Earticle

In the Internet-of-Things (IoT) and artificial intelligence (AI), complete implementations are dependent largely on the speed of the fifth generation (5G) networks. However, successive interference cancellation (SIC) in non-orthogonal multiple access (NOMA) of the 5G mobile networks can be still decoding latency and receiver complexity in the conventional SIC NOMA scheme. Thus, in order to reduce latency and complexity of inherent SIC in conventional SIC NOMA schemes, we propose a rate-lossless non-SIC NOMA scheme. First, we derive the closed-form expression for the achievable data rate of the asymmetric 2PAM non-SIC NOMA, i.e., without SIC. Second, the exact achievable power allocation interval of this rate-lossless non-SIC NOMA scheme is also derived. Then it is shown that over the derived achievable power allocation interval of user-fairness, rate-lossless non-SIC NOMA can be implemented. As a result, the asymmetric 2PAM could be a promising modulation scheme for rate-lossless non-SIC NOMA of 5G networks, under user-fairness.

Today people adopt various contents from their mobile devices which lead to numerous platforms. As technology of 5G, IOT, and smart phone develops, the number of people who create, edit, collect, and share their own videos, photos, and articles continues to increase. As more contents are shared online, the numbers of data being stolen continue to increase too. To prevent these cases, an authentication method is needed to encrypt the content and prove it as its own content. In the report, we propose a few methods to secure various misused content with secondary security. A unique private key is designed when people create new contents through sending photos or videos to platforms. The primary security is to encrypt the “Private Key” with a public key algorithm, making its data-specific “Timeset” that doesn’t allow third-party users to enter. For the secondary security, we propose to use Message Authentication Codes(MACs) to certify that we have produced the content.

We constructed an air-lifted seawater propulsion system for decreasing fuel consumption of the ships. The system has a form of pipes which can be easily installed on the sides of the ship. Seawater mixed with air, will rise along within the pipe, and will be discharged downward. If the directions of inlet / outlet of the pipe are designed properly, a propulsive energy can be obtained. We tested the system with a model ship in Jangsa port at Sokcho-city with a water depth of 2.5 meters. The system was supplied regulated air at 6 bars during the 3 tests. The model ship was moving forward at a rate of 0.18 meters per second. In case of large ships equipped zfrom clean energy.

With the rapid development of artificial intelligence and big data, a lot of medical data is effectively used, and the diagnosis and analysis of diseases has entered the era of intelligence. With the increasing public health awareness, ordinary citizens have also put forward new demands for panic disorder health services. Specifically, people hope to predict the risk of panic disorder as soon as possible and grasp their own condition without leaving home. Against this backdrop, the smart health industry comes into being. In the Internet age, a lot of panic disorder health data has been accumulated, such as diagnostic records, medical record information and electronic files. At the same time, various health monitoring devices emerge one after another, enabling the collection and storage of personal daily health information at any time. How to use the above data to provide people with convenient panic disorder self-assessment services and reduce the incidence of panic disorder in China has become an urgent problem to be solved. In order to solve this problem, this research applies the context awareness to the automatic diagnosis of human diseases. While helping patients find diseases early and get treatment timely, it can effectively assist doctors in making correct diagnosis of diseases and reduce the probability of misdiagnosis and missed diagnosis.

This study aims to provide basic data on establishing online learning by identifying the effects of self-efficacy as a medium on factors affecting self-control according to self-determination motivation through contactless online learning due to Covid-19. The research method used SPSS 25 and Sobel test to examine the causal relationship between the spokesmen and 196 middle and high school students in W-city, Gangwon-do. Self-determination motivation has had a significant effect on self-efficacy and self-control, and self-efficacy has been shown to have a significant effect on self-control. Also, Self-efficacy had a partial mediating effect on self-determination motivation affecting self-control. Based on this, fundamental and continuous development of online education programs to promote self-control of online learners is required, and efforts should be made to support learners' capabilities through psychological counseling.

At the time of entering the super-aged society, the health problem of the elderly is becoming more prominent due to the rapid digital era caused by COVID-19, but the gap between welfare budgets and welfare benefits according to regional characteristics is still not narrowed and there is a significant difference in emergency medical access. In response, this study proposes an ICT-based New Normal Smart Care System (NNSCS) to bridge the gap I n health and medical problems. This is an integrated system model that links the elderly themselves to health care, self-diagnosis, disease prediction and prevention, and emergency medical services. The purpose is to apply location-based technology and motion recognition technology under smartphones and smartwatches (wearable) environments to detect health care and risks, predict and diagnose diseases using health and medical big data, and minimize treatment latency. Through the New Normal Smart Care System (NNSCS), which links health care, prevention, and rapid emergency treatment with easy and simple access to health care for the elderly, it aims to minimize health gaps and solve health problems for the elderly.

