KJC Korea
Journal Central

Currently, smartphones are used in various online services such as electronic payments, stocks, and mobile banking. So far, there have been many studies to counter attacks that can occur when entering a password on a smartphone. Secure numeric keypads, which are currently popularly used, add spaces between keys or shuffle the order of keys to improve the security of existing keypads. Keypads with spaces have a problem that the location of the touched key is easily exposed to the attacker, and the method of shuffling the order of the keys can easily be exposed to the attacker when the password consists of the same number. In this paper, we propose a secure numeric keypad against password guessing attacks that can occur when entering a password on a smartphone. The proposed keypad shuffles the order of the keys and moves the touched keys to a random location so that the password composed of the same numbers is not easily exposed to the attacker. As a result, it is possible to avoid touching the same location when entering the same numbers. Therefore, the proposed keypad is strong against the password guessing attack that can occur when entering a password on a smartphone.

Recently Sensor network technology is a core infrastructure of ubiquitous environment in advanced intelligent society where anyone can use the knowledge and service they want anytime, anywhere by detecting or storing, processing, and integrating the information of things or environment from a number of miniaturized wireless sensors. In this paper, we use MIMO channel emulator for channel modeling in real environment and conduct wireless channel characteristic modeling which has a great influence on sensor data communication performance. We will design sensor network transceiver considering distortion by surrounding environment through measurement of USN sensor node, channel modeling and processing, visualization and analysis of channel measurement data. Cell planning is performed in advance using the wireless design software (RF-vu) of iBwave before the actual measurement-related equipment arrangement. The purpose of this step is to investigate the environment of the selected test site and to predict the received field strength (RSSI) through RF-vu. By using RF-vu, antenna is established in the arrangement on scenario and each location received intensity is measured. By doing so, time and effort can be reduced when actual related facilities are arranged and accuracy of channel modeling can be increased through the predicted result. In this paper, channel characteristics reappearance using Channel Emulator equipment is a method of reproducing channel characteristics based on standard channel model, and the other is channel emulator based on data measured using measurement equipment. The channel model was generated and the channel characteristics were reproduced.

Damage of the inner walls of a facility due to external factors such as earthquakes is not only difficult to diagnose but also includes visible crack. In the case of a crack detection system using a camera, blind spots were impossible to detect. Crack detection system which uses impedance characteristics and TDR which uses smart sheets didn't have blind spots, but had difficulties finding small cracks. Smart sheets were originally developed to detect damage of underground facilities, but it is possible to modify their form to attach them to the inside of the facility. The damage detection algorithm using impedance characteristics specified the damage location by filling the smart sheet with pulses of a certain length then measuring the time using the impedance discharge factor. However, this system's structure have to create approximation error between discharge start time and the measurement start time, which depends on warm-up situation and changes in the surrounding environment. In this paper, crack detection tape made with copper thin film is applied to the inner wall of the facility. The embedded system used one channel of ADS1015 to dataize detection pulses and reflected waves. Experiments and verification were conducted through simulated break testing after installing crack detection tape adapted for buildings using thin copper film tape on the walls of buildings. Collected the measured data to validate the enhanced crack detection system.

Automatic recognition technology is one of the representative technologies of the Fourth Industrial Revolution and is currently used in various fields. RFID and NFC systems that we know are also being used by applying automatic recognition technology. RFID systems have evolved to replace existing barcode systems in a variety of areas that can be utilized as automatic recognition technologies. The biggest problem with today's RFID-enabled auto-recognition systems is the conflict between the leader and the tag that occurs when sharing the radio spectrum. Collision occurs when a tag within the recognition distance sends a signal to the reader simultaneously. If multiple tags are present in the RFID system and want to be recognized at the same time, the recognition performance of the tags will be significantly reduced and the recognition system will be able to recognize them. Causes performance problems. In other words, collision arbitration is aimed at fast and reliable recognition between RFID readers and tags, so it must be done without fail. It's a necessary skill. Existing studies use a variety of complex multi-connection technologies and collision prevention algorithms to mediate conflicts between tags. The anti-collision algorithm between leader and tag proposed in this paper used mechanical learning used in artificial intelligence. The problem with the existing Anti-Collision algorithm is extracted by learning the appropriate number of frames to mediate tag conflicts using instructional learning. Performance was compared with existing algorithms. We would like to study how to improve the leader recognition rate by using collision prevention algorithm using mechanical learning in recognition between tags and readers.

