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  • Open Access

    ARTICLE

    Cold Start Problem of Vehicle Model Recognition under Cross-Scenario Based on Transfer Learning

    Hongbo Wang1, *, Qian Xue1, Tong Cui1, Yangyang Li2, Huacheng Zeng3

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 337-351, 2020, DOI:10.32604/cmc.2020.07290

    Abstract As a major function of smart transportation in smart cities, vehicle model recognition plays an important role in intelligent transportation. Due to the difference among different vehicle models recognition datasets, the accuracy of network model training in one scene will be greatly reduced in another one. However, if you don’t have a lot of vehicle model datasets for the current scene, you cannot properly train a model. To address this problem, we study the problem of cold start of vehicle model recognition under cross-scenario. Under the condition of small amount of datasets, combined with the method of transfer learning, load… More >

  • Open Access

    ARTICLE

    TdBrnn: An Approach to Learning Users’ Intention to Legal Consultation with Normalized Tensor Decomposition and Bi-LSTM

    Xiaoding Guo1, Hongli Zhang1, *, Lin Ye1, Shang Li1

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 315-336, 2020, DOI:10.32604/cmc.2020.07506

    Abstract With the development of Internet technology and the enhancement of people’s concept of the rule of law, online legal consultation has become an important means for the general public to conduct legal consultation. However, different people have different language expressions and legal professional backgrounds. This phenomenon may lead to the phenomenon of different descriptions of the same legal consultation. How to accurately understand the true intentions behind different users’ legal consulting statements is an important issue that needs to be solved urgently in the field of legal consulting services. Traditional intent understanding algorithms rely heavily on the lexical and semantic… More >

  • Open Access

    ARTICLE

    An Efficient and Practical Quantum Blind Signature Protocol with Relaxed Security Model

    Jun Zhang1, *, Hao Xiao2, Hongqun Zhai1, Xiaoli Meng3

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 301-313, 2020, DOI:10.32604/cmc.2020.07681

    Abstract Blind signature has a wide range of applications in the fields of E-commerce and block-chain because it can effectively prevent the blind signer from getting the original message with its blindness. Owing to the potential unconditional security, quantum blind signature (QBS) is more advantageous than the classical ones. In this paper, an efficient and practical quantum blind signature scheme relaxed security model is presented, where quantum superposition, decoy qubits and hash function are used for the purpose of blindness. Compared with previous QBS scheme, the presented scheme is more efficient and practical with a relaxed security model, in which the… More >

  • Open Access

    ARTICLE

    A Rub-Impact Recognition Method Based on Improved Convolutional Neural Network

    Weibo Yang1, *, Jing Li2, Wei Peng2, Aidong Deng3

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 283-299, 2020, DOI:10.32604/cmc.2020.07511

    Abstract Based on the theory of modal acoustic emission (AE), when the convolutional neural network (CNN) is used to identify rotor rub-impact faults, the training data has a small sample size, and the AE sound segment belongs to a single channel signal with less pixel-level information and strong local correlation. Due to the convolutional pooling operations of CNN, coarse-grained and edge information are lost, and the top-level information dimension in CNN network is low, which can easily lead to overfitting. To solve the above problems, we first propose the use of sound spectrograms and their differential features to construct multi-channel image… More >

  • Open Access

    ARTICLE

    Reliability Analysis of Slope Stability Considering Temporal Variations of Rock Mass Properties

    Xin Gu2, Lin Wang1, 2, 3, Fuyong Chen2, Hongrui Li2, Wengang Zhang1, 2, 3, ∗

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 263-281, 2020, DOI:10.32604/cmc.2020.07535

    Abstract Temporal variation of rock mass properties, especially the strength degradation due to drying-wetting cycles as well as the acidic wetting fluid (rainfall or reservoir water) is crucial to stability of reservoir rock slopes. Based on a series of drying-wetting cycling and experiments considering the influences of pH values, the degradation degree models of the reduced cohesion c′, friction angle φ′ are developed. 2D stability analysis of the slope is subsequently carried out to calculate the factor of safety (Fs) via limit equilibrium method (LEM) and a predictive model of Fs is built using multivariate adaptive regression splines (MARS), revealing the… More >

