Reviewerly/exHarmony huggingface dataset:
Design of Intelligent Fan System

With the introduction of the " low-carbon " life concept and the improvement of people's quality of life, the design of electric fans is developing in the direction of energy saving, intelligence and multi-function. Therefore, a relatively simple but practical fan is designed. A strong control system based on STM32F407VET6 multifunctional intelligent fan is necessary. The whole system is mainly composed of fan module, WiFi module, temperature and humidity module, power module, ultrasonic module and display module. The design and implementation of this system mainly center on the embedded system, and use the diversified control methods of external devices to make the fan's air supply angle and air supply speed controlled by the temperature and humidity sensor according to the change of the ambient temperature. In addition, for the system control of the fan, the system can control the start and stop, speed and timing of the fan either through the button mode or through the WiFi communication mode. Therefore, the fan system has the advantages of simple operation, low cost, simple structure and relatively intelligent, which makes the smart fan have a good development prospect.
Research on Online Game Design Based on Artificial Intelligence Algorithm

In today's online game, AI (artificial intelligence) has become a widely used technology. Because any game itself is a process of human-computer interaction, it more or less includes the use of AI. In this project, we try to combine the existing AI technology with online game design, and study a feasible online game design road based on AI algorithm. A decision-making model of game AI behavior is designed, and the proposed genetic SASarsa algorithm takes the value of exploration rate as the solution of chromosomes in the genetic process, and also represents the state in the annealing process. In the design of game AI engine, multithreading mechanism and the design pattern of producers and consumers are introduced, and the near-end strategy optimization algorithm is used to improve the search efficiency. Experiments show that reinforcement learning method can use the same reward function for similar intelligent agents, so as to achieve action decisions that conform to the game world view and set after training. It can complete the construction of game AI without reorganizing the decision structure, and improve the intelligence level of intelligent agents in the game.
Design an Efficient and Secure ECC-based Identity Authentication Scheme for Mesh Networks

Mesh networks, characterized by mesh topology and multi-hop connectivity, have emerged as a widely adopted solution for various wireless access networks. The self-organizing structure of mesh networks, which do not require a central node or infrastructure, endows them with flexibility, scalability, and robustness. However, mesh networks typically utilize wireless communication, which is more susceptible to public exposure compared to wired networks, making them prone to security threats and attacks. To address this issue, this paper proposes an identity authentication protocol for communication between distribution terminals and power consumers for mesh networks, aiming to ensure data security in distribution communication networks. The proposed solution in this paper has undergone security analysis and performance evaluation, demonstrating excellent security, efficient computational efficiency, and communication cost-effectiveness. It is capable of effectively mitigating attacks and safeguarding data confidentiality. Additionally, it exhibits high computational and communication efficiency according to the performance evaluation, making it suitable for serving distribution communication networks.
Investigating Data Encryption Technology's Use to Improve Security for Computer Network Communication

With the rapid development of information technology, computer network communication plays a crucial role in modern society. However, with the wide application of network communications, network security issues have become increasingly prominent. Risks such as information leakage and illegal access during data transmission pose a serious threat to the security of individuals, organisations and the state. Data encryption technology, as a key security safeguard, is widely used in network communications to protect the confidentiality and integrity of data. This study aims to explore the application of data encryption technology in computer network communication security. Through literature review and practical case analysis, we have discussed in depth the principle, classification and common algorithms of data encryption. Meanwhile, we explored the role of data encryption technology in network communication, including encryption of data transmission, authentication assurance and security key management. In addition, we also focus on the challenges facing data encryption techniques, such as performance loss and the rise of quantum computing. Finally, we emphasise the importance of strengthening the research and practice of data encryption technologies to address evolving cybersecurity threats. Taken together, data encryption technology plays an important role in securing computer network communications and provides strong support for building a secure and reliable network environment.
Consent Management System Based on User Data Security and Privacy Using Hyperledger Fabric Blockchain

