<abstract>
<title style='display:none'>Abstract</title>
This topic takes Vue framework as the front-end framework of e-commerce middle office management system, uses springboot framework as the construction mode of back-end framework, and uses Java to write function code. [<xref ref-type="bibr" rid="j_ijanmc-2022-0014_ref_001">1</xref>] The data of the system is stored in MySQL database, which can be provided to the employee end of registered employees and the management end of managers. Employees can complete registration and login through the e-commerce middle office management system, and then view department information, store information Warehouse information and view order information and add, view commodity file information. The system administrator manages employee information, department information, store type information, store information, warehouse information, commodity file information and order information through the management end. Through the realization of the different functions of the above employees and administrators, the normal operation of the system is ensured, and the process involving stores, commodities and orders is monitored, So as to make a complete set of e-commerce middle office management system that can be provided to all kinds of users.
</abstract>

Commerce Middle Office Management System Based on Springboot

<abstract>
<title style='display:none'>Abstract</title>
With the rapid development of the Internet of Things science and technology, people′s living standards are gradually improving, and the requirements for the living environment are also getting higher and higher, which makes smart homes gradually enter thousands of households. The purpose of this project is to design a system that integrates hardware and software and can measure and transmit various data. Among them, the hardware part includes data measurement and data display. The data measurement module consists of DHT11 temperature and humidity sensor, DSM501 particle number sensor and MQ3 alcohol concentration sensor. The experimental data will be displayed on the TFTLCD screen. The system software is partly run on the Windows operating system, using the Python language development. This system takes ESP8266 module as the transfer station, realizes the communication between STM32 development board and computer. The experiment shows that the system has the advantages of high measurement data accuracy, fast data refresh speed, complete data transmission, simple design, high reliability, easy installation, economical and practical, and has certain practical value in life, production, industry and other fields.
</abstract>

Design and Implementation of Smart Home System Based on STM32 Microcomputer

<abstract>
<title style='display:none'>Abstract</title>
The main goal of this paper are equate behavior of the piston with and without different thermal coating layer on the piston head under thermal and mechanical loads that arise in the piston due to its operating. Three dimensional model of a piston heavy diesel engine has been presented. The governing equations have been discretized using a finite-volume method (FVM) and solved using multi-physics COMSOL package version 5. The results of the numerical model are showing the distribution of temperature, temperature gradients, Von-Mises stresses, and displacement in the diesel engine piston with and without 200 μm of thermal coating layer as (La2Zr 2O7) which have low thermal conductivity. The results show great improving in the performance of the piston with thermal coating layer.
</abstract>

Mechanical And Thermal Stresses Anylsis In Diesel Engine Poiston With And Without Different Thermal Coating Layer On Piston Head

<abstract><title style='display:none'>Abstract</title>In the national grid enterprise system, the geographical environment of transmission, substation lines and equipment distribution is very complicated. Transmission lines and substation equipment built in complex environments such as plateaus, forests, canyons and borders are often subjected to earthquakes, floods and blizzards. The threat of mudslide disasters, the ground communication network is greatly affected by extreme natural disasters, and it is impossible to repair and rescue in time when disasters occur. In response to the needs of facility operation and maintenance under emergency anomalies, Tiantong No. 1 satellite is a communication satellite with independent intellectual property rights in China. It has functions such as voice communication, image transmission, positioning, and data reporting. It can set up satellite Internet of Things to realize real-time monitoring and equipment. Conveniences such as inspections and emergency rescues reduce the operation and maintenance costs of the power transmission and transformation process.</abstract>

Internet of Things Application in Satellite Communication in Power Transmission, Transform and Distribution

<abstract>
<title style='display:none'>Abstract</title>
Technology is everyplace we go in moment's life. So, scholars of seminaries or sodalities, or universities bear an operation that supports smartphones to get all types of information related to examination, lecture notes, placement, systems regarding announcement, events, transportation, etc. Rather of calling systems because nearly all mobile druggies have smartphones currently. This being system takes a pupil list and allocates administrators to scholars. Using a manual system in the management and allocation of projects to students is characterized by many problems, including the Inability of the project Guide to know that a title has been approved already for a student. Difficulty and inappropriate documentation of allocated project topics. Ineffective in entering, updating, and retrieving records of allocated projects. Difficulty in accessing the project Guide for approval of the topic. Duplication in project topics approved for students. We designed an operation to attain the demand of scholars. The main ideal of the pupil design allocation system is to make a system that will give information for each pupil. Projects can efficiently be allocated to students without delay, and topic conflict between students in the same department will not arise here. Pupil updates can be fluently penetrated if the database system is enhanced. This design will give a fruitful way to manage data at a low cost. The Student Project Allocation contains colorful options similar as login/logout, viewing and streamlining data, etc. It'll be secure. Data can be used by only those with an id and word while maintaining the data.
</abstract>

