Earticle

This paper studied a method of estimating target information using a radar in wireless communication. Position information on the target can be estimated angle, distance and velocity. The velocity information can be estimated since the Doppler frequency is changed in the moving target. The signal incident on the receiving array antenna is multiplied by the delay time and the reference signal to represent the output signal. This output signal is estimated by applying FFT (Fast Fourier Transform) after calculating signal correlation through correlation integrator. Since the output signal must be calculated within the correlator, it should be processed with the Dwell time. The correlation signal of the correlation integrator outside this Dwell time is indicated by the velocity measurement error. The FFT is applied to the signal that has passed through the correlated integrator in order to estimate the distance of the signal. The Doppler resolution must be improved because the FFT estimates target information using the Doppler information. The Doppler resolution decreases with increasing the integration time. The velocity information estimation should have no spread of the velocity. As a result of the simulation, there was no spread of the target velocity in this study.

In this paper, as part of the research for the infrastructure of very high flexible and reconfigurable data center using very high speed crossbar switches, we developed a simulator that can model two and three dimensional connection structure of switches with an efficient control algorithm using software defined network and verified the functions and analyzed the performance accordingly. The simulator consists of a control module and a switch module that was coded using Python language based on the Mininet and Ryu Openflow frameworks. The control module dynamically controls the operation of switching cells using a shortest multipath algorithm to calculate efficient paths adaptively between configurable computing resources. Performance analysis by using the simulator shows that the three-dimensional switch architecture can accommodate more hosts per port and has about 1.5 times more successful 1:n connections per port with the same number of switches than the two-dimensional architecture. Also simulation results show that connection length in a 3-dimensional way is shorter than that of 2-dimensional way and the unused switch ratio in a 3- dimensional case is lower than that of 2-dimensional cases.

The purpose of this paper is an analysis of the difference between convergence majors and single majors in the convergence core competency and educational performance. We used survey data for the analysis of the convergence core competencies, the results of the midterm and final exams for the education performance. Analysis targets are 10 students in big data business intelligence at Seokyeong University as convergence majors and 11 students in business administration as single majors. The target course was an analysis of economic data provided in the second semester of 2019. And the lecture contents were analysis of big data using R programming. The survey was conducted on December 5, 2019. The convergence core competences were creative thinking, critical thinking, understanding convergence knowledge, problem solving ability, communication skills, cooperation ability, use of convergence tools, consideration, and responsibility. As results of homogeneity tests, we found that there was no significant difference in all competencies, but there were very significant differences in the educational performance evaluated by the midterm and final exams. Therefore we can see willingness to convergence of single majors was no different from that of convergence majors, but had not led to practice. It is desirable to activate and support convergence courses.

The study is a phenomenological analysis of the video simulation clinical practice experience recently conducted on nursing students due to the outbreak of corona 19 worldwide. A total of eight students participated in the vSim class who understood the purpose of the study and wanted to participate voluntarily. The data collection conducted a total of three interviews until no new data was available, and the collection period was from June 22, 2020 to July 10, 2020. The collected data were analyzed with the Giorgi's Phenomenological Analysis Method. As a result of the study, three components and 13 semantic units were derived. vSim was difficult for students, but it was an interesting experience that made them feel like nurses, and it was an experience in which they were immersed in learning rather than face-to-face classes, and their skills improved.

The deployment of geographically distributed wireless sensors has greatly elevated the capability of monitoring structural health in social-overhead capital (SOC) public infrastructures. This paper deals with the utilization of a distributed mobility management (DMM) approach for the deployment of wireless sensing devices in a structural health monitoring system (SHM). Then, a wireless sensing mechanism utilizing lowenergy adaptive clustering hierarchy (LEACH)-based clustering algorithm for smart sensors has been analyzed to support the seamless data transmission of structural health information which is essentially important to guarantee public safety. The clustering of smart sensors will be able to provide real-time monitoring of structural health and a filtering algorithm to boost the transmission of critical information over heterogeneous wireless and mobile networks.

