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CFSeRec: A Contrastive Framework for Sequential Recommendation

CFSeRec: A Contrastive Framework for Sequential Recommendati...

引用

Chinese control Conference (CCC)

作者： Tong Wang Yaping Dai Shuai Shao School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing China

In sequential recommender systems, the main problems are the long-tailed distribution of data and noise interference. A Contrastive Framework for Sequential Recommendation (CFSeRec) is proposed to solve these two problems respectively. Token shuffling and adversarial attack data augmentation methods are used in the framework to improve the quality and quantity of training data, so that the long-tailed problem is mitigated. Through the application of projection head method, the sequence representation becomes more general and robust, rather than just adapted to the task of contrastive learning. Therefore, the impact of noise on sequence recommender systems is effectively alleviated. Experiments on four public datasets show that CFSeRec achieves state-of-the-art performance in the metrics of hit ratio and normalized discounted cumulative gain, when comparing to the seven previous frameworks.

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Identification and Prediction of Microvascular Invasion in Hepatocellular Carcinoma Based on Multiple Sequence Fusion Images

Identification and Prediction of Microvascular Invasion in H...

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Chinese control Conference (CCC)

作者： Mingguang Lu Yuan Zhu School of Automation China University of Geosciences Wuhan Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Hepatocellular carcinoma (HCC) is one of the most difficult diseases to be treated fundamentally in the medical field in today’s world, and the recurrence rate of HCC has been increasing year by year in recent years. The study on the identification and prediction of microvascular invasion phenomenon (MVI) in hepatocellular carcinoma is beneficial to the postoperative prevention of hepatocellular carcinoma patients, which can greatly improve the survival probability of patients after surgery. In this study, a new MVI prediction method (MSF-GWO-GPR) was proposed, which combines the multi-sequence image features of imaging histology, sifts out the unimportant features through the T-test method and the dimensionality reduction of Lasso regression, and establishes the multi-sequence Gaussian process regression (GPR) prediction model for data fusion, and combined with the Gray Wolf optimization (GWO) algorithm to design a suitable optimization objective function to optimize the hyper-parameters in the GPR, in order to get better prediction results. Compared with the existing methods, the data from different sequences of MRI images are selected for fusion in this study, which makes the feature data richer and more complete, and the model applicability is better; moreover, by optimizing the hyperparameters in the model through the GWO, the model can be made more accurate, reduce the risk of misidentified prediction, and improve the accuracy rate. The experimental results show that MSF-GWO-GPR outperforms widely used machine learning methods in terms of accuracy, F1 score, precision, recall and AUC metrics. This may provide a new idea for the identification and prediction of MVI in hepatocellular carcinoma.

关键词： Liver cancer Accuracy Magnetic resonance imaging Prevention and mitigation Surgery Predictive models Feature extraction

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Parallel systems Framework: A Safe and Efficient Testbed for Unmanned Ships 4

Parallel Systems Framework: A Safe and Efficient Testbed for...

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4th IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2024

作者： Fu, Long Shen, Zhen Dong, Xisong Han, Yunjun Yang, Shuguang Xiong, Gang Wang, Fei-Yue University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Beijing100190 China Chinese Academy of Sciences Guangdong Engineering Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Dongguan523808 China Shandong Jiaotong University Schoool of Rail Transportation Jinan250399 China Chinese Academy of Sciences State Key Laboratory for Management and Control for Complex Systems Institute of Automation Beijing100190 China

ISBN: (纸本)9798350349252

In this study, unmanned ships test platform based on the parallel systems framework is proposed to improve the test efficiency and accuracy of unmanned ships in complex ocean environment. The parallel intelligence theory and ACP approach, the efficient interaction between virtual and real environment is achieved, which provides more comprehensive and accurate data for unmanned ships testing. Future research will further expand the scope of virtual environment simulation and improve systems accuracy and response speed to a wider range of unmanned ships test requirements. © 2024 IEEE.

关键词： Virtual environments

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An Error Correcting Output Code Algorithm Based on Hierarchical Clustering for Lithology Identification

An Error Correcting Output Code Algorithm Based on Hierarchi...

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Chinese control Conference (CCC)

作者： Ao Li Xi Chen School of Rail Transit Hunan University of Technology Zhuzhou China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Lithology identification serves as a crucial foundation for the precise exploration and safe exploitation of geological resources. However, challenges arise from the inherent imbalance and overlap present in logging data, making the accurate identification of lithology a complex task. Addressing these challenges effectively, this paper introduces a novel algorithm, the Error Correcting Output Code algorithm based on Hierarchical Clustering(HC-ECOC). The proposed algorithm initially formulates a coding matrix using distance and overlap measures between class clusters. Subsequently, it extends the length of the coding matrix by considering both the accuracy of the integrated classifier and the diversity among base classifiers. To evaluate the efficacy of the proposed method, comparisons were conducted with alternative algorithms using UCI datasets and an authentic lithology dataset. The results unequivocally demonstrate the superior performance of our algorithm.

关键词： Codes Accuracy Geology Clustering algorithms Binary trees Encoding Classification algorithms

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Investigation of a tunnel magnetoresistance based vector magnetometer for magnetic anomaly detection 2

Investigation of a tunnel magnetoresistance based vector mag...