  • Open Access

    ARTICLE

    Human Action Recognition Based on Supervised Class-Specific Dictionary Learning with Deep Convolutional Neural Network Features

    Binjie Gu1, *, Weili Xiong1, Zhonghu Bai2

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 243-262, 2020, DOI:10.32604/cmc.2020.06898

    Abstract Human action recognition under complex environment is a challenging work. Recently, sparse representation has achieved excellent results of dealing with human action recognition problem under different conditions. The main idea of sparse representation classification is to construct a general classification scheme where the training samples of each class can be considered as the dictionary to express the query class, and the minimal reconstruction error indicates its corresponding class. However, how to learn a discriminative dictionary is still a difficult work. In this work, we make two contributions. First, we build a new and robust human action recognition framework by combining… More >

  • Open Access

    ARTICLE

    A Differentially Private Data Aggregation Method Based on Worker Partition and Location Obfuscation for Mobile Crowdsensing

    Shuyu Li1, Guozheng Zhang1, *

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 223-241, 2020, DOI:10.32604/cmc.2020.07499

    Abstract With the popularity of sensor-rich mobile devices, mobile crowdsensing (MCS) has emerged as an effective method for data collection and processing. However, MCS platform usually need workers’ precise locations for optimal task execution and collect sensing data from workers, which raises severe concerns of privacy leakage. Trying to preserve workers’ location and sensing data from the untrusted MCS platform, a differentially private data aggregation method based on worker partition and location obfuscation (DP-DAWL method) is proposed in the paper. DP-DAWL method firstly use an improved K-means algorithm to divide workers into groups and assign different privacy budget to the group… More >

  • Open Access

    ARTICLE

    Efficient Heavy Hitters Identification over Speed Traffic Streams

    Shuzhuang Zhang1, Hao Luo1, Zhigang Wu1, Yanbin Sun2, *, Yuhang Wang2, Tingting Yuan3

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 213-222, 2020, DOI:10.32604/cmc.2020.07496

    Abstract With the rapid increase of link speed and network throughput in recent years, much more attention has been paid to the work of obtaining statistics over speed traffic streams. It is a challenging problem to identify heavy hitters in high-speed and dynamically changing data streams with less memory and computational overhead with high measurement accuracy. In this paper, we combine Bloom Filter with exponential histogram to query streams in the sliding window so as to identify heavy hitters. This method is called EBF sketches. Our sketch structure allows for effective summarization of streams over time-based sliding windows with guaranteed probabilistic… More >

  • Open Access

    ARTICLE

    Performance Analysis of Relay Based NOMA Cooperative Transmission under Cognitive Radio Network

    Yinghua Zhang1, 2, Jian Liu1, *, Yunfeng Peng1, Yanfang Dong2, Guozhong Sun2, Hao Huang3, Changming Zhao4, 5

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 197-212, 2020, DOI:10.32604/cmc.2020.07059

    Abstract This paper proposes a hybrid spectrum accessing mechanism by using NOMA-based cooperative transmission and beam-forming technology. In this mechanism, the secondary user employs spectrum-sensing technology to detect the existence of the primary user. If the primary user does not exist, the secondary source user directly transmits data to the destination user. If the primary user exists, the secondary source user finds the optimal relay according to certain selection principle before transmitting data to the destination user through the chosen relay node. For the signal receiving stage, the secondary user takes use of beam-forming technology to receive the signal from both… More >

  • Open Access

    ARTICLE

    A Novel Steganography Algorithm Based on Instance Segmentation

    Ruohan Meng1, 2, Qi Cui1, 2, Zhili Zhou1, 2, Chengsheng Yuan1, 2, 3, Xingming Sun1, 2, *

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 183-196, 2020, DOI:10.32604/cmc.2020.05317

    Abstract Information hiding tends to hide secret information in image area where is rich texture or high frequency, so as to transmit secret information to the recipient without affecting the visual quality of the image and arousing suspicion. We take advantage of the complexity of the object texture and consider that under certain circumstances, the object texture is more complex than the background of the image, so the foreground object is more suitable for steganography than the background. On the basis of instance segmentation, such as Mask R-CNN, the proposed method hides secret information into each object's region by using the… More >

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