The fifth generation (5G) mobile communication has been more commercialized worldwide. One of the promising 5G technologies is non-orthogonal multiple access (NOMA). We present the achievable sum rate of non-orthogonal multiple access (NOMA) with correlated superposition coding (SC). Then this paper investigates the impacts of correlation on the achievable sum rate of correlated SC NOMA. It is shown that the achievable sum rate of correlated SC NOMA is greater than that of standard independent SC NOMA, for the most of the values of the power allocation factor over the meaningful range of the user fairness. In result, correlated SC could be a promising scheme for NOMA.

Ad Hoc network is a special wireless network, mainly because the nodes are no control center, the topology is flexible, and the networking could be established quickly, which results the transmission stability is lower than other types of networks. In order to guarantee the transmission of data packets in the network effectively, an improved Queue Ad Hoc On-demand Distance Vector Routing protocol (Q-AODV) for node detection by using blockchain technology is proposed. In the route search process. Firstly, according to the node's daily communication record the cluster is formed by the source node using the smart contract and gradually extends to the path detection. Then the best optional path nodes are chained in the form of Merkle tree. Finally, the best path is chosen on the blockchain. Simulation experiments show that the stability of Q-AODV protocol is higher than the AODV protocol or the Dynamic Source Routing (DSR) protocol.

The Avengers film produced by Marvel Comics shows visual effects that were impossible to produce in the past. Companies that produce film special effects were initially equipped with large personnel and equipment, but technology is gradually evolving to be feasible for smaller companies that do not have high-priced equipment and a large workforce. The development of hardware and software is becoming increasingly available to the general public as well as to experts. Equipment and software which were difficult for individuals to purchase before quickly popularized high-performance computers as the game industry developed. The development of the cloud has been the driving force behind software costs. As augmented reality (AR) performance of mobile devices improves, advanced technologies such as motion tracking and face recognition technology are no longer implemented by expensive equipment. Under these circumstances, after implementing mobile-based facial capture technology in animation projects, we have identified the pros and the cons and suggest better solutions to improve the problem.

The importance of international co-production that enables content production, diversification of overseas markets, and diversification has been highlighted as demand for content has soared due to intensifying competition between media outlets, while contents provision has become easier due to changes in media environment such as convergence of broadcasting and communication and the spread of mobile Internet. In particular, the boom in Korean dramas, called the Korean Wave in China, opened up a new market after "My Love from the Star" in 2014, and in 2016, Netflix's entry into Korea served as an opportunity for local broadcasters and producers to seek international co-production. In addition, "Good Doctor" which was aired on American Broadcasting Co. (ABC) in 2017, has topped the same time slot for the first time in 29 years, and is set to air season 4 this fall. Accordingly, overseas broadcasters and production companies wanted to collaborate with domestic broadcasters and producers, and since 2011, they have conducted a total of 12 co-produced dramas until 2019. Unfortunately, however, there are few studies related to international co-production dramas in the domestic industry and academia. In this paper, we present to help Korea, which used to be a powerhouse in complete export-type content, move toward becoming a powerhouse in international co-produced dramas. In addition, it is meaningful that the research focused on the current status and achievements of international co-production dramas, which have not been studied much, and the diversity of international co-production dramas in the future through the analysis of the form and structure of international co-production.

This study discusses research and development of large-sized 3D printers that can be applied to construction and civil engineering for various designs of protective casing on foam liner for concrete exteriors. The consistent use of concrete represents the current surroundings. However, concrete exteriors in Korea have not considered the regional characteristics, but the concrete has been poured solely for economical aspects for the last decade or two. There are many cases of poor installation and not enough design development projects to correct it. This study was conducted to apply various patterns, regional characteristics, and 3D printing for protective casing design for foam liner to create various designs for the concrete walls. Therefore, we started researching on a large 3D printer, and designed and developed this system. Considering the chronological process, the properties of concrete structures were identified, the application of designs for concrete in Korea and abroad and the 3D printing materials for the protective casing were surveyed and analyzed, and a stereotype was produced in the first year to study designs for the beauty of concrete surfaces. In the second year, images of regional characteristics were gathered, design ideas for regional promotion were derived, virtual images were produced along with design modeling to simulate the appearances, and verify the effect of application and promotion. Finally, in the third year, the 3D printer for concrete foam liner was constantly improved to analyze the 3D printing program and the various library elements to complete an actual largesized 3D printer.

