Reviewerly/exHarmony huggingface dataset:
Problems on Tagging of Parts of Speech of Chinese Two- Syllable Body Compound-Focused on Verb and Adjective

This paper analyzed the partiality of 42 two-syllable body compound words with different parts of speech as verbs and adjectives in various dictionaries through the modification of adverbs of degree. Type A body compound words consist of a subject predicate structure except for three predicate object structures. It is difficult to say that this type of compound word is lexicalized as a typical adjective because it is found that it receives little modification of adverbs of degree. Type B body compound words consist of predicate object structures, and it is a general view that as the internal closeness increases, they have been lexically converted from predicate object phrases into heterologous verbs. Many of these compound words can be seen as verb adjectives and concurrent verbs because they are relatively actively modified by adverbs of degree. The internal closeness of Chinese compound words is generally higher in the predicate object structure than the subject predicate structure. As the lexical progress of the predicate object structure with high internal closeness is more active, it is thought that type B compound words are more formulated by adverbs of degree.
Multi-task Federated Learning Medical Analysis Algorithm Integrated Into Adapter

Recently, the accumulated large amount of medical data has laid a solid foundation for the development of medical analysis. More and more data analysis methods have been proposed. But in this era, data security and data analysis capabilities have encountered significant challenges. First, medical data contains much information about the patient’s health status, disease progression, treatment, etc., and also involves much basic knowledge of patients. The adverse impact will be immeasurable if these data are attacked and leaked. Second, Data analysis capabilities are limited by security rules and cannot be improved. We propose a multi-task personalized clinical evidence-based analysis algorithm integrated into the task adapter, built with the federated learning architecture as the underlying architecture. We conduct extensive experiments on public datasets. The effect gap between our proposed model and the traditional central training model can be controlled by 5% for all medical tasks, which indicates the clinical evidence-based analysis algorithm based on the federated learning framework can achieve the same effect of approaching centralized training without data leakage. It will make Multi-task medical joint training possible.
Automatic Clothes Retriever (ACR)

As a tropical country, Indonesia is located below the equator and has sunshine all year round, the sun's rays have been used to dry wet clothes after people wash their clothes.However, with climate change happening, the current weather is difficult to predict.there are many chances of clothes getting wet due to unexpected rain.Especially now that people are busy at work and clothes are hung unattended.To solve this problem, many projects have been carried out, such as standalone clothes drying system, web-based drying clothes system, and the most advanced is clothes drying system that recycle AC heat waste as source of heat.In this paper, automatic clothes retriever (ACR) equipped with mobile apps-based monitoring system was made.Using the ESP32 as the main controller, LDR, rain sensor, limit switch, motor, fan and heating lamp, the ACR will automatically recognize the weather and retrieve-out or retrieve-in the hanger to protect clothes from unexpected rain.As a result, ACR managed to respond to weather change, by retrieveinning the clothes hanger in 14.82 seconds with 10 Kg clothes on it.During the experiment, the maximum energy consumption of ACR was measured, which is 0.289KWh in one hour with full load in the system.
An proficient and Confidentiality-Preserving Multi-Keyword Ranked Search over Encrypted Cloud Data

Cloud computing has developed progressively prevalent for data owners to outsource their data to public cloud servers while consenting data users to reclaim this data.For isolation disquiets, a secure rifle over encrypted cloud data has stirred numerous research mechanisms underneath the particular owner model.Conversely, most cloud servers in practice do not just assist one owner, as an alternative, their sustenance gives multiple owners to share the assistances carried by cloud computing.In this proficient and confidentiality-Preserving Multi-Keyword Ranked Search over Encrypted Cloud Data, new schemes to deal with Privacy preserving Ranked Multi-keyword Search in a Multi-owner model (PRMSM) has been introduced.To facilitate cloud servers to execute secure search without knowing the actual data of both keywords and trapdoors, we thoroughly build a novel secure search protocol.To rank the search results and domain the privacy of relevance scores amongst keywords and files.To thwart the assailants from snooping secret keys and fantasizing to be legal data users submitting pursuits, a novel dynamic secret key generation protocol and a new data user authentication protocol is discussed.
Test-Case Optimization Using Genetic and Tabu Search Algorithm in Structural Testing

