Reviewerly/exHarmony huggingface dataset:
An Analysis of Mainstream Animation Education in Japan and the United States Using Computer 3D Technology

Abstract As an important part of culture and entertainment, animation is also a form of artistic expression with entertainment and educational functions. The application of computer 3D technology makes the animation more vivid and expressive. This paper USES computer 3D technology to analyze the entertainment and educational functions of American and Japanese animation, as well as the educational significance of American and Japanese animation. This paper points out that computer 3D technology not only creates new cultural connotation of American and Japanese animation content, but also is one of the important factors of its educational significance.
LED Solar Spectrum Computer Simulation Based on Non-dominated Sorting Genetic Algorithm

Abstract The solar computer simulation technology has been extensively applied in the fields of polymer curing test, solar cell detection and calibration, and satellite heat balance test, etc. The non-negative least-squares solution of the overdetermined equations based on the non-dominated sorting genetic algorithm (NSGA) to optimize the monochromatic light-emitting diode (LED) matching light source combination, replace some monochromatic LED with white LED to simulate the solar spectrum, and discuss several LED lights with different peak wavelengths that can be replaced by white LED. The simulation results suggest that in the range of 300 ∼ 1100 nm, as the monochromatic LED types replaced by white LED increase, the total number of LEDs used is reduced, and the spectral match decreases. When LEDs with three different peak wavelengths are replaced, the correlation index in the fitting based on the algorithm is 0.9035, where the number of LEDs can be reduced by 15.6%, and the simulation spectrum is basically consistent with the target one. The proposed method has a small spectral mismatch and can be used to distinguish two absorption valleys of the standard solar spectrum AM1.5 accurately.
The Improvement of Teaching Design Ability of Physical Education Major Based on Computer Media Scene Teaching Video Model under the Concept of OBE Teaching

Abstract The teaching design ability of physical education specialty based on the teaching concept of computer media OBE can effectively carry out the teaching, improve the teaching quality and realize the optimization of physical education teaching. The teaching design of physical education major adopts the concept of OBE and computer media situational teaching video model, which requires the diversification of teaching skills training and the establishment of a comprehensive training system. This paper firstly analyzes the teaching objectives and teaching design of physical education major in China, and then studies the influence of computer media on the teaching design ability of students majoring in physical education. Finally, it gives the strategies to improve the teaching design ability of physical education major by integrating the conceptual model and scene teaching video of OBE.
A swarm intelligence labour division approach to solving complex area coverage problems of swarm robots

The complex area coverage problem is classical and widespread in the research field of swarm robots. In order to solve the complex area coverage problem with complex nonlinear boundary and special task area (forbidden area or threat area), firstly, the task area is adjusted and grid discretisation. Then, inspired by the labour division phenomenon of typical biological groups such as bee colony and ant colony, the paper analyses the performance characteristics of typical ant colony labour division model (response threshold model) and bee colony labour division model (activation-inhibition model) from the perspectives of individual and environment, individual and individual, and a new swarm intelligence labour division approach (activation-inhibition response threshold algorithm) to solve the complex area coverage problem of swarm robot. Three experiments are carried out to illustrate that the algorithm are endowed with great ability of area coverage and dynamic environment. It can respond to the sudden threat in time and make an efficient response, which has a good practical application prospects.
Learning Models for Concept Extraction From Images With Drug Labels for a Unified Knowledge Base Utilizing NLP and IoT Tasks

The evolution of humankind is through the exchange of information and extraction of knowledge from available information. The process of exchange of the information differs by the probability of the medium through which the information is exchanged. The Internet of things (IoT) contains millions of devices with sensors simultaneously transferring real time information to devices as rapid streams of data that need to be processed on the go. This leads to the need for development of effective and efficient approaches for segregating data based on class, relatedness, and differences in the information. The extraction of text from images is performed through tesseract irrespective of the language. SCIBERT models to extract scientific information and evaluating on a suite of tasks specially in classifying drugs based on free data (tweets, images, etc.). The images and text-based semantic similarity analysis provide similar drugs grouped together by composition or manufacturer.
QR-Code on tax relevant documents in Portugal

