Reviewerly/exHarmony huggingface dataset:
Contrastive Research on Performance of Face Detection based on Classical and Deep Learning Algorithms

Face detection technology has always been hot in the field of computer vision. However, current face detection algorithms are difficult to be applied to any scene with both high speed and accuracy. At present, there are few comparative studies between classical algorithm and deep learning algorithm. In this paper, our motivation is to study different types of face detection algorithm and make a comparison. We compare the average precision and receiver operating characteristic curve of RetinaFace with Mobilenet and Resnet. We also compare the performance of classical algorithm Viola-Jones with RetinaFace and deep neural network module in OpenCV library. We compare their detection performance in terms of computation time, frame rate, detection accuracy and model size under the conditions of multiple faces, high exposure and pose change. This study provides guidance and basis for researchers and developers to choose or design face detection algorithms.
Design of High Performance Reed-Solomon Encoder Based on A Novel Half-multiplier

In this paper, aiming at the problem of high computation complexity in the hardware implementation of the Galois Field (GF) multiplier in commonly used Reed-Solomon (RS) coding algorithms, a half-multiplier based on this matrix method is redesigned and the RS coding module is also optimized. The simulated results are provided to show that the hardware resource of using the designed encoder can decrease by about 15% than that of using the Xilinx official encoder, while the accuracy of the coding keeps the same level.
Delay Prediction for Real-Time Video Based on Improved LSTM

The scale of mobile video users increases year by year. Ensuring the quality of mobile video user experience can not only improve user satisfaction, but also further promote the process of informatization. The key to ensuring the quality of mobile video user experience is to be able to predict the time of mobile video delay and prevent the occurrence of video delay; for the prediction of video delay, this paper proposes an improved algorithm based on LSTM network with Dropout optimization. By merging multiple models according to their accuracy to balance the errors generated by the models, overfitting can be prevented, and at the same time, the influence of the model trained by some special eigenvalues on the whole can be avoided, and eliminate the model's dependence on some special eigenvalues. It solves the problems of the original model's low prediction accuracy, weak generalization ability, and overfitting for video delay prediction. At the same time, according to the idea of optimizing the part first and then the whole, to reduce the time complexity of model training. The experimental verification shows that under the same conditions, compared with the original LSTM model, the improved model's prediction accuracy is significantly improved for predicts the video delay, which provides a factual basis for the guarantee of video user experience quality.
Analysis and Design of Intelligent Music Player System Based on Gesture Recognition

Gesture recognition based on computer vision is an important part of artificial intelligence. Gesture recognition is an important way of human-computer interaction and is of great significance to improve user experience. Aiming at the problem of intelligent control of traditional music player, this paper designed and developed an intelligent music player system based on gesture recognition, this paper discusses the method of gesture contour extraction, presents the gesture recognition method about fourier descriptor and neural network, and gives the design of the intelligent music player based on software engineering. Experiments show that the system has the advantages of high recognition rate, excellent performance and good user experience.
Research on Standardization of Semantic Relation and Ontology Representation Based on MDR

With the in-depth application of big data and artificial intelligence in various fields, the standardization of knowledge representation has attracted much attention from researchers. However, the current research on knowledge representation standardization mainly focuses on system construction, term registration, technology and domain application, etc., and there is a lack of representation model research on semantic relation organization from the perspective of semantics. Therefore, in order to standardize the representation of the conceptual system model, firstly studies the series of metamodels used to represent and store concepts and conceptual relations in the ISO/IEC 11179 standard, and based on the division of relations in the ISO 1087 standard, proposed Semantic Relation Metamodel Based on MDR standard, SRMM. Then, in order to realize the mapping from MDR conceptual system model to ontology, the rules for mapping conceptual system to OWL are defined. Finally, a data element registration system is designed and developed based on the EPDM data model, which verifies the availability of the proposed ideas and methods. Since this research adopts general international standards, the ideas and methods are also applicable to metadata standardization and knowledge representation standardization in other fields.
Multi-resolution Small Sample Face Recognition Based on Coupled Dictionary Learning

Multi-resolution small sample face recognition has always been a challenge in the field of face recognition. This paper proposes a multi-resolution small sample face recognition method based on coupled dictionary learning (MCDL). To expose the relationship between the representation coefficients corresponding to dictionary atoms and samples at different resolutions, MCDL introduces an analysis dictionary and jointly learns it with the synthesis dictionary. Besides, various coding coefficients are applied to each sample with varied resolutions throughout the multi-dictionary learning process so that the learnt dictionary is more realistic. Furthermore, we introduce the fractional norm into the model to remove the redundant information. Experimental results show that MCDL achieves good results and its recognition rate is higher than that of many algorithms.
Security Flaws in Dhillon and Kalra's User Authentication Scheme for IoT

