Reviewerly/exHarmony huggingface dataset:
A Comparative Analysis of English Test Scores in the Vietnamese National High School Graduation Examination During the Period 2020-2023

English is the most used language online, with nearly one billion users typing and chatting in the language. English is now widely spoken throughout the world and is necessary for people to be able to communicate and fit into the real world. In Vietnamese high schools, learning English has become an important task for students. The aim of this paper is to cary out a comparative analysis of English test scores (ETSs) in the Vietnamese National High School Graduation Examination during the period 2020-2023. In this study, datasets of English test scores during the period 2020-2023 were first collected. To find patterns of ETSs, the frequency of ETSs was firstly calculated. Histograms were then used to plot the frequency against ETSs to study the distribution of ETSs in each year. Finally, a comparative analysis of ETSs during the period was carried out. It was found that the distribution of ETSs during the period 2020-2023 was skewed to the right, which shows that the number of high ETSs tends to be more prominent. In addition, the high ETSs in 2021 were found to be much higher than those obtained from the yeas of 2020, 2022 and 2023. Findings in this study suggest that ETSs during the period 2020-2023 met the requirements for graduate recognition. It can be concluded that the role of English language in career advancement is undeniable in this era of globalization. Keywords: Comparative analysis, English Test Scores, Vietnamese National High School Graduation Examination, Period 2020-2023.
A Discussion on the Reform of English Teaching in Local Engineering-Focused University based on the Data of Graduates’ Employment

With the goal of serving regional economy and social development, local universities have their own characteristics in many aspects, such as running orientation, targets of cultivating students, employment of graduatest, conditions of running universities and etc. This paper takes a provincial key Engineering-focused university as an example to analyze the data of graduates’ employment and requirements for English skill. The reasons for the students lacking adequate training in English for Special Purposes (ESP) and how to reform English teaching to satisfy the needs of students are discussed. A model to reform the current curriculum by integrating teachers’ resources of public English teaching and specialized courses teaching to complete the ESP teaching in every stage of university English teaching is proposed.
Sentiment Analysis of Student Evaluation of Teaching Based on Bi-LSTM Algorithm

As the basis of evaluating the teaching quality, the data of students' teaching evaluation play an important role in teaching management and improving teaching quality in universities. Nevertheless, it is challenging to conduct statistical analysis of a substantial number of instructional evaluation texts using manual or conventional technologies. How to deal with and make use of students' teaching evaluation texts efficiently has become an urgent problem to be solved. Based on Bi-directional Long Short-Term Memory (Bi-LSTM), this paper takes students' teaching evaluation texts dataset as the research object to analyze the emotional tendency of students. From the evaluation results, compared with Simple Recursive Neural Network (Simple RNN) and single Long Short-Term Memory (LSTM), the sentiment detection model based on Bi-LSTM has higher accuracy in students' teaching evaluation texts sentiment analysis, the verification accuracy can reach 90.77%, and the testing accuracy can reach 84.33%.
Evaluating User Experience and Effectiveness of an Immersive Virtual Learning Environment

This paper presents the user-centered prototyping and evaluation of an immersive Virtual Reality (VR) learning environment for vocational education. The VR prototype was developed to support Swiss apprentice electricians in preparing for their final practical exams. Based on proven questionnaires, an evaluation scheme was developed to assess the user experience both in the context of the iterative prototyping process and in the context of a field study. The field study with 70 apprentices was conducted to assess the impact of the VR learning prototype on learning success.
Hubungan Penerapan Model Reguler Pendidikan Kepramukaan dengan Hasil Belajar Kognitif Siswa SD

This study aims to determine the relationship of applying the regular model of scouting education (x) with students' cognitive learning outcomes (y) at sd negeri 01 kota bengkulu. This type of research is quantitative research. The population of this study amounted to 41 student scout members who followed the regular model of sampling total sampling technique. Data collection techniques used questionnaires, recapitulation of weekly repeat values ​​in cognitive and documentation aspects. Research instruments were tested using validity and reliability. While prerequisite analysis test using normality test, homogeneity test, and hypothesis test. Data analysis technique is done by using "product moment correlation" formula. This technique is used to determine the significance of independent variable relation and dependent variable by rhitung count with rtabel with 5% significant level. Based on the results of data analysis diproleh value rhitung = &gt; 0.698 rtabel = 0.308 which means there is a relationship of the regular modeling modeling of scouting education with students' cognitive learning outcomes with very strong interpretation. Furthermore, from the significance test results obtained t count 6.087 ≥ ttabel = 1.664 which means there is a significant relationship between variables, with a contribution of 48.72% between the application of regular model of scouting education with cognitive learning outcomes of elementary school students 01 kota bengkulu. Based on this, it can be concluded that ha accepted, where there is a relationship of application of regular model of scouting education with cognitive learning outcomes at state elementary school 01 kota bengkulu
Evaluation of Secondary Teachers’ Knowledge and Skills, Regarding the Information and Communication Technologies Utilization, before and after the COVID-19 Era, in Greece

