Reviewerly/exHarmony huggingface dataset:
Two Factor Authentication using Hardware and Biometrics Factors for IoT Devices and Users

The sensors of the decentralized Internet of Things (IoT) architecture collect information from several places, such as vehicles, buildings, and electronic devices. A sensor may be found in a wide variety of things, and it analyses data, works with other embedded systems, and communicates with end consumers through a decentralized network. It is necessary to provide both final communication security and an authentication mechanism in a dispersed network in order to protect the integrity and veracity of the data being shared. Password-based authentication methods might be made more secure and the system protected from more dangers with the use of two-factor identification. One must also consider the computational and storage costs of an authentication method when designing an IoT application. Although this has led to the development of a number of novel cryptographic methods for use in the IoT, we've seen a paucity in both the availability of lab testing environments and hardware modules and the availability of generic identification hardware. With both the restricted computing capabilities and energy resources of node and indeed the system's architecture with consideration for scalability, this research proposes creating and analyzing a hardware device for the IoT that permits the use of 2 distinct network access using intelligent cards.
Unity3D Based on the Impact of Landscape Planning and Design Virtual and Realistic

In recent years, with the development and popularisation of 4G and 5G information technology, virtual technology has also ushered in a new year of development. In the past, the planning and design of landscaping mainly relied on CAD planar mapping technology, which made the mapping more accurate. Compared to traditional hand-drawing, this has been a huge step forward in the landscape design industry. However, this technology does not allow for both aesthetics. Unity3D-based landscape planning and design is both more accurate and more aesthetically pleasing. It also allows people to participate in the virtual environment and observe the landscape in detail, giving them an immersive experience. This paper will design a simulation runtime system based on the concepts and editors of the Unity3D engine technology, which will reflect the features and advantages of Unity3D by comparing it with other virtual mapping technologies. Finally, the effect of the use of Unity3D engine technology will be used to analyse the relevance of the technology in landscape design. In this paper, Sketch Up as the platform, using CAD software to model and produce the corresponding scene model, and then using Unity3D unreal engine to build a realistic three-dimensional landscape world, and finally realize the garden effect drawing function. Through comparative experiments, it is proved that the authenticity of landscape designed by Unity3D technology engine reaches 94.5%, while that of BIM and Open Scene Graph technology systems is 86.3% and 90.30% respectively. Therefore, the practical significance of Unity3D engine technology in landscape design.
An Innovation Development of Smart Robotic System for Autonomous Monitoring

Autonomous monitoring systems are becoming increasingly popular as they can be used to monitor a number of different processes and tasks, ranging from security and surveillance to industrial optimization. Smart robotic systems are one of the most popular types of autonomous monitoring systems and can provide an effective and efficient way to monitor different situations. A smart robotic system consists of a robot that is programmed and equipped with sensors to detect and recognize objects and conditions in its environment. The robot is able to analyze the data from the sensors and use it to make decisions based on its programming. This allows the robot to act autonomously and autonomously monitor different areas, depending on its programming. The advantages of using a smart robotic system for autonomous monitoring include increased accuracy, efficiency, and safety. For example, a smart robotic system can be used to monitor and control industrial processes, such as production lines and assembly lines. The sensors allow the robot to identify objects and conditions, such as temperature, humidity, and pressure, and then adjust the parameters accordingly. This can help to optimize the production process, resulting in a more efficient process.
Personalized Chinese Course Recommendation Model of Online Vocational Education Learning Platform based on Collaborative Filtering Algorithm

The current Chinese education system is mainly based on traditional teaching methods. Facts have proved that this method cannot meet the needs of students and their learning methods. In order to improve China's education system, it is necessary to find a new teaching method. One of the most effective methods is to use technology. Technology can help teachers and students interact more effectively, thus improving students' learning outcomes. This study aims to develop a personalized Chinese course recommendation model for online vocational education learning platform. In order to achieve this goal, the author uses collaborative filtering algorithm to analyze students' past experience and preferences to provide personalized Chinese courses. The study was conducted using data sets collected from actual case studies. This dataset contains information about students who have registered for online careers. First, we will use the KDD process to develop a problem statement and data collection plan. Secondly, we will use a priori method to analyze the data and build a database for further analysis. Third, we will apply different algorithms and use different methods to solve this problem.
The Smart Application Development in Real Time Parallel Applications with Industrial Automation

