Reviewerly/exHarmony huggingface dataset:
Network Teaching System Design Based on Human-Computer Interaction Psychology and Artificial Intelligent Technologies

The wide application of artificial intelligence (AI) technology in education and teaching has widely changed the means and methods of distance network teaching. However, most intelligent network teaching systems and intelligent education platforms do not consider psychological factors such as learners' cognition, perception and emotions. This research studies the psychology factors of learners and the influence in the human-computer interaction (HCI) on the network teaching system. We hope to put forward the intelligent education platform based on HCI psychology design theory and a network teaching system design, while using AI technology to build software module and implement the network teaching system. Through the network teaching test, the test data of the ordinary network teaching system and the HCI psychology-based intelligent education platform are compared and analyzed. The analysis results show that the network teaching system based on HCI psychology improves the learning efficiency, knowledge acquisition rate and learning performance of learners. It shows that the combined application of AI technology and educational psychology is an important reform method of network teaching and intelligent education platform.
A named entity recognition model for fertilizer knowledge areas based on BERT and adversarial training

To address the problem of inaccurate identification of entities with fuzzy fertilizer knowledge areas boundaries. In this paper, we propose a named entity recognition model based on BERT with adversarial training. Disturbance factors generation by introducing FreeLB adversarial training method, combined with the vectors of the word embedding layer in BERT to form the adversarial sample. Improving model recognition of boundary ambiguous entities by adversarial training. Experimental results show that, the model proposed in this paper achieves 89.77% accuracy, 93.72% recall and 91.70% F1 on the dataset. compared with other models, the accuracy, recall and F1 values are improved by 1.75%, 0.53% and 1.17% respectively.
An equipment fault diagnosis method based on unbalanced industrial big data

With the development of the industrial big data, research on data-driven industrial equipment fault diagnosis has received more and more attention. However, in the process of data acquisition, the equipment failure frequency is low, and the data set becomes serious imbalance. In order to solve this problem, we propose an unbalanced data generated method based on GAN. And in order to improve the accuracy of equipment fault diagnosis, we propose a fault diagnosis method based on CNN-LSTM, which can effectively utilize the spatial and temporal characteristics of data.
Inner layer hyperparametric meta-learning based on feature reuse

Few-shot learning requires fast learning and adaptation during the learning process, which has been seen as a very challenging problem because of its stringent training requirements. With the development of deep learning, meta-learning is increasingly applied to solve few-shot problems. Model-agnostic meta-learning (MAML) is applied to model-agnostic tasks by finding common initialization parameters applicable to the model through both inner and outer loops. However, the generalization performance of MAML is not strong, and its inner loop is not fully functional. Therefore, we add learnable hyperparameters to the inner loop to make the model training results more relevant to the current task and reduce the number of layers of gradient updates without unnecessary computation. Experimental results show that the inner loop hyperparameter learning based on feature reuse (HLFR), finds better initialization parameters compared to MAML.
Optimization and implementation of Montgomery algorithm based on SM2 encryption

With the rapid development of the domestic Internet of Things, my country's self-designed SM2 public key cryptographic algorithm has been widely used in the integration of the Internet of Things and blockchain data of blockchain chips. However, the current SM2 public key cryptography algorithm has the problems of low calculation speed and excessive consumption of hardware resources. In view of the above problems, this article applies the Kogge-Stone adder method to solve the problem of low calculation speed; based on the characteristics of the AVR architecture, a method is proposed to optimize the inner loop operation of the Montgomery modular multiplication to reduce the consumption of hardware resources. Experiments show that the improved performance has a 26.2% performance improvement compared to before the improvement. The computing efficiency of the large integer modular multiplication operation is effectively improved, the resource consumption of hardware implementation is reduced, the balance between computing time and hardware overhead is better achieved, widely used in blockchain chips.
URLBiDCNN: malicious URL detection based on bidirectional long short-term memory and deformable convolutional networks

URLs (Uniform Resource Locators) are widely used on the Internet, but they are often used maliciously to carry out cyberattacks, causing significant losses to many enterprises and individuals. Therefore, it is crucial to spot those URLs to ensure network security. In this study, we propose a method for detecting malicious URLs that uses bidirectional LSTM and deformable convolutional network. First, the character vector corresponding to the URL is obtained by applying the embedding method, the bidirectional LSTM network is then fed the character vector to extract the global information in the URL, and the parallel deformable convolutional network receives the extracted data as input to learn multiple types of local area features. Finally, the fused local features are output to the FC network for URL classification. In this study, we conducted comparison experiments of different methods on different datasets. From the experimental results, on the three sampled datasets, the method's accuracy was 96.96%, 99.85%, and 96.43%, respectively, comparing with other research methods, the accuracy of the method proposed in this study for malicious URL detection was significantly improved.
Research on technology of part capability type recognition based on knowledge learning