Development of An Android-Based Visual Implementation of Student Project Allocation System

<abstract>
<title style='display:none'>Abstract</title>
With the rapid development of science and technology, it has brought about the improvement of human social productivity. It is very necessary to apply embedded technology to agriculture. Smart agriculture will gradually replace traditional agriculture, liberate productivity, and promote agricultural development more efficiently and intelligently. In recent years, intelligent agricultural greenhouse system has increasingly appeared in people's vision and played a great role in agriculture. At present, there are many intelligent agricultural greenhouse systems, but they have single function, relatively low integration and limited application environment. They are only suitable for large-scale cultivated land. Based on this, this paper designs and implements a more efficient and widely used intelligent agricultural greenhouse system, which plays a role in the development of agricultural greenhouse and better applies embedded technology to agricultural development. The system mainly completes three parts of functions: the first part uses the temperature and humidity module and light intensity module to display the collected temperature and humidity information and light intensity information on the screen through the STM32 single chip microcomputer FSMC interface, and upload these information to the terminal (upper computer) through the ESP8266 module for real-time viewing by the greenhouse owner. The second part is to automatically supplement the light source according to the change of light intensity through STM32 single chip microcomputer to promote the growth of crops in the greenhouse. The third part is to realize the function of monitoring and recording.
</abstract>

Design and Implementation of Intelligent Agricultural Greenhouse System

<abstract>
<title style='display:none'>Abstract</title>
In order to solve the problem of large positioning error and incomplete mapping of SLAM based on two-dimensional lidar in indoor environment, a multi-sensor fusion SLAM algorithm for indoor robots was proposed. Aiming at the mismatch problem of the traditional ICP algorithm in the front end of the lidar SLAM, the algorithm adopts the PL-ICP algorithm that is more suitable for the indoor environment, and uses the extended Kalman filter to fuse the wheel odometer and IMU to provide the initial motion estimation value. Then, during the mapping phase, the pseudo 2D laser data converted from the 3D point cloud data obtained by the depth camera is fused with the data obtained from the 2D lidar to compensate for the lack of vertical field of view in the 2D lidar mapping. The final experimental results show that the fusion odometer data has improved the positioning accuracy by at least 33% compared to a single wheeled odometer, providing a higher initial iteration value for the PL-ICP algorithm. At the same time, fusion mapping compensates for the shortcomings of a single two-dimensional lidar mapping, and constructs an environmental map with more complete environmental information.
</abstract>

Indoor Robot SLAM with Multi-Sensor Fusion

<abstract>
<title style='display:none'>Abstract</title>
In the context of rapid developments in drone technology, the significance of recognizing and detecting low-altitude unmanned aerial vehicles (UAVs) has grown. Although conventional algorithmic enhancements have increased the detection rate of low-altitude UAV targets, they tend to neglect the intricate nature and computational demands of the algorithms. This paper introduces ATD-YOLO, an enhanced target detection model based on the YOLOv5s architecture, aimed at tackling this issue. Firstly, a realistic low-altitude UAV dataset is fashioned by amalgamating various publicly available datasets. Secondly, a C3F module grounded in FasterNet, incorporating Partial Convolution (PConv), is introduced to decrease model parameters while upholding detection accuracy. Furthermore, the backbone network incorporates an Efficient Multi-Scale Attention (EMA) module to extract essential image information while filtering out irrelevant details, facilitating adaptive feature fusion. Additionally, the universal upsampling operator CARAFE (Content-aware reassembly of features) is utilized instead of nearest-neighbor upsampling. This enhancement boosts the performance of the feature pyramid network by expanding the receptive field for data feature fusion. Lastly, the Slim-Neck network is introduced to fine-tune the feature fusion network, thereby reducing the model’s floating-point calculations and parameters. Experimental findings demonstrate that the improved ATD-YOLO model achieves an accuracy of 92.8%, with a 31.4% decrease in parameters and a 28.7% decrease in floating-point calculations compared to the original model. The detection speed reaches 75.37 frames per second (FPS). These experiments affirm that the proposed enhancement method meets the deployment requirements for low computational power while maintaining high precision.
</abstract>

