Reviewerly/exHarmony huggingface dataset:
The development of learning media based markerless augmented reality (AR) in cell organelle sub concept

The concept of cell structure is an abstract concept that requires representation to help students understand. The representation that can be used is markerless augmented reality. The purpose of this study was to develop a markerless augmented reality-based learning media on the concept of cell organelles. The research method used is the ADDIE method (Analysis, Design, Development, Implementation, Evaluation). The research instruments were flowcharts, storyboards, interview sheets, and validation sheets (questionnaires). Data analysis was carried out descriptively for the stages of making markerless augmented reality learning media based on the results of interviews, Flowcharts & Storyboards. The data from validation was analyzed quantitatively. The Stages of analysis are by analyzing learning media in schools and analyzing the concept of cell organelles. The results of the stage analysis show that the cell organelle is an abstract concept so that it requires learning media to explain the concepts. Media development involves several visual processing applications (2D or 3D). Augmented Reality-based learning media application that is made markerless. Markerless Augmented reality consists of three main parts: Media database, camera, database processing device. The Validation testing with three validators. The results showed that interactive learning media based on markerless augmented reality got a valid and feasible category to be used as a learning resource by students in the learning process.
Job satisfaction and its impact on the performance of employees in the Ministry of Finance in the Red Sea State

The study aimed to identify the effect of job satisfaction on the performance of employees in the Ministry of Finance in the Red Sea State, Sudan. The study relied on the descriptive analytical approach. The study was applied to a random sample of employees in the Ministry of Finance in the Red Sea State, Sudan, and the sample size was (158) male and female employees. The results of the study showed that the level of job satisfaction and the performance level of employees in the Ministry of Finance is medium. There was no statistically significant difference in the responses of the study sample members regarding job satisfaction and the performance of ministry employees due to personal variables. The results also showed an impact of the dimensions of job satisfaction (salaries and incentives, job stability, and working conditions) on the performance of employees in the Red Sea State's Ministry of Finance. The study reached several recommendations, the most important of which was working to raise the level of job satisfaction in the Ministry of Finance in the Red Sea State.
A Study on Domestic and Foreign Current Status and Implications of the Data Economy: Comparison of Trends in the US, EU, Japan, and Korea

Purpose: This study aims to examine the main contents and meaning of the revision of the Data 3 Act, which took effect in August 2020, and to examine the current status of domestic and major countries for future data economy prospects centered on data transactions. In addition, I would like to present implications for Korea’s policies and market conditions to respond to a data economy-oriented society.&#x0D; Research design, data, and methodology: Due to the emergence of an intelligent information society and the development of the 4th industrial revolution, it is transforming into a digital data economy, and the importance of data use is increasing and interest in how to regulate data use is also increasing. In the meantime, it can be seen that the big data economy is being activated by allowing both individuals and companies to actively utilize big data, which is an essential element in the high-tech industry, with the recent revision of the Data 3 Act. Of course, the complexity and uncertainty of the Data Use Act in relation to the main contents of the Enforcement Decree of the Data 3 Act hinder the development of the data economy, and there are still issues to be discussed, such as conflicts between the Personal Information Protection Act and the Credit Information Protection Act. However, since encouraging results are expected in terms of revitalizing data use, this paper will first examine the data economic environment and domestic and international trends, and suggest ways to protect data rights, establish governance, and efficient management.&#x0D; Results: This study reviewed the concept definition of the data economy and the background of the emergence of the data economy market by examining trends in Korea and major countries, focusing on the Data 3 Act, and also presented directions and efficient management measures for data governance.&#x0D; Implications: At the transition to the data economy, legislation can be divided into two pillars: data utilization based on the various uses of big data and data protection based on personal information protection, and it can revitalize the data economy by sufficient technological supplementation. Data governance should be organized and operated, and data economy frameworks should be harmonized to establish, enforce, and interpret various laws related to data and have a consistent direction and orientation that can be fully recognized by various economic actors.
Analysis of Changes and Characteristics of the Global Supply Chain Between Korea, China and Japan