Real-time parallel applications with industrial automation are applications that are designed to run in parallel, in order to accomplish a task in a shorter amount of time. These applications are used in industrial environments to control machines and other processes in order to maximize efficiency and minimize waste. Real-time parallel applications allow machines and processes to be managed simultaneously. This means that instead of needing to wait for one process to finish before starting the next, multiple processes can be run at the same time. This increases the speed at which tasks can be completed, allowing for greater efficiency and productivity. Real-time parallel applications can be used to automate processes and machines. This means that instead of needing to manually manage and monitor a machine, the software can handle all of the work. This can help to reduce errors and improve the overall quality of the product being produced.
The Smart Optimization of Security Systems in Wireless Personal Sensor Networks

Wireless personal sensor networks (WPSNs) are an emerging technology that provides a platform for monitoring and collecting data from a variety of sources. These networks are used to monitor environmental, health, and even lifestyle factors. As the use of WPSNs continues to grow, it is important to consider the security implications of using these networks. WPSNs rely on a variety of technologies to ensure secure communication between devices. These include encryption, authentication, secure protocols, and secure key management. Encryption is used to protect data from being intercepted and decoded by an unauthorized user. Authentication is used to verify the personality of the user and the device attempting to access the WPSN. Secure protocols are used to ensure secure communication between the devices and the server. Finally, secure key management is used to manage and store the encryption keys used to protect the data. In addition to encryption, authentication, and secure protocols, WPSNs must also be designed with a robust access control system. Access control systems are used to limit access to the WPSN based on user credentials and other factors. This assist ensure that authorized users alone can access the data stored on the WPSN.
An Innovation Development of New Perspective of Efficient Approaches, Techniques and Challenges for Data Centers

Data centers are essential components of the modern digital world. They provide the necessary resources and infrastructure to enable access to online services and applications, enabling individuals and organizations to communicate, collaborate, and access information in real time. Data centers are an essential part of the internet and are used to manage and store data, providing access to a wide range of services. They provide organizations with the ability to store, access, and process data. Data centers are the backbone of the digital revolution, enabling organizations and individuals to connect with the world. Data centers are essential for providing secure access to data and resources. They are designed with security features such as firewalls, encryption, and authentication that protect data from unauthorized access. Data centers also provide advanced networking and storage solutions to ensure data is secure, reliable, and available for use. Data centers are also important for reducing operational costs. They provide the necessary resources and infrastructure to reduce hardware and software costs, as well as energy costs associated with running hardware and applications. This reduces the overall cost of doing business and allows organizations to focus on their core competencies.
Pharmaceutical Cold Chain Logistics Traceability System Based on Blockchain Technology

With the rapid development of China's pharmaceutical industry, higher requirements are put forward for drug quality, supply chain control and traceability system. Based on blockchain technology, this paper builds and runs a set of traceability database. The data storage adopts the combination of the Internet of Things and distributed sensing for collection, transmission, analysis and processing to form a new traceability information base. A perfect and stable and controllable mechanism has been established through the database to ensure a good circulation environment for drugs from the source to the terminal, and to ensure that consumers' requirements for effective and rapid tracking and feedback control of product quality and supply chain control during the use process have been fully reflected. After that, the performance of the system was tested in this paper. The test results showed that the blockchain technology-based pharmaceutical cold chain logistics system has a fast data transmission time and high system operation efficiency, which can show that the system can meet user needs.
The Development of Machine Learning innovation technology for Data Mining In Smart Healthcare

