<abstract xmlns="http://www.w3.org/1999/xhtml">

Under the scenario of moving target tracking is very important in the fields of computer vision and research direction, its purpose is to give computer vision, double eye for simulation of the human visual information processing and information feedback process, in the process of the research can obtain the target trajectory information and provide related data for target tracking, The relevant research results of target tracking have been successfully developed in many fields such as human-computer interaction, security monitoring, intelligent monitoring and face recognition. However in the scene moving target vulnerable to disorder interference, light, shade, and scale complex situations, such as the change of the apparent dynamic change in the process of movement target, research can achieve different scenario stable tracking method has important research significance and engineering related events in the field of value, the existing popular nuclear-related filter tracking algorithm was improved, To solve the problem of occlusion and multi-scale change of tracking target, a new tracking algorithm based on multi-feature and multi-scale anti-occlusion is proposed by using kernel correlation filtering method.
</abstract>

School of Computer Science and Engineering

Target Tracking System Based on Dynamic Scene

<abstract xmlns="http://www.w3.org/1999/xhtml">

The needs of the chip are growing on a daily basis as extremely large size integrated circuits evolve fast. As a result, the network-on-chip (NoC) was suggested and successfully developed to address the issue of communication on-chip. Current research focuses on NoC topology and routing algorithms that have a substantial influence on network performance. Because low power is a priority, the Mesh-of-Tree (MoT) architecture is preferable. However, certain MoT routers may perform extensive communication activities, which means they consume more power and are more likely to become hotspots. To improve power consumption, we presented a Simpler Mesh-of-Tree (SMoT) architecture based on MoT in this study. We also suggested a path-wise routing scheme for the Internet of Things, which takes into account both network traffic and the shortest path between two points. By altering the direction of data forwarding to reduce network latency, our methodology spreads communication over the whole network. When compared to MoT, our suggested strategy can lower network power consumption by 5.39%–23.3% while also reducing network latency by 4.23%–27.28%.
</abstract>

A Path-Wise Scheme for Simpler Mesh-of-Tree Model in Network-on-Chip Designs

<abstract xmlns="http://www.w3.org/1999/xhtml">

Fault diagnosis IETM is a digital technical manual which integrates editing, management, display and publication and faces the field of fault diagnosis. In its development process, there are some problems such as complex data management and difficult interaction. The successful application of XML technology becomes the key to solve these problems. In this paper, based on S1000D IETM development standard, the main characteristics of XML and its related technologies are first introduced, and then the application of XML and its related technologies in fault diagnosis IETM is analyzed and studied, including the creation of fault information data module, the display control of fault information and the comprehensive management of data. A conversion method between XML document data and database data is proposed, and the design process of fault diagnosis IETM based on XML is discussed. Finally, a fault diagnosis IETM display system based on XML is preliminarily developed by combining the related technologies mentioned above. Experiments show that XML technology can effectively manage the information in fault diagnosis IETM and display it to users in an interactive way, which has important theoretical value and certain practical significance for developing fault diagnosis IETM and exploring the deeper application of XML in IETM.
</abstract>

Research on the Application of XML in Fault Diagnosis IETM

<abstract xmlns="http://www.w3.org/1999/xhtml">

The traditional rain removal algorithm needs to optimize a large number of parameters, and it is only effective for rain of a specific shape, and the model generalization ability is poor. In recent years, the performance of rain removal methods based on deep learning is better than many traditional methods, but there are problems such as incomplete or excessive rain removal, and incomplete texture reconstruction of background details. This paper proposes a rain removal network based on generative confrontation, which connects the high and low frequency parts and integrates them into the model. At the same time, the attention mechanism cyclic neural network is organically combined, which can better preserve the background texture while removing rain. Theoretical can produce better rain streak removal with better color distortion.
</abstract>

