has a higher expansion efficiency. Experiments show that the HDM distributes the load more reasonably, provides a more stable gray release ratio, and has a higher expansion efficiency.
  • 摘要：In order to predict traffic flow more accurately and improve network performance, based on the multifractal wavelet theory, a new traffic prediction model named exo-LSTM is proposed. Exo represents exogenous sequence used to provide a detailed sequence for the model, LSTM represents long short-term memory used to predict unstable traffic flow. Applying multifractal traffic flow to the exo-LSTM model and other existing models, the experiment result proves that exo-LSTM prediction model achieves better prediction accuracy.

    中国邮电高校学报：英文版的期刊信息

    • 曾用名：中国邮电高校学报(英文版);The Journal of China Universities of Posts and Telecommunica
    • 创刊时间：1994
    • 地区：CN
    • 语言：中文
    • 热门主题：BASED_ON AUTHORS GUIDE OFDM MIMO ALGORITHM 码分多址 CDMA AN PERFORMANCE_ANALYSIS
    • 学科分类：

      Computer Science:Computer Networks and Communications;Information Systems;Signal Processing;

    中国邮电高校学报：英文版的获奖情况

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    • • 中国科学引文数据库（2017-2018）
    • • 中国科学引文数据库（2019-2020）
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