Software test-case generation is the process of identifying a set of test cases.It is necessary to generate the test sequence that satisfies the testing criteria.For solving this kind of difficult problem there were a lot of research works, which have been done in the past.The length of the test sequence plays an important role in software testing.The length of test sequence decides whether the sufficient testing is carried or not.Many existing test sequence generation techniques uses genetic algorithm for test-case generation in software testing.The Genetic Algorithm (GA) is an optimization heuristic technique that is implemented through evolution and fitness function.It generates new test cases from the existing test sequence.Further to improve the existing techniques, a new technique is proposed in this paper which combines the tabu search algorithm and the genetic algorithm.The hybrid technique combines the strength of the two meta-heuristic methods and produces efficient test-case sequence.
ANALYSIS OF CRITICAL THINKING ABILITY OF STUDENTS WITH ASD IN MATHEMATICS LEARNING

The article aims to describe the critical thinking abilities of students with autism (ASD) with regard to their comprehension of mathematical learning, especially fractions, using a qualitative approach.Students diagnosed with verbal autism served as participants in this research.Interviews, observations, testing, and documentation were the methods of data collection, used in this research.To ensure that the data are accurate, it is important to use strategies such as greater persistence of observation and triangulation.Reducing the amount of data, presenting the data, and generating conclusions are the phases involved in data analysis.Even though they are all part of the same group-the verbal group-three kids with autism were found to have distinct ways of thinking, according to the findings of the research conducted on them.Not all linguistic communities possess the capacity for critical thinking and have the same degree of comprehension.There are only two autistic pupils overall, but each of them has superior cognitive abilities and makes the content much simpler to comprehend than one other student.
Current problems of digital transformation in secondary education

Introduction . The article continues the series of publications within the framework of the Russian Foundation for Basic Research (RFBR) project “Construction of a Fundamental Model for the Digital Transformation of the General Education System”. Aim . The aim of the study was to analyse the current state of development of digital educational services and the development of digital competencies by participants in the educational process. Methodology and research methods . The authors used the materials from a number of secondary monitoring studies; however, the current research is based on completely original material. The data obtained during the survey are published for the first time. The main method of collecting information is an electronic questionnaire based on Google forms. The survey respondents were participants in the educational process, predominantly permanently residing in the territory of the Sverdlovsk region (99% of respondents). The survey was conducted on a voluntary and completely anonymous basis. Results . The research results of the study suggest that the mastery of digital technologies by the participants in the educational process is insignificantly associated with the implementation of state strategic programmes in the field of digital transformation of education. Although the ongoing changes such as the development of digital infrastructure in the school, the accumulation of digital educational content, the development of specialised services, the increase in the level of digital literacy of teachers are necessary. However, within the framework of the existing education management system, the aforementioned changes do not provide significant motivation for the actual use of opportunities of digital infosphere in education. Accordingly, at the moment, the transformation process is taking place according to the worst (inertial) scenario. Scientific novelty . The article makes it possible to more accurately assess the situation in regional education in order to make current management decisions and provides reference points for longitudinal research aimed at achieving the main goal of the project as a potential basis for the educational strategy of the Russian Federation.
A Distributed Streaming Computing Model Management System

IoT big data has many dimensions, many business types and many customized requirements, and each business needs to be implemented using a stream computing model with a wide variety of stream computing models. This paper proposes a management method for streaming computing models, which can dynamically manage streaming computing models and achieve hot loading of streaming computing models. This makes it easier to manage computational models in a streaming computing cluster.
Application Research on the English Writing Based on Unit Integrity Teaching Pedagogy in Junior High School

This study aims to explore ways to improve the writing ability of junior high school English learners guided by the Unit Integrity Teaching method. This article will take Go for it! (Grade 7) Unit 5 Why do you like pandas? for example to show an overall teaching design from the perspective of the Unit Integrity Teaching. The overall teaching design of the unit starts from the interpretation of teaching materials, analysis of learning situation, target positioning and teaching activity design, so as to found ways to improve students' writing level and develop students' core competences.
Analysis on Feasible Methods of Digital Image Tampering Detection

In order to solve the problem of image tampering detection in the blind forensics of digital images, this study first researches and summarizes the means and methods of image tampering and forgery, and provides suggestions for methods of tampering detection using open source tools for the methods that may be used for falsification. These methods have been publicly tested by open source companies for a long time, which proves their feasibility. The methods and conclusions suggested by the research can be used in the "falsification" application of pictures in many fields, and have certain academic value and social value.
Research in "Duty of Filtering" of Chinese E-commerce Platform in the Scope of Copyright Protection -- Refer to Article 17 of the Directive on Copyright in the Digital Singles Market