The current wide exploitation of information and communication technologies (I.C.T.) enhances students’ ability to further acquire knowledge and skills. In today’s era when society is overwhelmed by a multitude of gadgets (laptops, tablets, smart-phones, etc.), students adapt very easily to technologically supported learning environments and learn to utilize I.C.T. It is a fact that during the global pandemic (COVID-19) the I.C.T.’s implementation of modern and asynchronous distance education supported greatly the educational community at all educational levels. The purpose of the study was the detailed evaluation of the knowledge and skills of Greek teachers in the exploitation of I.C.T., and the comparison of their “armamentarium” with those of the pre-COVID-19 era, (where I.C.T.s’ tools in teaching were apparently very limited). Stratified sampling was carried out with proportional allocation (Panaretos & Xekalaki, 2000). Subsets of the population were selected which met certain properties. The method was used because there was an uneven population between the geographical prefectures of Greece from where the sample was collected. During the research process, appropriately structured questionnaires of 40 questions were fully completed by 130 teachers. The research questions were searching for: 1) The degree of satisfaction among teachers who used I.C.T. before and after COVID-19 pandemic. 2) The satisfaction rate of teachers towards the educational success of I.C.T.s’ tools, before and after COVID-19. With the term “success” we mean the degree of satisfaction with acquiring new knowledge thanks to the use of I.C.T.s’ tools in teaching. Following COVID-19 pandemic along with the forced implementation of distance learning, there was an increase in the number of teachers participating in I.C.T. training programs from 18.8% to 38%. The percentage of teachers who claimed that the quality of the provided education is improving, increased from 53.8% to 68%. Additionally, after the COVID-19 era, the percentage of teachers who were satisfied with the use of I.C.T. in theory courses increased from 47.5% to 64%, while the percentage of teachers who supported the use of I.C.T. in laboratory courses decreased from 60.9% to 51.3%. The percentage of teachers who wished for the existence of e-courses adapted to the students needs improved from 52.5% to 56%. An increase in teachers’ gaining satisfaction with school equipment was observed from 46.3% to 60%, while the percentage of schools that enhanced the implementation of I.C.T. techniques also increased from 37.5% to 58%. Teachers’ opinion over I.C.T. did not dramatically change after the implementation of distance learning. However, a more positive picture emerges regarding both the degree of satisfaction with the I.C.T. use, integration and implementation tools, as well as the degree of enhancement of students’ knowledge from the use of I.C.T.
Investigating of Deep Learning-based Approaches for Anomaly Detection in IoT Surveillance Systems

Anomaly detection plays a crucial role in ensuring the security and integrity of Internet of Things (IoT) surveillance systems. Nowadays, deep learning methods have gained significant popularity in anomaly detection because of their ability to learn and extract intricate features from complex data automatically. However, despite the advancements in deep learning-based anomaly detection, several limitations and research gaps exist. These include the need for improving the interpretability of deep learning models, addressing the challenges of limited training data, handling concept drift in evolving IoT environments, and achieving real-time performance. It is crucial to conduct a comprehensive review of existing deep learning methods to address these limitations as well as identify the most accurate and effective approaches for anomaly detection in IoT surveillance systems. This review paper presents an extensive analysis of existing deep learning methods by collecting results and performance evaluations from various studies. The collected results enable the identification and comparison of the most accurate deep-learning methods for anomaly detection. Finally, the findings of this review will contribute to the development of more efficient and reliable anomaly detection techniques for enhancing the security and effectiveness of IoT surveillance systems.
Sentiment Analysis on Banking Feedback and News Data using Synonyms and Antonyms

