Distributed data collection systems are often used in many fields, such as industrial control, power systems, seismic monitoring, and ocean exploration. In a distributed data collection system, the time of data collection and the efficiency of data collection are all related to the accuracy of the data. Subsequent analysis and processing show that the distributed data collection system is a very important performance indicator: this article combines the timing factors of the timing rules in the dataset, and after normalization and expansion, the rules will be edited according to the effective voting rate. Perform a weighted sum calculation on the rules in the edited sub-database to obtain the final timing rules. Finally, the algorithm is implemented by pseudo code. With the rapid development of information technology, we have entered the era of big data. Big data has the characteristics of resource sharing, large storage capacity, and high speed, so it has been widely used in various fields. In the context of the rapid development of the modern economy, the human resources department has provided a relatively complete infrastructure system for many large companies. It can be seen that the work of the personnel department is gradually becoming an important factor in the development of the company. Appropriate implementation of big data in the company’s human resource model can integrate resources into the industry and the company, improving operational efficiency, and laying a solid foundation for the company’s sustainable and long-term development. This article first outlines the hardware system and company management of temporal big data in a distributed environment, discusses in detail the needs of human resource management in companies in the era of big data, and proposes a suitable human resource management model.

Most movie recommendation methods use hard-clustering and simple collaborative filtering techniques in order to achieve their end results. However, these methods tend to overlook crucial aspects of both users and items. When these methods hard cluster a movie item into a cluster, they turn a blind eye to the fact that the item also exhibits some properties of another cluster’s items. Recommender systems facilitate users and relevant things expeditiously supported their requests and historic communications with alternative customers. Recommendation systems are a crucial portion of signifying things particularly in streaming amenities. For streaming motion-picture show services like Netflix, recommendation methods are vital for serving to users notice fresh movies to get pleasure from. However, massive amounts of information will turn out restrictions in recommendations due to accuracy as a result of diversity and meagerness problems. Our work proposes a unique hybrid technique that mixes collaborative filtering and characteristics of demographic filtering technique to point the close users, and associate against one another. This technique has been established over associate in tending analysis of the way to cut back the blunders in grading estimates supported users’ earlier communications that ends up in improved prediction accuracy in among completely different algorithms. Additionally, a feature combination technique is utilized that progresses the expectation accuracy and to check our method, using MovieLens 1M dataset, we contended an offline assessment, already available assessment tactics, and compared the same with the output factors to support authenticating the proposed procedure.

This article discusses methods of abnormal audio detection. Extract audio information from audio acquisition hardware, convert analog signals into digital signals, perform pre-focused audio processing on digital signals, and compare and analyze audio noise reduction algorithms, such as wave noise reduction, homomorphic filtering, and Wiener filtering. After noise reduction processing is performed on the audio data, endpoint detection is performed on the continuous noise reduction frequency data, and the actual audio segment is separated from the continuous audio signal. Consistent with this, the blockchain-based IoT data service reputation evaluation model designed and implemented in this paper can support the data service reputation evaluation requirements. Users can upload IoT data sources to the platform or retrieve data from the platform, and research the data based on reputation or data provider analysis. The interaction with the data authority is realized through access control based on permissions. Finally, according to the latest requirements of the national sports team, based on the research foundation of the “athlete military division,” a new visual word model is used to explain the research on the image discrimination of athletes’ movements, and introduces the athletes’ movements, including traditional word models and automatic algorithms, and then introduces the research content and research methods to improve the traditional new visual word model to adapt to the characteristics of athletes. This algorithm minimizes the impact of short recognition rate and slow recognition rate, the latter causing problems such as the background similarity of the athlete’s image and the difference between the athlete’s actions. By understanding the available modules in the athlete’s motion recognition system, the prototype design of the basic functions and the athlete’s video system was completed.

Speech recognition has become a necessary feature of high-quality service industry products. Therefore, the accuracy and efficiency of speech recognition are the key to product applications. At the same time, this article also designs various modular functions for speech recognition. In order to solve the problem of poor recognition performance when the existing convolutional neural network recognizes continuous speech data, we provide an improved convolutional neural network algorithm and backpropagation algorithm to reduce the weight range. In a real speech recognition system, due to the large amount of training data and model parameter training efficiency of the convolutional neural network is very low. Vocational education reform is an important way to realize modern education, and it is also an effective way to improve students’ comprehensive quality and promote personal development. According to the analysis of the current teaching situation in higher vocational colleges, the effect of vocational education reform has not reached the expected standard. This has led to a decrease in the teaching efficiency of higher vocational colleges, coupled with the increasingly fierce competition in modern society, the reform of higher vocational education has become the top priority of the education department and the school. In order to improve the scientific nature of vocational education reform research, it is necessary to strengthen the research on current and future development trends. The research scope of vocational education reform needs to be coordinated, integrated, and expanded. To strengthen research on the integration of industry and academia, it is necessary to establish a team of experts. The cross-border characteristics of vocational education are reflected in the integration of production and education to a large extent. This article will explore how to realize the reform of vocational education in higher vocational colleges based on the improved convolutional neural network and speech recognition.

In embedded systems, embedded database systems are widely used as carriers for storing, managing, and accessing data. In internal database applications, the data associated with the system may be available in different database systems in different locations. How to determine the exchange of data and the consistency of the data and how to verify the integrity of these databases have become increasingly prominent issues in the development of systems and applications. The embedded database distribution system is an integral part of the embedded database system. Distributed database is an organic combination of computer network and database system. The rapid development of communication and network technology has promoted the development of distributed databases, but at the same time, it has also increased the complexity of the security issues of distributed databases. How to effectively ensure the security of distributed databases is a key issue that needs to be solved urgently in distributed database applications. On this basis, it also analyzes relevant data and conducts research. This article introduces the embryonic form of children’s mental health education—the development of PCT services—and focuses on the development of current mobile resources and terminal children’s mental health education. Implementing the mental health education application program, after recognizing the needs of children, we designed a mental health education platform based on the promotion of information dissemination through the use of ubiquitous learning theories and integration of current learning trends. Use the now popular micro-communication method to be embedded in the system, thereby increasing the usability of the system. The application of wireless local area network improves the comfort of platform applications and provides users with a variety of communication methods, accompanied by strong security and practical services.