Research and Implementation of Image Rain Removal Based on Deep Learning

<abstract xmlns="http://www.w3.org/1999/xhtml">

After the completion of the process of industrialization in the world, a large number of electrified equipment appeared, people's daily life is also more and more dependent on electricity security, electricity consumption has risen sharply. At present, various lights driven by electricity play a crucial role in our daily life, which is also the main cause of electricity consumption. We often notice that even when the room is empty, or during the day, the lights are still on, which is a waste of electricity. The waste of power resources caused by traditional lighting equipment cannot be ignored. Therefore, intelligent home furnishing equipment is the favored object of people. So here for a kind of indoor lighting control system is designed, in order to meet the lighting needs on the basis of more humane, more importantly, can save power resources. With the rapid application of automation in daily life and the continuous development of computer technology, lighting control has become increasingly intelligent and automated. The control function of the system is realized by the STM32F103 chip, the illumination is automatically detected by the BH1750 module, and the time parameters are recorded and fed back by the DS3231 clock module. The infrared reflection sensor is used to detect whether there are people in the room. When there is no one, the light will be automatically turned off to save energy. If there are people, when the ambient light intensity is lower than the set value, the light will be automatically turned on to ensure the comfort of the ambient brightness. And can use OLED module real-time display indoor light intensity, number of people and working time. This indoor lighting control system can not only automatically turn on the light according to the environment, but also detect whether there is a human body in the current environment and turn on or off the light by itself, which has more practical significance.
</abstract>

Xi'an University of Posts and Telecommunications

School of Humanities and foreign languages

Design and Research of Indoor Lighting Control System Based on the STM32

<abstract xmlns="http://www.w3.org/1999/xhtml">

In the information age, with the continuous development of Internet technology, information data occupies every field of contemporary society. The development of the big data age makes these data more and more prominent. While users read the information they need from these massive data, data quality has also become a concern of users. A large number of data are preprocessed before data analysis, such as some duplicate values, missing values deal with inaccurate and other abnormal data, and filter the data through the data cleaning system to improve the standardization of the data, so as to improve the analysis efficiency of the data, reduce some unnecessary expenses, and save time and effort. The data cleaning system in this paper is implemented based on flash framework. Taking Python as the main language for data cleaning, technical cleaning and standard integration are carried out for some structural problems, duplication problems and missing problems of some different source data. Through the processing of abnormal data, the data quality and data analysis efficiency are greatly improved.
</abstract>

Research on Oil Well Data Cleaning System

<abstract xmlns="http://www.w3.org/1999/xhtml">

Because, the existing named entity recognition models lack the Specificity of the field, and most of their combine the prediction of entity Location and entity category, which results in the accumulation of errors. So, named entity recognition model based on multi-task learning and pointer network is proposed, and innovations are made in the task Construction and domain entity information utilization in the model of Named entity recognition. This model is based on Transformer with multi-Head attention mechanism, and decomposes traditional tasks in entity recognition tasks and entity classification tasks, and carries out multi-tasks Task learning to reduce the accumulation of errors between tasks. Model in this paper also uses the similarity calculation based on the Comprehensive description of the entity category in entity classification Task for better pertinence of the domain entity. Experiments are conducted on public datasets and domain datasets to prove the advancement of the Model.
</abstract>

A Named Entity Recognition Model Based on Multi-Task Learning and Cascading Pointer Network

<abstract xmlns="http://www.w3.org/1999/xhtml">

Using the giant parallelism of photons to develop a new type of computer with more processor bits and data, the ternary optical computer, with the birth of the ternary optical computer SD 16 physical machine, the team built a monitoring system structure for task management, It is mainly used to deal with various complex data problems and provide parallel services for computing requests of multiple users. The storage of data in the monitoring system has also become a crucial issue. Based on the existing achievements of the team, this paper designs a data storage scheme for the management software of the ternary optical computer monitoring system, and finally summarizes and looks forward to the next research direction of the ternary optical computer data storage.
</abstract>