Sentiment analysis is crucial for deciphering customers’ enthusiasm, frustration, and the market mood within the banking sector. This importance arises from financial data’s specialized and sensitive nature, enabling a deeper understanding of customer sentiments. In today’s digital and social marketing landscape within the banking and financial sector, sentiment analysis is significant in shaping customer insights, product development, brand reputation management, risk management, customer service improvement, fraud detection, market research, compliance regulations, etc. This paper introduces a novel approach to sentiment analysis in the banking sector, emphasizing integrating diverse text features to enable dynamic analysis. This proposed approach aims to assess the sentiment score of distinct words used within a document and classify them as positive, negative, or neutral. After rephrasing sentences using synonyms and antonyms of unique words, the system calculates sentence similarity using a distance control mechanism. Then, the system updates the dataset with the positive, negative, and neutral labels. Ultimately, the ELECTRA model utilizes the self-trained sentiment-scored data dictionary, and the newly created dataset is processed using the SoftMax activation function in combination with a customized ADAM optimizer. The approach’s effectiveness is confirmed through the analysis of post-bank customer feedback and the phrase bank dataset, yielding accuracy scores of 92.15%and 93.47%, respectively. This study stands out due to its unique approach, which centers on evaluating customer satisfaction and market sentiment by utilizing sentiment scores of words and assessing sentence similarities.
SACINet: Semantic-Aware Cross-Modal Interaction Network for Real-Time 3D Object Detection

LiDAR-Camera fusion-based 3D object detection is one of the main visual perception tasks in autonomous driving, facing the challenges of small targets and occlusions. Image semantics are beneficial for these issues, yet most existing methods applied semantics only in the cross-modal fusion stage to compensate for point geometric features, where the advantages of semantic information are not effectively explored. Further, the increased complexity of the network caused by introducing semantics is also a major obstacle to real-time. In this paper, we propose a Semantic-Aware Cross-modal Interaction Network(SACINet) to achieve real-time 3D object detection, which introduces high-level semantics into both key stages of image feature extraction and cross-modal fusion. Specifically, we design a Lightweight Semantic-aware Image Feature Extractor(LSIFE) to enhance semantic samplings of objects while reducing numerous parameters. Additionally, a Semantic-Modulated Cross-modal Interaction Mechanism(SMCIM) is proposed to stress semantic details in cross-modal fusion. This mechanism conducts a pairwise interactive fusion among geometric features, semantic-aware point-wise image features, and semantic-aware point-wise segmentation features by the designed Conditions Generation Network(CGN) and Semantic-Aware Point-wise Feature Modulation(SAPFM). Ultimately, we construct a real-time(25.2fps) 3D detector with minor parameters(23.79 MB), which can better achieve the trade-off between accuracy and efficiency. Comprehensive experiments on the KITTI benchmark illustrate that SACINet is effective for real-time 3D detection, especially on small and severely occluded targets. Further, we conduct semantic occupancy perception experiments on the latest nuScenes-Occupancy benchmark, which verifies the effectiveness of SMCIM.
Analysis and Design Directions for the 4-year University Beauty Department Curriculum and Microdegree Programs

The purpose of this paper is to propose directions that should be considered when designing microdegree programs in 4-year university beauty departments, in order to adapt to rapidly changing society and industries. To gather data, we utilized the Academic Research Information Service (RISS) to collect and analyze literature on the curriculum of 4-year university beauty departments and literature regarding directions for domestic microdegree programs. As a result, the problems in the curriculum of 4-year university beauty departments have been identified as ‘Lack of emphasis on practical skills’, ‘Disorganized curriculum structure’, ‘Absence of personalization and suitability considerations’, ‘Inadequate incorporation of industry changes and trends’, ‘Challenges in practical application’, ‘Incomplete educational environment and facilities’, ‘Failure to address student demands and opinions’. As suggestions for the direction of domestic microdegree programs, it has been proposed to ‘The development and operation of microdegree programs focused on competency-based education in specific fields according to students' career interests is necessary’, ‘Promotional activities for motivating student engagement and participation in microdegree courses are required’, ‘Continuous student needs assessment, evaluation, and monitoring are necessary for improving the quality of microdegree programs and fostering institutional innovation’, ‘Enhancement of credit recognition for diverse educational experiences and collaboration with industries and government policies is needed’, ‘An establishment of a microdegree committee within universities and the promotion of participation from industry representatives, government policies, alumni, professors, and current students should be encouraged’, ‘The review of government support programs is necessary, and microdegree programs should not be operated superficially by universities solely for the sake of achieving results based on government support’, ‘The organization of competitions utilizing microdegree learning experiences and providing certification opportunities for job-related competencies should be implemented’. Based on the analysis of literature, the following conclusions were drawn regarding the directions to consider when designing microdegree programs in 4-year university beauty departments ‘Establishment of a committee for quality management of microdegree education’, ‘Design and feedback of microdegree programs based on the demands of beauty department students’, ‘Encouragement of easy goal-setting for beauty department students using microdegrees’, ‘Enhancement of competencies through integration between microdegrees and academic disciplines’, ‘Provision of job experience opportunities through microdegrees’, and ‘Importance of industry-academia collaboration and expansion of resources for microdegrees’.
Measures to Revitalize Overseas Employment through In-depth Study of People with Overseas Employment Experience