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2022 2nd International Conference on Advanced Materials and Mechatronics, ICAMM 2022

作者： Wang, Hongpeng Yang, Ruiping Luo, Wang Ge, Jian Liu, Huan Dong, Haobin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

The development of high-performance and miniaturized magnetometers is important for small-scale target magnetic anomaly detection. In this work, a miniaturized three-axis vector magnetometer based on the tunnel magnetoresistance (TMR) technique is investigated for magnetic anomaly detection. First, the miniaturized three-axis TMR vector magnetometer is constructed, and then, the limit of detection tests and the magnetic anomaly detection tests are performed. The indoor experimental results show that the proposed magnetometer can capture the magnetic anomalies higher than 3.9 nT, with the low-frequency equivalent magnetic noise of 46.89 pT/√Hz@1Hz. The outdoor experimental results show that the proposed magnetometer can effectively detect small-scale magnetic targets such as hammers at a distance of about 1.5 m. With the advantages of small size, low power consumption, and high magnetic measurement sensitivity, the TMR magnetometer has great application prospects for long-term magnetic anomaly monitoring, high-density magnetic imaging, and other fields. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Magnetometers

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Speech Emotion Recognition Based on Clustering Assistance

Speech Emotion Recognition Based on Clustering Assistance

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2022 Chinese Automation Congress, CAC 2022

作者： Peng, Zhi-Kun Liu, Zhen-Tao Han, Meng-Ting China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665465335

Speech emotion recognition (SER) is a key technology to achieve natural human-computer interaction. The development of SER is significantly influenced by the scale of the sample. In recent years, the study of SER has been intensified by introducing data augmentation methods. However, most of these methods directly augment the sample data scale, neglecting the rational analysis and utilization of the feature distribution of samples. In this paper, we propose a new framework for SER based on clustering assistance, which can utilize the feature distribution information of the sample data directly and effectively. It considers the sample proportion of each emotion category in the clusters obtained by clustering, converts it into a probability score, which is called the clustering emotion probability score, and fuses it with the emotion probability score from the simple classification model according to different fusion weighting factors. We evaluated the proposed method with the baseline model on the IEMOCAP dataset. Experimental results show that our method achieves better results than the baseline model in terms of both weighted and unweighted accuracy. © 2022 IEEE.

关键词： K-means clustering

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Axial-torsional coupled drill-string vibration analysis based on the bit-rock interaction model considering the drilling fluid factor 13

Axial-torsional coupled drill-string vibration analysis base...

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13th Asian control Conference, ASCC 2022

作者： Huang, Hengyu Wu, Min Lu, Chengda Cao, Weihua Chen, Xin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9788993215236

To characterize drill-string system's dynamic reaction, the axial-torsional coupled drill-string vibration model need to be studied. The drill-string takes little consideration for the drilling fluid factor, and drill-string vibration model for torque and drawworks pull inputs have limited relevance in geological drilling. So an axial-torsional coupled drill-string vibration model is established, with inputs of rope lowering and rotary table rotating speed, and the influence of the drilling fluid factor is taken into account. Firstly, we build a drill-string model with the winch rope speed and rotating speed inputs based on material mechanics theory. Then, the axial-torsional coupled bit-rock interaction model is established, taking the factor of drilling fluid into consideration, and the axial and torsional drill-string vibration is coupled through the bit-rock interaction model. Finally, the model's validity is proved by simulation of the drill-string system and the verification of field data. © 2022 ACA.

关键词： Drilling Vibrations Couplings Analytical models Fluids Torque Geology

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Design of intelligent monitoring and dynamic early warning system for geological hazards

Design of intelligent monitoring and dynamic early warning s...

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2022 Chinese Automation Congress, CAC 2022

作者： Yu, Ziliang Cao, Weihua Gan, Chao School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665465335

intelligent monitoring system is crucial to the process of geological disaster prevention and control, and plays a vital role in improving prevention and control efficiency and early warning accuracy. An intelligent monitoring and dynamic early warning system for geological hazards is designed. First, four main functional requirements of data fusion and visualization, single landslide dynamic warning, regional landslide susceptibility evaluation and risk level inquiry are analyzed in detail. Then, the system network architecture is analyzed and a six-layer software framework is designed. Finally, a new online data architecture is proposed. The designed system provides a feasible solution for geological disaster prevention and control. © 2022 IEEE.

关键词： Disaster prevention

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Oilwell Downhole RFID Reader based on Discrete Components

Oilwell Downhole RFID Reader based on Discrete Components

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2021 International Conference on Signal Processing and Communication Technology, SPCT 2021

作者： Liu, Xiaokun Zhu, Jixuan School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (数字)9781510653344

ISBN: (纸本)9781510653337

RFID (Radio Frequency Identification) is expected to provide a new way for the efficient and low-cost control of oilwell downhole tools, and bring huge economic benefits. However, the RF (radio frequency) base station chips on the market could not withstand the high temperature of downhole. In this paper, discrete components are used to build RF front-end circuits to realize the drive and demodulation functions of RF base station chips. The circuit parameters are adjusted and optimized through circuit simulation. Then, the software and hardware design of the downhole reader are accomplished. Finally, experimental results show that the proposed downhole reader based on discrete components can successfully demodulate and read the tag data. © 2022 SPIE.

关键词： Circuit simulation

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Surface Roughness Measurement of Ceramic Products Based on Impedance control 18th

Surface Roughness Measurement of Ceramic Products Based on I...

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18th Chinese intelligent systems Conference, CISC 2022

作者： Gao, Xu Chen, Xin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789811962257

A contact force tracking method based on variable impedance control was proposed to solve the problem of compliant contact of industrial robots in contact tasks. Firstly, the mathematical model between the contact force steady-state error and the impedance model parameters is analyzed according to the impedance control and second-order environment model. Secondly, the adaptive control rate of robot contact force error and damping parameters are established according to PD controller idea. Finally, the stability of the controller is verified by Routh criterion, and the stability range of the controller parameters is obtained. Experimental results show that compared with impedance control, variable damping impedance control has the characteristics of low overshoot, zero steady-state error, and rapid response, and can follow the dynamic expected force and adapt to the uncertain environment. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Surface roughness

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