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检索条件"任意字段=CIBDA 2022;3rd International Conference on Computer Information and Big Data Applications"

共 1227 条记录，以下是81-90 订阅

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Research on computer Intelligent Proofreading System Based on Improved Phrase Translation Model 3

Research on Computer Intelligent Proofreading System Based o...

引用

2022 3rd international conference on computer information and big data applications, cibda 2022

作者： Liu, Junyan The Department of Foreign Language and Literature Wuhan Donghu University Hubei Wuhan China

ISBN: (纸本)9783800758760

In view of the fact that the English translation and proofreading system of syntax and phrase attaches importance to accuracy calibration and can not solve the problem of poor coherence, an intelligent proofreading system based on improved phrase translation model is proposed. First of all, translation algorithms based on phrases' translation can create the models of semantic ontology. Furthermore, the general scheme systematic design is carried out through the overall architecture of the system. In order to improve the searches' accuracy, it's better to set search modules as the main parts of hardware. Software is required to support multi-language translations and proofreading. Thus, the modules of software should primarily include the system applications' frameworks, network analysis situs, clients, the organizations and managements of translators, internet cooperative translations and other modules. [1]. The last procedure is to test the designed system. The testing results prove that those systems can fulfil the users' needs of translation proofreading and raise greatly the efficiency of proofreading. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Semantics

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Back Propagation Neural Network Based Stroke Prediction 3

Back Propagation Neural Network Based Stroke Prediction

引用

2022 3rd international conference on computer information and big data applications, cibda 2022

作者： Tan, Bowen ANU College of Engineering and Computer Science Australia National University Canberra2601 Australia

ISBN: (纸本)9783800758760

Stroke prediction is crucial to help doctors or specialists' diagnosis the survival rate of patients. To help people prevent stroke, which has a high fatality rate, this paper preprocessed a dataset got from Kaggle website, then did the feature selection process by constructing decision tree model, and a deep learning based back propagation neural network (BPNN) model was built. After that, the cleaned data were fed into the model for training and testing to obtain results. Meanwhile, some experiments are done for selecting the most appropriate hyper parameter of the model, including hidden layer number and the neuron nodes number. Finally, the neural network model reached 98.13% training accuracy and 97.97% testing accuracy, which shows that the back propagation neural network model this paper constructed is feasible and fit for stroke prediction in this study. More datasets will be considered in the future for further verification based on our proposed methodology. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Neural network models

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Pavement crack detection method based on deep learning 3

Pavement crack detection method based on deep learning

引用

2022 3rd international conference on computer information and big data applications, cibda 2022

作者： Huang, Jian Wu, Dandi School of Communication and Information Engineering Xi 'an University of Science and Technology China

ISBN: (纸本)9783800758760

Pavement crack detection is an important step to achieve the task of pavement maintenance. Only by detecting pavement cracks in time can ensure road safety. Road crack detection has very important practical significance. This paper proposes to detect and extract road surface cracks based on deep learning, and based on the segmentation results, the crack types are classified and the crack area is quantitatively calculated. In this paper, after improving the ASPP module of the DeepLabV3+ network, the crack image is extracted, and then the extracted crack image is classified by the MobilenetV2 network, and finally it is quantified according to the quantization algorithm proposed in this paper. The experimental results show that the improved segmentation network has better extraction effect on crack images, the mIoU reaches 77.48%, the classification accuracy of the classification network for various types of cracks reaches more than 85%, and the quantization algorithm can accurately quantify the crack area and other information. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Deep learning

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Multi-label topic classification for COVID-19 literature annotation: A BioBERT-based feature enhancement approach 3

Multi-label topic classification for COVID-19 literature ann...

引用

2022 3rd international conference on computer information and big data applications, cibda 2022

作者： Wang, Xin Wang, Jian Tang, Wentai Zhang, Hongtong College of Computer Science and Technology Dalian University of Technology Dalian116024 China

ISBN: (纸本)9783800758760

With the rapid expansion and exponential growth of biomedical literatures, especially in the current environment of COVID-19 pandemic, it is urgent to explore an effective technology to automatically manage and categorize massive information for biomedical texts. The wide application and powerful performance of BERT have shown promising results in the field of natural language processing. Thus, we first choose the improved pre-trained language models CovidBERT and BioBERT as the basis, from the best performance of which further enhances semantic representation of abstract with extra title information. Finally, a novel feature enhancement method is proposed to exploit and integrate the distribution of label information effectively. The experimental results show that our model achieves an instance-based F1 score, precision and recall of 93.94%, 93.5% and 94.38% in the task of multi-label topic classification from track 5 BioCreative VII. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： COVID-19

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Improved indoor location algorithm based on Wi-Fi fingerprint and random forest 3

Improved indoor location algorithm based on Wi-Fi fingerprin...

引用

2022 3rd international conference on computer information and big data applications, cibda 2022

作者： Han, Xuefa Han, Xuefang Wu, Fei Zhu, Hai School of Computer Science Wuhan Donghu University Wuhan China College of Education Zhejiang University of Technology Hangzhou China School of Electronic and Electrical Engineering Shanghai University of Engineering Science Shanghai China

ISBN: (纸本)9783800758760

Aiming at the influence of the similarity of Wi-Fi signal strength on indoor positioning, this paper proposes an improved indoor positioning algorithm based on Wi-Fi fingerprint and random forest. The algorithm uses Wi-Fi as a signal source to construct a Wi-Fi fingerprint library by receiving signal strength indication and basic service set identifiers, thereby establishing a random forest model for indoor location sensing. The simulation results show that the positioning error of the algorithm is about 2.26m. Compared with similar algorithms, it has better performance in execution time and positioning accuracy, and the accuracy of the algorithm is improved by about 3.2%. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Wireless local area networks (WLAN)