Dhillon and Kalra proposed a multi-factor user authentication scheme for IoT. The authors claim their scheme to have practical utility for the IoT environment. However, we find that their scheme has numerous flaws such as insider attack and inefficient authentication. An adversary can work as a middle-man between the sensor node and the user, and the user can set-up a session key with the sensor node. Besides, the scheme does not establish the mutual authentication between every pair of entities. Thus, the scheme is inconvenient for practical use. We conclude this article by providing some suggestions for the improvement of the analysed scheme to remove the weaknesses identified in it.
StylePortraitVideo: Editing Portrait Videos with Expression Optimization

Abstract High‐quality portrait image editing has been made easier by recent advances in GANs (e.g., StyleGAN) and GAN inversion methods that project images onto a pre‐trained GAN's latent space. However, extending the existing image editing methods, it is hard to edit videos to produce temporally coherent and natural‐looking videos. We find challenges in reproducing diverse video frames and preserving the natural motion after editing. In this work, we propose solutions for these challenges. First, we propose a video adaptation method that enables the generator to reconstruct the original input identity, unusual poses, and expressions in the video. Second, we propose an expression dynamics optimization that tweaks the latent codes to maintain the meaningful motion in the original video. Based on these methods, we build a StyleGAN‐based high‐quality portrait video editing system that can edit videos in the wild in a temporally coherent way at up to 4K resolution.
Sentiment Analysis on Book Reviews Using Convolutional Neural Network (CNN) Long Short-Term Memory (LSTM) Hybrid

Sentiment analysis is one of the most prominent methods on gathering and analyzing insightful textual data from various sources. The information produced from such a method can be imperative in understanding the general public's sentiment on a certain product or service. Over the years, countless sentiment analysis models have already been established using known algorithms such as Naive Bayes, Support Vector Machine, and many more. However, with the advent of novel technologies and neural networking, recent studies have employed Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) Recurrent Neural Network together to formulate more efficient and modernized models (Rehman, Malik, Raza, & Ali, 2019). As such, the study proposed a similar model to analyze the sentiments of book user reviews from GoodReads categorized according to three distinct genres – children's, young adults’, and romance. The paper also aimed to determine the viability and effects of amalgamating features such as Word2Vec, POS, and SenticNet to the overall accuracy (Ayutthaya & Pasupa, 2018). Once the model was trained to the procured dataset, the results suggested that combining Word Embedding, POS, and SenticNet features drastically improves its performance in contrast to other tested variations. Amalgamating the three features to a CNN-LSTM hybrid model yielded an F1-score of 90%; whilst other variants with lacking features or a standalone CNN or LSTM model only resulted to F1-scores around 86% below. Graphing the performance of all the constructed models to an ROC curve also indicated the effectiveness of the proposed model – having an AUC value of 0.9588.
SISTEM PAKAR DIAGNOSA PENYAKIT SAPI SEBAGAI UPAYA PENCEGAHAN PENYEBARAN WABAH PMK DI LAMONGAN

On May 5, 2022, Indonesia was hit by an outbreak of PMK in livestock. Until now, in August 2022, there are 20 provinces, 215 districts/cities, 1,808 sub-districts and 7,434 villages that are still actively infected with nail and mouth disease (PMK). The emergence of PMK is an epidemic that results in huge losses to cattle farmers. Especially if you do not have knowledge about the transmission of the disease. One of the efforts to prevent the spread of livestock disease is to implement an expert system for diagnosing cattle disease using the forward chaining method. Where this system will help farmers to provide knowledge of disease symptoms and diagnosis of disease, so that farmers are able to take initial action to handle their livestock.
Analysis of College Major Textbooks on Play Instructions Reflecting the 2019 Revised Nuri Curriculum