In order to promote overseas employment for beauty majors and successfully establish overseas employment, this study conducted an indepth study on beauty majors with overseas employment experience in English-speaking countries and analyzed the motivational factors, prior preparation, and problems of overseas employment. The purpose of the subjects' overseas employment was to accumulate experience and improve technical skills by taking on new challenges in various fields, such as learning new language related to work. The subjects studied the language through various methods, and said that preparation of practical skills was necessary. Therefore, there is an urgent need to develop a specialized program that allows overseas employment candidates to acquire both practical skills and language skills in a practical and systematic way. Korean beauty majors are capable of performing various procedures such as cuts, perms, and blow drying, and have delicate hand techniques and fast procedures, so they are recognized not only for their technical skills, but also in terms of beauty trends and services. This is believed to be because Korea's beauty education has developed into a segmented and organized system. However, they responded that the differences in the type of procedure, lack of experience with the equipment used, and cultural differences in performing tasks are weaknesses. In particular, it was pointed out that if you lack technical skills, you may be treated as a worker lacking both language and skills. In addition, problems such as customer complaints, racial discrimination, relatively high prices, medical emergencies, safety issues related to drugs, tax issues, and homesickness were mentioned. All subjects were satisfied with the overseas employment and said they would recommend overseas employment to their acquaintances. This is because it can be a new challenge to experience various experiences and cultures. In particular, it seems to have provided satisfaction to those who pursue an independent lifestyle due to freedom of working hours, working environment, and salary. As mentioned above, it is necessary to supplement strengths through developing language skills and practical capabilities, traits commonly identified from those who have overseas employment experience, to differentiate themselves from local hairdressers and to reduce problems in the early stages of settlement, thereby revitalizing overseas employment.
Optimization and Formulation of Fenofibrate Transfersome Using The Thin Layer Hydration Method

Abstract &#x0D; Background: Fenofibrate is a lipophilic drug that is used to treat hypercholesterolemia and hypertriglyceridemia in patients.. The low solubility of fenofibrate can be improved by creating a phenofibrate transfersome delivery system. The objective of this research was to determine the effect of phosphatidylcholine 90G, Tween 80, with sonication on fenofibrate transfersomesand to obtain the optimum composition of phosphatidylcholine 90G, tween 80, with sonication on critical parameters including particle size, zeta potential, absorption efficiency. For formula optimization, the factorial design method was applied. Phosphatidylcholine 90G composition, tween 80, with sonication were used as independent variables, with particle size, zeta potential, and sorption effectiveness as dependent variables.&#x0D; Method: The optimization was carried out with critical parameters of the fenofibrate transfersomes tested including particle size, zeta potential, and adsorption efficiency. The critical parameter test data were analyzed using factorial design.&#x0D; Result: The results showed that there was an effect of phosphatidylcholine 90G, tween 80, and sonication on fenofibrate transfersomes provide effect by including particle size, zeta potential, and sorption efficiency.&#x0D; Conclusion: The optimum proportion of phosphatidylcholine 90G was 95%, tween 80 was 5%, and sonication was 33,39 time. The transfersome ability of fenofibrate was good in the optimum formula in the particle size test was 23,675 nm and zeta potential 52,231 mv and the entrapment efficiency was 96,915 %.&#x0D; &#x0D; Keyword : Fenofibrat, Transfersome, phospatidicoline 90G, thin film layer, Factorial Design.