By making deep analysis on the big data information of historical product, the technology of structured data classification based on deep learning can form knowledge for part capability type recognition and judgment, build a model of capability type recognition on the basis of deep neural network, and also develop a software system of capability type automatic recognition ,for assisting the recognition of part capability type. For part newly imported into the system, combined with its attached attribute information, this technology can automatically identify and recommend the capacity type, and forms a set of knowledge-based method for the recognition and judgment of part capacity type.
Portrait video matting via depth information and temporal-spatio consistency

We propose a stable portrait video matting method without any auxiliary inputs like pre-captured background or trimap, but achieves competitive or even better performance compared to existing methods. In this paper, we observe that depth information has significant effect on human matting task since the target is at smaller depth with high probability especially for conference scenes. To this end, we design two decoder branches for coarse depth estimation and matting respectively. Furthermore, we utilize a temporal-spatio consistency module (TSCM) to improve temporal coherence and enforces our network to pay more attention to the foreground at smaller depth. Moreover, existing video matting evaluation metrics are almost derived from image matting, we introduce a simple but efficient algorithm to check flicker clips of the alpha video which reflects its stability.
Perancangan Model Prototype Sistem Informasi Pengelolaan Barang Bukti Pada Divisi PB3R Di Kejaksaan Negeri Kota Bekasi

Kejaksaan has various special fields, one of which is the field of Evidence and Confiscated Goods. This field has the task of managing data and storing evidence of cases, but the existing data management process is still not effective because data management is still done manually. In the process of searching for evidence, there are often obstacles in finding the required evidence, either for the needs of the trial or to be returned to the rightful owner of the evidence. To solve the existing problems, the design of an evidence data management information system in which there are several features supporting work activities will solve the existing problems. The design of this information system uses a prototype model which includes analysis of user needs, interface design and interface display testing. With the design of an information system for managing evidence data, it has facilitated the performance of the prosecutor's staff, especially in the field of Evidence and Confiscated Goods, in managing existing evidence.
SISTEMPENDUKUNG KEPUTUSANMENENTUKAN MAHASIWA LULUSAN TERBAIK DI FAKULTAS ILMU-ILMU SOSIAL UNIVERSITAS DEHASEN BENGKULUMENGGUNAKAN METODE AHP

Abstract: Decision Support System for Determining the Best Student in the Faculty of Social Sciences, University of Dehasen Bengkulu Using the "Analytical Hierarchy (AHP) Method"&#x0D; The ability to make quick and careful decisions will be the key to success in global competition in the future. Having a lot of information alone will not be enough, if you are able to mix it quickly into the best alternatives for decision making, to help humans, especially decision makers in determining virtues, in a precise, efficient and effective manner, a decision-making model known as the System is needed. Decision Support (SPK). Data processing aids accompanied by software can increase the ability of decision makers, improve accuracy and speed up the process.&#x0D; From the design process to the implementation of the system that has been carried out in the Decision Support System for Determining Outstanding Students at the Faculty of Social Sciences, Dehasen University, Bengkulu Using the Analytical Hierarchy (AHP) method, several conclusions can be drawn as follows:&#x0D; &#x0D; Decision Support System for Determining Outstanding Students at the Faculty of Social Sciences, University of Dehasen Bengkulu Using the Analytical Hierarchy Method (AHP is a website application that can be accessed flexibly by both users and admins/campus parties, only with an internet connection.&#x0D; This system can already be used to provide detailed purchase transaction reports, sales reports and product reports.&#x0D; &#x0D; Keywords, AHP, SPK, Mysql &amp; PHP
Analysis of Sentence Errors in Fiction Text Essays Theme 8 Class V MI Al-Iman Bulus School Year 2021/2022

This study aims to describe several errors in sentences, namely (1) errors in the use of periods, (2) errors in the use of sentence structures, (3) errors in the use of prepositions, and (4) errors in the use of parent sentences and subsentences in class V MI fiction text essays. This study uses qualitative research methods with qualitative descriptive research types. The subjects of the study were students of class V MI Al-Iman Bulus. Data collection techniques use observation and documentation. Data collection in this study used an interactive model from Miles and Huberman, namely, data collection, data reduction, data presentation, and drawing conclusions. The results showed that the total number of sentence writing errors was 200. 96 errors in the use of periods with an error percentage of 48%, 42 errors in the use of sentence structures with an error percentage of 21%, 30 errors in the use of prepositions with an error percentage of 15% and 32 errors in the use of parent sentences and children with an error percentage of 16%.
Analysis of the Value of Character Education in Arleen Alexandra's Fairy Tale I am a Great Leader and Its Relevance as a Learning Support Book for Elementary School Students

