Reviewerly/exHarmony huggingface dataset:
Anomaly Detection Algorithm of Cerebral Infarction CT Image Based on Data Mining

Anomaly detection is one of the important applications in the fields of image processing and pattern recognition. Through the use of image processing technology and machine learning algorithms to analyze the image, and check the variation of the graphics, that reduces the workload of manual data processing, but also solves the subjective difference between different operators, and because of its high sensitivity. The advantages of high detection rate, low false alarm rate, fast processing speed, and high precision have been increasingly used in different occasions such as medical image processing, and are expected to be widely used. This paper aims to study the abnormal detection algorithm of cerebral infarction CT images based on data mining. Based on the analysis of the characteristics of CT images, image segmentation technology and image abnormality detection algorithms, the algorithm is tested using 50 cerebral infarction CT images provided by a hospital. The test results show that the proposed algorithm has high accuracy in the abnormal detection of cerebral infarction CT images, which proves that the proposed algorithm has good generalization ability.
English Speech Recognition Hybrid Algorithm Based on BP Neural Network

At present, with the development of society and the progress of language teaching technology, the use of computer-assisted language learning has become an important way to solve this problem. This paper mainly studies the hybrid algorithm of English speech recognition (SR) based on BP neural network (BPNN). This paper first introduces the principle of BPNN, and analyzes the application of BPNN in SR. According to the requirements of English SR, the BPNN model is improved by optimizing the momentum factor and adjusting the adaptive rate. It can be seen from the simulation results that the recognition rate of IBPNN SR model proposed in this paper reaches 97.2%, which provides a new idea for the improvement and optimization of SR.
Rural Landscape Simulation System Based on Virtual Reality Technology

The traditional rural landscape expression method has limitations such as unintuitive expression effect, and the characteristics of virtual reality technology can just make up for these defects. The purpose of this paper is to study the design of rural landscape simulation system based on virtual reality technology. On the basis of understanding the limitations of traditional expression methods of rural landscape landscaping and the increasingly close integration of virtual reality technology with various industries, the virtual reality technology and rural landscape simulation are combined, and the virtual reality modeling tools that can be used for rural landscape simulation and The application platform conducts research and screening, and draws on the form of virtual roaming to propose the general process of applying virtual reality technology to rural landscape simulation. Through the production and comparison of experimental cases, the advantages and applications of virtual reality technology-assisted rural landscape simulation system design were discussed by means of questionnaires. The experimental results show that the respondents’ evaluation of the display effect of the rural landscape simulation system of virtual reality technology exceeds 4.3 points, and the respondents are satisfied with the effect of the rural landscape simulation system.
Shipping RDF Model Construction and Semantic Information Retrieval

In the era of big data, China’s shipping industry is developing rapidly, but the level of shipping information management is still at a low level, which becomes a hindering force for shipping industry to advance to a higher level. In order to solve this drawback, this paper combines the technology of semantic web and shipping information, constructs the shipping RDF semantic model and realizes the shipping semantic information retrieval to achieve the purpose of improving the efficiency of shipping information management.
Design and Development of Health Data Platform for Home-Based Elderly Care Based on AAL

China has entered an aging society gradually, and it is the country with the largest elderly population in the world. Now it is an aging society in China, which has the largest number of elderly people in the world. With the improvement of medical software and hardware facilities and the improvement of intelligent systems in China, many intelligent medical devices are approaching the life of the elderly, such as home blood glucose monitors, ambulatory blood pressure meters, etc. The elderly also gradually accept and widely use these smart devices and other mobile Internet products. This paper introduces the design and development of health data platform for home-based elderly care based on AAL, describes the technical architecture and core functions of the platform, so as to improve home-based elderly care through AAL technology, address the challenges of aging society, and enhance the happiness of elderly home-based elderly care.
The Application of VR Technology in Han Embroidery Digital Museum

Since With the development of the digital age, virtual reality technology tends to be mature and has been applied in many fields such as education, military affairs and cultural heritage protection. From the perspective of cultural confidence, this paper discusses the significance and application of virtual reality technology in the construction of digital museums, and takes the construction method of Han Embroidery digital museum, an intangible cultural heritage in Hubei Province, as an example to summarize the concrete steps of its construction.
Development of Ground Target Image Recognition System Based on Deep Learning Technology