The surveillance camera market has developed and plays an important role in the field of video surveillance. However, in recent years, the identification of areas requiring surveillance has been limited by reflective light in the surveillance camera market. Cameras using polarization filters are being developed to reduce reflective light and facilitate identification. Programs are required to automatically adjust polarization filters. In this paper, we proposed an optimal angle extraction method from surveillance cameras using polarization filters through histogram analysis. First of all, transformed to grayscale to analyze the specifications of frames in multiple polarized angle images, reducing computational throughput. Then we generated and analyzed a histogram of the corresponding frame to extract the angle when the highlights are the fewest. Experiments with 0˚ and 90˚ showed high performance in extracting optimal angles. At this point, it is hoped this technology would be used for surveillance cameras in place like beach with a lot of reflective light.

In this paper, based on the real estate registration model in the Chinese internet environment, we propose a model for the joint business of banking collateral registration. This is to increase the efficiency and service level of the real estate mortgage registration process. And it can solve the problems that in the process of registering a mortgage loan, difficulty of data sharing between the real estate registration agency and the bank, and ordinary users and bank clerks duplicate unnecessary work. In addition, it realizes joint processing and data sharing of real estate registration work with real estate registration agencies and banks, increases the efficiency and level of government affairs services, and offers an optimized solution to realize a one-stop service for real estate security registration. The results of this study are expected to provide theoretical support for the application and innovation of the Internet environment real estate registration model.

In order to broadcast 8K UHD, domestic broadcasting is upgrading production, operation, and transmission technologies in a new way that has various forms such as terrestrial broadcasting, IPTV, mobile, and streaming services. In order to overcome the existing SDI transmission technology that has reached its limit, new transmission technologies using ICT-based convergence such as IT, Network, IOT, and Big Data are developing. Internet Protocol(IP) transmission technology is an IT-based core protocol that transcends various broadcasting infrastructures. Therefore, it can be said that the technology for converting the broadcasting system based on IP is a natural one for preparing for 8K UHD in the future. In this paper, we propose an IP transmission system that adopts a network that can transmit 8K with hardware of 12G Serial Digital Interface (SDI), in order to prepare for the future broadcasting system according to the development of ALL IP interface technology.

XML message brokers have a lot of importance because XML has become a practical standard for data exchange in many applications. Message brokers covered in this document store many users. This paper is a study of the processing of twig pattern queries in XML documents using branching node streams in XML message broker structures. This work is about query processing in XML documents, especially for query processing with XML twig patterns in the XML message broker structure and proposed a method to reduce query processing time when parsing documents with XML twig patterns by processing information. In this paper, the twig pattern query processing method of documents using the branching node stream removes the twigging value of the branch node that does not include the labeling value of the branch node stream when it receives a twig query from the client. In this paper, the leaf node discovery time can be reduced by reducing the navigation time of nodes in XML documents that are matched to leaf nodes in twig queries for client twig queries. Overall, the overall processing time to respond to queries is reduced, allowing for rapid questionanswer processing.

Recently, the number of people who visit the hospital due to diabetes is increasing. According to the Korean Diabetes Association, it is statistically indicated that one in seven adults aged 30 years or older in Korea suffers from diabetes, and it is expected to be more if the pre-diabetes, fasting blood sugar disorders, are combined. In the last study, the validity of Triglyceride and Cholesterol associated with diabetes was confirmed and analyzed using Random Forest. Random Forest has a disadvantage that as the amount of data increases, it uses more memory and slows down the speed. Therefore, in this paper, we compared and analyzed Random Forest and XGBoost, focusing on improvement of learning speed and prevention of memory waste, which are mainly dealt with in machine learning. Using XGBoost, the problem of slowing down and wasting memory was solved, and the accuracy of the diabetes recognition factor was further increased.

Speech recognition technology refers to a technology in which a computer interprets the speech language spoken by a person and converts the contents into text data. This technology has recently been combined with artificial intelligence and has been used in various fields such as smartphones, set-top boxes, and smart TVs. Examples include Google Assistant, Google Home, Samsung's Bixby, Apple's Siri and SK's NUGU. Google and Daum Kakao offer free open APIs for speech recognition technologies. This paper selects three APIs that are free to use by ordinary users, and compares each recognition rate according to the three types. First, the recognition rate of "numbers" and secondly, the recognition rate of "Ga Na Da Hangul" are conducted, and finally, the experiment is conducted with the complete sentence that the author uses the most. All experiments use real voice as input through a computer microphone. Through the three experiments and results, we hope that the general public will be able to identify differences in recognition rates according to the applications currently available, helping to select APIs suitable for specific application purposes.

