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Convolutional neural network-based identification of malicious traffic for TLS encryption 7

Convolutional neural network-based identification of malicio...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Chen, Jianxi Huang, Jiahao Lu, Xinghua Institute of Computer Control Technology Guangzhou Huali College Guangzhou China St. Paul University Philippines Tuguegarao Philippines

ISBN: (纸本)9781665478571

By converting network traffic into images and using convolutional network prediction methods, the accuracy of malicious network traffic can be effectively improved. As TLS traffic encryption is used in more and more network applications, while protecting security and privacy, network attackers can achieve the purpose of evading detection by encrypting malicious traffic. the traditional method of using a firewall and anti-virus software to decrypt the encryption key to access the encrypted data is not only inefficient and destroys the original purpose of encryption to protect privacy, but also when the key cannot be decrypted, the traditional method the decryption capability of the traditional method is insufficient. In this paper, we propose a method to transform network traffic into network fingerprint images without decrypting the encrypted data, and then feed the images into a convolutional neural network for prediction to achieve the classification of malicious traffic. the experimental results show that the method of identifying network fingerprint images by using CNN has high accuracy and prediction capability. © 2022 IEEE.

关键词： Convolution

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A Hybrid Deep Learning Model for Predicting PM2.5 7

A Hybrid Deep Learning Model for Predicting PM2.5

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Yuan, Peng Mei, YiFei Zhong, YongLong Xia, Yan Fang, Liang Hunan University College of Computer Science and Electronic Engineering Changsha China

ISBN: (纸本)9781665478571

Accurate prediction of PM2.5 concentration is of great significance to air pollution control and human health protection. However, how to extract effective features of numerous information from a large amount of relevant monitoring data has become a challenging problem. In this paper, we propose a hybrid deep learning model (HDL) for predicting PM2.5 concentration. Firstly, we select four models that can process time-series data, including simple-RNN, LSTM, GRU, and TCN. these models have been trained as base models respectively with the air quality data and meteorological data in Changsha in the past two years. Secondly, the four base models are integrated into a new HDL model, which inherits all the advantages of the four base models. Finally, MAE, MAPE, MSE, RMSE, and R2 are employed to evaluate the prediction accuracy of these models. the experimental results show that the HDL model has higher accuracy in most numerical scenarios than the above four models. © 2022 IEEE.

关键词： Meteorology

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Fault Detection For Automatic Guided Vehicles Based on the Two-tower Model 7

Fault Detection For Automatic Guided Vehicles Based on The T...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Ding, Xiaohu Zhang, Dongdong Zhang, Liangang Zhang, Lei Zhang, Changjiang Xu, Bin Tongji University Department of Computer Science Shanghai China Qingdao Port International Co. Ltd Technology Center Qingdao China Qingdao Port International Co. Ltd New Qianwan Container Terminal Qingdao China Qingdao Port International Co. Ltd Corporate Management Qingdao China

ISBN: (纸本)9781665478571

Automated Guided Vehicle (AGV) is one of the most important automation equipment in Automated Container Terminal (ACT), the normal operation of AGV equipment plays a vital role in maintaining high efficiency and quality operation of ACT. In this paper, We propose an end-to-end fault detection algorithm for AGV equipment that obtains both spatially regular and temporally dimensional features from the sensor data, which introduces a two-tower model structure for fault detection. the attention network is used to learn the key variables in the sensor data, and the LSTM network is combined to learn the temporal dimensional features in the data to construct a two-tower model for fault detection. In addition, we provide a real dataset from AGV at Qingdao port container terminals to evaluate the effectiveness of the algorithm. the experimental results show that this algorithm outperforms better than existing methods in terms of classification performance, and can achieve 98.83% accuracy. © 2022 IEEE.

关键词： Containers

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TOWARDS AUTOMATIC 2D MATERIALS DETECTION USING YOLOV7 19

TOWARDS AUTOMATIC 2D MATERIALS DETECTION USING YOLOV7

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19th IEEE international computer conference on Wavelet Active Media technology and information processing (ICCWAMTIP)

作者： Zenebe, Yutra Abel Li Xiaoyu Chaos, Wang Wen Yi Endris, Hassen Ahmed Fanose, Mola Natnael Univ Elect Sci & Technol China Sch Informat & Software Engn Chengdu 611731 Peoples R China Inst Elect & Informat Ind Technol Kash Silk Rd Talent BldgShenka Ave Kash 844000 Xinjiang Peoples R China Southwest Inst Tech Phys Chengdu 610041 Peoples R China Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu 6117731 Peoples R China

