Massive unsourced multiple access scheme based on block sequence codebook and compressed sensing by Jing ZHANG, Lin MA, Chulong LIANG, Hongxu GAO

“…A massive unsourced multiple access scheme based on block sequence codebook and compressed sensing was proposed for sporadic burst scenario in massive machine type communication (mMTC).Firstly, a large-capacity spreading codebook generation scheme was designed according to a specific shift pattern, thus the codebook space was expanded.Secondly, the sparse structure of uplink signal was combined with multi-carrier technology to support overlapping transmission of multi-user data on some subcarriers, thus the spectral efficiency was improved.Finally, a multi-carrier CS-MUD model was established, and a group orthogonal matching pursuit algorithm based on codebook sequence blocks was designed to achieve the joint detection of active users and their uplink data.Simulation results show that the proposed scheme can effectively reduce the bit error rate of massive random access.…”
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Combining machine learning and single-cell sequencing to identify key immune genes in sepsis by Hao Wang, Linghan Len, Li Hu, Yingchun Hu

“…Next, a Biological association network was constructed, and five key hub genes (CD4, HLA-DOB, HLA-DRB1, HLA-DRA, AHNAK) were identified using a combination of three topological analysis algorithms (MCC, Closeness, and MNC) and four machine learning algorithms (Random Forest, LASSO regression, SVM, and XGBoost). immune cell distribution showed that the key genes correlated with multiple immune cell infiltrations. …”
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An Exploration of the Triplet Periodicity in Nucleotide Sequences with a Mature Self-Adaptive Spectral Rotation Approach by Bo Chen, Ping Ji

“…It outputs a random walk, that is, TP walk, in the complex plane for the query sequence. …”
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Hybrid genetic algorithm based optimization of pilotpattern by Hanbing ZHENG, Xiang YU, Weiwei WANG

“…In OFDM system,sparse channel estimation based on compressed sensing(CS)can make full use of the inherent sparse degree of the wireless channel,which can reduce the pilot overhead and improve the spectrum efficiency.Therefore,a new method based on hybrid genetic algorithm was investigated for the pilot design of CS channel estimation,which was based on the minimization of the matrix cross correlation in the CS theory.In this method,genetic algorithm was used to obtain the initial sub-optimal pilot sequence,and then combined with the pilot position and pilot power,each entry of pilot pattern could be sequentially updated and optimized to make the minimum correlation of measurement matrix.Simulation results show that the proposed method can ensure a better mean square error and bit error rate compared to the pseudo-random pilot design and the equal distance pilot design.…”
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Encrypted traffic identification scheme based on sliding window and randomness features by LIU Jiachi, KUANG Boyu, SU Mang, XU Yaqian, FU Anmin

“…For each data block, randomness measurement algorithms were utilized to extract sample features and construct randomness features for the original payload. …”
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Machine learning-driven identification of critical gene programs and key transcription factors in migraine by Lei Zhang, Yujie Li, Yunhao Xu, Wei Wang, Guangyu Guo

“…Key transcription factors regulating critical gene programs were identified using a random forest model based on regulatory networks derived from the GTEx consortium. …”
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HASHING ALGORITHM BASED ON TWO-DIMENSIONAL CHAOTIC MAPPINGS by A. V. Sidorenko, I. V. Shakinko

“…The statistical characteristics of the sequence formed of hash-values are identical to those of the sequence with the randomly obtained values of the elements, pointing to the adequate performance of this algorithm. …”
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Mass, Luminosity, and Stellar Age of Early-type Stars from the LAMOST Survey by Qida Li, Jianping Xiong, Jiao Li, Yanjun Guo, Zhanwen Han, Xuefei Chen, Chao Liu

“…The convex hull algorithm is employed to select the main-sequence stars. …”
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Identification of microsatellite loci according to BAC sequencing data and their physical mapping to the bread wheat 5B chromosome by M. A. Nesterov, D. A. Afonnikov, E. M. Sergeeva, L. A. Miroshnichenko, M. K. Bragina, A. O. Bragin, G. V. Vasiliev, E. A. Salina