Deep learning is a new and efficient learning method. It uses computers as information processing tools to effectively apply knowledge, experience and non-cognitive abilities, and obtain required information at different levels. Due to the complexity of ground information and the efficiency of deep learning, this paper proposes the development of a ground target recognition system based on deep learning technology. The purpose is to master the deep learning method and improve the accuracy of the recognition system. This article mainly uses experimental method and case analysis method to carry out correlation analysis and experiment on ground target image recognition technology. The experimental results show that the accuracy of the SAR algorithm of the ground target recognition system with mirror image reaches 92%, which is suitable for the research and development of the system.
Design of Decoration Construction Technology Management System Based on Intelligent Optimization Algorithm

Intelligent optimization algorithm is in the process of system operation, according to the actual situation, reasonable configuration of each parameter, in order to achieve the optimal goal. The management of decoration construction technology (DCT) is a complex, huge and tedious project. Therefore, applying the intelligent optimization algorithm to the design of the DCT management system can meet the needs of the system. To this end, this article uses experiments and examples to study the building DCT management system, and integrates related algorithms. Experimental results show that the data input response time of the system is 213 ms. The results of the performance test are mainly system requirements, and database access performance can be improved by adding data table indexes and stored procedures.
Certificateless Blind Proxy Signature Algorithm Based on PSS Standard Model

In recent years, the theory and technology of certificateless public key system are constantly enriched and developed, and the security and efficiency are further improved. Therefore, the research on proxy blind signature in certificateless public key cryptosystem can well meet the higher requirements of security and efficiency in the application of proxy blind signature. Therefore, this paper studies and analyzes the certificateless blind proxy signature(BPS) algorithm based on PSS standard model(SM), analyzes the formal definition and security model of certificateless standard signature protocol of PSS SM, discusses the specific process of certificateless proxy blind signature scheme, and proposes a certificateless BPS algorithm. Through security analysis and efficiency comparison analysis, the results show that the proposed scheme not only meets the security of proxy blind signature scheme, but also has high efficiency.
Monitoring Algorithm of Digital Power Grid Field Operation Target Based on Mixed Reality Technology

With the progress of society and the transformation of contradictions, people’s desire for a better life is getting stronger and stronger, and in the construction of society and life, the demand for electricity is also increasing. The digitization of the power grid makes the national grid closely connected, and the power supply is more stable and reliable. The purpose of this paper is to study the target monitoring algorithm of digital power grid field operation based on mixed reality technology. Firstly, the composition of virtual reality technology and the combination of three-dimensional GIS technology and smart grid are studied. Secondly, the design of the interactive technology in the digital power grid field operation target monitoring system is introduced. The interaction technology includes the design of speech recognition technology and gesture recognition technology. Finally, the key algorithm of this paper is introduced. The target monitoring experiment in three-dimensional space is carried out based on the visual target monitoring technology, which proves that the algorithm in this paper can be applied to the real experimental scene and has a good recognition rate and real-time performance.
An AIS Trusted Requirements Model for Cloud Accounting Based on Complex Network

Trusted demand model is the primary method of cloud accounting audit, and in a complex network environment, it is easy to have the problem of inaccurate demand analysis, which reduces the accuracy of cloud accounting audit and even occurs in mistakes. So it aims at the problems of inaccurate accounting audit analysis and the inability of traditional audit methods to carry out credible demand models effectively. This paper proposes an AIS trusted demand model to comprehensively analyze cloud accounting, comprehensively identify accounting audit data, and shorten the time. Then conduct a credible requirements analysis for exception audits and violation audits. Finally, leverage online audit data and output trusted requirements results. MATLAB shows that the AIS trusted requirements model could accurately perform accounting audits, with an audit error rate of less than 10% and an audit accuracy rate of more than 90%, which is better than traditional auditing methods. Therefore, the AIS trusted requirements model can meet the requirements of cloud accounting and is suitable for accounting auditing.
The Temperature and Humidity Measurement for the Rooftop Type of Solar Power Plant Development Planning at the Building of Universitas Ichsan Gorontalo