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A Network Intrusion Detection Method based on K-Means 3

A Network Intrusion Detection Method based on K-Means

引用

2022 3rd international conference on computer information and big data applications, cibda 2022

作者： Fang, Mingyang Liu, Feng School of Computer Science and Technology Anhui University Anhui Hefei China

ISBN: (纸本)9783800758760

With the continuous development of computer technology and the expansion of network scale, intrusion has become more and more serious threats to the security of computer systems and networks. An intrusion is an unauthorized and deliberate attempt to access information, tamper with it, and make the system unreliable or unusable. For illegal intrusion behavior, we propose an unsupervised anomaly detection method, which combines clustering analysis method with intrusion detection technology, and uses K-Means algorithm to cluster unlabeled data, so as to provide as pure normal behavior data as possible for establishing normal behavior model. In the process of modeling, a new normal behavior modeling algorithm based on hyperrectangle is proposed, which is helpful to detect intrusion behaviors quickly and accurately. Experiments on KDDcup99 dataset show that this method can effectively detect intrusion behaviors in network data, with high detection rate and low false detection rate. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Intrusion detection

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Early Warning System for Safe Operation of Grain Silos based on Intelligent Video Analysis 3

Early Warning System for Safe Operation of Grain Silos based...

引用

2022 3rd international conference on computer information and big data applications, cibda 2022

作者： Xu, WenHao Yang, Wei Liang, KangBo Wu, YiBo Yang, WeiDong College of Information Science and Engineering Henan University of Technology Zhengzhou450001 China

ISBN: (纸本)9783800758760

China is a country with a large population. Ensuring the effective supply of grain is of great significance to ensuring the stable operation of the national economy. In order to improve the security capability of grain purchase, storage and supply, it is necessary to carry out intelligent upgrading and transformation of grain depots. At present, the identification of violations in the granary is mainly by installing sensors in key areas and manually reviewing video records. This method not only takes up a lot of resources, but also is unsatisfactory in real-time and accuracy. This paper proposes a video behavior recognition algorithm based on deep learning, combined with the analysis of the unsafe operation behavior of granary workers, to achieve effective, real-time recognition and reminders to ensure the safety of food and employees. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Deep learning

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Design and Realization of Simulation TestBed for Intelligent Unmanned Swarm System 3

Design and Realization of Simulation TestBed for Intelligent...

引用

2022 3rd international conference on computer information and big data applications, cibda 2022

作者： Li, Shuang Zhao, Dequn Ye, Jiazi Deng, Qianhua Department of Information Beijing University of Technology Beijing100124 China Poly National Defense Technology Research Center Co. Ltd Beijing100086 China China Telecom Group Beijing100035 China

ISBN: (纸本)9783800758760

Aiming to meet the needs of unmanned swarm testing and verification in intelligent unmanned systems as well as solve the high-risk issues faced in physical testing, this paper designs and implements a simulation testbed. The main research includes: building a testbed architecture for a scaled-up unmanned swarm system;designing a Docker-based unmanned swarm support platform;and building a ROS-based unmanned swarm drive engine. In order to verify the feasibility of the platform, we perform a fixed-wing UAV swarm relay communication test and a semi-physical semi-simulation unmanned vehicle queue test in this paper. The test results show that the simulation testbed implemented in this paper can effectively evaluate the cooperative operation of multiple unmanned devices, and the test datas are accurate and reliable, which is of certain significance to the unmanned swarm test and evaluation. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Fixed wings

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Vulnerability mining for DoIP based on weighted mutation for combined fields 3

Vulnerability mining for DoIP based on weighted mutation for...

引用

2022 3rd international conference on computer information and big data applications, cibda 2022

作者： Li, Jingru Xie, Yong School of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing210003 China

ISBN: (纸本)9783800758760

emote diagnostic services based on DoIP protocols provide convenience for vehicle bootloader and diagnostics but inevitably posing a potential risk to automotive information security. Therefore, it is of practical importance to perform the security testing of DoIP implementations. The use of existing fuzzing frameworks for network protocol is blind and requires high computing resources for vehicle devices. To address the above problems, a weighted mutation for combined fields is proposed, combined with depth-first search algorithm for protocol state machine traversal to form a two-layer data generation strategy. Further, the weight matrix is adjusted during test iterations based on a feedback mechanism to optimize the quality of the test case set, ultimately ensuring fuzz efficiency despite limited test resources. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Network protocols

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Research on a Trend Forecast Model of Time Series data Based on Deep Learning 3

Research on a Trend Forecast Model of Time Series Data Based...

引用

2022 3rd international conference on computer information and big data applications, cibda 2022

作者： Jiang, Yaping Li, Xing Ni, Zihao Department of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou450000 China

ISBN: (纸本)9783800758760

The prediction of stock price trends is of great significance in the study of time series. Based on deep learning, this paper combines a convolutional neural network (CNN) for feature extraction and a long short-term memory network (LSTM) for prediction, and proposes a 3dCNN-LSTM stock price trend prediction model. The three-dimensional input tensors of the model are the technical indicators of the stock index, the correlation between the stock indexes and the historical information of the time series. Among them, this paper converts the traditional technical indicators for predicting stock prices into trend-deterministic data, and secondly uses distance correlation coefficients to sort the stock indices, and designs a CNN module that can extract three-dimensional input features, and sets up simulation experiments under different conditions to determine the optimal parameters of the model. Through comparison with other prediction models, the results of simulation experiments show that the 3dCNN-LSTM model has a better prediction effect and improves the F1 measurement value. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Long short-term memory

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