The challenge of safeguarding user data privacy becomes pronounced when private data is outsourced to cloud services, potentially exposing it to unauthorized access. The challenge of centralized storage of user data introduces heightened security risks and a dependence on a single authority, posing difficulties in safeguarding against internal breaches. This study is dedicated to advancing user privacy and data security, especially in scenarios involving the sharing of sensitive information within or across organizations, including small enterprises functioning in a distributed environment. The research introduces a consent management framework built on Blockchain technology, with a particular focus on user consent management. This framework is designed to prioritize the principles of privacy, security, scalability, and data integrity. It utilizes Hyperledger Fabric which is a permissioned distributed ledger solution, and incorporates Hyperledger Composer to establish and maintain a secure record of user data. To enhance the security of stored data, the framework incorporates the Interplanetary File System (IPFS) and employs a unique cryptographic public key encryption algorithm for data encryption. The overarching aim of this research is to establish a robust security solutions foundation against cyber threats by harnessing the inherent capabilities of blockchain technology, ultimately strengthening the security landscape for sharing user information.
Handwritten Digital Image Recognition based on Fusion of Multiple Machine Vision Algorithms

Handwritten digit recognition technology is increasingly used in a wide range of fields, but the recognition rate still has room for further improvement. Currently, there are a large number of studies focusing on the use of activation functions to improve the handwritten digit recognition rate, compared with ReLU, Sigmod and other activation functions, this paper chooses to take the Mish activation function to optimise the handwritten digit recognition algorithm, using Pytorch machine learning framework, designed a deep convolutional neural network model based on the MNIST dataset to carry out digit recognition, and to improve the accuracy of model recognition through the learning of image features for digit classification to improve the model recognition accuracy. The experimental results show that the Mish activation function can increase the accuracy of handwritten digit recognition to 99%.
Simulation of Optimization Model of Power Professional Knowledge Retrieval Based on Improved Genetic Algorithm

The traditional retrieval method based on standard bibliographic database has limited the effective use of technical standards, resulting in low utilization of technical standards. In order to build the application of intelligent knowledge management of electric power professional technology and realize the knowledge retrieval and query of docking units, this paper puts forward an optimization model of electric power professional knowledge retrieval based on improved GA (Genetic Algorithm). In the process of electric power professional knowledge retrieval, GA is introduced, and the next search page is selected with the help of genetic operators. In the early stage of the algorithm, the fitness function value of individuals in the population is reduced to avoid the generation of super individuals and ensure the diversity of individuals in the population. The simulation results show that the improved GA can improve the efficiency of power professional knowledge retrieval, and the time consumption is 45ms less than that of the traditional GA-based power professional knowledge retrieval model. The power professional knowledge retrieval model based on improved GA can improve the accuracy of the search, which is 17.309% higher than that based on traditional GA. Provide technical support for preventing such power grid accidents in the future, improve the stability of power grid operation and enhance the management level of business personnel.
A Systematic Analysis of Data Diversity in Machine Learning for EDA

With the exponential growth of Very Large-Scale Integration (VLSI) scale and complexity, traditional algorithms of Electronic Design Automation (EDA) are gradually encountering bottlenecks. The successful application of Machine Learning (ML) in various fields has opened a new path for the development of EDA. The ML model has strong adaptability and generalization ability, which can discover patterns in complex circuit designs, make fast and accurate predictions, and effectively optimize with high quality. Data serves as an important link between ML algorithms and circuit design, and effective data features can improve the assistance of ML models to EDA. This article provides a summary of the front-end of circuit design and selects an ML based EDA application framework with typical data characteristics. It analyzes the data and features in each ML model, lists their predictions or optimizations based on algorithms, and proposes suggestions and considerations for the future development trend of this field. Academic research has demonstrated the enormous potential of ML in EDA applications. Future development requires the integration of stakeholders in the entire design and EDA ecosystem to bring future expansion benefits to the entire industry and society.
Optimal Design of Power Marketing Decision Support System Based on Power Big Data

As a new technical means, electric power big data analysis technology provides new ideas and methods for marketing decision-making of electric power enterprises. In this article, the problem of consumer propensity prediction in power marketing is studied, aiming at discussing the optimal design of power marketing decision support system (DSS) based on power big data, providing better marketing decision support for power enterprises and realizing sustainable development. The results show that the accuracy of this algorithm is over 94%, which is more than 10% higher than ID3 algorithm. And the recall has reached more than 85%, which is more than 8% higher than ID3 algorithm. The algorithm in this article has obvious advantages in forecasting the consumption tendency of consumers in power marketing. These advantages mainly come from the fact that the algorithm in this article considers more features, adopts more flexible and efficient methods for prediction, and uses regularization technology. These advantages enable this algorithm to predict consumers' consumption tendency more accurately and cover more potential consumers. Therefore, this method can provide more accurate and reliable basis for the marketing decision of power enterprises.
Research on Insulator Multispectral Image Registration Model Based on SuperPoint and SuperGlue