“…Totally, 130 randomly selected BAC clones from the 5BS library were sequenced on the Ion Torrent platform and assembled in contigs using MIRA software. …”
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An optimized deep-forest algorithm using a modified differential evolution optimization algorithm: A case of host-pathogen protein-protein interaction prediction by Jerry Emmanuel, Itunuoluwa Isewon, Jelili Oyelade

“…The performance of the optimized deep forest model was evaluated on human-Plasmodium falciparum protein sequence datasets using 10-fold cross-validation. The results were compared with standard optimization methods such as traditional Bayesian optimization, genetic algorithms, evolutionary strategies, and other machine learning models. …”
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Adaptive steganography algorithm in digital image based on Arnold transform by Qi LI, Xin LIAO, Guo-qing QU, Guo-yong CHEN, Jiao DU

“…Previous adaptive steganography algorithms were based on ordinal and full-embedding method.However,these algorithms might cause the concealment of secret information not good enough.Therefore,a random and non-fully embedding method was proposed to improve the concealment.The image system parameters could be obtained,so that the image full capacity was exactly greater than the length of information for non-full embedding.Moreover,these parameters made steganography more flexibility by reducing the modifications of image.Then,secret information embedding sequence was scrambled based on Arnold transform for the purpose that the steganalyst cannot detect out information orderly.Therefore,the secret information can be more concealed,which can improve the security of the algorithms.Experimental results show that the algorithm not only improves the concealment of steganography but also reduces stego distortion,and random non-full embedding operating can be applied to many other similar algorithms.…”
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Application of FMICW technology based on stagger algorithm in automotive radar by Yuanhui ZHANG, Jian YANG, Junjiang ZHU, Xiaolu LI, Yuchen HE

“…The problem of spurious spectral peaks produced by the traditional method of using a single switching frequency in automotive FMICW radar was focused by the proposed scheme.The system accuracy depended on the previously estimated range if a bandpass filter was utilized to eliminate the spurious spectral peaks,and the noise floor could be too high to achieve the required dynamic detection range if the random interrupted sequence method was utilized.A stagger algorithm based on multiple switching frequencies was used,in which the spurious peaks from the frequency domain could be removed by minimizing each frequency position on multiple spectrums.Simulation results show that the proposed method is close to the equivalent FMCW radar detection performance,and is good in multiple targets scenario.…”
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Test case minimizing based on combination chaos genetic algorithm by Qing SHEN, Yunliang JIANG, Zhangguo SHEN, Jungang LOU

“…Test case minimizing is one of the most important research fields in software testing.Uniformly distributed Chebyshev and Logistic chaos sequence were introduced in the selection，crossover and mutation of genetic algorithm.Chaos disturbance was also added in genetic testing suite to address the common problems of weak ability in local search and premature convergence，thus to optimize the test result.Experiments were conducted in randomly generated test suites and Siemens test suites.Comparisons were also made with classical methods regard to the scale of production of test suite and the execution time of the algorithms.The results of the experiment indicate that based on the same execution time of the algorithms，a smaller scale test suite can be produced by introducing chaotic sequence in genetic testing suite selection.…”
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An improved blind detection algorithm of chaos Hopfield neural network by Dawei YU, Shaowei CHEN, Shujuan YU

“…In order to improve the flexibility of the activation function of the blind detection algorithm in Hopfield neural network,an activation function with better nonlinear approximation ability near the origin was proposed.For the case where the algorithm trapped in local optima,utilizing the good ergodicity and randomness of chaos mapping,chaos was used to generate the initial sequence at the starting point of the algorithm,and small-amplitude chaotic perturbation was performed when the current global optimum value was constant,so as to reduce the error performance of the algorithm.The simulation results show that the proposed algorithm reduces the sensitivity of neurons to input values,has strong anti-interference ability and fast convergence speed,and improves the blind detection performance.…”
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A novel chaotic interleaving algorithm for mobile wireless channels by Xianping WANG, Hui CAO