Lightweight Low-Altitude UAV Object Detection Based on Improved YOLOv5s

<abstract>
<title style='display:none'>Abstract</title>
This study introduced a novel energy enhancement approach for Wireless Sensor Networks (WSNs) by leveraging the shortest path transmission technique to minimize energy consumption and extend the network’s lifetime. Unlike traditional methods that heavily relied on cluster heads (CHs) for data transmission, our model proposed a non-cluster-based routing algorithm, utilizing Dijkstra’s algorithm to identify the most energy-efficient paths for data transmission. Simulation results, based on varying node densities (100, 200, and 300 nodes) within a 200x200 network area, demonstrated the effectiveness of our approach. Our findings indicated a significant reduction in energy consumption, with the network lifetime extending to approximately 100,000 rounds, surpassing traditional LEACH-based and other related protocols. This enhancement not only promised a sustainable WSN deployment but also offered a scalable solution adaptable to different network sizes and configurations.
</abstract>

A Modified Energy Enhancement in WSN Using the Shortest Path Transmission Technique

<abstract>
<title style='display:none'>Abstract</title>
Operating system (OS) security is paramount in ensuring the integrity, confidentiality, and availability of computer systems and data. This research manuscript presents a comprehensive investigation into the multifaceted domain of OS security, aiming to enhance understanding, identify challenges, and propose effective solutions. The research methodology integrates diverse approaches, including an extensive exploration for available knowledge process mechanics, empirical data collection, case studies investigations, experimental analysis, comparative studies, qualitative analysis, synthesis, and interpretation. Through various experimental perspectives, theoretical foundations, historical developments, and current trends in OS security are also explored. Empirical data collection involves gathering insights from publicly available reports, security advisories, case studies, and expert interviews to capture real-world perspectives and experiences. Case studies illustrate practical implications of security strategies, while experimental analysis evaluates the efficacy of security measures in controlled environments. Comparative studies and qualitative analysis provide insights into strengths, limitations, and emerging trends in OS security. The synthesis and interpretation of the findings offer actionable insights for improving OS security practices, policy recommendations, and providing towards future research directions. This research contributes to advancing knowledge in OS security and informs the development of effective strategies to safeguard computer systems against evolving threats and vulnerabilities.
</abstract>

Securing Operating Systems (OS): A Comprehensive Approach to Security with Best Practices and Techniques

<abstract>
<title style='display:none'>Abstract</title>
In order to meet the needs of military, road construction, multimedia industry and other aspects, UAVs are gradually given more functions. As the basic function of UAV applications, the fixed-point delivery problem model has higher and higher accuracy requirements. However, in the actual scene, the UAV delivery problem is affected by the interaction of various factors such as flight height, air resistance, and dive angle, which makes it difficult to achieve high stability and high hit accuracy. This paper will analyze the complex motion model based on the fixed-point delivery of explosives by UAV, study the relationship between the stability of UAV delivery and the hit accuracy, and analyze the influence of relevant parameters on the problem by using modeling. In this paper, a multivariate nonlinear continuous time change model is proposed, and a continuous time slice discretization idea operation model is introduced to approximate the time slice splitting inside the UAV launch motion. Secondly, the design quantified evaluation index reaction the initial velocity of the explosive, the launch Angle, the height off the ground and other parameters to analyze the model. Finally, the best scheduling strategy is obtained and verified by using the idea of variable traversal and trial- and-error simulation. The experimental results show that the variation of UAV flying height, speed, depression and other interference factors is consistent with the prediction of score and hit accuracy, according to the environment setting of this model, when the UAV is 300 meters above the ground and 290 meters away from the target horizontal position, the delivery speed is 250m/s, and the pitch angle is about 27°, the fixed-point delivery of explosives is the best strategy.
</abstract>

Research on Simulation Approximate Solution Strategy for Complex Kinematic Models

<abstract>
<title style='display:none'>Abstract</title>
Time-Sensitive Networking (TSN) occupies a vital position in modern communication domains, with the 802.1Qbv standard being an important network technology designed to meet real-time requirements. This standard requires network traffic to be transmitted within strict time windows, presenting challenges in network planning, necessitating efficient resource allocation and scheduling strategies. This paper addresses the 802.1Qbv planning problem through the introduction of reinforcement learning algorithms, offering an automated and intelligent solution. We have designed a reinforcement learning agent capable of perceiving network status, learning optimal resource allocation strategies, and dynamically adjusting in real-time environments. Through simulation and experimentation, we have validated the effectiveness of our proposed method, comparing it with traditional planning approaches. The contribution of this study lies in introducing a novel solution to the 802.1Qbv planning problem for time-sensitive networks, enhancing network resource utilization and performance. This approach offers strong support for the development and enhancement of TSN-like networks, holding significant importance for meeting the growing demands of real-time applications.
</abstract>