With the Big Data growing in the popularity, more and more architectures are being proposed, but no unified solution is at hand. The main objective of this thesis is to specify and prepare a conceptual measurement model on which selected Big Data Platform Architecture will be mapped and compared. The conceptual measurement model is split into multiple components with the specification of responsibilities, and the their scope of the conceptual measurement model is set. All architectures mapped in a single structure are then evaluated and compared. Our research contains a brief overview of the Big Data concept and a summary of technologies used in evaluated architectures, if available. In addition, social commerce is a new paradigm infrastructure model of commercial market, which use of Web 3.0 technologies and social data to support their exchange activities. While it is popular, being a subset of commercial market, has been increasing tremendously since its introduction in 2012, there exists a general particular of research on their framework and applications’ effectiveness, especially in areas beyond the general social commerce practices. This research develops a comprehensive social commerce framework in big data environment that has four key components. Then our research applies the Big Data Platform (BDP) to analyze the usability and adaptability with the framework by applying it to social commerce successful companies. Accordingly, we provide a set of metrics for social commerce-based Big Data Platform design. The proposed our framework and they are used to lead the design and evaluation in social commerce environment. This research makes a contribution to the social commerce in proposing a new design framework and also, we have to examine in providing inside for effective approach of concerning with their social business.

The change in the cloud-based computing environment and the development of computing technology are moving toward supporting to maximize the use of data that is so called Bigdata. This direction will be an environment leading to a truly ubiquitous computing environment that Mark D. Weiser emphasized. As the 4th Industrial Revolution spreads, structured or unstructured data is being produced in vast amounts every moment. These Bigdata are collected, pre-processed, and stored somewhere in a distributed processing system to be used to create the value of Bigdata. Along with such changes in the computing environment, mobile cloud services support providing a variety of desired services through mobile devices and other cloud services. However, most of these services are provided using only location information, and the user directly searches for and uses the service. In order to improve this problem, context recognition technology is being used. Recently, there is a lot of interest in healthy beauty. Accordingly, or as a trend, many people are showing a lot of interest in various data generated as they wear wearable devices, walk, run, and go up and down stairs. To support more efficient personalization services, this paper proposed a context recognition method for personalization services in Bigdata that uses user information and profiles after collecting and pre-processing data generated.

Smelt fishing is one of the representative winter activities in Korea, and The Ministry of Culture and Tourism selected the smelt festival as a representative regional festival. Although smelt fishing is a popular leisure activity, it is difficult for ordinary people to experience it individually. With the recent development of a mobile-based smelt fishing game, the ordinary people can easily experience smelt fishing. However, it is difficult to provide high presence and high immersion with existing mobile-based smelt fishing games. VR technology is needed to solve this problem. In this paper, we propose a VR-based immersive smelt fishing game composed of a virtual environment considering real smelt fishing environment and a VR controller shaped like a smelt fishing rod. In the virtual environment, the fishing rod moves according to the movement of the VR controller held by the user. and so that the user can recognize that smelt bites, The virtual environment send the data packet which operate vibration motor to VR controller and then user is provided with haptic information(vibration) about of virtual environment was modeled with reference to the objects(smelt rod, fishing rod holder, bucket, bobber) that can be seen in the real smelt fishing environment. And since the graphic model developed in this study is used as an element of virtual environment map composition, virtual environment can provide high presence to users. The VR controller consists of a microcontroller, a vibration motor, a rotating motion sensor, a wired communication module, and a smelt rod-shaped housing. The VR controller shaped like a smelt fishing rod can give the user the sensation of holding a real smelt fishing rod. In addition, user evaluation was conducted to verify the empirical validity of the developed VR controller. The proposed VR-based immersive smelt fishing game is expected to be widely used for other fishing games and fishing-related festivals or programs.

In conventional communication systems, throughput optimization problems have been mainly dealt with in terms of protocol designs such as routing, scheduling, and encoding/decoding efficiency. However a new optimization solution has been required and widely studied for complex multivariate systems such as multi-hop MIMO networks. Cross-layer optimization has been introduced as the basic framework for the theoretical solutions to improve the network performance, and there has been a plethora of approaches to extend the cross-layer optimization processes to the multi-hop MIMO networks. Contrary to the legacy SISO, if the cross-layer optimization is applied to MIMO networks without appropriate variables reduction, the computation complexity increases exponentially. Linking the physical layer operations of MU-MIMO to other layer features such as MAC scheduling may cause a tremendous computational overhead. The problem itself has characteristics that cannot be easily expressed in LP, and even if expressed in LP, numerous variables presented in the system prevent a practical optimization. The purpose of this paper is to solve the problem of minimum length scheduling that satisfies a given traffic demand in a multi-hop MIMO network with a cross-layer optimization scheme. The solution we proposed is to devise an optimized scheduling algorithm based on LP decomposition through column generation. Through various mathematical analysis and test results, we have confirmed that the proposed method greatly improves the system performance significantly.