Purpose: This paper analyzes how the manufacturing supply chain has changed over the past 20 years according to the trilateral division of labor between Korea, China and Japan. Also, by measuring changes in the trade structure and competitiveness between Korea, China and Japan during the same period, the effect on the changes in the supply chain between the three countries is examined.&#x0D; Research design, data, and methodology: This study analyzes the trade structure, export competitiveness, and supply and distribution structure of 10 manufacturing industries in Korea, China and Japan. The analysis period was set from 2000 to 2020. The statistics use the UN Comtrade and the Asian International Input-Output Table. In the analysis of the trade structure between Korea, China and Japan. The Revealed Symmetric Comparative Advantage (RSCA) index was introduced to analyze the trade structure between Korea, China and Japan. And for the supply chain structure between the three countries, the Leontief inverse multiplier decomposition of the International Input-Output Analysis was used.&#x0D; Results: As a result of the analysis, it was observed that the supply chain of the manufacturing industry between Korea, China and Japan has changed to an interdependent structure since 2010, and the reason for this is that the production technology gap between the three countries has been greatly reduced. Accordingly, the supply chain of the manufacturing industry between the three countries has shifted from the past one-way dependence structure to a two-way dependence structure. In terms of industry, the deepening dependence among the three countries centered on electrical/electromechanical machinery, metal products, general machinery, chemical products, transportation machinery, precision machinery and textile products, which are key export industries for both Korea, China and Japan, means that the supply and distribution structure is being strengthened.&#x0D; Implications: Considering the relationship between the supply chain between Korea, China and Japan from 2000 to 2020, institutional integration, such as the trilateral FTA, is delayed, but functional integration is deepening due to interdependence and complementarity and increased production and trade. However, if trade frictions or disputes between Korea, China and Japan occur between specific countries, it is interpreted that this can lead to negative effects, so-called big losses, not only for the country concerned but also for the other country.
Effects of Flipped Classroom on EFL College Students’ Intrinsic Motivation, Extrinsic Motivation and Self-Efficacy

The present study aims to explore the effects of the flipped classroom on Korean college students’ intrinsic motivation, extrinsic motivation and self-efficacy in comparison to the traditional EFL classroom, using mixed methods research. Ninety-eight participants (control: 45, experimental: 53) attending the English speaking classes in a Korean university for 12 weeks were asked to respond to Motivated Strategies for Learning Questionnaire (MSLQ) before and after the intervention of flipped classroom. A paired sample t-test and ANCOVA were employed to determine statistically significant differences in students' responses. In addition, the fifteen students in the experimental group participated in the semi-structured interviews. The results showed that only experimental group showed a statistically significant improvement in both intrinsic and extrinsic motivation. Both groups improved their self-efficacy for learning and performance, but the experimental group showed greater improvement. The qualitative data confirmed the quantitative results in more detail. Furthermore, it also provided some suggestions for further study.
Analysis of the Experiences of the Nueva Ecija University of Science and Technology’s BSIT Students: A Follow-Up Study

This study aimed to analyze the experiences of the NEUST Graduating Students S.Y. 2021-2022 during their four-year stay at the University. This paper was a follow-up study of research entitled "Analysis of the Expectations and Experiences of the NEUST First Year BSIT Students for S.Y. 2018-2019." The main objective was to gather comparative and comprehensive results of the students' expectations, experiences, and overall satisfaction rating of their residency in the College of Information and Communications Technology (CICT) now that they have completed their degree in Information Technology. The researchers used the descriptive research method to describe the respondents' profiles and satisfaction with their experiences. The purposive sampling technique was used to gather the satisfaction ratings of the students. A questionnaire was distributed online as the primary data gathering tool, where the results were evaluated using a weighted average. The findings showed that the NEUST CICT produced students confident enough to find related jobs with the skills they have acquired from their education. During their stay at the University, they were able to give satisfaction ratings on their experiences and the services offered by the College during pre-pandemic and pandemic semesters. Based on their evaluation, both categories garnered very satisfactory ratings, but the pre-pandemic set-up was rated noticeably higher. As the final output, the researchers have come up with a list of improvements needed through a proposed action plan that can be adopted by the College of Information and Communications Technology for capability enhancement and service improvement.
A method for constructing public-key block cipher schemes based on elliptic curves

The article proposes a method for constructing public-key block cipher schemes based on the difficulty of the discrete logarithm problem on elliptic curves. The schemas are construc according to the proposed method and can simultaneously perform security functions and authenticate the origin and integrity of the encrypted message. In addition, a shared secret key is established between the sender/encryptor and the receiver/decryptor for each encrypted message based on public key cryptography which also improves the security of these cipher schemes.
Research on Text Naming Recognition Algorithm Based on Text Mining