This cross-sectional survey research carried out with the inquisitive agenda on satisfaction of the translation outcomes as performed by human translation and (machine translation) post-editing. The survey group consisted of 166 Korean translators primarily working with the English, Chinese, and Japanese languages. They were asked to rate the satisfactory level with accuracy, fluency, idiomatic expression, and terminology in the Richter’s scale of four. The result reveals that human translation is more satisfactory than post-editing with respect to accuracy, but it is uneasy to assert that accuracy is unsatisfactory in post-editing. On the other hand, the Korean translators are less satisfied with fluency, idiomatic expression, and terminology than accuracy. It can be assumed that although human translation is more satisfactory than post-editing, the accuracy of post-editing seems to be more acknowledged than fluency, idiomatic expression, and terminology, which lead the translators to take the accuracy of raw machine-translation products and to go on to improve the fluency, idiomatic expression, and terminology. Nevertheless, Korean translators believe Korean idiomatic expressions cannot be satisfactorily produced in post-editing, while fluency and terminology can be improved in post-editing.

This study attempted to confirm the factors that the meaning of work perceived by organization members and job embeddedness affects creative behavior. In addition, we tried to confirm the relationship between the meaning of work and job embeddedness. On the other hand, we tried to verify the mediating effect of job embeddedness between the meaning of work and creative behavior. Accordingly, the following results and implications were derived through the hypotheses set for the members of small and medium-sized enterprises. First, the meaning of work showed a positive effect on job embeddedness and creative behavior, and it was empirically analyzed that job embeddedness was improved on creative behavior. In order to improve the creative behavior of organizational members, the need for advancement of the management and training system to systematically improve and strengthen the meaning of work and job embeddedness has emerged. Second, job embeddedness showed a mediating effect between the meaning of work and creative behavior. In other words, the employee's job embeddedness acted as a direct or indirect factor according to the improvement of the meaning of work and creative behavior. Accordingly, as one of the major factors in human resource management and strategic human resource development for the advancement of the sustainable management system, the need for institutional establishment and implementation was required as it became more efficient and effective.

With the development of 3D graphics software and the speed of computer hardware, it is an era that can be realistically expressed not only in movie visual effects but also in console games. In the production of such realistic 3D models, 3D scans are increasingly used because they can obtain hyper-realistic results with relatively little effort. Among the various 3D scanning methods, photogrammetry can be used only with a camera. Therefore, no additional hardware is required, so its demand is rapidly increasing. Most 3D artists shoot as many images as possible with a video camera, etc., and then calculate using all of those images. Therefore, the photogrammetry method is recognized as a task that requires a lot of memory and long hardware operation. However, research on how to obtain precise results with 3D photogrammetry scans is insufficient, and a large number of photos is being utilized, which leads to increased production time and data capacity and decreased productivity. In this study, point cloud data generated according to changes in the number and resolution of photographic images were produced, and an experiment was conducted to compare them with original data. Then, the precision was measured using the average distance value and standard deviation of each vertex of the point cloud. By comparing and analyzing the difference in the precision of the 3D photogrammetry scans according to the number and resolution of images, this paper presents a direction for obtaining the most precise and effective results to 3D artists.

The purpose of this study is to analyze the relationship between dance passion, self-management, and dance immersion. Specifically, passion for dance was subdivided into obsessive-compulsive passion and harmonious passion, and these were selected as exogenous variables. In addition, it is intended to provide theoretical and educational implications by analyzing the structural equation model composed of endogenous variables of self-management and dance immersion. The subjects of this study were college students majoring in dance, and the final 206 students were selected as effective samples by the convenient sampling method. For data processing, frequency analysis and reliability analysis were performed using SPSS 23. In addition, AMOS 21 was used for confirmatory factor analysis, correlation analysis, and structural equation model analysis. As a result of the study, first, it was found that both compulsive passion and harmonious passion have a positive effect on self-management. Second, self-management was found to have a positive effect on dance immersion. Third, it was found that compulsive passion had a positive effect on dance commitment, but harmonious passion did not have a statistically significant effect on dance commitment.

In the current software project, it is still very difficult to extract and define clear requirements in the requirement engineering. Informal requirements documents based on natural language can be interpreted in different meanings depending on the degree of understanding or maturity level of the requirements analyst. Also, Furthermore, as the project progresses, requirements continue to change from the customer. This change in requirements is a catastrophic failure from a management perspective in software projects. In the situation of frequent requirements changes, a current issue of requirements engineering area is how to make clear requirements with unclear and ambigous requirements. To solve this problem, we propose to extract and redefine clear requirements by incorporating Design Thinking methodologies into requirements engineering. We expect to have higher possibilities to improve software quality by redefining requirements that are ambiously and unclearly defined.