Recently, computer hardware is evolving toward increasing the number of computing cores, not increasing the clock speed. In order to use the performance of parallelized hardware to the maximum, the running program must also be parallelized. However, software developers are accustomed to sequential programs, and in most cases, write programs that operate sequentially. They also have a lot of difficulty designing and developing software in parallel. We propose a method to automatically convert a sequential C/C++ program into a parallelized program, and develop a parallelization tool that supports it. It supports open multi-processing (OpenMP) and parallel patterns library (PPL) as a parallel framework. Perfect automatic parallelization is difficult due to dynamic features such as pointer operation and polymorphism in C/C++ language. This study focuses on verifying the conditions of parallelization rather than focusing on fully automatic parallelization, and providing advice to developers in detail if parallelization is not possible.

We studied the Implementation and design of inertial sensor that enables to improve performance by reduce the noise of rotor which Angle of inclination. Analyze model equation including motion equation and error, signal processing filter algorithm on high frequency bandwidth with eliminates error using estimation of error coefficient method is was designed and the prototype inertial sensor showed the pick off noise up to 0.2 mV and bias error performance of about 0.06 deg/hr by the experiments. Accordingly, we confirmed that the design of inertial sensor was valid for high rotation.

Recently, the number of people visiting the hospital is increasing due to diabetes. According to the Korean Diabetes Association, statistically, 1 in 7 adults over the age of 30 are suffering from diabetes. As such, diabetes is one of the most common diseases among modern people. In this paper, in addition to blood sugar, which is widely used for diabetes awareness, BMI, which is known to be related to diabetes, triglycerides and cholesterol that cause various complications in diabetics it was studied using random forest techniques and decision trees known to be effective for classification. The importance of each element was confirmed using the results and characteristic importance derived using two techniques. Through this, we studied the diabetes-related relationship between BMI, triglyceride, and cholesterol as well as blood sugar, a factor that diabetic patients should pay much attention to.

Blended learning is a teaching method utilizing all the advantages in ‘on and off-line’ learning circumstances in order to enhance the learning effect and efficiency, more than the simple use of online factors in the classroom education. In this paper, we present the realization and simulation of algorithm for the realtime evaluation of low-grade and high-grade subjects in order to implement smart e-learning system, considering a lecture intelligibility. In order to grasp the levels of student’s intelligibility, we simulated a function that automatically summarizes the study contents of class given by a lecturer. Especially, in administrator mode of smart e-learning system, we suggested and simulated a system in order to help the lecturer to easily manage the student’s grades, and we have provided software to tell the student’s intelligibility of lecture, analyzed the rate of incorrect answers, automatic judgment of lecture intelligibility and judge the weakest subject

The advantage of the distance learning universities based on the 4th Industrial Revolution is that anyone can conveniently take lectures anytime, anywhere on the web. In addition, research has been actively conducted on the effect of light color and temperature control upon student performance during online classes. However, research on how the conditions of subjects, lighting colors, and music selection improve the degree of a student’s concentration during online lectures has not been completed. To solve these problems in this paper, we have developed automatic analysis system SW for the weak subjects of learners by applying intelligent analysis algorithm, have proposed and simulated music therapy and art therapy. Moreover, It proposed in this paper an algorithm for an automatic analysis system, which shows the weak subjects of learners by adopting intelligence analysis algorithms. We also have presented and simulated a music therapy and art therapy algorithms, based on the blended learning, in order to increase students concentration during lecture.