In the process of scientific research, the naming of Chinese texts is very critical, which often affects scholars' cognition and judgment of things, and also has a certain impact on a series of operations such as experiments. On the other hand, in the process of professional research, many uncommon words often need to be verified by retrieving the corresponding knowledge system. The naming and recognition of these specialized words are very difficult, and there are many complex problems, such as polysemy and the nesting of wings. Therefore, under the above background conditions, this paper uses text mining method to conduct related research on the text naming of scientific research objects and uses the text mining method to construct and improve the text naming recognition algorithm accordingly. The support vector machine method and neural network model are used to build a text naming method suitable for Chinese, and good results are obtained in the application process.
Optimal Path Planning for Underwater Robots Based on Improved Ant Colony Algorithm

When applying traditional ant colony algorithm in the path optimization of underwater robots, there are several problems such as slow convergence speed and poor optimization effect. In this paper, an improved ant colony algorithm was proposed. The improved algorithm enhances the pheromone concentration in the core area of the grid map in the first inquiry stage, which can improve the confluence efficiency of the algorithm. In order to reduce the number of turns of the ants and make the path smoother, the corner heuristic function was added to the state transition probability equation. The position of the target point was added to the heuristic function to boost the target point's guiding influence on the ant colony. In the pheromone update part, the allocation strategy of the wolf pack algorithm was introduced to strengthen the pheromone of the optimal path and at the same time limit the pheromone concentration to reduce the generation of local optimal solutions. In the MATLAB simulation verification, the improved ant colony algorithm plans a shorter path length and fewer turns. The algorithm can effectively avoid obstacles, has better global optimization, and avoids the energy loss of underwater robots. This paper verifies the feasibility and superiority of the improved ant colony algorithm in static path planning.
Research on Improvement Strategy of Clustering Algorithm Based on Density Parameter Optimization Algorithm

In the Internet era, the Internet technology is in a rapid development stage, and more and more fields have introduced clustering algorithms. The main function of this algorithm is to process data information. UIn this case, there is no doubt that clustering algorithm has become a hot research topic for experts and researchers. In many clustering algorithms, the most important application is the clustering algorithm based on the density parameter optimization algorithm. This algorithm is simple and efficient in filtering, so it has received widespread attention from researchers. This paper proposes a clustering algorithm improvement strategy based on the density parameter optimization algorithm. Average clustering algorithm, in order to improve the quality of the algorithm, the nearest neighbor collaborative filtering algorithm can be selected. In addition, this paper optimizes the clustering method and clustering characteristics of the clustering algorithm to be better applied to the data analysis process.
Application of voice recognition control technology in wind power field operation

This paper designs a wind power equipment operation monitoring platform based on speech recognition, wind power equipment information collection module, information processing unit, central control room monitoring system, mobile monitoring system and remote terminal monitoring system. Compared with the current technical level, the interaction efficiency between the monitoring terminal and the wind turbine operation monitoring equipment solved by the new system is relatively weak, especially the interaction efficiency of the data obtained by the diagnostic personnel is relatively small. The reduction of interaction efficiency will eventually lead to the problem of the quality of wind power equipment operation guarantee.
Sentiment Classification Model of Online Reviews Based on Word Features and Bi-LSTM

With the rapid development of e-commerce, many purchase and comment records are produced. Sentiment classification of commodity reviews is of great value for automatically monitoring bad reviews and assisting merchants in analyzing consumer feedback. At present, the Bi-LSTM model is representative of Chinese text sentiment classification, which can understand the semantic information in time sequence. However, due to the lack of processing lexical information, there is a problem that word vectors cannot highlight the information of sentiment words. Therefore, this paper proposes a sentiment classification model of Chinese product reviews based on word features and Bi-LSTM. The new model firstly uses Word2vec's CBOW model to train the word vectors, secondly uses an improved information gain algorithm with the word distribution and sentiment weights to calculate the amount of information, and finally uses the Naive Bayes model to classify the network classification results twice, which solves the problem that the basic Bi-LSTM model lacks understanding of lexical information. The experimental results show that the new model achieves better results relative to the basic Bi-LSTM model and can capture the sentiment information of the comments more accurately. In the test set, the accuracy rate reached 89.03%.
Utilization of Renewable Energy Technologies: School Buildings in Baghdad as a Case Study

