Reviewerly/exHarmony huggingface dataset:
Research on Key Technologies of Dynamic Maintenance of Urban and Rural Planning Data Based on Mobile GIS

Urban and rural planning data related to urban and rural development and internal management must keep pace with the times. It is an important work in data maintenance requirements. Therefore, in order to help to do a good job of data maintenance and data dynamic maintenance, this article is based on mobile GIS technology study, introduces the basic concept of mobile GIS and data dynamic maintenance, and then, around the mobile GIS, the key technologies are analyzed.
Construction of Financial Early Warning System Based on Binary Time Series Algorithm

It needs to establish a financial crisis early warning system that can be analyzed based on past data. Building a financial crisis early warning system based on binary time series algorithm is one of the methods to detect financial crisis. The main goal of this project is to design and implement an efficient financial early warning system based on binary time series algorithm. The research of government officials and investors will help prevent the occurrence of economic crisis.
Proof-of-Concept (PoC) Biometric-Based Decentralized Digital Identifiers

This article describes decentralized digital identifiers based on proof-of-concept (PoC) biometrics and the application-level implementation of these identifiers for user authentication through blockchain with a smart contract. To establish PoC, user credentials are calculated from the biometric data of the user’s own face, which is cryptographically encrypted (PKI-less infrastructure), stored, and decrypted when necessary at both on-chain and off-chain level. Data recording, storage, and access at the on-chain level are provided by smart-contract functions.
Electronic Book About Information of Higher Education for Career Guidance Services in Senior High School: Is It Practically?

High Scool graduates are prepared to continue their studies to higher education.Before high school students choose to continue in higher education, ideally they need to understand information about higher education.Awareness of information about higher education becomes an important aspect for students in planning their career development.The purpose of this study was to describe the practicality of the electronic book about information of higher education on career guidance services in high school.The results of the study will facilitate guidance and counseling teachers in providing career guidance services to high school students.This study was used for research and development (RnD).The model used is the ADDIE model which includes analysis, design, development, implementation, and evaluation.Data collection in this study used a practicality test instrument by the guidance and counseling teacher and followed by a focus group discussion (FGD).The results of the practicality test, this electronic book are included in the very practical category with a total score of 163 and the average percentage obtained from the practicality test by guidance and counseling teacher is 81.5%.Based on the results of the practicality test, the electronic book about information of higher education on career guidance services in high school is very practical and suitable for use without revision.
Design and Implementation of Distributed Web Crawler for Knowledge Entity

At present, with the leap development of big data science and technology, people have more and more demands for information on the Internet in their life and work. The importance of search engine technology is becoming more and more obvious, and a very important technology in the network search engine is web crawler, for the performance of the previous stand-alone crawler has been difficult to meet the rapid development of the explosive growth of Internet data, distributed web crawler to solve this dilemma. According to the characteristics in this paper, with the advantages of distributed system algorithm was improved and the relation between knowledge and based on the realization of the distributed web crawler system, the function and performance of the crawler system is stable, extensibility, also can with the change of the deployed number of nodes and has a good scalability, reached a stable and scalability of distributed crawler system target. The distributed search engine is supported, and the system solves the problems of slow crawler speed and low efficiency.
Research on Statistical Machine Translation of Bilingual Resources Lacking Language Pairs Based on Active Learning

The research on machine translation for bilingual resources and lack of language pairs is a hot and difficult issue in the field of machine translation. Based on the research background of statistical machine translation with language pairs lacking in resources, this paper uses active learning strategy to design an effective sentence selection algorithm rich in information, obtain high-quality bilingual data from large-scale monolingual corpus, and give full play to the maximum efficiency of limited bilingual data, so as to significantly improve the performance of statistical machine translation for language pairs lacking in bilingual resources. This is a research project aimed at developing statistical machine translation of bilingual resources lacking language pairs. The main idea of this study is to use active learning technology to improve the quality of translation, so as to increase the number of available translations of each resource. In other words, by using active learning methods, it will be possible to translate more languages into more accurate fields. The main benefit of this research project is that it will provide many new resources and languages that were previously inaccessible due to the lack of language pairs.
Using SHAP-Based Interpretability to Understand Risk of Job Changing