At the end of 1997, the volatility of the exchange rate intensified as the nation's exchange rate system was converted into a free-floating exchange rate system. As a result, managing the exchange rate is becoming a very important task, and the need for forecasting the exchange rate is growing. The exchange rate prediction model using the existing exchange rate prediction method, statistical technique, cannot find a nonlinear pattern of the time series variable, and it is difficult to analyze the time series with the variability cluster phenomenon. And as the number of variables to be analyzed increases, the number of parameters to be estimated increases, and it is not easy to interpret the meaning of the estimated coefficients. Accordingly, the exchange rate prediction model using artificial neural network, rather than statistical technique, is presented. Using DNN, which is the basis of deep learning among artificial neural networks, and LSTM, a recurrent neural network model, the number of hidden layers, neurons, and activation function changes of each model found the optimal exchange rate prediction model. The study found that although there were model differences, LSTM models performed better than DNN models and performed best when the activation function was Tanh.

The cabbage extract of the research does not show cytotoxicity, and thus can be used safely. In an experiment performed on an animal model with liver injury induced by a drug (APAP), it could be seen that the cabbage extract exhibited the effects of protecting liver and improving liver function by effectively reducing AST and ALT which are liver injury markers, indicating that the cabbage extract is effective as a pharmaceutical composition for preventing or treating liver disease. In particular, the cabbage extract was effective in treating inflammation of the liver by reducing the expression of the inflammatory mediators iNOS and COX-2 and the proinflammatory cytokine IL-1β, which are involved in acute inflammatory reactions accompanying liver injury. In the research, an extract of cabbage heat-treated at a temperature of 100 to 150°C had a better liver function-improving effect or anti-inflammatory effect than an extract of raw cabbage.

Red rose petals are usually disposed but they are an abundant source of phenolics and traditionally used as food supplement and as herbal medicine. Of the Various phenolics, they are known to have anticancer, antioxidant, and anti-inflammatory properties. In this study, we investigated the anti-inflammatory effects of red rose ethanolic extracts (GRP) on lipopolysaccharide (LPS)-activated RAW 264.7 cells. The results demonstrated that pretreatment of GRP (500μg/mL) significantly reduced NO production by suppressing iNOS protein expression in LPS-stimulated cells. Anti-inflammatory effects by red rose petals were observed in the following. Red rose petals inhibited the translocation of NF-κB from the cytosol to the nucleus via the suppression of IκB-α phosphorylation and also inhibited LPS-stimulated NF-κB transcriptional activity. These findings suggest that red rose petals exert anti-inflammatory actions and help to elucidate the mechanisms underlying the potential therapeutic values of red rose petals. Therefore, red rose petals could be regarded as a potential source of natural anti-inflammatory agents.

Air pollution is a problem of environmental health risk in big cities. Recently, researchers have proposed using various artificial intelligence technologies to predict air pollution. The proposed model is Cooperative of Artificial Neural Network (ANN) and Fuzzy Inference System (FIS), to predict air pollution of Korean cities using Python. Data air pollutant variables were collected and the Air Korean Web site air quality index was downloaded. This paper’s aim was to predict on the health risks and the very unhealthy values of air pollution. We have predicted the air pollution of the environment based on the air quality index. According to the results of the experiment, our model was able to predict a very unhealthy value.

Wireless Sensor Network (WSN) field is mainly studied to monitor and characterize large-scale physical environments to track various environmental or physical conditions, such as temperature, pressure, wind speed and humidity. WSN can be used in various applications such as wild surveillance, military target tracking and monitoring, dangerous environmental exploration and natural disaster relief. We design probabilistic mobile models that apply to mobile ad hoc network mobile environments. A probabilistic shift model proposed by dividing the number of moving nodes and the distance of travel into two categories to express node movement characteristics. The proposed model of movement through simulation was compared with the existing random movement model, ensuring that the width and variation rate of the first node node node node (FND) was stable regardless of the node movement rate. In addition, when the proposed mobile model is applied to the routing protocol, the superiority of network life can be verified from measured FND values. We overcame the limitations of the existing random movement model, showing excellent characteristics in terms of energy efficiency and stable in terms of changes in node movement.