Recent attention has been focused on solar energy as a sustainable energy source that can be directly converted to electricity using solar panels. Renewable energy sources are becoming more important as a solution to provide clean energy. The power production of photovoltaic (PV) systems is directly proportional to the solar irradiance acquired. Consequently, these panels must be perpendicular to sun irradiation in order to collect the greatest amount of energy. This research aimed to provide a contemporary method for planning and constructing school buildings by analyzing the current condition of electricity consumption and the practicality of investing in renewable energy sources in school buildings. For this reason, a new school building under construction in the city of Baghdad with a total area of around 2000m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> was chosen, and one of the renewable energy sources (PV system) was installed to supply the electric power required to operate the school. The average monthly power usage of different energy users in the school building during January and July that represent various seasons is about (57.1 and 83.6) kWh, respectively. Two scenarios have been analyzed: fixed-angle as well as tracking PV systems that generate electricity at varying tilt angles. Also, the computation of each case's monthly energy output and the annual PV energy production (kWh) are presented. The results show that the annual production of the PV system within the exploited area of the roof of the school building is about (1181.3, 1239.3, and 1225.8) kWh at vertical axis and at inclined axis about(1243.1, 1233.8, and 1184.1)kWh in the case of fixed tilt angle(30°, 45°, and 90°), respectively. Also, the tracking PV system was better than fixed-angle PV systems for energy generation, where the energy output reached about 1284.9 KWh. Thus, school buildings can attain zero building energy consumption. Besides, additional installations of rooftop PV systems provide extra power to offset energy demands.
Research and design of robot obstacle avoidance strategy based on multi-sensor and fuzzy control

With the development of microcontrollers, inertial sensors, communication chips and other devices, the popularity of robots and their applications are gradually expanding, and the motion or operating environments they face are becoming more and more complex. In this paper, we use multi-sensor technology to collect information about obstacles, then analyze and identify the collected data, and use fuzzy control algorithms to build a multi-sensor information fusion obstacle avoidance method for robots based on the analyzed obstacle information, improve the robot's obstacle avoidance accuracy and optimize the robot's obstacle avoidance route, and realize the robot's autonomous obstacle avoidance function. This method is used to improve the obstacle avoidance accuracy of the robot and optimize the obstacle avoidance route of the robot.
Realization of Online Intelligent Platform Matlab of Three-Round Education Mechanism in Universities Under the Environment of Multi-Dimensional Information Technology

The intelligent experimental data processing system is designed and implemented by using Matlab. This system has functions of data input and output, intelligent processing, etc. Its processing functions cover most of the items in physical experiments. Strengthen ideological and political education, optimize the pattern of education to build a platform for all employees, improve the effectiveness of the whole process of education, and achieve the goal of all-round education. Theoretically, it gives a comprehensive explanation of “Three Comprehensive Education”, and according to the new requirements and new background of the Party and the government for the establishment of morality in colleges and universities in the new era, combines theory and practice, and sorts out the basic concept of “Three Comprehensive Education”. Explain the inner connection between “Three Complete Education” and Lide S huren.
Microcontroller based Smart Tablet Dispenser (STD) for Elderly People

A Smart Tablet Dispenser (STD) prototype is presented in this study. The major goal of this approach is to make it easier for patients, particularly the elderly, to take their medications on time and without skipping any medication and also to avoid taking medicines in an arbitrary quantity. It may result in complications such as varied recovery time, and prolonged sickness and may even lead to death. This Novel smart medication dispenser (SMD) will help to cope with this issue by giving periodical alerts and notifications at the needed time for the patient and caregiver as it will tell the caregiver instantly if the patient misses a medication. In addition, STD offers a touch interface as an option to the user. In addition, STD provides a touch interface that can be accessed via a Smartphone application and allows users to take care and provide pill schedules even remotely.
Edge-Assisted Virtual Viewpoint Generation for Immersive Light Field

Light field (LF), which describes the light rays that emanate at each point in a scene, can be used as a six-degrees-of-freedom (6DOF) immersive media. Similar to the traditional multiview video, LF is also captured by an array of cameras, leading to a large data volume that needs to be streamed from a server to users. When a user wishes to watch the scene from a viewpoint that no camera has captured directly, a virtual viewpoint must be rendered in real time from the directly captured viewpoints. This places high requirements on both the computing and caching capabilities of the infrastructure. Edge computing (EC), which brings computation resources closer to users, can be a promising enabler for real-time LF viewpoint rendering. In this article, we present a novel EC-assisted mobile LF delivery framework that is able to cache parts of LF viewpoints in advance and render the requested virtual viewpoints on demand at the edge node or user’s device. Numerical results demonstrate that the proposed framework can reduce the average service response latency by 45% and the energy consumption of user equipment by 60% at the cost of 55% additional caching consumption of edge nodes.