“…Interleaving technique is an efficient technique to resist serious burst errors over mobile wireless fading channels.To resist 2 dimensionality burst errors effectively,a novel chaotic interleaving algorithm based on Baker map was proposed.In the proposed scheme,the binary source sequence was converted to the data matrix,and then the data matrix was dispersed randomly by using the chaotic Baker map approach,in order to realize the function of transforming 2 dimensionality long bust error into the short 1 dimensionality short bust error after de-interleaving.In additional,the proposed algorithm was combined with the convolution code based on Viterbi decoding,and was applied into the scenario of convolutional codes (2,1,3) and the scenario of (2,1,7) separately for a performance comparison.The simulation results show that the performance of the proposed algorithm outperforms better than the traditional algorithms under image transmission over mobile wireless channel.Moreover,the anti-fading capability of the proposed algorithm grows as the packet length increases,while reducing the complexity significantly.Finally,the chaotic interleaver can also enhance every transmitted packet's security with different secret keys.…”
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Two-stage community detection algorithm based on label propagation by Xueliang SUN, Wei WANG, Junheng HUANG, Guodong XIN, Bailing WANG

“…Community detection is an important research topic of complex network analysis.The detection results help to understand the community structure of complex networks and provide support for downstream tasks, such as content recommendation, link detection.Considering the challenge of community detection in complex networks, a two-stage community detection algorithm based on label propagation (TS-LPA) was proposed.The TS-LPA algorithm quantified the propagation capability of nodes based on the extended neighborhood.Then a new evaluation index was proposed to measure the probability of influence between nodes using the information of nodes and the weight of edges in the network.Based on the calculation of node centrality, the algorithm determined the updating sequence of node labels and the selection strategy of seed nodes, which eliminated the instability of the algorithm in the updating process.The TS-LPA algorithm used the breadth-first propagation idea and introduced the second-stage label propagation method to improve the quality of community detection.When label began to spread, all neighboring nodes had an influence on the label of the related node.Meanwhile, the influence of neighboring seed nodes was added to complete label updating, in order to reduce the dominance of neighboring nodes on the updated node.The experimental results of different real data sets and synthetic data sets show that TS-LPA algorithm can eliminate randomness and show strong stability while effectively improving the quality of community detection.…”
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Influence maximization algorithm of social networks based on Transformer model by YU Shuke, YAO Yao, YAN Chenxue

“…Seconcly, the topology structure information and connection framework information of the candidate nodes were discovered by use of the random walk strategy. Finally, the Transformer model was improved, in order to support scalable node feature sequences, and the improved Transformer model was taken advantage to predict the seed nodes of the social network. …”
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Adaptive Multihypothesis Prediction Algorithm for Distributed Compressive Video Sensing by Jinxiu Zhu, Ning Cao, Yu Meng

“…The simulation results show that the proposed framework can provide better reconstruction quality than the framework using original MH prediction algorithm, and for sequences with slow motion and relatively simple scene composition, the proposed method shows significant performance gains at low measurement subrate.…”
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A Detection Algorithm for the BOC Signal Based on Quadrature Channel Correlation by Bo Qian, Guolei Zheng, Yongxin Feng

“…In order to solve the problem of detecting a BOC signal, which uses a long-period pseudo random sequence, an algorithm is presented based on quadrature channel correlation. …”
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Design of SCMA codebook based on chaotic signal and system performance analysis by Geng ZHAO, Yanyan MA, Yingjie MA

“…Sparse code multiple access (SCMA) technology is one of the multiple access technology schemes for the new generation of 5G.In order to solve the transmission requirement of massive users,the logistic chaos sequence was proposed instead of the random sequence in the original system to select the codeword.The constellation method based on trellis coded modulation (TCM) subset segmentation with the mapping matrix was used to generate codebook in the encoder,and decoded through message passing algorithm (MPA) detection method.The simulation results show that the bit error rate (BER) is low when the system uses the pseudo-random sequence of chaos to select the codeword,and the system also performs well under the condition of high overload rate.…”
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