检索结果-内蒙古大学图书馆

9th International Conference on Orange technology, ICOT 2021

作者： Wang, Xiaogang Tang, Chong Changzhou College of Information Technology Software and Big Data Department Changzhou China

ISBN: (纸本)9781665478427

With the rapid development of economy and society, power customers require higher quality for power supply, which puts forward higher requirements for electric power service. Obviously, high quality service is vital to survival and development of power enterprises. Due to the lack of effective warning analysis of customer power failure, it is impossible for power enterprises to carry out scientific scheduling according to the urgency of customer fault emergency repair, resulting in poor customer service experience and prominent customers' demolition problems. Based on historical repair information of customers in the power industry and combined with the indicators such as repair efficiency, external environment and customer historical complaint times, this paper proposes a complaining behavior predicting model (CBPM) for electric customers by exploiting RFC random forest and the grid search algorithm to optimize the model parameters. Our model can be used by power enterprises to predict the complaint risk of current circulating work orders, and quickly locate the work orders with high complaint tendency, thereby guiding the customer service department to take targeted measures. Theory and practice show that our CBPM mode outperforms existing complaining behavior predicting methods, and our prediction model can effectively realize the pre-warning of complaints, thereby reducing the amount of customer complaints and improving customer satisfaction effectively. © 2021 IEEE.

关键词： Customer satisfaction

来源：评论

学校读者我要写书评

暂无评论

Accumulative Time Based Ranking Method to Reputation Evaluation in Information Networks

引用

Journal of Computer Science & technology 2022年第4期37卷 960-974页

作者： Hao Liao Qi-Xin Liu Ze-Cheng Huang Ke-Zhong Lu Chi Ho Yeung Yi-Cheng Zhang National Engineering Laboratory on Big Data System Computing Technology College of Computer Science and SoftwareEngineeringShenzhen UniversityShenzhen 518060China Guangdong Province Key Laboratory of Popular High Performance Computers Shenzhen UniversityShenzhen 518060China Guangdong Province Engineering Center of China-Made High Performance Data Computing System College of ComputerScience and Software EngineeringShenzhen UniversityShenzhen 518060China Institute of Big Data Intelligent Management and Decision Shenzhen UniversityShenzhen 518060China Department of Science and Environmental Studies The Education University of Hong KongHong Kong 999077China Department of Physics University of FribourgFribourg 1700Switzerland

Due to over-abundant information on the Web, information filtering becomes a key task for online users to obtain relevant suggestions and how to extract the most related item is always a key topic for researchers in various fields. In this paper, we adopt tools used to analyze complex networks to evaluate user reputation and item quality. In our proposed Accumulative Time Based Ranking (ATR) algorithm, we take into account the growth record of the network to identify the evolution of the reputation of users and the quality of items, by incorporating two behavior weighting factors which can capture the hidden facts on reputation and quality dynamics for each user and item respectively. Our proposed ATR algorithm mainly combines the iterative approach to rank user reputation and item quality with temporal dependence compared with other reputation evaluation methods. We show that our algorithm outperforms other benchmark ranking algorithms in terms of precision and robustness on empirical datasets from various online retailers and the citation datasets among research publications. Therefore, our proposed method has the capability to effectively evaluate user reputation and item quality.

关键词： temporal network behavior dynamics reputation evaluation ranking algorithm

来源：评论

学校读者我要写书评

暂无评论

Multi-layer network embedding on scc-based network with motif

引用

Digital Communications and Networks 2024年第3期10卷 546-556页

作者： Lu Sun Xiaona Li Mingyue Zhang Liangtian Wan Yun Lin Xianpeng Wang Gang Xu Department of Communication Engineering Institute of Information Science TechnologyDalian Maritime UniversityDalian116026China Key Laboratory of Big Data Intelligent Computing Chongqing University of Posts and TelecommunicationsChongqing400065China Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province DUT School of Software Technology&DUT-RU International School of Information Science and EngineeringDalian University of TechnologyDalian 116620China College of Information and Communication Engineering Harbin Engineering UniversityHarbin 150001China School of Information and Communication Engineering Hainan UniversityHaikou 570228China State Key Laboratory of Millimeter Waves School of Information Science and EngineeringSoutheast UniversityNanjing 210096China