ISBN: (纸本)9781665493895

Two-dimensional (2D) materials have become a research focus in the field of nanotechnology. Because of their unique physical and chemical properties, these materials can be applied to various industries such as sensors, batteries, and display screens. However, identifying if optical microscope images contain 2D materials flakes is a tedious and time-consuming process. In this paper, we propose a deep learning-based object detection system using YOLOv7, to automatically search for 2D materials with few atomic layers (thickness in between 1 to 13 layers). To train the model, we have constructed Molybdenum Disulfide (MoS2) image dataset that is captured in 20x magnification and applied digital image processing and data augmentation techniques to increase the model performance. In addition, we developed a software pipeline that can be easily integrated with the optical microscope to detect 2D materials and store the result in the database. the result of the experiments shows that the trained model achieves high accuracy in detecting a few layers of MoS2. © 2022 IEEE.

关键词： 2D Materials Object Detection MoS2 Deep Learning YOLOv7

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Meteorological and Hydrological Monitoring technology Based on Wireless Sensor Network Model and Its Application 7th

Meteorological and Hydrological Monitoring Technology Based ...

引用

7th international conference on Cognitive Systems and information processing, ICCSIP 2022

作者： Wang, Ni Guo, Zhongwen Wang, Jinxin Qi, Suiping College of Information Science and Engineering Ocean University of China Tsingdao China Shangdong Technological Center of Oceanographic Instrumentation Co. Ltd Tsingdao China Tsingdao China National Engineering and Technological Research Center of Marine Monitoring Equipment Tsingdao China

ISBN: (纸本)9789819906161

In view of the difficulty to realize the meteorological and hydrological observation on the unmanned islands or reefs, the complexity of using wireless sensor network cannot be too high and the requirement of reliability is higher, so a master-slave dual-cluster head network trust model based on adaptive weighted D-S evidence theory fusion calculation is proposed. At the same time, the reliability is adaptively adjusted according to the time sliding statistics of the node measurement data. the base station determines whether to receive data and determines the master-slave cluster head in the next cycle according to the fusion result difference and their historical data evaluation, which reduces the complexity of trust calculation and develops the remote unattended Islands and reefs meteorological and hydrological wireless sensor monitoring technology. the test results show that the technology is effective and feasible, with the advantages of convenient layout and reliable data transmission. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Wireless sensor networks

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Study on computer Simulation Prediction of the Feasibility of Heme Determination of Pb 7

Study on Computer Simulation Prediction of the Feasibility o...

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7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Wang, Xiaofeng Lan, Wenbo He, Liping Wang, Binbin Wang, Yuzhu Wang, Liping Bu, Zhijian Li, Jianhuang Meng, Yanbin Nie, Changming Xiangnan University School of Public Health Chenzhou China Xiangnan University Office of Network Information Technology Chenzhou China Xiangnan University School of Basic Medicine Chenzhou China University of South China School of Chemistry and Chemical Engineering Hengyang China

ISBN: (纸本)9781665478571

In order to explore why heme can be used for the determination of lead, the central iron atom (Fe) of heme was replaced with lead atom (Pb). the structural characteristics and spectral characteristics of the molecules before and after the substitution, as well as the binding ability of the heme ligand to the central atom and the stability of the formed complex were compared. the results show that complex-Pb has obvious infrared characteristic spectrum and obvious ultraviolet absorption peak. After Fe in heme is replaced by Pb, the formed complex pb can exist stably, and the binding capacity of heme ligand to Pb is greater than that of Fe atom, and the chemical stability of complex pb is also better than that of heme. © 2022 IEEE.

关键词： Porphyrins

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Distributed Immutable Ledger to maintain integrity and anonymity in Health Insurance - A Blockchain approach 7

Distributed Immutable Ledger to maintain integrity and anony...

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7th international conference on Computing in Engineering and technology, ICCET 2022

作者： Mahajan, Apurva Khandelwal, Disha Kapuskari, Richa Chaudhari, Rutwik Shingade, Sandip Department of Computer Engineering and Information Technology Veermata Jijabai Technological Institute Mumbai India

ISBN: (纸本)9781839537042

Health Insurance application and claim process involve doctors, hospitals, lab professionals and policy holders for approvals, making it slow and increasing the chances of anomalies. Previous research has made it possible to store medical reports on decentralised blockchain networks primarily by using private blockchain networks like Hyperledger fabric which doesn't assure no data leakage. Our blockchain's proposed solution will help in easing out the whole process and helping in maintaining integrity and establishing anonymity. We designed data structures for storing insurance payments and agreements, medical service records, and patient records within the ledger. We use smart contracts to automate the insurance claim process and to ensure privacy. this compliance system for the health insurance claim process will increase the privacy of patients' records along with maintaining integrity and anonymity. © 2022 the Institution of Engineering and technology.