Solar Power Plants can be a solution for future electricity needs in increasing Indonesia's environmentally friendly economy.It can save electricity costs more significantly than fossil energy sources such as coal.It is a profitable investment as Solar Power Plant is proven more environmentally friendly for not causing much pollution.It even helps increase electrical energy capacity.It is very strategic in supporting the direction of leading industrial cluster development in the Sulawesi region, particularly in helping overcome the electricity crisis in Gorontalo City.The Gorontalo City Government must continue to make various efforts to be energy independent in building investment in Gorontalo City.The research sample was the trial results of Internet of Things (IoT)-based monitoring instruments for measuring temperature and humidity.The results of observations on the testing of the instruments illustrated that the difference graph at high humidity with hot air conditions indicated the production of electrical energy on the solar panels.Another condition was the humidity due to weather factors was high.It was covered by clouds above the instruments set up on the building of Universitas Ichsan Gorontalo.The measurement results proved that the roof of the building of Universitas Ichsan Gorontalo is a potential area for the rooftop construction of the Solar Power Plant.Its building roof is uniquely curved with varying slopes.No other buildings share the same large area for an evenly distributed temperature around Universitas Ichsan Gorontalo in Gorontalo city.
A Design for Block Chain Service Platform

In this paper, a designing for blockchain service platform is applicable to enterprises, a decentralized, distributed, tamper-proof, and traceable trusted data recording technology platform can be constructed for supporting innovative business models with multi-subject participation that can be used in a weak credit environment. The platform that supports multi-subject participation is able to store data from different businesses, uniformly, on the blockchain. The data on the chain can be queried when extraction and verification are required. After setting the design objects, the business requirements and functional requirements are analysed as the base for design. The design scheme is conclude access management, operation management and system management totally 4 modules. The key technologies is about data uploading. The usage of computing resource in IaaS is measured as floating-point operations per second (FLOPS) when they are running as the catagery in load balance, database, cache for database, message queue, object storage, application for block chain, node for block chain, etc.
Development of a Public Engagement Scenario in Metaverse Toward Maintaining the Sustainability of Valuable Historic Buildings in the Kayutangan Area, Malang, Indonesia

The development of immersive spatial multimedia in Metaverse Urban Historical is the latest innovation that encourages the development of Smart Governance in historic area management.This innovation carries the concept of sustainable business and tourism (green e-commerce), leading to various tourism business developments in digital innovation and supporting the green economy concept.The Metaverse technology supports asset management and historical buildings to support the historical tourism industry in Malang.This research aims to develop the Semesta Digital application (Metaverse) by creating an immersive digital experience that builds an exciting and interactive public engagement concept.This study examines the history of the Kayutangan street corridor, the first trade and service corridor built in the Dutch colonial era and gave birth to three crucial developments in Dutch East Indies architecture in Malang.The development of Metaverse in the Kayutangan street corridor aims to create historical tourism management that accommodates the wider community to enjoy an immersive digital experience by accessing and having a dialogue with the visual-spatial information of the historic area.This study results in a conceptual framework for the metaverse prototype on the Kayutangan street corridor, which focuses on four public engagement strategies, namely virtual purchases in building interiors, changing the appearance of making colors, the passage of time for historic buildings, and replacement of new buildings.The system development integrates a heuristic and features evaluation that examines aspects of the use and user experience related to user convenience and the responsiveness of user commands and describes the quality of the graphics, presence, interaction, environment, control, and hardware in the Metaverse world.
Design and Application of Personalized Recommendation Module for English Writing Marking System Based on Theme Model

Topic model is a common personalized recommendation model, which is suitable for the design of personalized recommendation module of English writing marking system. Therefore, this paper will study the design and application of this module. This paper first introduces the basic concept of the topic model, and then proposes a personalized recommendation module design method based on the English writing marking system. Through the research, the personalized recommendation module design module can be realized in the English writing marking system by using the theme model. The module can understand the personalized needs of students’ writing according to the marking results and push relevant materials to them with good accuracy.
Application of Embedded Computer Digital Simulation Technology in Landscape Environment Design