The systematization of the information underlying the electronic invoice and, according to the new measures, published in Decree Law No. 28/2019 of 15 February, is aimed at optimizing the billing process, allowing to create the conditions for the dematerialization of documents, stimulating the development and use of new technological instruments, incorporating a philosophy of innovation and de-bureaucratization. From 2020 onwards, the invoices and other fiscally relevant documents must contain a two-dimensional bar code (QR-Code) which will encompass all the information related to the invoice, thus allowing the consumer to send this information digitised to his e-invoice, without the introduction of the NIF. The aim of this article is to evaluate the contribution that this modification will originate on the different stakeholders present in the system, in order to guarantee the authenticity of the origin, the integrity of the content, and legibility of the invoices. It is also intended, to analyze the advantages of the QR-Code in invoices, and describe the different stakeholders in the system. The methodology used in the execution of this article was Design Science Research (DSR). The research method was based on the analysis of diverse bibliographic sources that deal with the most relevant aspects of the invoice evolution process, namely legal diplomas as well as the analysis of international standards, frameworks and technological specifications. The paper's contributions have as underlining the presentation of an Approach that enables process stakeholders to understand the differences, requirements and development strategies to be followed for the implementation of the QR-Code in the fiscal context.
A Study of the Impact of Educational Qualifications of Parents on the Academic Performance of Students of Class XI in English Medium CBSE Schools in PCMC Area

This is an era of competitiveness in every field of life. Interest and aspiration of most of children depends on willingness of parent. Parents are considered as the powerhouse of experience along with Indian child is depending on their parent in every aspect during study. Researcher have used descriptive and survey method of the study. Here representative sample from the population in order to generalize from the sample to the population. The researcher has used simple random sampling method for sampling. This research aimed for find out qualification of parents and to compare and contrast the impact of parental education as a reason for the difference in academic performance as well as to find the academic performance of the students. Irrespective of the qualifications of the parent, the parents are involved with the kids by just being around and supervising. The parents irrespective of their boards in class X were under performing in class XI.
Brief Analysis of the Influence of Chinese Culture Teaching on the Building of Chinese Image in Teaching Chinese as a Foreign Language

&lt;p&gt;In the process of China’s going global, building a positive Chinese image is of great significance to the development of our country. It is important to promote Chinese culture when teaching Chinese as a foreign language. This article aims at analyzing the influence of Chinese culture teaching on building Chinese image when we teach Chinese as a foreign language, so as to improve the popularity and understanding of Chinese image within a wider range internationally.&lt;/p&gt;
Factors Influence Employee Level of Integrity in Automotive Company

This study investigated the factors that influence employee level of integrity at UMW Toyota Motor. There are three factors identified as the predictor in the study, namely, individual, organizational, and situational factors, which are expected to affect employee level of integrity. Data were collected through questionnaires distributed between October 2018 and March 2019 to all employees of UMW Toyota Motor. A total of 300 respondents were approached, and 137 (46%) questionnaires were returned for analysis. The data collected were analyzed using descriptive, correlation, and regression analysis. The finding concluded that the level of integrity among employees of UMW Toyota Motor is high. The regression analysis result showed that situational factors have significant and positively associated with the employee level of integrity. The result indicated that situational factors such as peer pressure, financial distress, leadership influence, and ethical norms at the workplace affected the integrity level of employees.
Efficient Construction of Neural Networks Lyapunov Functions with Domain of Attraction Maximization

This work deals with a new method for computing Lyapunov functions represented by neural networks for autonomous nonlinear systems. Based on the Lyapunov theory and the notion of domain of attraction, we propose an optimization method for determining a Lyapunov function modelled by a neural network while maximizing the domain of attraction. The potential of the proposed method is demonstrated by simulation examples.
Research on Methods for Complex Chinese Entity Recognition

Abstract Named entity recognition(NER), as a key task of natural language processing, is of great significance in relational capture, information retrieval, knowledge mapping, machine translation, and question and answer systems. In the neural network-based Chinese named entity recognition method, the vectorized word representation only maps words into one vector, which cannot represent the above problem, In order to solve these problems, this paper proposes a Cascading model based on the character vectorization, This method uses BERT to represent the ambiguity of the word. In the agile BIGRU model, the initial entity recall is completed to increase the entity recall rate. Then the output of this layer is input into the high-level bilstm model of self attention mechanism to further filter and improve the accuracy of the final recognition. Finally, the CRF is used to complete the output of the final recognition result. Experiments show that the model can effectively improve the accuracy, accuracy and recall rate of complex Chinese entity recognition. The f1 value has increased by about 2% overall.
An Automated Recognition Model for Sensitive Information

