Damage Detection for Large-Scale Grid Structure Based on Virtual Axial Strain by Jian-xin Yu, Hui-feng Tan

“…The damage detection process was performed based on the dynamic simulation flowchart. Firstly, random signals were used for excitation and the damage was simulated by decreasing beam elasticity modulus. …”
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Percutaneous Ethanol Injection in Combination with Laser Ablation for a 100 ml Partially Cystic Thyroid Nodule by Roberto Negro, Gabriele Greco

“…The combination of these two procedures allowed firstly complete disappearance of the cystic component and secondly a significant reduction of thyroid nodule, which finally measured 17 ml in volume (82% reduction compared to baseline). …”
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Fault Diagnosis Method Based on Information Entropy and Relative Principal Component Analysis by Xiaoming Xu, Chenglin Wen

“…Furthermore, the simulation experiments based on Tennessee Eastman process and Wine datasets demonstrate the feasibility and effectiveness of the new method.…”
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Risk Assessment of BRONJ in Oncologic Patients Treated with Bisphosphonates: Follow-Up to 18 Months by Scilla Sparabombe, Lucia Vitali, Alessandra Nori, Ricarda Sara Berlin, Marta Mazur, Giovanna Orsini, Angelo Putignano

“…The aim of the study is to monitor the BRONJ level of risk health in patients with cancer, according to a preventive clinical protocol, which is firstly aimed at reducing risk factors such as the periodontal infections. …”
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Few-shot cybersecurity event detection method by data augmentation with prompting question answering by TANG Mengmeng, GUO Yuanbo, ZHANG Han, BAI Qingchun, CHEN Qingli, ZHANG Bowen

“…The result showes that the proposed method’s substantial superiority in low-resource network security event detection tasks compared to other baseline methods.…”
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A Proactive Robust Scheduling Method for Aircraft Carrier Flight Deck Operations with Stochastic Durations by Xichao Su, Wei Han, Yu Wu, Yong Zhang, Jie Liu

“…Then, in terms of proactive planning, both serial and parallel schedule generation schemes for baseline schedule and robust personnel allocation scheme and equipment allocation adjustment scheme for resource allocation are designed. …”
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Noisy voice detection algorithm based on feature stream fusion by Hua LONG, Mingliang YANG, Yubin SHAO

“…Aiming at the problem that the initial detection performance of voice segment was poor,and the voice continuity structure was damaged in voice communication,a noisy voice detection algorithm based on feature stream fusion was proposed.Firstly,the time domain feature stream,the spectral pattern feature stream and the statistical feature stream were extracted according to the voice characteristics.Secondly,the voice segment in the noisy audio was estimated by different voice feature streams.Finally,the voice prediction probability obtained by each feature stream was weighted and fused,and the voice estimation probability was processed in short time by the hidden Markov model.The performance test of composite voice database under the condition of multi-type noise and different signal-to-noise ratio shows that compared with the baseline model based on Bayesian and DNN classifier,the voice detection accuracy of the proposed algorithm is improved by 21.26% and 11.01% respectively,and the quality of target voice is significantly improved.…”
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AMTD:a way of adaptive moving target defense by Danjun LIU, Guilin CAI, Baosheng WANG

“…Moving target defense is a new way to change the asymmetry state between attack and defense,by dynamically moving target’s attacking surface.Frequency conversion of MTD is of great importance for the weighing between usability,security and defense cost.Nowadays,however,frequency conversion is usually determined by manager’s experience,which cannot create a balance between usability and security cost for the lack of theory basis.An adaptive moving target defense framework(AMTD)was proposed.AMTD can maximize system security at the lowest cost while ensuring that the system is available.The adaptability of AMTD has two modes.Firstly,the defense mode,it contains an adaptive conversion strategy to provide reacting defense triggered by security alerts and active defense triggered by timer expiration events.The other mode is the frequency conversion,which obtain the optimal conversion frequency by establishing mathematical models.Four series of simulation experiments were taken to verify the effectiveness of the solution.…”
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Damages of Underground Facilities in Coal Mines due to Gas Explosion Shock Waves: An Overview by Dezhi Ran, Jianwei Cheng, Rui Zhang, Yu Wang, Yuhang Wu

“…Research results provide a baseline for judgments of hazard effects by explosions. …”
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Design of beamforming for IRS multi-partition-aided THz multi-subarray by Zufan ZHANG, Rui TANG

“…In the IRS-aided THz communication system, in order to break the channel sparsity limitation on the system spatial multiplexing gain, a hybrid beam forming architecture with wide-spaced multi-subarrays at the transceiver/transmitter side was proposed and the transmission scheme of IRS multi-partition-aided THz multi-subarrays was designed.Firstly, a non-convex objective function with multivariate coupling and non-convex constraints was constructed based on the principle of maximizing spectrum efficiency.Then, the optimization problem was decoupled into two easy-to-solve sub-problems, namely, the reflection coefficient matrix design of IRS and the hybrid beamforming matrix design at the transceiver/receiver.Finally, the Riemannian manifold optimization algorithm was used to calculate the reflection coefficient matrix of IRS, and the closed solution of the hybrid beamforming matrix design at the transceiver/receiver was obtained through mathematical derivation.Simulation results show that compared with the baseline scheme, the proposed scheme can achieve better spectrum efficiency.…”
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Quantitative Attribution of Runoff and Sediment Changes in the East River Basin and Impact on Erosion and Siltation of River Channel by LI Huadong, ZENG Jiali, PAN Yifei, ZHANG Li, LAI Zhigang

