The Comparison of Tree-Sibling Time Consistent Phylogenetic Networks Is Graph Isomorphism-Complete by Gabriel Cardona, Mercè Llabrés, Francesc Rosselló, Gabriel Valiente

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Business process mining based insider threat detection system by Tai-ming ZHU, Yuan-bo GUO, An-kang JU, Jun MA

“…Current intrusion detection systems are mostly for detecting external attacks,but sometimes the internal staff may bring greater harm to organizations in information security.Traditional insider threat detection methods of-ten do not combine the behavior of people with business activities,making the threat detection rate to be improved.An insider threat detection system based on business process mining from two aspects was proposed,the implementation of insider threats and the impact of threats on system services.Firstly,the normal control flow model of business ac-tivities and the normal behavior profile of each operator were established by mining the training log.Then,the actual behavior of the operators was compared with the pre-established normal behavior contours during the operation of the system,which was supplemented by control flow anomaly detection and performance anomaly detection of business processes,in order to discover insider threats.A variety of anomalies were defined and the corresponding detection algorithms were given.Experiments were performed on the ProM platform.The results show the designed system is effective.…”
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Correlation between the Quality of Talent Training and Regional Economic Development Based on Multivariate Statistical Analysis Model by Yana Yuan

“…This paper incorporates machine learning algorithms to construct a multivariate statistics analysis model based on the correlation analysis model between talent training quality and regional economic development. …”
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A low complexity dynamic subarray combination method for MIMO transmitter by Cui WANG, Peng PAN, Shuai ZHANG, Junrong YAN

“…For the mmWave MIMO system using a partially-connected structure,in order to improve the spectral efficiency,the antenna composition of each subarray will be dynamically adjusted according to the channel conditions.However,the optimal grouping of antennas requires exhaustive searching for all possible antenna combinations according to certain criteri,which leads to unacceptable complexity.In response to the problem,a low-complexity sub-array dynamic allocation method was proposed.The core was to introduce certain rules when grouping array elements,thereby significantly reducing the number of combinations and reducing the search range.Specifically,two low-complexity antenna combination algorithms were proposed.Firstly,considering the strong correlation between mmWave antennas,multiple adjacent antennas were virtualized as an array element,thereby reducing the search space.Secondly,by dividing all antennas into upper and lower half areas,the antenna combination based on partition was realized,and the search space was also reduced.Simulation results show that the proposed method can achieve a good trade-off between performance and complexity.…”
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Nonlinear Augmented Proportional Navigation for Midrange Rendezvous Guidance and Performance Assessment by Weilin Wang, Xumin Song

“…This paper builds on previous efforts in polynomial chaos expansion (PCE) to develop an efficient analysis technique for guidance algorithms. A large scope of uncertainty sources are considered to make state evaluation trustworthy and provide precise prediction of trajectory bias. …”
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Blind SNR estimation for OFDM signals in cognitive radio by Ming-qian LIU, Bing-bing LI, Ning-jie TANG, Zhao LI

“…The traditional blind SNR estimation algorithms had problems of poor performance and high computation complexity for OFDM systems in cognitive radio with low signal to noise ratio(SNR)and multi-path channel conditions,in view of which a novel blind SNR estimation method for orthogonal frequency division multiplexing(OFDM)signals was proposed.Firstly,the channel order was roughly estimated by utilizing the characteristics of autocorrelation function to determine the data interval which was free of inter-symbol interference(ISI).Secondly,the signal average power was estimated by computing the autocorrelation values of data in the determined interval.Finally,the noise average power was estimated by utilizing the characteristics that the data in cyclic prefix which was replication of part useful data.So the SNR of the received signals could be estimated.The simulation results show that the proposed method doesn’t need any prior information and has better performance and lower computation complexity,which is more suitable for OFDM systems in cognitive radio.…”
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A VVC intra coding method based on fast partition for coding unit by ZHONG Hui, LU Yu, YIN Haibing, HUANG Xiaofeng

“…Moreover, the performance of proposed method is superior to other comparative algorithms.…”
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Pairing Optimizations for Isogeny-Based Cryptosystems by Shiping Cai, Kaizhan Lin, Chang-An Zhao

“…We use (modified) Jacobian coordinates and present new algorithms for Miller function computations to compute pairings of order 2∙ and 3∙. …”
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PCA-based membership inference attack for machine learning models by Changgen PENG, Ting GAO, Huilan LIU, Hongfa DING

“…Aiming at the problem of restricted access failure in current black box membership inference attacks, a PCA-based membership inference attack was proposed.Firstly, in order to solve the restricted access problem of black box membership inference attacks, a fast decision membership inference attack named fast-attack was proposed.Based on the perturbation samples obtained by the distance symbol gradient, the perturbation difficulty was mapped to the distance category for membership inference.Secondly, in view of the low mobility problem of fast-attack, a PCA-based membership inference attack was proposed.Combining the algorithmic ideas based on the perturbation category in the fast-attack and the PCA technology to suppress the low-migration behavior caused by excessive reliance on the model.Finally, experiments show that fast-attack reduces the access cost while ensuring the accuracy of the attack.PCA-based attack is superior to the baseline attack under the unsupervised setting, and the migration rate of model is increased by 10% compared to fast-attack.…”
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Model pruning techniques in the Internet of things: state of the art, methods and perspectives by ZHAO Junhui, LI Huaicheng, WANG Dongming, LI Jiamin, ZHOU Yiqing, SHU Feng

“…In the context of the rapid development of Internet of things (IoT) technology, IoT devices faced challenges in running complex artificial intelligence (AI) algorithms, especially deep learning models, due to the limitations of computing power, storage space, communication bandwidth, and battery life. …”
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The Necessity for Information Space Mapping for Information Retrieval on the Semantic Web by Gregory B. Newby