Interconnection of all things challenges the traditional communication methods,and Semantic Communication and Computing(SCC)will become new *** is a challenging task to accurately detect,extract,and represent semantic information in the research of SCC-based *** previous research,researchers usually use convolution to extract the feature information of a graph and perform the corresponding task of node ***,the content of semantic information is quite *** graph convolutional neural networks provide an effective solution for node classification tasks,due to their limitations in representing multiple relational patterns and not recognizing and analyzing higher-order local structures,the extracted feature information is subject to varying degrees of ***,this paper extends from a single-layer topology network to a multi-layer heterogeneous topology *** Bidirectional Encoder Representations from Transformers(BERT)training word vector is introduced to extract the semantic features in the network,and the existing graph neural network is improved by combining the higher-order local feature module of the network model representation network.A multi-layer network embedding algorithm on SCC-based networks with motifs is proposed to complete the task of end-to-end node *** verify the effectiveness of the algorithm on a real multi-layer heterogeneous network.

关键词： Semantic communication and computing Multi-layer network Graph neural network Motif

来源：评论

学校读者我要写书评

暂无评论

Injections Attacks Efficient and Secure Techniques Based on Bidirectional Long Short Time Memory Model

引用

Computers, Materials & Continua 2023年第9期76卷 3605-3622页

作者： Abdulgbar A.R.Farea Gehad Abdullah Amran Ebraheem Farea Amerah Alabrah Ahmed A.Abdulraheem Muhammad Mursil Mohammed A.A.Al-qaness School of Big Data&Software Engineering Chongqing UniversityChongqing401331China Department of Management Science Engineering Dalian University of TechnologyDalian116024China Software College Northeastern UniversityShenyang110169China Department of Information Systems College of Computer and Information ScienceKing Saud UniversityRiyadh11543Saudi Arabia Department of Management Science and Engineering South China University of TechnologyGuangzhou510641China Department of Computer Engineering and Mathematics University of Rovira i VirgiliTarragonaSpain College of Physics and Electronic Information Engineering Zhejiang Normal UniversityJinhua321004China

E-commerce,online ticketing,online banking,and other web-based applications that handle sensitive data,such as passwords,payment information,and financial information,are widely *** web developers may have varying levels of understanding when it comes to securing an online *** Query language SQL injection and cross-site scripting are the two vulnerabilities defined by the OpenWeb Application Security Project(OWASP)for its 2017 Top Ten List Cross Site Scripting(XSS).An attacker can exploit these two flaws and launch malicious web-based actions as a result of these *** published articles focused on these attacks’binary *** article described a novel deep-learning approach for detecting SQL injection and XSS *** datasets for SQL injection and XSS payloads are combined into a single *** dataset is labeledmanually into three labels,each representing a kind of *** work implements some pre-processing algorithms,including Porter stemming,one-hot encoding,and the word-embedding method to convert a word’s text into a *** model used bidirectional long short-term memory(BiLSTM)to extract features automatically,train,and test the payload *** payloads were classified into three types by BiLSTM:XSS,SQL injection attacks,and *** outcomes demonstrated excellent performance in classifying payloads into XSS attacks,injection attacks,and non-malicious ***’s high performance was demonstrated by its accuracy of 99.26%.

关键词： Web security SQL injection XSS deep learning RNN LSTM BiLSTM

来源：评论

学校读者我要写书评

暂无评论

Medical Analysis of Social Media data Based on Spark and Machine Learning in China 2

Medical Analysis of Social Media Data Based on Spark and Mac...