“…Under the disturbance of global warming and intensive human activities,runoff and sediment in the river basin have changed significantly,thus causing enormous ecological and environmental pressure in rivers,estuaries and coastal waters.Taking East River basin as the research object,this paper analyzes the temporal characteristics of runoff and sediment by M-K test and Pettitt test,quantitatively separates the impact of climate change and human activities on runoff and sediment in the river basin by the double mass curve method and modified SWAT model,and evaluates its effect on erosion and siltation of downstream river channel.Results show that:①SWAT model was suitable for the daily and monthly runoff and sediment simulations in the East River basin,with poor simulation for runoff and sediment with daily average discharges higher than 1 500 m³/s;②The change point of runoff and sediment was 1973 and 1988 respectively.Therefore,the baseline period for runoff was 1967—1973 and sediment was 1967—1988,while impact period was 2009—2016;③The impact of human activities on water and sediment changes in the basin is significant.Contribution of climate change and human activities for runoff in 2009—2016 was about 57% and 43% respectively.Climate change and population growth were the main contribution factors for annual runoff reduction.While human activities,especially dam construction,contributed over 90% of sediment.Population growth,soil and water conservation project,and dam construction in basin were the major factors for annual sediment reduction;④Affected by sand mining in river channel,after the baseline period,the impact of human activities,especially dam construction on the middle and lower channel was firstly decreased and then increased.During the impact period,the contribution of dam construction to the erosion and siltation of middle and lower river channel was 25.8%,which was not the main factor for the evolution of the middle and lower river channel.…”
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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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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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TAGAN: an academic paper adversarial recommendation algorithm incorporating fine-grained semantic features by Jinyang SUN, Baisong LIU, Hao REN, Jiangbo QIAN

“…Academic paper recommendation aims to provide users with personalized paper resources.Collaborative filtering methods face the problems of highly sparse data and lack of negative samples.Considering the above challenges, an academic paper recommendation algorithm TAGAN（title and abstract GAN）which incorporated fine-grained semantic features was presented.Firstly, based on titles and abstracts provide abundant semantic features, convolutional neural networks (CNN) was used to extract the global features of the titles, a two-layer long and short-term memory network (LSTM) was built to model abstract words separately.At the same time, the attention mechanism was proposed to associate the title and the abstract semantically.Then, the semantic features of the paper were integrated into the recommendation framework based on generative adversarial network (GAN).The generative model will fit the user’s interest preferences and can effectively replace the negative sampling process.Finally,through the experimental comparison on the public dataset, TAGAN is better than the baseline models in all indicators, which verifies the effectiveness of TAGAN.…”
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Identification method for malicious traffic in industrial Internet under new unknown attack scenarios by ZENG Fanyi, MAN Dapeng, XU Chen, HAN Shuai, WANG Huanran, ZHOU Xue, LI Xinchun, YANG Wu

“…The experimental results on two benchmark datasets show that compared with the baseline method, the recognition performance of the proposed method is increased by more than 2.7% in the new unknown attack scenario, which shows its high efficiency and practicability in the industrial Internet environment.…”
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Chinese herbal medicine recognition network based on knowledge distillation and cross-attention by Qinggang Hou, Wanshuai Yang, Guizhuang Liu

“…Finally, experiments on the public dataset NB-TCM-CHM showed that the accuracy (ACC) and F1_score of the proposed ShuffleCANet model reached 98.8%, with only 128.66M model parameters. Compared with the baseline model ShuffleNet, the parameters are reduced by nearly 50%, but the accuracy is improved by about 1.3%, proving this method’s effectiveness.…”
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Modeling the Impacts of Boreal Deforestation on the Near-Surface Temperature in European Russia by Zhihui Li, Xiangzheng Deng, Qingling Shi, Xinli Ke, Yingcheng Liu

“…Then the land cover datasets in different years (2000 as baseline year, 2010, and 2100) was used in the WRF model to explore the impacts of boreal deforestation on the near-surface temperature. …”
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Dynamic heterogeneous network representation learning method based on Hawkes process by CHEN Lei, DENG Kun, LIU Xingyan

“…Experimental results on various benchmark datasets indicate that the proposed method significantly outperforms baseline methods. In node classification tasks, Macro-F1 average is increased by 0.15% to 3.45%, and NMI value in node clustering tasks is improved by 1.08% to 3.57%.…”
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Speaker verification method based on cross-domain attentive feature fusion by Zhen YANG, Tianlang WANG, Haiyan GUO, Tingting WANG

“…Aiming at the problem that the lack of structure information among speech signal sample in the front-end acoustic features of speaker verification system, a speaker verification method based on cross-domain attentive feature fusion was proposed.Firstly, a feature extraction method based on the graph signal processing (GSP) was proposed to extract the structural information of speech signals, each sample point in a speech signal frame was regarded as a graph node to construct the speech graph signal and the graph frequency information of the speech signal was extracted through the graph Fourier transform and filter banks.Then, an attentive feature fusion network with the residual neural network and the squeeze-and- excitation block was proposed to fuse the features in the traditional time-frequency domain and those in the graph frequency domain to promote the speaker verification system performance.Finally, the experiment was carried out on the VoxCeleb, SITW, and CN-Celeb datasets.The experimental results show that the proposed method performs better than the baseline ECAPA-TDNN model in terms of equal error rate (EER) and minimum detection cost function (min-DCF).…”
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OBC-YOLOv8: an improved road damage detection model based on YOLOv8 by Shizheng Zhang, Zhihao Liu, Kunpeng Wang, Wanwei Huang, Pu Li

“…The new proposed model is named OBC-YOLOv8 and the experimental results on the RDD2022-China dataset demonstrate its superiority compared with baselines, with 1.8% and 1.6% increases in mean average precision 50 (mAP@0.5) and F1-score, respectively.…”
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