With the development of Internet technology and the advent of the era of user-generated content, copyright infringement occurs frequently. The e-commerce platform, which is dominant in the operating transaction space, needs to supervise and manage the selling activities of the merchants in the platform. The issue under discussion in this paper is whether the "duty of notice" to be performed by e-commerce platforms in the regulation of infringement occurs after the infringement and does not require the right holder to give effective notice of infringement to the e-commerce platform, and the criteria for determining the platform's high duty of care ("Duty of Filtering") in judicial practice. This paper adopts a literature and doctrine analysis method to summarize and analyze the core claims of scholars. By adopting the empirical analysis method, a sample of 200 judicial decisions related to the "Duty of Filtering" of e-commerce platforms in online copyright infringement was collected from various platforms, and the typical cases retrieved were summarized and integrated to summarize the current situation of judicial application of the Duty of Filtering of e-commerce platforms. Through a combination of empirical and theoretical research, the current status of the determination of the "filtering obligation" of e-commerce platforms in China is explored, as well as the court's thinking on the case that should be adjusted in light of Article 17 of the EU Directive on Copyright in the Digital Singles Market.
Research on Online Review of Ice and Snow Sports Based on Text Mining

Ice and snow economy, with the development of times and economy and the heat of 2022 Winter Olympic Games, ice and snow sports have gradually become a trend.However, domestic and foreign scholars to this emerging economy research is less, the level is shallow.This paper takes Ctrip platform as the data source, grabs the online review text of ice and snow sports, processes the data, quantifies the comment attribute of consumers by TF-IDF method, then uses LDA model to explore its potential theme, and finally constructs emotion classification model to analyze consumers 'emotion.The purpose is to understand their emotional bias and provide reference suggestions for national decision-making and ice and snow economic development.
A Study on the Effect of Political Efficacy of Youth generation on Social Trust and Government Trust: Focusing on the Mediating Effect of Social Fairness

The younger generation has become the focus of various policies proposed by political circles, including those discussed during South Korea’s recent 20th presidential election. Despite the prioritization of “fairness,” which is considered the most important value by the younger generation, and efforts to secure their votes, political circles have failed to gain their sympathy. Numerous surveys have shown that the younger generation perceives society as unfair, which leads to a decline in trust in the government and society.&#x0D; This study attempted to analyze the relationship between the political efficacy of the younger generation, social fairness, and trust in the government and society. To accomplish this, descriptive statistical analysis, exploratory factor analysis, reliability analysis, and covariance structure analysis were conducted. The results indicate that the internal and external political efficacy of young people has a positive effect on government trust and social trust through social fairness. Thus, enhancing the political efficacy and social fairness of the younger generation is necessary to increase their trust in the government and society. The study concludes by presenting theoretical and political implications.
Research on group distribution leakage analysis method for RSM

Side channel attack is a new and simple attack idea, and its proposal has created a significant threat to the security of cryptographic devices. With the continuous development of deep learning techniques, deep learning-based side channel attacks have enabled the attack techniques to reach new heights, but the attack efficiency and training time have become new problems. In order to improve the attack efficiency, researchers have proposed a large number of leakage analysis methods, which can effectively extract the intervals with significant leakage in the energy consumption curve and reduce the training parameters and data volume. In order to deal with side channel attacks, researchers have proposed various resistance strategies, among which masking protection is the simplest and widely used way. RSM rotating S-box masking scheme is a particularly important masking protection scheme, which uses a first-order masking scheme to randomize the leakage energy consumption of sensitive information using random masks, thus making the algorithm resistant to first-order side channel attacks. For this type of masking algorithm, this paper proposes a new leakage analysis algorithm, namely "Group Distribution Difference" (GDD). This algorithm is based on the distribution difference of energy consumption, and the energy consumption frequency in the group is calculated instead of the probability distribution. The KL distance is used to calculate the difference between groups and find out the leakage interval, so as to achieve an efficient attack.
Template attack based on uBlock cipher algorithm

The uBlock cipher algorithm is a family of lightweight block cipher algorithms, which was proposed by Wu Wenling, Zhang Lei and others in 2019. Its block length and key length support 128 and 256 bits. It has certain flexibility in different environments to meet the application of algorithms in different software and hardware conditions. At present, the research of side channel attack against uBlock cipher algorithm is mainly differential fault analysis. In order to explore the application of template attack against uBlock cipher algorithm analysis attack, a template attack method against uBlock cipher algorithm is proposed. When constructing the template, the S-box output of uBlock cipher algorithm is selected as the attack point of energy analysis, and the Hamming weight is used as the analysis model to build the template about S-box output.
The Effect of Source’s Credibility on Determining the Authenticity of Misinformation: Focusing on the Moderating Effect of Receiver’s Characteristics