This study aims to (1) analyze the intrinsic elements in Arleen Alexandra's fairy tale I am a great leader, (2) the value of character education in Arleen Alexandra's fairy tale I am a great leader, (3) the relevance of Arleen Alexandra's fairy tale I am a great leader as a learning support for elementary school students. This type of research uses descriptive qualitative research. The object used in this study was the fairy tale book I am the Great Leader by Arleen Alexandra. This research focused on the educational value of character education contained in Arleen Alexandra's fairy tale I am a great leader and its relevance as a supporting book for elementary school students' learning. The data source is a collection of fairy tales, fairy tale quotes. The research instruments used in this study are data recording cards containing narratives and conversations used in this study are Data logging cards that contain narrations and conversations that are fairy tale quotes. Data collection in this study was carried out using library techniques, reading techniques, and recording techniques. In data analysis techniques, content analysis (contect analysis) is used. The results of the analysis in this study can be concluded that (1) the intrinsic elements of the fairy tale I am the great leader of Arleen Alexandra's jarya consist of: (a) themes, (b) characters and characterizations, (c) plot, (d) setting, (e) point of view, (f) message. (2) the value of character education in Arleen Alexandra's fairy tale I am a great leader, namely: honest, tolerance, hard work, creative, independent, curiosity, respect for achievement, friendly or communicative, peace-loving, social care, responsibility. (3) The fairy tale book I am a great leader by Arleen Alexandra is relevant to be used as a learning support book for elementary school students, namely: sentence length and vocabulary in accordance with the reasoning power and reading ability of students, themed friendship, health and other themes that are relevant to the age and daily experience of students, in accordance with the interests and hobbies of students, In accordance with morals and religion that is conveyed without patronizing, the structure of written language (spelling, grammar, cohence) is correct, which is presented variously (through rhyming words, poetry and dialogue) that is easy to understand, the information in the book does not harass any particular group of people.
The Influence of Collaborative Strategic Reading (CSR) Strategy on Students' Learning to Read Comprehension of Explanatory Texts in Class XI SMA Pertiwi 1 Padang

There are three objectives of this research. First, it describes reading comprehension skills before using Collaborative Strategic Reading (CSR) strategies in learning to read and understand explanatory texts for class XI SMA Pertiwi 1 Padang. Second, it describes reading comprehension skills after using Collaborative Strategic Reading (CSR) strategies on the reading comprehension skills of class XI SMA Pertiwi 1 Padang. Third, analyzing the effect of Collaborative Strategic Reading (CSR) strategy on the reading comprehension skills of explanatory texts of class XI SMA Pertiwi 1 Padang. This type of research is quantitative research with experimental methods. The research design is a one group pretest and posttest design. The population in this study were students of class XI SMA Pertiwi 1 Padang for the academic year 2022/2023, totaling 307 students. Data were analyzed using percentage formula, arithmetic average formula, and t-test. The research instrument was an objective test, namely a test of reading comprehension skills before and after using Collaborative Strategic Reading (CSR).
Digital Handbook Development Design "Religious Board Games" for Early Childhood

This study aims to develop teaching materials using a game system that is considered suitable for Early Childhood, which is still in process which is also adjusted to the psychological aspects of students. Teachers also involve students in the learning process through the Digital Guidebook "Religious Board" to stimulate children's brains to develop properly according to their age. This research also uses Thiagarajan's 4-D (Four-D) development model consisting of 5 units, but this research only reaches the design stage. The results of teaching material research according to experts show that the teaching materials developed have very feasible criteria as evidenced by the games played by students in schools, especially kindergartens, get very good appreciation.
Modernization of Teacher Education in China: from Metaphor to Program

The relevance of the study is due to the need to rethink and apply successful reform practices in the national education system of China. One of the effective means of translating ideological and political concepts is metaphorical language. The publication reveals the essence of the metaphor “Four rays and eight pillars”. The aim of the article is to study the peculiarities of development and implementation of reforms in China on the example of modernization of professional and pedagogical education. The methodological basis of the study is an interdisciplinary approach, the theory of education development in the transition to a post-industrial society, comprehensive research in the field of education reforming. The concepts, principles, ways, state guarantees of professional education reform in China were characterized. The features of educational reform development in China were revealed: close connection with national strategies (“One Belt and One Road”, “Innovation Drive”, “Artificial Intelligence”, “Rural Restoration”), ideological education of teachers, strengthening of basic education teachers. Teacher training includes content and instrumental-technological aspects. The following ideas may be useful for the Russian educational system: self-study as a teacher’s norm of life; active mastering of hybrid learning; anticipatory rather than catch-up teacher training; organization of motivated activities (Strong Teachers program); accuracy, discipline and order in educational practice; creation of digital platforms for continuing teacher education. The conclusion outlines the prospects for the development of the system of teacher education, taking into account the Chinese specificity.
Formation of Goal-Setting Skills as an Integral Component of a Teacher’s Professional Development