The purpose of this research is to organize panels centered on professional workers and experts in the sports media industry, identify structures and items of sports media commentators' attributes that conform to the present era through the collective agreement process, and evaluate the derived measures according to the scale development procedure. We would like to shed new light on the nature of commentators due to the rapid development of broadcasting technology and the emergence of new media platforms, the emergence and expansion of smart media receptors and the changing environment of modern sports broadcasting. For this purpose, a panel of experts from academia and industry related to sports management and sports media was organized and the attributes of commentators were analyzed using the Delphi method. Technology development in the sports market has created a new sports consumption environment. In these consumer environments, various environmental factors influence the consumer's consumption culture of sports consumers. For example, professional information, as well as interpretations of sports culture, history and society are becoming their share for sports commentators, and viewers are demanding more diverse characteristics from sports commentators. In this respect, the study of sports commentator attributes can be a deep understanding of the rapidly changing culture of sports consumption.

This paper presents an implementation of a gesture recognition platform that can be used in a factory workplaces. The platform consists of signages that display worker’s job orders and a control center that is used to manage work orders for factory workers. Each worker does not need to bring work order documents and can browse the assigned work orders on the signage at his/her workplace. The contents of signage can be controlled by worker’s hand and arm gestures. Gestures are extracted from body movement tracked by 3D depth camera and converted to the commands that control displayed content of the signage. Using the control center, the factory manager can assign tasks to each worker, upload work order documents to the system, and see each worker’s progress. The implementation has been applied experimentally to a machining factory workplace. This flatform provides convenience for factory workers when they are working at workplaces, improves security of techincal documents, but can also be used to build smart factories.

The Muslim population is growing significantly in Asian countries. By conducting an experiment, this study examines the cultural differences between South Korean and Indonesian female, young adults, and their perception of hijabis who are represented in the media. The main goal of this study is to compare the perception towards hijabis in a homogenous country new to Muslims against a Muslim-majority country. Results showed that non-hijabis were deemed more physically attractive, empathetic, and enjoyable among Koreans when compared to Indonesians. Through this study, we provide a theoretical explanation using cultivation theory and (parasocial) contact hypothesis to clarify the differences between South Korea and Indonesia. This study provides a baseline of understanding to determine where both cultures are at in perceiving hijabis. Our results suggest that it will be compelling to correct media representation in order to reduce stereotypes and lead to a successful understanding of both cultures.

Smart contract, one of the applications of blockchain, is expected to be used in various industries. However, there is risks of damages caused by attacks on vulnerabilities in smart contract codes. Tool support is essential to detect vulnerabilities, and as new vulnerabilities emerge and smart contract implementation languages increase, the tools must have extensibility for them. We propose a design model for extensible architecture of smart contract vulnerability detection tools that detect vulnerabilities in smart contract source codes. The proposed model is composed of design pattern-based structures that provides extensibility to easily support extension of detecting modules for new vulnerabilities and other implementation languages of smart contract. In the model, detecting modules are composed of independent module, so modifying or adding of module do not affect other modules and the system structure.

The purpose of this study is to identify the subjectivity of patient and describe the characteristics of each type to understand the categorization of types on patient safety. Q methodology was applied to the study. A total of 40 patients admitted to the S hospital in Seoul were asked to categorize 33 statements on patient safety. The collected data was analyzed using QUANL PC Program. After analysis, patient safety as perceived by the admitted patient was categorized into 6 types. The types were as follows: Type 1 ‘Those who note adequate patient safety’, Type 2 ‘Those who consider preventive safety to be lacking’ Type 3 ‘Those who see the evaluation criteria to be met’, Type 4 ‘Those who see the facility safety to be lacking’, Type 5 ‘Those who find the patient and facility safety to be adequate’, Type 6 ‘Those who see patient support to be lacking’. The study provides a basic set of data for developing mediation measures needed to identify the direction in which patient safety should be promoted.