The purpose of this study is to analyze the relationship among selection attributes, consumption value brand attitude, fun, brand loyalty and quality of life. The subjects of the empirical study were selected by the Korea Fashion Industry Research Institute using the convention sampling method and the quota sampling method for 241 consumers who have purchased brands classified as "athleisure" within the past year For each variable constructed to verify reliability and validity of the measurement model, reliability tests using Cronbach' alpha were performed using IBM SPSS Win Ver. 23.0. To verify the unidimensionality of the measurements, we conducted a confirmatory factor analysis using AMOS 22.0 and a structural equation model to determine the structural relationship between variables. As a result of the study, First, both intrinsic and extrinsic attributes, which are sub-factors of selection attributes, have been shown to have a significant effect on consumption value. Second, consumption value has been shown to have a significant impact on brand attitude and fun. Third, brand attitudes have been shown to have a significant impact on brand loyalty. Finally, fun has been shown to have a significant impact on quality of life.

Patients with Pressure injuries (PIs) may have pain and discomfort, which results in poorer patient outcomes and additional cost for treatment. This study was a part of larger research project that aimed at prediction modeling using a big data. The purpose of this study were to describe the characteristics of patients with PI in critical care; and to explore comorbidity and diagnostic and interventive procedures that have been done for patients in critical care. This is a secondary data analysis. Data were retrieved from a large clinical database, MIMIC-III Clinical database. The number of unique patients with PI was 2,286 in total. Approximately 60% were male and 68.4% were White. Among the patients, 9.9% were dead. In term of discharge disposition, 56.2% (33.9% Home, 22.3% Home Health Care) where as 32.3% were transferred to another institutions. The rest of them were hospice (0.8%), left against medical advice (0.7%), and others (0.2%). The top three most frequently co-existing kinds of diseases were Hypertension, not otherwise specified (NOS), congestive heart failure NOS, and Acute kidney failure NOS. The number of patients with PI who have one or more procedures was 2,169 (94.9%). The number of unique procedures was 981. The top three most frequent procedures were ‘Venous catheterization, not elsewhere classified,’ and ‘Enteral infusion of concentrated nutritional substances.’ Patient with a greater number of comorbid conditions were likely to have longer length of ICU stay (r=.452, p<.001). In addition, patient with a greater number of procedures that were performed during the admission were strongly tend to stay longer in hospital (r=.729, p<.001). Therefore, prospective studies focusing on comorbidity; and diagnostic and preventive procedures are needed in the prediction modeling of pressure injury development in ICU patients.

Livestock farmers are using animal carcasses to dispose of the carcasses of livestock that have died of natural causes or disease. Most of the existing livestock carcass processors are mechanical in their structure without considering the environment. It has a function of sterilizing dead bodies at high pressure after processing them and causes environmental problems such as carbon monoxide emissions. If livestock carcasses occur, livestock farmers have to purchase their own livestock carcasses or entrust them to the outside world, which is costly. For this reason, the possibility of environmental pollution, infectious diseases, and spread has been increased recently by frequent dumping of dead bodies. The carcass of livestock mixed with manure not only serves as a medium for infectious diseases but also needs to be buried on a large scale as foot-and-mouth disease and avian influenza spread. As a result, the possibility of environmental pollution, such as contamination of groundwater, is increasing, so research is needed to protect and improve the environment. We aim to improve the process of processing livestock carcasses and purify the agricultural environment through development results on the form, structure and function of eco-friendly livestock carcasses. Its shape is applied with natural shapes such as stones and seeds. The material used in the dead body process is a brown beggar biocouple and is applied with an eco-friendly industrial animal recycling process. As a result of the study, it is expected to improve odors and the environment, and to be used as data to improve and help the livestock industry in the future.

Fishery industry is an important part of agricultural industry in coastal countries. The purpose of this study is to use the theory of industrial competitiveness for reference, use Analytic Hierarchy Process (AHP) and Delphi method to establish the evaluation index system, and analyze the fishery industry competitiveness of 11 coastal provinces in China. This study data came from China Fishery Statistical Yearbook 2020. The results show that Shandong Province is the most competitive province in fishery industry among the coastal provinces. The inter-provincial differences are great. Not only the resource endowment is the factor that affects the fishery industry competitiveness, but also the long-term profitability is too. The proportion of recreational fishery in the fishery economic output value has become one of the main indicators to measure the competitiveness of the fishery industry. The findings of this study suggest that all regions should adopt measures in accordance with local conditions, promote the integrated development of the fishery industry, enhance the added value of fishery products and enhance the competitiveness of fishery industry. The disadvantage of this study is that the fishery industry competitiveness of China's coastal provinces is only compared and analyzed. The future direction is to carry out a comparative study on the international competitiveness of fishery with other east Asian countries.