The accurate registration of insulator multispectral images is an important prerequisite for high-quality online evaluation of the status of transmission line insulators using multi-lens cameras carried by drones. An insulator multispectral image registration model based on SuperPoint feature point extraction algorithm and SuperGlue feature matching algorithm was constructed in this paper. Then, a multi-lens multispectral camera was used to collect multispectral image information of insulators from different angles, lighting conditions, and spectral bands, and comprehensive mutual information was introduced as an index to analyze and compare common traditional image registration models and the model constructed in this paper. Finally, a decision model for insulator multispectral image matching was constructed, providing a key prerequisite for evaluating insulator status using multispectral images.
Yoga Pose Classification Based on Transfer Learning of Vision Transformer

Yoga is gaining popularity for fitness and medical purposes due to its benefits in many aspects. However, inappropriate performance of yoga poses may have some disadvantageous effects. To help reduce inappropriate performance, the computer vision method, which is helpful in recognizing different types of yoga poses to provide suggestions and guidance, can be employed. In this work, a dataset was created by combining two existing datasets. Considering the relatively small scale of the dataset, transfer learning was used to perform yoga pose classification task. The Vision Transformer model was selected, fine-tuned, and evaluated for classifying yoga poses, reaching 92.61% accuracy and 92.62% F1 score. Compared with several typical CNN-based models of different scales, including GoogLeNet, ResNet, Inception, DenseNet, ShuffleNet, MobileNet, EfficientNet, the Vision Transformer had the best performance in every metric used in this work, including accuracy, precision, recall and F1 score, making it possible to be applied to real yoga pose classification tasks. Notably, due to the largest number of the parameters of Vision Transformer, reducing the parameters of Vision Transformer may be one of the research directions in the future.
Topic-Theoretic Extensions of Analytic Implication

Like many intensional logics, William Parry's logic of analytic implication PAI admits extensions determined by imposing semantic conditions on its account of modality. PAI is unique, however, in its allowing a second dimension—a topic-theoretic dimension—along which extensions can be defined. The recent introduction by Francesco Berto of topic-sensitive intentional modals (TSIMs)—which disagree with PAI on this type of condition—provide further motivations to examine such topic-theoretic extensions. In this paper, we introduce, motivate, and characterize a number of such extensions of PAI, paying special attention to applications to Berto's framework and to ways in which the modal and topic-theoretic dimensions influence one another.
Modern information technologies for holding a tournament for UralGUFC applicants

UralGUFC decided on the expediency of holding a large-scale weekend tournament (200 participants) among applicants in football, basketball, badminton and table tennis on a weekly basis. An online form of personal championship in team sports is proposed, while maintaining the number of parties, which allows you to announce an open competition for a place in the club, national youth teams, and hold a weekend tournament in UralGufc. An automatic competition system is being created based on the judges entering the results, processing and receiving ratings of participants, forming further schedules and SMS notifications for each of the participants. An online resource has been created http://personal-champ.ra-first.com/championships which allows you to generate a large number of personal championship micro-matches with the usual ratio of players (4 by 4, 5 by 5, 6 by 6, etc.) with an even distribution of all players, both partners and rivals. This allows you to see the difference created by the player during his stay on the field, arrange them in descending order of such a difference and, thereby, hold a competition among an arbitrarily large number of participants. Personal superiority excludes the subjectivity of the third assessment.
Intensification of education as a means of improving quality in the implementation of the general education discipline "Physics"

Relevance. One of the most significant areas of development of the secondary vocational education system today is to improve the quality of training of students. In recent years, the number of students of secondary vocational education studying the secondary general education program at colleges has increased significantly. As a result, there is a contradiction between the need to improve the quality of students' training and the intensification of training in the implementation of secondary general education within the framework of secondary vocational education. The purpose of the research. To analyze the normative documents for the implementation of general education disciplines in the system of secondary vocational education. Methods and organization of research. The analysis of the documents of the Yekaterinburg Institute of Physical Culture and the Sverdlovsk Regional Medical College of normative documents for the implementation of general education disciplines in the system of secondary vocational education was carried out. Conclusions. The problem of intensification of education in the implementation of secondary general education within the framework of secondary vocational education is quite relevant. At the moment, work is continuing to improve educational technologies in the implementation of the general education discipline "Physics.
From quarantine to in-person modality: Effects of the pandemic on music technology education and possible solutions for the loss of social interactivity