Abstract Civil aviation business system carries a lot of passenger information. How to strengthen the management and use of civil aviation passenger information has become an important issue for the civil aviation industry. For the sensitive passenger information with huge data type and quantity, it is extremely inefficient to comb and analyze it manually alone. In this paper, we establish an automatic sensitive information identification model to effectively identify the passenger sensitive information in structured and unstructured files, improve the identification efficiency of sensitive information in civil aviation business system and the ability of data security management.
A Real-time Image Recognition System Based on Improved Jacintonet Convolutional Neural Network

Abstract With the emergence and development of new automation industries such as unattended supermarkets and smart picking orchards, the demand for real-time systems based on embedded platforms is increasing day by day. Heterogeneous multi-core processors are widely used in modern integrated circuit design due to their advantages of low power consumption and high parallelism. More and more real-time systems are implemented on heterogeneous multi-core platforms. Based on the heterogeneous multi-core embedded system, the network parameters and architecture of jacintonet model are improved, and a real-time system for fruit image recognition is realized by using the improved network. A small sample data set is used to train the modified network and the trained network is imported into the system for testing. The result shows that the improved jacintonet network can run well on heterogeneous multi-core system and has the same recognition performance as the original network.
Attribute-based Access Control for Cloud-based Electronic Health Record (EHR) Systems

Electronic health record (EHR) system facilitates integrating patients' medical information and improves service productivity. However, user access to patient data in a privacy-preserving manner is still challenging problem. Many studies concerned with security and privacy in EHR systems. Rezaeibagha and Mu [1] have proposed a hybrid architecture for privacy-preserving accessing patient records in a cloud system. In their scheme, encrypted EHRs are stored in multiple clouds to provide scalability and privacy. In addition, they considered a role-based access control (RBAC) such that for any user, an EHR access policy must be determined. They also encrypt the EHRs by the public keys of all users. So, for a large amount of EHRs, this scheme is not efficient. Furthermore, using RBAC for access policy makes the policy changing difficult. In their scheme, users cannot search on encrypted EHRs based on diseases and some physicians must participate in the data retrieval by a requester physician. In this paper, we address these problems by considering a ciphertext-policy attribute-based encryption (CP-ABE) which is conceptually closer to the traditional access control methods such as RBAC. Our secure scheme can retrieve encrypted EHR based on a specific disease. Furthermore, the proposed scheme guarantees the user access control and the anonymity of the user or data owner during data retrieval. Moreover, our scheme is resistant against collusion between unauthorized retrievers to access the data. The analysis shows that our scheme is secure and efficient for cloud-based EHRs.
An improved FAHP-cloud-based security risk assessment model for airborne networks

In connection with problems such as difficulty in the objective and accurate calculation of the index weight in the security risk assessment of an airborne network, as well as a unitary assessment result and poor descriptiveness, a risk assessment method for airborne network security based on an improved fuzzy analytic hierarchy process (FAHP)-cloud model has been proposed. First, the particularity of the airborne network is taken into account to establish an index system for the risk assessment of airborne network security. the traditional FAHP, information entropy is introduced to calculate the comprehensive weight, which is subsequently combined with the cloud model theory to construct an actual integrated cloud model. By calculating the degree of similarity between the actual integrated cloud model and the standard cloud model, the risk levels of airborne network security are determined. The simulation experiments show that this method can reflect the objectivity of the index weight, make the assessment results more visual and reliable, and fully reflect the fuzziness and randomness in the assessment.
THE RELEVANCE CRITERION OF ARGUMENT EVALUATION: PRAGMATIC INTERPRETATION

In the paper I consider the relevance criterion for argument evaluation within informal logic. I focus on the dialectical relevance concept, which is the result of dialogical interpretation of argumentation process.The research topicality is due to the lack of the relevance notion unified understanding within the contemporary argumentation theory. This notion analysis is important because relevance is one of the criteria for argument evaluation. The elimination of its interpretation`s contradictions can be the step towards to both better practical argument evaluation using and integrative relevance understanding conception.The purpose of the article is to find out the specific features of the dialectical relevance in compare with others relevance kinds. To achieve this goal I, firstly, analyzed the key characteristics of the dialogue argumentation model in the relevance perspective. Secondly, I clarify the essential features of the dialectical relevance and irrelevance. Thirdly, I provide a comparative analysis of the dialectical and premissary relevance.The methodology of this research is based on the informal logics and dialogical approaches to an argument and argumentation analysis.The novelty of the research results is the dialectical and premissary relevance notions comparison. As the result I conclude that, firstly, dialectical relevance is merely dialectical, not logical criterion of evaluation. Secondly, dialectical relevance deals with argumentation process, not with argument as a premise-conclusion relation. Thirdly, dialectical and premissary relevance have common features, as the relation to the conclusion justifying. However, the dialectical relevance specifics are its rule`s compliance, dynamic and dialectical character, and relation to the argumentation correctness.
Computer programming for clinicians: five steps to your new favourite skill. Part 1