引用

2nd International Conference on Computer Science and Management technology, ICCSMT 2021

作者： Peng, Siqi School of Software Shandong University Department of Data Science and Big Data Technology Shandong province Jinan China

ISBN: (纸本)9781665420631

Social media embracing a huge amount of real-time data of all kinds plays an important role in data analysis in the era of big data. Knowledge between medical workers and ordinary people can be popularized and exchanged via social media. At the same time, the collection and utilization of medical data on social media can effectively grasp the public health situation and provide better help to improve people's health status. From the perspective of medical care and health, this paper uses Weibo, the largest public social media in China, to obtain data for analysis. The study was developed under the Spark framework, using naive Bayes, random forest and two different feature extraction methods to clean, pre-process and classify data. Furthermore, the accuracy rate and F1 Score were used to evaluate the model, to find the most appropriate method. The result of this research shows that the data obtained from Weibo within certain age groups has a good reference value in the public awareness and current situation, and are good for grasping the trend of diseases. © 2021 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Establish a smart healthcare system with AIoT for Chinese Medicine 10

Establish a smart healthcare system with AIoT for Chinese Me...

引用

10th International Conference on Orange technology, ICOT 2022

作者： Wei, Chun-Cheng Chen, Ching-Wen Hung, Lon-Chen School of Software and Big Data Changzhou College of Information Technology China Lunghwa University of Science and Technology Department of Multimedia and Game Science Taoyuan Taiwan Lunghwa University of Science and Technology Department of Electronic Engineering Taiwan

ISBN: (纸本)9781665454193

This study establishes an intelligent medical system for diagnosis and treatment of Chinese medicine. Temperature and heart rate were measured using a variety of Internet of things technologies, including the WeMos D1 Mini with ESP8266 integrated and thermistors, and then the resistance was learned to relate to temperature via a neural network. In addition, the AD8232 biomedical sensor and the WeMos D1 Mini were used for ECG measurements and heart rate conversion. A self-written mobile application designed with multiple units to collect data from a variety of patients. The tongue diagnosis unit can recognize the characteristics of tongue substance and coating. The pulse examination unit adopts the five layer pulse method of Yaowangmai pulse. The inquiry unit adopts the syndrome differentiation method of Dr. Shaogong Shen. These IoT data, information if the patient's tongue diagnosis, five-layer pulse examination data and various inquiry data can all be read and transmitted to the cloud. The intelligent medical system of Chinese medicine in this study can also make preliminary treatment recommendations based on a variety of patient data and provide corresponding treatment drugs © 2022 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Fuzzy Neural Network Sliding-Mode Control with Actor-Critic for a Class of Robot Systems 10

Fuzzy Neural Network Sliding-Mode Control with Actor-Critic ...

引用

10th International Conference on Orange technology, ICOT 2022

作者： Hung, Lon-Chen Wei, Chun-Cheng Chen, Hung-Jen Yang, Chih-Fu Cheng, Wei-Min Lunghwa University of Science and Technology Department of Electronic Engineering Taiwan School of Software and Big Data Changzhou College of Information Technology China Lunghwa University of Science and Technology Department of Computer Information and Network Engineering China

ISBN: (纸本)9781665454193

In this article, a robust fuzzy RBF neural network sliding-mode control with actor-critic for a class of robot systems. Trajectory tracking control of robotic systems has favorable performance for tracking control. The fuzzy RBF neural network sliding-mode and actor-critic method is handled to compensate the uncertainty and disturbance of system. The stability analysis is based on for the proposed adaptive and robust control method. The simulation results show the effectiveness under the uncertainties. © 2022 IEEE.

关键词： Sliding mode control

来源：评论

学校读者我要写书评

暂无评论

Monkeypox Detection based on MIRNET-v2 and Transfer Learning 23

Monkeypox Detection based on MIRNET-v2 and Transfer Learning

引用

Proceedings of the 2023 6th International Conference on Artificial Intelligence and Pattern Recognition

作者： Xiaoyin Wang Wenao Li Department of Software Engineering Xi'an University of Posts and Telecommunications China Big Data Technology and Engineering Xi'an University of Posts and Telecommunications China