A Datum Schemes Based on TOC Monitoring System

<abstract xmlns="http://www.w3.org/1999/xhtml">

Aiming at the problems of low object detection accuracy due to complex background and insufficient semantic information of shallow features in the object detection SSD algorithm, this paper improves the existing SSD algorithm. First, the original vgg16 network is replaced by the ResNet50 network, and the residual network structure as well as the Batch Normalization layer are added, which are used to improve the accuracy of the feature extraction network; Second, a feature fusion module is designed to fuse adjacent feature maps to improve the detection effect by integrating contextual information; Third, the SE attention mechanism is introduced to give channel weights adaptively and enhance the useful feature channels; Finally, the object detection analysis experiments are conducted on the PASCAL VOC2012 dataset. The experimental results show that the improved SSD algorithm in this paper is able to achieve an mean average precision of 72.7% in the data set, which is 2.1% better than the original SSD-VGG16 and greatly improves the object detection effect.
</abstract>

SSD Object Detection Algorithm Based on Feature Fusion and Channel Attention

<abstract xmlns="http://www.w3.org/1999/xhtml">

In the face of a large amount of news text information, how to make a reasonable classification of news text is a hot issue of modern scholars. To solve the problem that only word co-occurrence was considered in the Text Graph Convolutional Network (Text-GCN) method to build a graph model, a news text classification algorithm which fuses themes and is based on Graph Convolution Network, is presented. Firstly, the LDA topic model is used to process the corpus to obtain the distribution of themes of the corpus. Secondly, a graph model is built to construct a global map by using the related topic words and their subject distribution in each article. Finally, the text graph is input into the Graph Convolution Network layers to compute the learning representation of combining feature in order to complete the text classification task. The experimental results show that this method can effectively realize the word level interaction of information in text. In the experiment on Chinese and English datasets, adding theme information improves the accuracy by 1% compared with the Text-GCN method.
</abstract>

School of Computer Science and Technology

Research on Topic Fusion Graph Convolution Network News Text Classification Algorithm

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International Journal of Advanced Network, Monitoring and Controls

The International Journal of Advanced Network, Monitoring and Controls (ISSN:2470-8038）is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills, especially in the fields of advanced network, monitoring, sensors and controls. It is also the Journal's objective to promote engineering and technology education.  All papers submitted to the Journal will be blind peer-reviewed. Every paper is reviewed by two Professors and blind. All reviewers are independent of the editorial board. Only original articles will be published.  Open Access Policy  This journal provides immediate open access to its content under the Creative Commons CC BY-NC-ND 4.0 license on the principle that making research freely available to the public supports a greater global exchange of knowledge. Under the CC BY-NC-ND 4.0 license users are free to share the work (copy and redistribute the material in any medium or format), if the contribution is properly attributed and used for non-commercial purposes. The material published in the journal may not be altered or build upon.  Rejection rate: 50%  All submitted papers will be reviewed by more than two expert referees in their relevancy to the call for paper. After refereeing process, all accepted papers will be published and the full text is online available.   The acceptance process is as follows:   First of all, check the paper format and theme, and then entering the technical review process according to the quality standards.   The paper will be submitted to two reviewers for review according to the content of the paper; two blind reviewers will make comments and revisions to the paper, and then give an acceptance or rejection.   ABOUT SOCIETY  Xi'an Technological University has over 20,000 students and is authorized by Chinese government to award Ph.D. degrees. The State and Provincial Joint Engineering Laboratory of Advanced Network and Monitoring Control is located within the School of Computer Science and Engineering, Xi'an Technological University. The Lab.is mainly focused on researches in theoretical researches and practical applications of computing technologies, advanced networks, system simulations, artificial intelligence, automated monitoring and controls.  Archiving  Sciendo archives the contents of this journal in Portico - digital long-term preservation service of scholarly books, journals and collections.  Plagiarism Policy  The editorial board is participating in a growing community of Similarity Check System's users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process. 