The field of Smart Healthcare has undergone a revolution due to the development of machine learning technologies. Artificial intelligence (AI) has a subfield called machine learning that allows computers to learn from data and develop over time without explicit programming. Healthcare workers can now discover trends, diagnose diseases, and make decisions based on more precise and timely data thanks to machine learning’s capacity to comprehend and analyze enormous amounts of data. Finding patterns and links in massive datasets is known as data mining. Data mining is used in Smart Healthcare to locate patterns in patient data that can be utilized to comprehend a patient’s health status better, diagnose specific disorders, and forecast the most effective course of therapy. Data mining can create novel cures and treatments customized to a person’s genetic profile. Data mining in Smart Healthcare is now considerably more effective and efficient, thanks to machine learning. Using complex algorithms, machine learning models can analyze vast amounts of data markedly faster and more correctly than conventional methods. Healthcare experts may not immediately notice hidden patterns and connections in data that machine learning algorithms can find. As a result, machine learning can assist healthcare practitioners in making decisions that are better informed, improving patient outcomes.
A Data Mining Algorithm for Optimization of the Path of Financial Management

In order to improve the accuracy of financial management and shorten the optimization time of management path, this paper proposes a data mining algorithm. Firstly, the big data theory is used to process financial management data, eliminate the irrelevant attributes of the data, and form a financial management collection. Then, use audit standards, risk thresholds, and optimization strategies to continuously optimize financial management data, and identify solvency and profitability. Finally, with reference to the financial indicators and optimization thresholds, the path optimization level is determined and the optimization plan is output. The simulation results show that the data mining algorithm proposed in this paper, under the guidance of big data theory, can improve the accuracy of financial risk management and shorten the optimization time, which is significantly better than the manual audit method . In addition, the optimization degree of data mining algorithm for financial management path is more than 40%, and the optimization time is less than 15 seconds, which is superior to previous path optimization methods.Therefore, the data mining algorithm can effectively select the path of financial management and meet the requirements of path optimization.
Integration of Computer Application Technology and Information Management of Cloud Computing Technology

Cloud computing is a new technology that utilizes the Internet to provide services to users. In the development process of cloud computing technology, the value of information integration is mainly achieved through the collection, collation, and processing of large amounts of data based on information and networks. In order to improve the integration effect of computer application technology and information management, this article explores cloud computing technology. This article mainly uses experimental testing and data comparison methods to test the information management system under cloud computing technology. The experimental data shows that when the number of users exceeds 400, the CPU utilization can reach a basic level, and the response time of its subsystem does not exceed 5 seconds. The main research achievement to meet the basic requirements is to obtain the concurrent user and CPU usage and usage conditions data table through experiments, and finally summarize the performance test results analysis and discussion.
Library Information Personalized Information Service Management System Based on Improved Genetic Algorithm

Library and information plays a more and more important role in social development. It is the most direct reflection of a country's development level and comprehensive national strength, and also opens up broad space for its future sustainable development. This article mainly aims at the library reader information management based on genetic algorithm and puts forward my own opinions. The system adopts B/S structure and MySQL database technology to realize the modular combination design of the system functions, and takes the library information management system as the core subsystem to develop a set of intelligent material dynamic web pages that are suitable for personalized demand analysis of books and have strong data integration and processing capabilities and are easy to maintain. After that, this paper uses simulation to test the function of the system's operation module. The test results show that the library and information personalized information service management system based on improved genetic algorithm operates normally, is compatible with the platform, and has a short running delay, which shows that the system can meet the needs of users.
An Innovative Solution for Data Persistence Problem in Reliable Data Transmission

Data persistence is a major problem in reliable data transmission. It is defined as the ability of data to remain the same even when it is sent over a network. Data persistence is essential for ensuring data integrity and accuracy. Without data persistence, data sent over a network could be corrupted, lost, or altered. Data persistence is especially important in distributed systems, where data may need to be stored across multiple nodes. To ensure that data is not lost or altered, systems must employ various methods to keep data persistent. These methods include replication, snapshot ting, and journaling. Replication involves maintaining multiple copies of data across multiple locations. This ensures that if one copy is corrupted, the other copies can be used to restore the data. Snapshot ting involves taking a "snapshot" of the data at a certain point in time. This allows for data to be restored to a certain point in time in the event of data corruption or loss. Journaling involves tracking every change in the data over time, allowing for the data to be restored to any point in time. Data persistence is an essential part of reliable data transmission. Without it, data sent over networks could be corrupted, lost, or altered. By employing methods such as replication, snapshot ting, and journaling, systems can ensure that data remains consistent and intact.
Multi-scenario Dynamic Path Planning Method for Multiple Construction Robots Based on A * Algorithm