The Time-Sensitive Networking Scheduling Algorithm Based on Q-learning

<abstract><title style='display:none'>Abstract</title>Combined with the actual situation, this paper explores how to develop a crawler method based on the specific framework for the complete interface of steam manufacturers and stores, which should be able to automatically and efficiently crawl the data of specific targets, analyze the dynamic pages, and complete the data cleaning, downloading, saving and other operations, explore the methods of general data analysis, and Analyze the downloaded data, extract useful information from it, analyze and summarize the specific crawler method and data analysis method through practical application.</abstract>

Application Research of Crawler and Data Analysis Based on Python

<abstract><title style='display:none'>Abstract</title>3D point cloud segmentation is one of the key steps in point cloud processing, which is the technology and process of dividing the point cloud data set into several specific regions with unique properties and proposing interesting targets. It has important applications in medical image processing, industrial inspection, cultural relic’s identification and 3D visualization. Despite widespread use, point cloud segmentation still faces many challenges because of uneven sampling density, high redundancy, and lack explicit structure of point cloud data. The main goal of this paper is to analyse the most popular algorithms and methodologies to segment point clouds. To facilitate analysis and summary, according to the principle of segmentation we divide the 3D point cloud segmentation methods into edge-based methods, region-based methods, graph-based methods, model-based methods, and machine learning-based methods. Then analyze and discuss the advantages, disadvantages and application scenarios of these segmentation methods. For some algorithms the results of the segmentation and classification is shown. Finally, we outline the issues that need to be addressed and important future research directions.</abstract>

Review of 3D Point Cloud Data Segmentation Methods

<abstract>
<title style='display:none'>Abstract</title>
In this paper, genetic algorithm (GA) is used to optimally determine the architecture of a convolutional neural network (CNN) that is used to classify handwritten numbers. The CNN is a class of deep feed-forward network, which have seen major success in the field of visual image analysis. During training, a good CNN architecture is capable of extracting complex features from the given training data; however, at present, there is no standard way to determine the architecture of a CNN. Domain knowledge and human expertise are required in order to design a CNN architecture. Typically architectures, The GA determine the exact architecture of a CNN by evolving the various hyper parameters of the architecture for a given application. The proposed method was tested on the MNIST dataset. The results show that the genetic algorithm is capable of generating successful CNN architectures. The proposed method performs the entire process of architecture generation without any human intervention.
</abstract>

Designing Convolutional Neural Network Architecture Using Genetic Algorithms

<abstract>
<title style='display:none'>Abstract</title>
Group velocity superluminal phenomenon, also known as negative group delay or negative group velocity phenomenon, refers to a group of envelope signal at the output end of the medium before the input, in the time axis, is to leave the medium envelope appears before entering the medium, but this does not violate causality. Based on the waveguide theory of negative group delay, this paper uses the transfer function, amplitude response and phase shift response of the electronic circuit to control group velocity, and introduces three first-order bandpass amplifier RC circuits to control group velocity in low frequency band, which realize positive group delay, negative group delay and filtering functions respectively. Finally, the phenomenon of negative group delay is preliminarily realized by using circuit simulation software, which lays a foundation for subsequent research. As an envelope that can carry and transmit information, the study of negative group velocity is of great significance to the improvement of signal transmission efficiency.
</abstract>

A Circuit Principle and Simulation Test for Negative Group Delay

<abstract><title style='display:none'>Abstract</title>In order to implement the integration of the tool libraries from CATIA and the tool database, CATIA software was further developed using CAA. CAA macro-based integration project about the two libraries is proposed, and the development process is presented. In CAA environment provided by CATIA, though further developed using CAA, calling for information, converting information and valuating information of CATIA and TOOLMANAGER were researched. Finally, the dynamic calling, association and driving of CATIA-based tool information were implemented successfully.</abstract>

Research of Integration Technology between CATIA and TOOLMANAGER Based on CAA

<abstract><title style='display:none'>Abstract</title>In view of the fact that oil pumps exist in the more complex mountains and plains, external temperature, humidity, crude oil characteristics and other adverse factors make the oil pumps control system appear the problem of drift, Fuzzy neural network PID algorithm is studied and designed to realize controling the oil pump system in this paper, combined with the advantages of conventional PID control, fuzzy control and neural network control, the composition and structure of the oil pump control system are analyzed, the model structure and algorithm implementation of fuzzy neural network PID control algorithm are designed in detail. The simulation results show that the control algorithm has good adaptability and anti-interference ability.</abstract>

Research of Oil Pump Control Based On Fuzzy Neural Network PID 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...

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The International Journal of Advanced Network, Monitoring and Controls (ISSN:2470-8038）is aimed at providing a platform for researchers,...