关键词： Blockchain

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Method for Relation Extraction Based on Entity Boundary Features 24

Method for Relation Extraction Based on Entity Boundary Feat...

引用

2024 7th international conference on computer information Science and Artificial Intelligence, CISAI 2024

作者： Wang, Zining Ge, Jike Yang, Xiaolu Tan, Jie Xiang, Yu School of Computer Science and Engineering Chongqing University of Science and Technology Chongqing China

ISBN: (纸本)9798400707254

As a key task in natural language processing, the current knowledge extraction methods mostly involve joint extraction, simultaneously extracting named entities and relationships. When conducting relationship extraction, entities containing multiple words are usually represented using pooling or weighted sum methods, leading to the neglect of entity boundary information. To address the issue of reduced accuracy in relationship classification due to the introduction of intermediate noise information based on entity segment features, a relationship extraction method focusing on entity boundary features is proposed. Firstly, the semantic representation of the text is obtained using the pre-trained language model DeBERTa. then, features of the head and tail positions of entities in the text are extracted and concatenated into a composite embedding vector containing information from these two key positions, used to enhance entity representation. By concatenating the composite embedding vectors of the head and tail entities, the final embedding vector of the entity pair is obtained, representing the information of each entity and enhancing the model’s understanding of entity boundaries and semantic information. Finally, the existence of relationships between entity pairs is determined by the relationship discriminator and relationship classifier, simultaneously classifying the relationship types of the entity pairs for relationship classification. Experimental results show that the proposed method achieves F1 scores of 89.3%, 94.4%, 94.2%, and 94.9% on the NYT, NYT*, WebNLG, and WebNLG* datasets, respectively, significantly outperforming the baseline models. Additionally, ablation experiments demonstrate the importance of the relationship discriminator, further confirming the superiority of the relationship extraction method focusing on entity boundary features. © 2024 Copyright held by the owner/author(s).

关键词： Boundary features

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Optimal Capacity Configuration and Adjustment of Communication Network Devices 7

Optimal Capacity Configuration and Adjustment of Communicati...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Xu, Qingzheng Wang, Na Fu, Weinan Tian, Balin National University of Defense Technology College of Information and Communication Wuhan China Qinghai Armed Police Corps Haixi Detachment Delingha China

ISBN: (纸本)9781665478571

As an important infrastructure, communication network can support military training, combat readiness and daily life. However, at present, the effective method is lack to reasonably configure the capacity of communication network devices. In this paper, according to the communication and construction requirements, a typical network is firstly divided into two stages: initial layout and network operation. In the initial layout stage, a novel definition of the importance degree of node is proposed, and then the optimal device capacity allocation is obtained by linear programming model. In the network operation stage, the minimum spanning tree is obtained by using the ring-breaking method, and the optimal communication scheme is constructed in order to occupy the minimum capacity. Based on a typical communication network, some results are given in this paper. the simulation results state clearly our proposed approach is effective and suitable in designing the optimal capacity configuration of communication network devices. © 2022 IEEE.

关键词： Linear programming

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Research on the influence mechanism of job crafting on the suggestion behavior of the new generation of employees based on system dynamics simulation 7

Research on the influence mechanism of job crafting on the s...

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2022 7th international conference on information Science, computer technology and Transportation, ISCTT 2022

作者： Sun, Yue International Business School Shaanxi Normal University Shaanxi Xi'an710119 China

ISBN: (纸本)9783800760565

In the VUCA era, the work of the new generation of employees is the potential power source of enterprises. their suggestion behavior plays a very important role in the innovation and development of enterprises. this paper will explore the impact mechanism of job crafting on employees' suggestion behavior. Based on the theories of job requirements resource theory, self-determination theory and social exchange theory, this paper believes that job crafting has a positive impact on the suggestion behavior of the new generation of employees, the sense of professional mission plays an intermediary role between job crafting and employees' suggestion behavior, and the sense of organizational support positively regulates the relationship between the sense of professional mission and employees' suggestion behavior. the influence mechanism of job crafting on the suggestion behavior of the new generation of employees is simulated and analyzed, and finally some ways to improve the effectiveness of management are put forward. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Behavioral research

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