Multiple scenes refer to the same building, different places, different time, or space with a certain number of location relationships and common characteristics or similar attributes. Each building has its own unique functions and characteristics. Therefore, in the process of construction, it is necessary to take into account the important impact of multiple target users (i.e., robots) on the whole system due to their interaction, interaction and other factors. This paper studies and designs the path of the robot based on the multi-scene dynamic planning method. We will implement the whole model based on the A * algorithm. Firstly, the kinematics equation and mathematical model of the robot are established, and then the optimized parameters are solved by MATLAB software and the optimal solution is obtained in the actual situation; At last, a multi-level fusion strategy is given, and the simulation results are analyzed to verify the performance indicators and operation effects of the scheme. The test results show that the A * algorithm can be used to dynamically plan the path, explore the navigation and create the matrix map. The final table mapping is a subset of the table mapping corresponding to the actual environment. Therefore, after defining different starting points, destinations and navigation paths, the information recorded by the matrix map will be closer to the real environment information, making the environment information of the mobile robot clearer, and providing reference and guidance for similar engineering applications in the future.
The Analysis of Multi Objective Reactive Power Optimization Based on Improved Particle Swarm Algorithm

This paper discusses the Multi-Objective Reactive Power Analysis of the improved particle swarm optimization algorithm, adjusts the transformation ratio of the on load regulating transformer, and changes the output measures of the reactive power compensation device, so that the system can achieve the optimization of multiple performance indicators under the premise of meeting the relevant constraints. The traditional particle swarm optimization algorithm has local extremum problem, and the optimization results are different from the actual results. In order to improve the limitations of particle swarm optimization, the simulated annealing algorithm is introduced to weight the PSO to improve the accuracy of calculation. The simulation results show that the improved particle swarm optimization algorithm optimizes the terminal voltage and reactive power compensation measures of reactive power target, and obtains a more effective power system optimization scheme. Therefore, the improved particle swarm optimization algorithm provides more accurate guidance for multi-objective non-function analysis, and adjusts the terminal voltage and power compensation measures of reactive power target.
Application of 5G Data-Oriented System Task Scheduling Algorithm in Community Public Sports Service Construction

Developing local public sports services is a crucial part of urban public services. It directly affects the quality of life of the people and plays an essential role in the development of sports construction. However, there are still many problems with the current public sports service system. Cloud computing is a paradigm of parallel and distributed computing. Critical features of Virtual Machines (VMs) include self-service provisioning, flexibility, and cloud computing while paying. This is because performing the tasks that a user has submitted through the Internet provides a different type of resource. The main task scheduling problem is load balancing, response time, resource utilization and memory. To resolve this problem, the Cuckoo Optimization-based Task Scheduling Algorithm (CO-TSA) is used to schedule the community public sports service construction details stores in the cloud, then the proposed allocate task into VM. The population and the operation, the setting calculation unit of the nest of the order relationship birds task of switching to another task in virtual machines. An efficient proposed CO-TSA scheduling algorithm may be implemented to improve the overall performance of different cloud environments.
The Smart Development of Multichip Communication Systems with The Help of Short Transmission Nodes

Multichip communication systems offer faster and more efficient data transmission and processing than single-chip systems. Multichip communication systems are made up of multiple chips that are interconnected and communicate with each other to carry out tasks more quickly. By using multiple chips, more complex operations can be completed faster and more efficiently than if done by a single processor. Multichip communication systems are used in many different industries, from automotive to aerospace to consumer electronics. Short transmission nodes are nodes that are used to transfer data from one network to another, usually over shorter distances. They are often used in the networking of computers, as they allow data to be sent more quickly and securely than over long distances. Short transmission nodes are also frequently used in wireless networks, where they provide a more reliable connection than longer distance nodes. In general, short transmission nodes are designed to be more efficient than longer distance nodes, allowing for faster data transfer speeds and more reliable connections. They are also often used for security purposes, as they are harder to intercept than signals passing over longer distances.