“…When the match is less precise, sets of rules or algorithms may be employed to map between information spaces. …”
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Bayesian and non-bayesian analysis for stress-strength model based on progressively first failure censoring with applications. by Salem A Alyami, Amal S Hassan, Ibrahim Elbatal, Olayan Albalawi, Mohammed Elgarhy, Ahmed R El-Saeed

“…In the end, for illustrative reasons, an algorithmic application to actual data is investigated.…”
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Accelerated computational implementation of reconciliation for continuous variable quantum key distribution on GPU by Shao-ting LIU, Xiao-kai WANG, Da-bo GUO

“…For the low computing speed of reconciliation for current continuous variable quantum key distribution， CPU＆amp;GPU-parallel reconciliation algorithms was designed based on LDPC of SEC protocol to speed up decoding computing.In order to raise decoding speed without sacrifice reconciliation efficiency,a static two-way cross linked list to efficiently store large scale sparse parity matrix was employed.The simulation experimental results show that the speed of the decoding rate reaches 16.4 kbit/s when the channel SNR is over 4.9 dB and the reliability of the 2×10⁵continuous variable quantum sequence,with reconciliation efficiency of 91.71%.The experimental based on the Geforce GT 650 MB GPU and the 2.5 GHz and 8 GB memory CPU hardware platform.Relative to the only CPU platform,computing speed increased by more than 15 times.…”
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The power of dialogue and discovery by Kalina Jastrzębowska

“…Our classrooms offer algorithmic and rote teaching methods, depriving students of important elements of successful mathematics learning. …”
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Towards an optimization of catheter guidance in vascular surgery: A comparative analysis of the contribution of reinforcement learning by Cheima Bouden

“…Future research should aim to refine these algorithms for wider clinical use and integration.…”
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Review on Fault Diagnosis Technology for High-speed EMU Gearboxes by Zhang Jianchao, Chen Xiangsong, Hao Rujiang, Gu Xiaohui, Ren Bin

“…The single diagnosis technology can not accurately diagnose the multi-type failures of the gearbox due to its limitations, and the fusion of multiple techniques based on advanced intelligent algorithms is expected to be one of the research focuses for fault diagnosis in this field in the future.…”
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An overview of artificial intelligence assisted channel estimation by Kun LI, Jing ZHANG, Xiao LI, Shi JIN

“…As the mainstream of the sixth generation mobile communication development,intelligent communication assisted by artificial intelligence technology is vigorously developing,and has initially demonstrated its advantages over traditional communication methods.As an important component of intelligent communication,artificial intelligence assisted channel estimation shows its superiority over traditional channel estimation algorithms in the existing research results,especially those researches based on compressive sensing technology,super resolution technology,residual learning,etc.Aiming at the channel estimation technology assisted by artificial intelligence,combined with the latest research results in the academic field,the whole picture of the channel estimation technology assisted by artificial intelligence from the four dimensions of deep convolution neural network,deep recurrent neural network,super-resolution technology and compression sensing technology were showed.Finally,the advantages and disadvantages of four kinds of channel estimation methods and their future research directions,and the broad prospect of the combination of channel estimation and deep learning were looked forward.…”
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Pattern synthesis method for arbitrary arrays with desired mainloble response by Dian-fei PAN, Nai-ping CHENG

“…A pattern synthesis method based on adaptive array theory and convex optimization principle was proposed for arbitrary arrays,especially considering the influence of different orientation on array pattern.Firstly,the array pattern with special sideloble shape is obtained by adaptive array theory method; and then,the mainloble pointing to 0° is taken as reference to determine the pattern mainloble with variant steering angle.Finally,the optimal array pattern synthesis with desired mainloble response is converted to a second-order cone programming problem.The resulting optimization problem is nonconvex and is implemented via iterative algorithms of convex optimization,which can be solved using the second-order cone programming method at each iteration.Taking the method developed can obtain satisfied mainlobe response and less synthesized error in sideloble region.Theoretical analyses and simulation results show that the synthe-sized pattern has the same mainloble performance as the desired mainlabole in different orientation,and also the sideloble can maintain the shape to suppress the dynamic interference.…”
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Exploiter un corpus de données textuelles sans post-traitement : l’écriture burlesque de la Fronde by Karine Abiven, Jean-Baptiste Tanguy, Gaël Lejeune

“…The aim is therefore to present the approach of a corpus in all the steps of the process: from the selection of data, their acquisition, and their transformation into a corpus, to their statistical and algorithmic exploitation, and their interpretation through text mining.…”
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Scheduling framework based on reinforcement learning in online-offline colocated cloud environment by Ling MA, Qiliang FAN, Ting XU, Guanchen GUO, Shenglin ZHANG, Yongqian SUN, Yuzhi ZHANG

“…Some reinforcement learning-based scheduling algorithms for cloud computing platforms barely considered one scenario or ignored the resource constraints of jobs and treated all machines as the same type, which caused low resource utilization or insufficient scheduling efficiency.To address the scheduling problems in online-offline colocated cloud environment, a framework named JobFusion was proposed.Firstly, an efficient resource partitioning scheme was built in the cloud computing platform supporting virtualization technology by integrating the hierarchical clustering method with connectivity constraints.Secondly, a graph convolutional neural network was utilized to embed the attributes of elastic dimension with various constraints and the jobs with various numbers, to capture the critical path information of workflow.Finally, existing high-performance reinforcement learning methods were integrated for scheduling jobs.According to the results of evaluation experiments, JobFusion improves the resource utilization by 39.86% and reduces the average job completion time by up to 64.36% compared with baselines.…”
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