We propose a possible solution to the socio-economic problem of understanding the decision of Data Scientists to early change or leave their job. This problem is mainly relevant from a Human Resource perspective, to better understand the factors leading persons working on a Data Science position to change their job in the short term. We consider two Machine Learning prediction models based on Decision Tree and Logistic Regression. For each model we study the importance of the involved features using a Cooperative Game Theory approach based on Shapely value. The experiments were done using a public domain dataset from Kaggle.
Product Design System of 3D Image Experience for the Elderly with Multi-dimensional Perception of Users

With the support of the current mature system of 3D technology, the visual experience of 3D image experience products has appeared in more and more industries, and 3D experience technology has even become an indispensable part of life. It can be seen that 3D image experience product technology is the main trend in the current visual sensory field. As the elderly are a special group in society, the research on the use of 3D products by the elderly is still worthy of attention. This paper analyzes the user's multi-dimensional perception and designs a 3D image experience product design system for the hobbies of the elderly. The product design system studied in this paper is mainly aimed at the elderly user group, and the related content is set according to the collected hobbies of the elderly, so as to improve the product satisfaction of the elderly users. The final results of the research show that 58 people choose financial management, accounting for 28%, and the family chooses the most, with 66 people, accounting for 33%. It can be seen that the 3D image experience product design system for the elderly should start from financial management and family content. The reason is that because the elderly lack care, they pay more attention to their families, and with the improvement of living conditions, many elderly people hope to help themselves create wealth through wealth management products.
Clothing Image Recognition and Classification Based on Deep Learning

With the development of the Internet of Things, big data, artificial intelligence, the rapid economic growth and the improvement of human living standards, in the field of intelligent image recognition, the application research based on clothing recognition and classification has received more and more attention. The purpose of this paper is to study clothing image recognition and classification based on deep learning. The convolutional neural network and residual network are introduced, and the clothing image dataset used in this paper is introduced and explained in detail. Three different convolutional neural networks based on single-task learning are designed for the obtained clothing dataset, these networks are: conventional convolutional neural network, convolutional neural network including Inception module, Inception module and residual module Convolutional Neural Networks. The experimental results show that the performance of the third convolutional neural network model is better, and the training time is only 21 h, and it can achieve better classification results.
Student Management Information Security System Based on Artificial Intelligence and Cloud Computing

Campus big data has the characteristics of large scale, wide variety, low density, objective reality, and so on. Through the analysis of campus data, the inherent and predictable characteristics of college students can be excavated, which is of great significance for improving the level of information management in colleges and universities. The main purpose of this paper is to research the optimal design of the security system for student management information based on artificial intelligence and cloud computing. Based on the real student campus data, through the processing and analysis of various student data, this paper realizes accurate financial aid determination, student three-dimensional portrait research, and student emotional fluctuation research and builds a student information management platform to assist students in “accurate and precise” and carefully handle the daily management of student work. Experiments show that the proportion of students from poor families who feel anxious is much greater than that of students from poor families and rich living expenses; in addition, students from poor families who feel that their lives are full of hope and relaxed and happy are 16.18% lower than students with rich living expenses.
Face Detection System Based on Deep Learning

The face is a special target. In order to obtain better detection results, researchers have improved and optimized the target detection algorithm, and proposed many excellent face detection algorithms. This paper improves the target detection algorithm Faster RCNN, uses ResNet50 to extract convolution features, performs multi-scale fusion of feature maps of different convolution layers. At the same time, the anchor boxes generated by the region proposal network are changed from the original 9 to 15 to better adapt to the small-scale face detection scene. On this basis, this paper integrates the SRGAN image super-resolution reconstruction module to perform data enhancement on low-resolution faces and form a detection network that can improve the performance of low-resolution small face detection. Train and test on the Wider Face dataset and conduct network comparison experiments. The final analysis of the experimental data shows that using the image deblurring algorithm of ResNet50 and SRGAN, compared with the original model, the accuracy is 2.06% higher than the original model, especially in low-resolution face detection.
Grid Voice Interaction Platform Based on Voice Recognition Engine