The decline in agricultural labor force not only makes it difficult to operate the agricultural machinery itself, but also leads to a tendency to avoid more dangerous work when it is involved, leading to a decrease in agricultural productivity. In particular, in the case of agricultural fields such as orchards, which target field crops, there are many restrictions on the development of unmanned technologies to reinforce the labor force. In the case of orchards, the most common work is to use a control device to spray pesticides. The control method of the existing batch spraying method causes excessive use of pesticides and scattering problems to neighboring farms, and in particular, farmers in the field are damaged by exposure. For this study, using a LiDAR sensor that has strong straightness and can accurately recognize the location of an object, it recognizes the shape of a fruit tree based on 3D location data, and applies down sampling and threshold processing techniques. In addition, it has been prepared so that hardware can be easily configured by simply installing an injection device, a controller, and a sensor in the existing commercial control unit. By recognizing the shape of the fruit tree and spraying pesticides only where necessary, a control algorithm was developed to reduce the use of pesticides and efficiently control work, and the effects were compared and analyzed through the paper cut.

Recently, as the real-time data generated by sensors in connection with location information rapidly increases in the IoT environment, studies on various services using a big data platform have been conducted. In this big data platform, research on continuous query processing including data aggregation operation has been proposed to effectively analyze sensor big data constantly flowing for multi-user needs. However, the existing resource-sharing-based aggregation operation has a problem of concurrent execution of time-based and tuple-based queries and an increase in memory usage and deterioration in query processing performance due to duplicated maintenance of aggregate information. Therefore, in this paper, we propose a resource sharing method to effectively support continuous aggregation query processing based on Spark, an in-memory based distributed processing framework. The proposed method minimizes the increase in the cost of processing aggregate information through linear resource sharing based on summary information for the scope of query processing, and reduces the memory usage required for continuous aggregate query processing. Also, our method improves query processing performance by preventing duplicate generation of aggregate information. The proposed approach is implemented based on Spark framework to ensure real-time performance of continuous aggregate query processing for big data. Finally, through performance evaluation, it is shown that the proposed resource sharing technique can be effectively used for continuous aggregation query processing.

This is a control system identification study using a fuzzy logic algorithm to handle the issue of the controller parameter tuning in a control system with time delay. Among the studies related to the controller parameter tuning for control system identification, Yunwana-Seborg's controller parameter tuning method showed a rapid response in plants with no time delay or with small-time delays due to the phase error caused by Pade's first-order approximation method. However, a large time delay causes a higher time delay estimate and it cannot be applied to the actual system. Zigler-Nichols' loop tuning method, which is widely applied in the industrial field, requires much time to tune controller parameters because it goes through many trials and errors. Although Cohen-Coon's controller parameter tuning method using the process response curve has an advantage of shortening the time required for controller parameter tuning than the Zigler-Nichols’s loop tuning method, it can only be applied to an open loop system. To overcome these shortcomings, Suh proposed to set a phase controller in Pade’s approximation method to reduce the phase error, between the estimated model transfer function while converting time delay into Pade’s first-order approximation and the time delay of an actual plant, as a controller parameter tuning. However, it has a disadvantage that it is not analytical because this method derives by substituting a phase regulator proportional to a constant value in time delay. This study discussed an analytical method that could solve the issue of the phase error between the actual plant and the estimated transfer function using a fuzzy logic algorithm. This study proved that the proposed method could overcome the shortcomings of causing the large time delay estimation and provide quick response and stability by suggesting a logical way to set up a phase regulator based on the comparisons of Zielger-Nichols' loop tuning method, Yunwana-Seborg's method, and the proposed controller parameter tuning method.