Korea is ranked as the world's No. 1 country in its aging rate. While the interest and demand for health is rapidly increasing, the health status of the elderly is in the lowest among OECD members. Increased chronic diseases, the burden of medical costs and digital/untact changes of societies after COVID-19 have caused the direction of healthcare to be changed from treatment oriented to health care and prevention oriented, along with increased income levels and a desire for a healthy life. Amid this paradigm of change, the gap in health standards and health inequality for the elderly according to local structure and social conditions affects not only socio-economic but also the quality of life for individual senior citizen. Utilizing prior data of Aging Research Panel Survey, this study aims to compare and analyze health conditions and regional gaps which are significant influences on the satisfaction of the life of the elderly, and to suggest direction of studies for health care to provide solutions for health inequalities. The findings are intended to be a basic data for researching models of the New Normal Smart Healthcare System that bridge the health gap between the elderly and enhance life satisfaction with health care models suitable for regional characteristics in aging society.

We have studied the speed regulation of the permanent magnet synchronous motor (PMSM) servo system in this paper. To optimize the PMSM servo system's speed-control performance with disturbances, a non-linear speed-control technique using a back-propagation neural network (BP-NN) algorithm for the controller design of the PMSM speed loop is introduced. To solve the slow convergence speed and easy to fall into the local minimum problem of BP-NN, we develope an improved BP-NN control algorithm by limiting the range of neural network outputs of the proportional coefficient Kp, integral coefficient Ki of the controller, and add adaptive gain factor β, that is the internal gain correction ratio. Compared with the conventional PI control method, our improved BP-NN control algorithm makes the settling time faster without static error, overshoot or oscillation. Simulation comparisons have been made for our improved BP-NN control method and the conventional PI control method to verify the proposed method's effectiveness.

Data conversion refers to the process of extracting the data existing in the existing system, that is, the past data accumulated by the old information system or other methods and transferring it to the improved table of the new system. The person in charge of data conversion refers to the entire process of converting to the final destination table according to the rules designed/planned in advance. In most cases, data conversion design should be consider when the old system replace or the data of another existing system is converted and applied to a newly constructed information system. The goal of data conversion is to understand the current database system of operating environment, understand the characteristics of the DBMS in use, maintain the optimal database structure, and make the new system perform at its best. Data conversion methods are largely divide into a method using a tool and a conversion method using a program preparation. In this paper, we examine the advantages and disadvantages of the data conversion method, and try to derive the problems of the existing data conversion method. Based on this, an improved data conversion method for the system upgrade project was proposed, and verified through a questionnaire of an IT expert to prove its effectiveness

The purpose of this study is to analyze the structural relationship among self-leadership, grit, and performance.Specifically, self-leadership was selected as an independent variable, two dimensions of grit were selected as mediator variables, and performance was selected as a dependent variable. This structural equation model is based on previous studies.The subjects of this study were middle and high school Taekwondo players, and the survey was collected using the online survey system KSDC (Korean Social-Science Data Center). The sampling method was a non-probability sampling method, convenience sampling method.A total of 367 copies were collected through this process, and 355 copies were used as the final valid samples after excluding the insincere data.Data processing was done with SPSS 23 for frequency analysis, exploratory factor analysis and reliability analysis. Also, AMOS 21 was used for confirmatory factor analysis and structural equation model analysis. The results of the analysis are as follows: First, self-leadership had a positive effect on bothi interest consistency grit and effort persistence grit. Second, it was found that both interest consistency grit and effort persistence grit have a positive effect on performance.Third, self-leadership had a positive effect on performance.

Recently, artificial intelligence(AI) has been used throughout society, and social interest in it is increasing. Accordingly, the necessity of AI education is becoming a big topic in the education field. As a response to this trend, the Korean education authorities have also announced plans for AI education, and various studies have been performed in academic field to revitalize AI education in the future. However, the curriculum research on what differentiates AI education from existing SW education and what and how to train AI is still in its infancy. In this paper, Therefore, we focused on the experiences of elementary school students in solving problems in their own lives, and developed a teaching-learning model based on design-based research so that students can design a problem-solving process and experience the process of feedback. We applied the developed teaching-learning model to the problem-solving process and confirmed that it increased students' understanding and satisfaction with AI education.