The development of artificial intelligence technology has brought a lot of convenience to people and also provided technical support for system development. Using artificial intelligence technology to design a voice interaction platform to interact with the power grid system, it can judge whether there is a fault in the power grid equipment according to the power grid signal, which ensures the safety of the power grid and the normal operation of the equipment. In this paper, based on the speech recognition engine, an interactive platform that can be applied to power grid speech recognition is constructed. When testing the power grid speech with noise, its noise immunity is close to 100%. The recognition accuracy of power grid voice signals of amplitude and different frequencies is also as high as 85%, which shows the high accuracy of power grid voice recognition of the platform.
Topic Model with Fully-Connected Layers for Short-Text Classification

The Internet news always contain a few words, which affects the performance of text analysis and classification. To solve the problem, based on the co-occurrence of words, Biterm Topic Model (BTM) builds the word biterms in corpus to extract the topic features for short-text classification. However, BTM ignores the relationship of topics. To overcome the limitation, we propose a model which integrates fully-connected layers of convolutional neural networks (CNN) into the framework of BTM. The model reflects the co-occurrence of words by biterms and builds the relationship of topics in the fully-connected layers by connecting the topic features with the cells of neighbor fully-connected layer. Thus, the model makes full use of topic features and the relationship of topics and enhances the representations of short-text documents. In the experiments of short-text classification, the performances of the model outperform the other baseline models on two benchmark datasets.
Research on Cloud Accounting System Design in Enterprise Information Construction Under the Background of Big Data

Cloud accounting system is the core of enterprise information construction, cloud accounting system, data storage, and data analysis. In this study, we will study the design of cloud accounting. The first part reviews the current situation of enterprise information construction industry and analyzes how to improve it. The second part analyzes the characteristics in enterprise information construction. The third part discusses different types of cloud accounting systems according to various requirements such as security, reliability, and cost-effectiveness.
Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms

Empirical data plays an important role in evolutionary computation research.To make better use of the available data, ontologies have been proposed in the literature to organize their storage in a structured way.However, the full potential of these formal methods to capture our domain knowledge has yet to be demonstrated.In this work, we evaluate a performance prediction model built on top of the extension of the recently proposed OPTION ontology.More specifically, we first extend the OPTION ontology with the vocabulary needed to represent modular black-box optimization algorithms.Then, we use the extended OPTION ontology, to create knowledge graphs with fixed-budget performance data for two modular algorithm frameworks, modCMA, and modDE, for the 24 noiseless BBOB benchmark functions.We build the performance prediction model using a knowledge graph embedding-based methodology.Using a number of different evaluation scenarios, we show that a triple classification approach, a fairly standard predictive modeling task in the context of knowledge graphs, can correctly predict whether a given algorithm instance will be able to achieve a certain target precision for a given problem instance.This approach requires feature representation of algorithms and problems.While the latter is already well developed, we hope that our work will motivate the community to collaborate on appropriate algorithm representations.
Technology and System Development of 3D Visualization of Medical Images

Medical image visualization is an important part of PACS. The integration of computer technology and digital imaging equipment provides favorable conditions for the rapid development of image visualization. The purpose of this paper is to study the technology and system development of 3D visualization of medical images. Firstly, the research background and significance of this paper are summarized, and the 3D visualization technology of medical images, DICOM international standard, including DICOM file structure and coding rules are introduced. The moving cube (MC) algorithm in 3D imaging and the RC algorithm in 3D medical imaging are described. The two reconstruction methods are implemented in detail and combined with software programming. Many major interactive imaging techniques have also been developed. The performance of the system is tested by the Load Runner performance testing tool. The experimental results show that the system supports seven users to run stably at the same time, and the performance meets the needs of practical applications.
Computer Network (CN) Security Privacy Data Fusion (DF) Method in Cloud Computing Environment

With the development of information collection technology, more and more human data needs to be processed, which leads to problems such as heterogeneous data types, poor data quality, and fast data processing speed. The main purpose of this paper is to analyze and study the methods of CN security privacy DF in the cloud computing environment. This paper analyzes the characteristics of CN information security and the factors that affect CN security, classifies DF methods and fusion structures, proposes related algorithms, and conducts experiments. It can be seen from the experimental results that the FC-SAE and SVR are the methods with better performance, and have obvious advantages over traditional time series forecasting methods.
Technique for Investigating Attacks on a Company’s Reputation on a Social Media Platform