Many of you will be familiar with clinical projects reliant on unwieldy spreadsheets containing hand-curated data, needing laborious processing by a dedicated but time-poor clinician. Wouldn't it be nice if a machine could do the work for you? The good news is that computer programming is more accessible than ever before. This article aims to point the reader towards getting started: there is no single ‘right’ way to learn. We will focus mainly on open-source, free software, but paid alternatives do exist. In this article we discuss steps 1 and 2 of 5.Two popular, free and well documented languages for analysis are Python and R.1 Python is described as a ‘general purpose’ language—it can be applied to many computing applications. R describes itself as for ‘statistical computing and graphics’. It is not unusual to use different languages for different applications. I use Python for ECG processing and R for final statistical analysis prior to publication—but this is purely …
Using the peer teaching method in higher education: basic models.

The article is devoted to the study of such a phenomenon as the peer teaching method in higher education. Two categories of peer teaching are considered, as well as their advantages and disadvantages. It is proved that peer teaching methodology appeared almost simultaneously with the time when education became available to most of the population. It is concluded that the main reason for the popularity of this method of training is due to financial reasons. The analysis shows that peer education is the most effective in combination with other teaching methods. This method has great potential both for the “teacher” student, and for the “student”- student, especially if they seek to expand active participation and develop skills of cooperation and social interaction.
abstractXOR: A global constraint dedicated to differential cryptanalysis

Constraint Programming models have been recently proposed to solve cryptanalysis problems for symmetric block ciphers such as AES. These models are more efficient than dedicated approaches but their design is difficult: straightforward models do not scale well and it is necessary to add advanced constraints derived from cryptographic properties. We introduce a global constraint which simplifies the modelling step and improves efficiency. We study its complexity, introduce propagators and experimentally evaluate them on two cryptanalysis problems (single-key and related-key) for two block ciphers (AES and Midori).
Proposal for a Comprehensive (Crypto) Asset Taxonomy.

Developments in the distributed ledger technology have led to new types of assets with a broad range of purposes. Although some classification frameworks for common instruments from traditional finance and some for these new, so called cryptographic assets already exist and are used, a holistic approach to integrate both worlds is missing. The present paper fills this research gap by identifying 14 attributes, each of which is assigned different characteristics, that can be used to classify all types of assets in a structured manner. Our proposed taxonomy which is an extension of existing classification frameworks, summarises these findings in a morphological box and is tested for practicability by classifying exemplary assets like cash and bitcoin. The final classification framework can help to ensure that the various stakeholders, such as investors or supervisors, have a consistent view of the different types of assets, and in particular of their characteristics, and also helps to establish standardised terminology.
Evaluating Crypto Exchanges in the Absence of Governmental Frameworks - A Multiple Criteria Scoring Model

Since the introduction of Bitcoin in 2008, trading venues for cryptocurrencies, so called cryptocurrency exchanges, have undergone a fast development. Today cryptocurrencies totaling to more than USD 16bn are traded on more than 200 of such platforms, thereby surpassing the volume traded of numerous national stock exchanges. At the same time cryptocurrency exchanges are oftentimes not subject to a specific regulatory framework. Consumers who want to use these novel services are virtually left blindfolded when it comes to pivotal selection criteria. Yet, not even attempting to differentiate the quality levels provided by the various cryptocurrency exchanges would be tantamount to throwing out the baby with the bath water. In this work-in-progress paper, we develop an innovative scoring system to discriminate among cryptocurrency exchange offerings. In the absence of regulatory frameworks we identify 34 factors that may be considered by consumers when choosing the right cryptocurrency exchange offering. The advantages and disadvantages of such a scoring system are discussed and we provide suggestions for further development.