This study was carried out for the purpose of collecting basic data by monitoring the silkworm breeding environment for the development of an automated silkworm breeding system. Therefore, the silkworm growth characteristics according to the CO2 concentration, the silkworm growing environment according to the temperature change, and the silkworm wet change according to the humidity change were investigated. As a result, silkworms showed low CO2 concentration during the process of transformation from larva to moth during the pupa period. In addition, it shows the characteristic that the concentration of CO2 is particularly high from the 3rd day of the 4th to the 5th, when the feeding activity is active. In addition, when breeding while raising the breeding density, it can be seen that the CO2 environmental control condition is maintained at around 1,000 ppm, so that the silkworm density can be increased while being raised healthy. It was confirmed that breeding temperature management should be kept low as silkworm breeding progresses, and indoor humidity has a close influence on the feeding activity of silkworms. Therefore, the results of this study will be used as basic data for the development of an automated silkworm breeding systems and are expected to contribute to the improvement of farm household income.

Korea's total exports to small and medium-sized enterprises account for about 70 percent of the FTA's exports to other countries, but most of them are made in Asia, and the proportion to Europe is relatively small. Meanwhile, The prosperity of the cultural contents industry due to the popularity of the Korean Wave has the economic ripple effect of increasing Korea's exports of consumer goods. This means that consumption of the same cultural products increases the cultural proximity between the regions, thereby promoting trade by increasing preference for consumer goods that involve tastes in the selection. Through this, it is expected that Korea's small and medium-sized enterprises will be able to increase their relatively low exports to Europe. As interest in K-pop and Korean broadcasting is growing in Europe, consumer goods such as cosmetics and food are likely to become promising export items to Europe. To take advantage of these opportunities effectively, efforts will be needed to link related products with the Korean Wave content in each field. In this paper, I suggest ways to increase marketing effects and even utilize 'FTA' special regulations for European market by organizing promising items due to the Korean Wave as a set.

The aviation software is developed by dividing the object code part and the parameter part into files. This is because various parameters need to be corrected for optimized flight control, so it is possible to correct only by modifying the parameter file without changing the configuration of the object code. As a result, if the changed parameter is within the valid range proved by the test for the code, the test cost can be reduced because the test for the code verification is unnecessary. These parameters are referred to as Parameter Data Items(PDI) in DO-178C, the standard for aviation software conformance. The conversion of this PDI into a binary file is called PDIF. In this paper, We design and implement a PDIF converter that generates an Excel sheet gain set with various flight scenarios for flight control law data and converts it into a PDIF set. The implemented PDIF converter can perform flight test without changing its configuration when a test is applied to the dynamic environment of Hardware In the Loop Simulation(HILS) for flight safety. The use of the Converter improves test convenience and saves test time as it enables continuous testing of various flight scenarios through PDIF set without interruption compared to the conventional sequential test for each single flight scenario. In addition, the (.dat) file can apply to other types of OFP and reduce the impact of OFP modification.

This study aims to propose a big data center to construct the information on medicinal biological resources and provide the infrastructure to open and share them. The information on the medicinal biological resources consists of basic data such as effects, treatments, and warnings of medicinal biological resources, biochemical data such as chemical compounds of medicinal materials and mappings among compounds and targets, and utilization data such as locations and times of discovery of medicinal resources. In order to ensure the data compatibility, all data was constructed in an open format. The bigdata of medicinal biological resources are opened and searched on our bigdata center (http://kmbigdata.kr) which is constructed based on CKAN. Our bigdata center provides medicinal biological resource data in CSV and RDF file format along with their metadata in DCAT format. Moreover, medicinal biological resource data are provided to the forest bigdata platform using ESB. Therefore, our data can be obtained on the forest big data exchange (http://bigdata-forest.kr). By using the bigdata center and forest big data exchange, it is expected that domain experts and the publics will be able to use the accurate and useful data on medicinal biological resources for the health care and biotechnology companies will be able to search our data to make products such as new drugs and functional foods.

In this study, We study the market dominance strategy of e-commerce. The Internet has mad changes in the commercial environment faster than ever before. So the development of e-commerce through the Internet directly leads to changes in commodity sales platforms. As the market embraced the Internet, the Internet shopping mall developed, and mobile shopping was created as it became possible to sell goods on mobile devices. This paper contains information on the market size and status of e-commerce and provides comparative analysis of the strategies of Coupang and WeMakePrice, the largest social commerce in Korea. This paper contains information on the market size and status of e-commerce and provides comparative analysis of the strategies of Coupang and WeMakePrice, the largest social commerce in Korea. It is hard to conclude that anyone is doing better, but it is clear that both social commerce are doing better in the e-commerce market. Although the e-commerce market is currently saturated, it is likely to be more extreme than degenerate. Comparing the two social commerce, there are some strategic similarities, such as collaboration with other brands and diversification of the number of categories, but Coupang has a clear difference in that it focuses on “fast delivery” and WemakePrice focuses on “price special prices.”