Few people will be able to live a day without being exposed to information. Whether it"s through books, YouTube or Internet searches, people live by searching and accepting various information every day, with different routes. However, compared to the vast amount of information, people have physical limitations, including time and cognition, so they process all the information exposed to them in their own ways. Among the various problems that may occur in this process, the damage caused by the inclusion of misinformation in the individual"s information acceptance process is so great that it cannot be overlooked. Therefore, in order to create a healthy information accepting environment, this study focused on exploring factors that affect the process of recognizing information as fact or false when people encounter it. As a result of empirical analysis of the structural model using PLS-SEM, the source"s credibility had a significant effect on the perceived falsity of the information. It was also confirmed that the effect of confirmation bias was significant among the moderating effects of the three receiver characteristics. In other words, the greater the belief in the source who provides information, the higher the level of a true recognition of the provided information, and the difference in the degree of influence of public confidence on the information acceptance process is occurred depending on each person"s opinion.
"Helping People Get Cheated" to "Anti-Fraud Star"

In recent years, there have been frequent cases of telecom network fraud. Because cunning crooks have long extended their claws to the pure campus. "Post-00" college students grow up in the Internet era and like to participate in online activities and online part-time jobs. In order to prevent college students from falling into the crisis of telecommunications network fraud, although colleges and universities have repeatedly reminded them of security education, the effectiveness of education still needs to be improved. Among them, the fake identity fraud encountered by Xiao Chen is a typical high-incidence telecom network fraud case. By analyzing the causes of cases, the case handling process of ideological and political workers is expounded, and the case reflection and enlightenment are summarized, which provides effective reference ideas for the prevention and control of campus online fraud.
Multimodal Emotion Analysis Model based on Interactive Attention Mechanism

In traditional multi-modal sentiment analysis, feature fusion is usually achieved by simple splicing, and multi-modal sentiment analysis is only trained as a single task, without considering the contribution of inter-modal information interaction to sentiment analysis and the correlation and constraint relationship between multi-modal and single-modal (text, video and audio) tasks. Therefore, a multi-task model based on interactive attention mechanism is proposed in this paper, which uses inter-modal attention mechanism and single-modal self-attention mechanism to train multi-modal sentiment analysis and single-modal sentiment analysis together, so as to make full use of inter-modal and inter-task information sharing, mutual complement, and reduce noise to improve the overall recognition performance. Experiments show that the proposed model performs well on MOSI and MOSEI common data sets for multimodal sentiment analysis.
Auxiliary feeding device and feeding method of soil element analyzer

Based on the limitations of traditional soil analyzers, this paper proposes an auxiliary feeding device and feeding method of soil element analyzer, including an outer cylinder with a discharge port and a hollow structure, and a material conveying device in the outer cylinder. The outer cylinder is also provided with a feeding device coaxially, and the feeding device is provided with a plurality of storage silos, and the feeding device rotates the materials placed in the storage silo into the material conveying device in turn, and is transported to the discharge port by the material conveying device; The feeding device is set on the sliding bracket, the outer cylinder is set on the base, and the sliding bracket is sliding connected with the base. This method can realize a large number of automatic feeding at one time, which greatly reduces the labor intensity of the staff.
Multimodal Emotion Recognition and Fluctuation: A Study on Sentiment Analysis of Online Public Opinion

Emotion is an important way for individuals to express their views on the Internet and an important variable that shapes public opinion. Considering the multimodality of data, such as text, picture and video, and the subtlety of emotional expression, a multimodal sentiment analysis model that addresses content involving difference senses, such as sight, hearing and touch at the same time is very necessary. This study outlines the basic steps, classification strategies and research methods of sentimental analysis and acknowledges the differences between sentimental analyses on text, picture and video. As multimodal sentiment recognition is still in its initial stage, there’s still room for improvement in cross-disciplinary research on multimodal data of text, picture, audio, video in terms of weighted scoring, complex emotion and intensity recognition. It’s concluded that future studies should focus on the intensity of different emotions, multimodal data fusion and how weighted scoring influences an emotion recognition model and explore application possibilities.