In this paper, we present the technique for investigating attacks on a company’s reputation on a social media platform as a part of an arsenal of digital forensics investigators. The technique consists of several methods, including (1) identifying the attack based on sentiment analysis, (2) identifying the actors of the attack, (3) determining the attack’s impact, and (4) determining core actors to identify the strategy of the attacker, including (4a) usage of bots, (4b) attempts to conflict initiation, (4c) competitor promotion, (4d) uncoordinated user attack. In the paper we also present the evaluation of this technique using the real investigation of use-case, where we investigate the attack on a retail company X, that occurs after the company changed its policy dedicated to COVID-19 QR codes for their visitors.
A Novel Two-Stages Information Extraction Algorithm for Vietnamese Book Cover Images

This study presents a novel deep learning based two-stage algorithm for extracting information from Vietnamese book cover images. First, the Vi-BCI dataset, which is the first dataset for Vietnamese book cover information extraction, was built. This dataset contains 7,875 images of Vietnamese book covers annotated with the text location on the cover, the text content, the text label Title, Author, and Publisher of the books. Next, a novel two-stages deep learning based algorithm is proposed and implemented on the Vi-BCI dataset to extract text information presented on book cover images. The experimental results show that the proposed algorithm archives an outstanding performance of information extraction with the accuracy of 95.50%.
Experimental Research on Outdoor Sweeping Robot

With the rise of robot technology in the new era, the demand for outdoor and indoor cleaning robots is increasing. Among them, outdoor cleaning robots are gradually emerging. How to efficiently realize the above common scenarios and some complex road conditions to achieve stable and safe cleaning work, which needs to be solved and invested in a lot of research and exploration. The main purpose of this paper is to discuss the research on solar-powered outdoor sweeping robots. In this paper, the cleaning robot is verified by physical experiments, including the motion control and ROS communication experiments of the cleaning robot, the obstacle crossing performance and the suspension buffer effect experiment, and the physical experimental test of the full-coverage sweeping trajectory tracking of the bow. Experiments show that, through the improvement of the trajectory estimation link, the average tracking error under the two road conditions is within 5 cm, which meets the requirements of the actual setting. The adjustment times are increased, and the driving efficiency is improved.
Value-Based Approach in Psychology

The article reveals the essence of the value-oriented approach in psychology, the methodology of its application in the practical work of a psychologist, as well as the need to form the position of a "student" at the client At present, when the whole world is experiencing a state of instability, the work of psychologists in society is more important than ever. The psychological community tries to find, synthesize methods and tools that will show high efficiency in working with clients and will have a long-term effect. The purpose of this article is to introduce readers to the value-oriented approach (VOP) in psychology, which is the latest psychological direction that summarizes the achievements of psychological science and formulates universal principles of psychological practice. The VOP methodology represents a conceptually new approach to solving psychological problems. The psychological problem is seen not as a hindrance that needs to be addressed, but as a positive feedback from life. In the philosophy of this approach, life is seen as a sentient, supportive force for the existence of man, and man as a part of the whole associated with reality through many physical, mental and spiritual connections. In the case when a person violates harmony in relations with reality by his actions, he receives a signal about this in the form of various problematic circumstances and psychological difficulties. The work also uses the results of a study of the use of a VOP - approach among young people (100 people) aged 19 to 30 years. It seems to the authors of this article that the method of effective psychological assistance to people at the present time, which helps and teaches to cope with problems, is the method of value-oriented psychology. There is one wise popular statement: "If you want to feed a person - give him fish, and if you want him to be full all your life - teach him to fish."
Around the moving image

The article is devoted to the analysis of the "moving image" as a phenomenon of noospheric significance, a phenomenon of historically unavoidable, existential-authentic, extremely objective symbolic fixation of the temporal-spatial processuality of the world. It was found out that this "moving image" put an end to the polemic presented by the German educator Lessing in his treatise "Laokoon, or on the limits of painting and poetry", outlining the boundaries between "spatial arts" that reflect "space, objects in it" and poetry (properly language art), which embodies first of all time, and in this way connected Time and Space in its very structure. A very specific interaction of spatial and temporal information in the very architecture of the human brain has been established, in which the left hemisphere forms language-speech, and the right hemisphere forms spatial representationsformations, and the human brain itself "films" the surrounding world in the same way as a movie camera, but in full awareness.