Objectives The goal of this study is to suggest the directionality of college major textbooks on play instructions so that the play-oriented curriculum of the 2019 revised Nuri curriculum can be actively implemented in the field of early childhood education. Methods This paper selected 10 play instruction textbooks published by September 2021, reflecting the 2019 revised Nuri course and analyzed the content by dividing the total composition ratio of textbooks and the theoretical and practical sections of textbooks. Results Regarding the development directions of college major textbooks on play instructions, the findings raise a need to strike balance between theory and practice in terms of composition. In terms of content, the study proposed to increas the purpose of curriculum revision and implementation cases, increas the contents and examples of reconstructing the play environment, change the content of play observations and assessments, increase real practices for infants, reach a universal consensus on the composition of real practices in advance, provide directionality for teachers' play supports, integrate the five areas and content categories of the Nuri Curriculum in composition, and provide a variety of play types and materials. Conclusions The present study analyzed the content of revised college major textbooks on play instructions and provided several implications for the development of future college major textbooks on play instructions, thus holding its significance.
The effect of creativity and character activities through traditional play on playfulness and creative personality for child

Objectives In this study, we tried to investigate the effect on children's playability and creativity through creative personality activities through various traditional games. Methods For this purpose, creative personality activities through traditional play were conducted for 40 children in two classes of 5 years old, 20 each, at S daycare center located in M city. ANCOVA was performed as a covariate. Results The group that performed creative personality activities through traditional play showed a significant difference in playability and creativity from the comparison group. Conclusions Creative personality activity through traditional play had a significant overall effect on physical spontaneity, social spontaneity, cognitive spontaneity, expression of pleasure, and sense of humor during the development of children's playability. In creativity, there were significant effects on uniqueness-curiosity, openness-humor, sensitivity-various interests, imagination-playability, and independence-preoccupation.
An effects meta-analysis of using games in elementary school English classes

Objectives The effects of individual studies on using games in elementary school English classes are synthesized to confirm or deny the individual result against the average effect sizes. Recommendations follow for the design of games in elementary school English classes using an optimal combination of modulated variables. Methods Twenty domestic academic publications in the subject of English education made up the set of papers to be examined. The data were arranged in Excel, and the effect size was determined using the meta-analysis program CMA. According to the composition time and type of the game, organizational form, and the 2022 updated curriculum, the results of comparing and assessing the effects of elementary school English curriculum games were separated into knowledge-understanding, process-function, and value-attitude categories. Results The benefits of learning new words have been established in terms of knowledge and comprehension. In terms of process and function, understanding was more important than expressing, and in terms of value and attitude, interest was more important than attitude and confidence. Regarding the length of the game's configuration, utilizing it for the entire 40 minute class was more efficient than using it only in part (about 10 to 30 minutes). The use of online games, followed by bingo and cards, has the biggest impact in terms of game types. Group sessions, followed by individual and paired tasks, had the most positive impacts on game organization. Conclusions Textbook analyses on attention level improvement(Lee, Jung-Hyeon &amp; Ihm, Hee-Jeong, 2014; Jang, Jin-Kyung &amp; Lee, Seong-Won, 2014; Kim, Sung-Shin &amp; Boo, Kyung-Soon, 2009; Choi, Hye-Wook, 2006), game types(Eun, Ji-Seon &amp; Lee, Je-Young, 2018; Hwang, Hui-Jae, 2006), and pair impact studies(Han, Mi-Yun &amp; Kim, Hye-Ryun, 2014) are only a few examples of the individual or textbook analysis studies that may be seen in earlier research. These individual studies presents limitations to understand the full impacts of using games to teach English in elementary school despite the fact that these researches are significant as individual studies. By synthesizing the results of previous experimental studies, this study comprehensively examined the effects of knowledge, understanding, process function, and value attitude according to the 2022 revised curriculum. An additional significant conclusion was attained as to how the effects of games are varied depending on categories like organization type, duration and types of games in elementary school English classes.
A Study on the Effectiveness of TBL Field-Based Early Childhood Movement Subjects: Focusing on the Perception and Level of Early Childhood Movement Education by Pre-service Early Childhood Teachers, Movement Teaching Efficacy, and Cooperative Self-efficacy