With the development of social economy and the acceleration of urbanization, people pay more attention to the harmony and beauty of Landscape environment (LE) design, and are committed to building an environment in which people live in harmony with nature, so that people, life, environment and nature form a harmonious and beautiful organic whole. As an independent design subject, environmental design plays an important role in promoting the level and superiority of decoration design. At the same time, in recent years, people have added more landscape elements to environmental design to create a green, ecological and environmental. Landscape element is an innovative design mode integrating natural landscape and human landscape. Its application in environmental design contributes to improving and enriching people's quality of life and LE. Extracting the elements that can be used for reference in landscape design from the traditional environment, natural elements: the commonalities between elements and landscape design, and highlighting the natural culture needed in the application of LE design, are crucial to the formation of a design road with the characteristics of the times. On the other hand, we should dare to break through the shackles of traditional concepts to design more new landscape phenomena. It seems that the practical value of LEal works is not only to beautify the living environment on which we live, but also to extract the beautiful elements of nature and humanistic art, bringing more spiritual experience to modern people. Based on this, in the future landscape design, environmental designers should fundamentally improve the importance of natural beauty and harmonious beauty, and rationally apply and innovate the LE on the basis of not damaging the ecological environment. This paper briefly analyzes and explores the application of LEal design.
Unsupervised Data Anomaly Detection Based on Graph Neural Network

The anomaly detection algorithm proposed in this paper uses deep learning to realize automatic equipment abnormality monitoring in view of the time-consuming and laborious problem of manual equipment abnormality monitoring in converter station scenarios. Although the overall performance of supervised learning is better than unsupervised learning at this stage, supervised learning faces problems such as difficulty in labeling massive data and deteriorating performance of pre-trained models in actual scenarios. Therefore, this paper proposes an anomaly detection system based on graph neural network, which not only focuses on visual features but also introduces attribute features to extract deep features of monitoring data. The algorithm first extracts attribute features from the data and constructs a graph neural network through attributes. In the iterative process, the graph neural network mines data information from two dimensions, visual and attribute, and solves the problem of performance degradation caused by the difference between the data of the source domain and the target domain. The model pre-trained in the source domain can be applied to the target scenario and maintain the original anomaly detection capability.
A High Resolution Wavelet Chaos Algorithm for Optimization of Image Separation Processing in Graphic Design

Image separation is the key to image processing, but in image separation, it is easily disturbed by abnormal signals, which reduces the separation accuracy, and causes key image loss and blurred separation edges. Based on this, this paper proposes a high-resolution wavelet chaos algorithm to perform high-frequency resolution of image separation information, enhance image signal, and shorten pixel distance. Grayscale value analysis is then performed on pixel gradients and neighborhoods. Finally, the standard wavelet algorithm separates the edge signals for search, and the final separation results are output. The results show that the high-resolution wavelet chaos algorithm can accurately separate images, the abnormal signal interference rate is less than 10%, and the separation accuracy is greater than 90%, which is better than the standard wavelet algorithm. Therefore, the high-resolution wavelet chaos algorithm can meet the requirements of image separation and is suitable for image processing.
Data Interaction of Scheduling Duty Log Based on B/S Structure and Speech Recognition

In daily work, it is often necessary to carry out tedious business scheduling and statistical work. Through the scheduling duty log system developed based on the B/S structure, the functions of overall import, partial modification and historical query of duty information can be realized, and the statisticians will be liberated from the complicated work, thereby improving the office efficiency of the staff and scheduling. The core technology of these functions of the duty log system is the interactive acquisition of data. In this regard, this paper introduces voice recognition technology in the design of the dispatch log system. With the support of this technology, the on-duty personnel only need to input voice commands to realize log information modification, query and other functions, which greatly facilitates the log management of the on-duty personnel.
Understanding the Effect of Cohesion in Academic Writing Clarity Using Education Data Science

Presenting complex information in a clear and concise manner in an academic paper is often considered a daunting task for many students. In particular, writing an abstract that could effectively convey the highlights of research findings is important to capture the reviewers’ attention. While cohesion has been considered a critical feature for supporting comprehension in academic papers, a recent study has introduced a possible reverse effect that depends on reader knowledge. The purpose of the present study is to explore the effect of text cohesion on writing clarity using the data science methods of text mining and a hybrid classifier that employs fuzzy reasoning to consider a broader range of potential labels. We focused on using educational data science to automatically detect and investigate how referential cohesion features affect writing clarity in the abstracts of academic papers. We introduce a neuro-fuzzy approach to investigate these effects. Referential cohesion features were extracted from the abstract of 224 research articles using Coh-Metrix. We used these features to predict writing clarity scores. Accurate classification results, above 70%, were achieved using the hybrid neuro-fuzzy inference system. Subsequent analyses indicated that text cohesion features negatively impacted writing clarity for peer reviewers.