ISBN: (纸本)9798400707674

At present, the infectious disease caused by monkeypox virus is spreading rapidly all over the world. In order to diagnose it quickly and accurately and then block the transmission chain of the epidemic, this paper proposes an improved transfer learning method based on MIRNet-v2 image enhancement model. Firstly, the network structure of five different deep learning models, ResNet50, ResNet101, AlexNet, VGG19 and VGG16, was adjusted, and the transfer learning method was used to pre-train the models. Secondly, the MIRNet-v2 image enhancement model was combined with the transfer learning model to improve the model performance without reducing the training speed of the transfer learning model. In addition, LIME model is used to explain the internal principle of training for the black box of deep learning model. The “Monkeypox2022” monkeypox dataset was used as the experimental dataset. The optimal performance model of this method was ResNet101, whose accuracy, precision, recall rate and F1 value reached 84.14%, 81.75%, 81.86% and 81.31%, respectively. These data are superior to standard deep learning training methods, so the method proposed in this paper provides a feasible protocol for health personnel to conduct mass screening for monkeypox virus.

关键词： Deep learning MIRNet-v2 model image processing monkeypox recognition and detection transfer learning

来源：评论

学校读者我要写书评

暂无评论

Hierarchical Machine Unlearning 1

引用

17th International Conference on Learning and Intelligent Optimization, LION-17 2023

作者： Zhu, HongBin Xia, YuXiao Li, YunZhao Li, Wei Liu, Kang Gao, Xianzhou Big Data Center State Grid of China Beijing100012 China State Grid Smart Grid Research Institute Shanghai200016 China State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University Nanjing200016 China

ISBN: (数字)9783031445057

ISBN: (纸本)9783031445040

In recent years, deep neural networks have enjoyed tremendous success in industry and academia, especially for their applications in visual recognition and natural language processing. While large-scale deep models bring incredible performance, their massive data requirements pose a huge threat to data privacy protection. With the growing emphasis on data security, the study of data privacy leakage in machine learning, such as machine unlearning, has become increasingly important. There have been many works on machine unlearning, and other research has proposed training several submodels to speed up the retraining process, by dividing the training data into several disjoint fragments. When the impact of a particular data point in the model is to be removed, the model owner simply retrains the sub-model containing this data point. Nevertheless, current learning methods for machine unlearning are still not widely used due to model applicability, usage overhead, etc. Based on this situation, we propose a novel hierarchical learning method, Hierarchical Machine Unlearning (HMU), with the known distribution of unlearning requests. Compared with previous methods, ours has better efficiency. Using the known distribution, the data can be partitioned and sorted, thus reducing the overhead in the data deletion process. We propose to train the model using the hierarchical data set after partitioning, which further reduces the loss of prediction accuracy of the existing methods. It is also combined with incremental learning methods to speed up the training process. Finally, the effectiveness and efficiency of the method proposed in this paper are verified by multiple experiments. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： data privacy

来源：评论

学校读者我要写书评

暂无评论

Motion data Collection for Dance Movements based on Inertial Sensors

Motion Data Collection for Dance Movements based on Inertial...

引用

IEEE International Conference on Orange Technologies (ICOT)

作者： Keyan Yang Xingzhi Chang Xiaohan Long School of Basic Teaching Department Changzhou College of Information Technology Changzhou China School of Software and Big Data Changzhou College of Information Technology Changzhou China

ISBN: (数字)9798331523602

ISBN: (纸本)9798331523619

Dance requires professional instruction during the learning and training process, but high-level guidance at any time and any place can be a challenge. In the context of Orange technology oriented towards human well-being and health care, this paper proposes fixing the data acquisition device terminals on different parts of the body of dancers, motion data during dance performances can be automatically collected. This data is sent to the server side for processing and then stored in the database, and the nine-axis dynamic data collected from various body parts is displayed on the Web page of the user side in time. By reviewing this data, dancers can be guided to improve their pose, helping them enhance their professional skills and experience a sense of satisfaction and happiness during the dance.

关键词： Training Performance evaluation Humanities Inertial sensors databases Web pages data collection Real-time systems Social implications of technology Servers

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：