During the pandemic, educators in the music technology field faced challenges. One of these challenges is the loss of social interactivity. As classes return to in-person modality, effects of this loss are still greatly present within the classroom. This article observes possible solutions that educators may utilize to bring back social interactivity within the classrooms with the addition of incorporating technologies to create a crossfade between remote and in-person learning.
Exploring art schema and their relevance to DAW teaching and pedagogy: Examples of artistic practice in the field of music production

This article discusses my ongoing exploration of art schema and their potential role to develop Digital Audio Workstation (DAW) and music technology teaching. Arts practices have been noted by various researchers as potentially assisting creativity, DAW or otherwise. One useful advantage of this approach is advocating for more exploratory and materials based approaches for DAW learning and teaching. This is not necessarily under the banner experimental, but, instead, being different from a discrete set of engineering or technical decisions. For this article, I discuss Peter Osborne’s art schema and Keith Sawyer’s creativity framework to establish some principles, illustrated by six short artist examples. These are in a common practice context, sampling. The examples illustrate how these schema are broadly useful for technology teaching, and how they could be incorporated into current and future music production curricula.
The disconnected keyboard: Inclusive learning and musicking practice with modular synthesis

Since the 1960s, electronic sound synthesis and the keyboard interface have been so closely associated that many young musicians have come to see them as inseparable components, if not interchangeable terms. In this article, we ‘disconnect the keyboard’ and explore an alternative history of electronic sound synthesis – modular synthesis – that has remained largely overshadowed by keyboard-based synthesizers since the Minimoog. Researchers in music education signal that Eurocentric aesthetic norms, ableist performance ideals and exclusionary practices are interwoven in keyboard technologies, creating barriers that extend into popular music education. Drawing upon critical discussions in music education and science and technology studies (STS), we examine the underexplored opportunities of using modular synthesizers for music learning. We examine how modular synthesis, liberated from the keyboard-controller, serves as a basis for exploring an alternative model for sound-based inquiry and for rethinking the possibilities of instrument design and ways of musiking that are more inclusive.
Analysis of the Application of Regional Government Information Systems (SIPD) in the Budgeting Process at The Staffing and Human Resources Development Agency (BKPSDM) of Mataram City

Purpose: The purpose of this study is to determine the effectiveness of the Regional Government Information System (SIPD) in the budgeting process at the Personnel and Human Resources Development Agency (BKPSDM) of Mataram City and to find out whether there are obstacles and how to overcome them based on existing indicators in theory based on the Technology Acceptance Model (TAM).&#x0D; Design/Methodology/Approach: This research uses descriptive with a qualitative approach, with data collection techniques through interviews and validation through documentation.&#x0D; Findings: BKPSDM of Mataram City's implementation of SIPD in 2021 still has trouble, especially regarding recording the budgeting operations. So, they also use the previous system called SIMDA. However, in 2022, BKPSDM of Mataram City will use the SIPD complete system for its budgeting process.&#x0D; Implications/Originality/Value: The results of this study conclude that the implementation of SIPD in the existing budgeting process using the TAM model consists of five things: Perceived Usefulness, Perceived Ease of Use, Attitude Towards Behavior, Behavioral Intention and Behavior. From the existing indicators, only Behavioral Intention follows the TAM Model, meaning that the implementation of SIPD is not optimal according to the TAM Model theory.
Expert System for Diagnosing Dragon Fruit Plant Diseases Using Website-Based Purposive Sampling and Forward Chaining Methods

Objective: Purpose: This research aims to build a system that can make it easier for farmers to detect dragon fruit diseases presented in the form of a website. The system is used to be able to anticipate in overcoming a decrease in production or harvest levels.&#x0D; Methodology: The methodology used in this research is to take samples using the purposive sampling method can be used to make certain considerations. These considerations are based on samples obtained from experts on dragon fruit plant diseases. Then the samples were analyzed using the forward chaining method to obtain conclusions about disease diagnoses in dragon fruit plants using predetermined rules.&#x0D; Results: The results of this study are in the form of a website that can provide information about the disease and its symptoms to dragon fruit farmers. Using purposive sampling can increase the value of the accuracy of disease diagnosis.&#x0D; Implication: This study presents a system to make it easier for farmers to detect dragon fruit diseases. It is presented as a website so that farmers can easily access it. This paper provides a valuable reference for farmers and the public to analyze the diseases in dragon fruit plants easily.