Objectives The purpose of this study is to investigate the effectiveness of the TBL field-based early childhood movement subject, focusing on the perception and level of early childhood movement education, movement teaching efficacy, and cooperative self-efficacy. Methods For this, SPSS 25.0 was used to verify the statistical significance between the pre-average score of the research variables and the post-average score of 45 students who took the TBL field-based early childhood movement education among early childhood education students of A University in Chungcheong-do. The corresponding sample T-test, which compares and analyzes the data of paired samples of study variables, was confirmed in the 95% confidence interval. Results These are the main findings. First, it showed that the descriptive statistics for each variable of the perception of movement education, movement teaching efficacy, cooperative self-efficacy were higher than the median, whereas the post-score of the level of movement education was in the 3 point range and the pre-score was relative low in the 1 point range. Normality has been shown to be satisfactory. The difference in the average score of the research variables between pre- and post- TBL field-based early childhood movement education classes was found to have improved from at least .16 to 2.15 points. In addition, as a result of verifying the difference between pre- and post scores in the importance, necessity, and practicability of early childhood movement education, the post-average score was higher than the pre-average score, and had statistically significant differences. Second, it was found that there was a statistically significant difference in the effect of the TBL field-based early childhood movement subjects on the perception and the level of early childhood movement education, movement teaching efficacy, and cooperative self-efficacy. This can be interpreted as the effectiveness of the early childhood movement subjects applied with the TBL field-based innovation teaching method has been verified. Conclusions The results of this study were helpful in improving early childhood teachers’ confidence in applying movement education to the early childhood education field. These are the results of confirming the effectiveness of improving their expertise in early childhood movement education. Through this, we suggested the ways to apply the TBL field-based innovation teaching method to the early childhood education subjects.
Exploration of implementation plans for Marine Exchange Education Bsed on Multicultural and Convergent Perspectives in Elementary Social Studies

Objectives This study presented the necessity and specific action plans for maritime exchange education according to the perception that marine exchange education is insufficient in elementary social studies in the era of increasing marine exchange. Methods Since Korea has three sides of the sea, it has been developing maritime exchanges with various countries for a long time. Therefore, in this study, how Korea has developed maritime exchanges from the past to the present was examined through various literature. In this process, I looked for what is easy to present to elementary school students. In addition, the maritime exchange section presented in the current elementary social studies textbook was analyzed and problems and alternatives were presented. Results Currently, there is no content related to marine exchange in elementary social studies textbooks. The textbook identifies the ocean with the topography of the sea. Accordingly, the focus is on the lifestyle of people living in the sea. Through this, students cannot find the importance and meaning of marine exchange. Accordingly, the specific steps and methods of marine exchange education in the elementary social studies department were presented from the perspective of marine ethics, multicultural perspective, convergent thinking ability cultivation, and recognition of regional identity in the historical transformation process. In addition, the specific steps and methods of marine exchange education presented were presented and generalized by presenting cases of applying them to international exchange classes. Conclusions With globalization, maritime exchanges are increasing. Accordingly, elementary social studies departments should actively include contents related to marine exchange education in textbooks. However, the field does not know what marine exchange education is and how to practice it. Therefore, in this study, the necessity of marine exchange education and specific practical steps were presented. In addition, it was possible to generalize by showing actual practice cases according to the research results. It is meaningful that this research is the first attempt in the elementary social studies department, and we hope that complementary research will be actively conducted in the future.
Operation Review

The purpose of this paper is to examine the current status and problems of the operation of the Korean language curriculum so that the Korean language curriculum (KSL) can establish its status as a true national level curriculum and to find ways to improve its operation. Accordingly, the current status and problems of the operation of the current Korean language curriculum were examined and measures were sought to improve the operation of the Korean language curriculum so that the 2012 Korean language curriculum and the 2017 revised Korean language curriculum could establish their status as true national-level curriculum. Three problems of the Korean language curriculum that need to be improved in order to acquire a status suitable for the national level curriculum were pointed out. First, there was a problem that the opening of Korean language classes could not keep up with the needs of students. Second, it was pointed out that the operation of the Korean language education instructor support system was insufficient. Third, it pointed out the problem of the Korean language education support delivery system that cannot deliver it to learners even though systems and means are in place. And three measures were proposed to improve this. First, it was proposed to operate a Korean language curriculum by sharing local community educational resources. It was argued that by integrating and operating Korean language education programs operated by various ministries and institutions, the limitations of the Ministry of Education's physical human resources can be overcome and learners' access to educational services can be improved. Second, in order to operate the Korean language curriculum by sharing local community educational resources, it is necessary to change the consciousness of specific ministries, especially the Ministry of Education. It was argued that the Ministry of Education's leading and active attitude is necessary to clarify the delivery system of Korean language education conducted by various ministries and institutions. Third, it was argued that the diversification of delivery media such as online content should be made as a way to increase accessibility to Korean language education. In particular, the 'lowest level of achievement' introduced in other curriculums was applied to the Korean language exchange course, and the necessity of online content degradation was argued.