The article reveals the concept of goal-setting. In defining the concept of a goal, we proceed from the fact that the goal should express the planned results of activities. The goal-setting ability is considered as a system-forming skill both in the preparation of future teachers and in the improvement of professional competencies of practical teachers. The purpose of the article is to present the results of a study on the justification and development of the content of teaching teachers aimed at the formation of goal–setting skills. The methodology of the research is a system-activity approach, in which the results of education are considered as a system-forming component. In the analysis of psychological, pedagogical and methodological literature, the concept of goals in teaching was clarified, generalized areas of goal-setting – subject and meta-subject– were identified, problems of the formation of professional competencies of teachers in terms of goal-setting and ways to solve them were identified. The identification of problems in the formation of goal-setting skills occurred both on the basis of the analysis of literature, written works of teachers and students, and in the process of observing their practical activities. As the main methodology for the formation of goal–setting skills, the SMART method was chosen– the method of setting “smart” goals. In the process of teaching mathematics teachers at advanced training courses, as well as teaching students– future teachers, training aimed at developing goal-setting skills using the SMART methodology was conducted as an approbation. In conclusion, conclusions are drawn about the expediency of organizing special training in goal-setting skills for both future teachers and working teachers as part of professional development.
INVESTIGATION OF THE BIOREMEDIATION PERFORMANCE OF COW-DUNG AND WIRE-CROTON ON CRUDE OIL POLLUTED SOIL

Crude oil exploration is associated with oil spillage causing environmental degradation including loss of soil fertility and biodiversity. Various technologies are available for remediating crude oil polluted soil, but, bioremediation seems to be more environmentally friendly and cost effective. Thus, the current work is on the bioremediation of crude oil polluted soil using cow dung and wire croton leave as the amendments. It was conducted as a batch process and was monitored for 42 days (six weeks). Separate cow dung and wire croton, and different quantities of cow dung and wire croton were blended to remediate the soil. The analysis conducted included the Total Petroleum Hydrocarbon (TPH), Hydrocarbon utilizing Bacterial (HUB) and the Total Organic Carbon (TOC) content of the soil. The result shows that wire croton and cow dung have the potential to be used as bioremediation nutrients. When these nutrients were mixed at different proportions, the combination involving 30 g of cow dung and 30 g of wire croton gave the least performance in terms of HUB, TPH and TOC across the duration of the study, and the maximum was achieved using 200 g of cow dung and 200 g of wire croton as shown by over 650 thousand HUB increment, 95 % hydrocarbon degradation, and 76.3 % total organic carbon obtained. This shows that appropriate combinations of cow dung and wire croton is required to obtain a higher performance using both nutrients for remediating a crude oil polluted soil. KEYWORDS: Bioremediation; cow dung; wire croton; nutrients; degradation
Utilizing Deep Learning Techniques for Text and Image Capturing Summarization in Information Retrievals

In this paper, a novel information retrieval and text summarization model based on deep learning (DL) is introduced. The model comprises three primary stages, including information retrieval, template generation, and text summarization. The initial step involves utilizing a bidirectional long short term memory (BiLSTM) technique to retrieve textual data. This approach considers each word in a sentence, extracts relevant information, and converts it into a semantic vector.
Cyber Risk among High School Students: A Thematic Review

Technology Industrial Revolution 4.0, such as the internet, continues to develop in surprising ways where today, our life, education, and business rely on it. People, specifically high school students, are the majority using the internet in all countries, which means they have a higher risk of being exposed to cyber risk. However, some academic research has been done on cyber risk among high school students in Malaysia. Therefore, this thematic review (TR) aims to synthesise literature from 2018 to 2022 on the cyber risk among high school students using ATLAS.ti 22. A keyword search, followed by a filter using inclusion criteria from SCOPUS and Science Direct, identified 179 peer-reviewed journal articles. Yet, after the inclusion and exclusion process, only 33 articles were used as the final articles to be reviewed. A thematic review identified four clusters: cyber risk types, cyber risk effects, victim characteristics, and cyber risk prevention. Hence, this paper incorporates the latest information on cyber risk examples that high school students usually face. The findings will help future research on eliminating the cyber risk for high school students. They can serve as a directive and a remedy for the education sectors and policymakers to address the cyber threat.