The purpose of this study is to analyze the structural relationship among information attitude, brand attitude, usage satisfaction, brand image and brand loyalty of YouTube sports Contents. The survey subjects to achieve the purpose of this study were selected the 490 YouTube sports contents Viewer in the metropolitan area. Data processing was done with SPSS 23 for frequency analysis, Cronbach's α analysis. Also, AMOS 21 was used for confirmatory factor analysis and structural equation model analysis. The results of the analysis are as follows: First, it is more effective to increase the attitude toward the brand itself rather than information attitude to use satisfaction Second, both information attitude and brand attitude were found to have a positive effect on enhancing brand image. In relation to attitude and image, it was possible to achieve research accumulation for YouTube users. Third, it was found that both the use satisfaction and the brand image presented in the previous study had a positive effect on brand loyalty.

Visual art elements can most intuitively express the information expressed by a game character and play an important role in shaping a successful game character. We compares and analyzes the role design in the skins of the "Five Tiger-like Generals" series in Glory of Kings in terms of color, line, graphic and other visual elements. Different visual elements form different visual impacts and influences, which brings people different psychological feelings and presents different emotional colors. The reasonable use of visual elements gives people a refined visual experience and a comfortable psychological feeling, adding more influencing factors to the "immersion" of the game. It not only can strongly attract the attention and love of players, but also spreads traditional culture of the nation and the country. Therefore, whether the visual art elements of a game character can be appropriately used is an important part of the success of the game work. The analysis of visual art elements of game characters has important learning and research value.

This paper investigates the non-intrusive speech intelligibility estimation method in noise environments when the bottleneck feature of autoencoder is used as an input to a neural network. The bottleneck featurebased method has the problem of severe performance degradation when the noise environment is changed. In order to overcome this problem, we propose a novel non-intrusive speech intelligibility estimation method that adds the noise environment information along with bottleneck feature to the input of long short-term memory (LSTM) neural network whose output is a short-time objective intelligence (STOI) score that is a standard tool for measuring intrusive speech intelligibility with reference speech signals. From the experiments in various noise environments, the proposed method showed improved performance when the noise environment is same. In particular, the performance was significant improved compared to that of the conventional methods in different environments. Therefore, we can conclude that the method proposed in this paper can be successfully used for estimating non-intrusive speech intelligibility in various noise environments.

Repetition of landing with visual control in sports and training is common, yet it remains unknown how landing with visual control affects postural stability and lower limb kinetics. The purpose of this study was to test the hypothesis that landing with visual control will influence on lower limb control for intrinsic dynamic postural stability. Kinematics and kinetics variables were recorded automatically when all participants (n=10, mean age: 22.00±1.63 years, mean heights: 177.27±5.45 cm, mean mass: 73.36±2.80 kg) performed drop landings from 30 cm platform. Visual control showed higher medial-lateral force, peak vertical force, loading rate than visual information condition. This was resulted from more stiff leg and less time to peak vertical force in visual control condition. Leg stiffness may decrease due to increase of perturbation of vertical center of gravity, but landing strategy that decreases impulse force was shifted in visual control condition during drop landing. These mechanism explains why rate of injury increase.

The purpose of this study was to investigate the changes in the use of mobile phones due to COVID-19. The subjects of this study were those who lived in Jeju City and used their own mobile phone for more than 2 years, and were included in adult men and women aged 15 to 80 years old. The purpose of this study was explained and a questionnaire survey was conducted on 156 people who agreed. The survey period lasted from June 15 to July 4, 2020. As a result, the daily use time and function of the mobile phone, which were used more than before the occurrence of COVID-19, increased. This was a statistically significant trend (p<0.001) with increasing trend after COVID-19 in all age groups. In addition, in the mobile phone function, all age groups used more ‘KakaoTalk’ than 'call', but it was found that only the group with less than 1 hour of daily using time used the call function a lot.