Recently, various solutions have been proposed according to the rapid increase in the level of fine dust. However, technologies such as artificial rainfall and large-sized air purifiers that have been developed or studied to date have the disadvantage of lack of feasibility. Rather, the use of a mask, which has become more important and convenient due to the corona crisis, is emerging as one of the most feasible measures among domestic fine dust countermeasures. Therefore, this paper aims to develop an app system that enables people to efficiently and conveniently pay or purchase masks. In addition, through the developed app system, a response system that allows users to know in real time when a disaster alert such as fine dust occurs can be built. When a fine dust disaster alarm occurs, information on fine dust in the area can be immediately checked in real time using a mobile phone app. When a fine dust alarm occurs, QR code issuance is activated, and through a map in the application, the location of the nearest mask dispensing station, phone number, and mask inventory can be checked in real time. When a mask is provided to a user, the mask dispensing station can modify the mask-related data in the corresponding dispensing station database in real time, and various statistics related to the mask can be checked in real time on the web page and in the dedicated application for administrators. In the future, additional functions will continue to be supplemented by securing disease information and data on various epidemic diseases such as cold and flu, and the algorithm will be continuously improved to more accurately predict the level of fine dust.

This study aims to design and implement a mobile app for health management in Korean medicine. So far, many wearable devices and mobile apps for personal health care have been released. However, there are few mobile apps that manage users’ health based on the knowledge of Korean medicine. Our mobile app in this paper provides the functions such as medical checkup, sasang constitution test, life log record, and Korean medicine knowledge search. Currently, it is being used to input health checkup questionnaires conducted at the Korean medicine medical checkup centers and receive the results. Users also can perform a simplified sasang constitution test with body and questionnaire information in the mobile app. Like general wearable devices, it records and manages daily, weekly, and monthly activity and sleep information. In addition, it helps personal health by allowing users to search for the knowledge of Korean medicine by constitutions and diseases. In the future, we plan to conduct research on adding and improving functions of our mobile app. By linking with the Korean medicine PHR system, it is planned to supplement the personal health record function based on the Korean medicine. In particular, it will be possible to improve the quality of medical care by using daily personal health information with hospital clinical information through linking with hospital electronic medical records or charts.

The purpose of this study was to identify the level of academic persistence and to investigate the effects of content quality factors on academic persistence, and the mediating effect of learning flow, learning satisfaction between content quality factors and academic persistence in online education on 1st semester of 2020 responding to COVID-19. The survey was conducted to the students who were taking online education on 1st semester of 2020 in offered by N University in Chungnam, and 665 cases were analyzed for this study. Data was analyzed structure equation modeling and the mediating effect was verified by Sobel test. The results of this study were as follows. First, service quality factor among content quality factors had one of the biggest direct impacts, information quality factor did not affect, system quality factor had on of negative direct impacts on academic persistence. Second, learning flow and learning satisfaction positively mediated content quality factors and academic persistence. In other words, learning flow has influenced positively on learning satisfaction, learning satisfaction has influenced positivelty on academic persistence. Based on these findings, the following suggestions were made. First, professor should focus on increasing the quality of service quality as guide of learning activities, sharing of teaching materials, inspire to further efforts, immediate feedback for effective online education on second semester. Second, students should have enough self-directed learning capability for flow on learning. And university should be provided training contents dealing with communication strategy for professors, motivational strategy and self-directed learning method for students.

This preliminary study aim to investigate the effects of performance of Mendelsohn maneuver and volition on swallowing function and diet level in stroke patients with dysphagia. Fourteen chronic stroke patients with dysphagia participated in present study. The subjects received conventional rehabilitation. The intervention dose for Mendelsohn maneuver was 15 min/days, three times a week, for 8 weeks. The subjects performed Mendelsohn maneuver performance after the first session of treatment and after interventions for 8 weeks. The measurements for swallowing function was performed initial test and after intervention. The canadian occupational performance measure (COPM) and the volitional questionnaire (VQ) was used to evaluate the performance of Mendelsohn maneuver and the volition of rehabilitation. The modified Mann assessment of swallowing ability (MMASA), the swallowing function test (SFT), and the function outcome intake scale (FOIS) was used to assess the swallowing function and dietary level. Performance of Mendelsohn maneuver showed significant improvement after 8 weeks compared to the initial test (p<.05). The SFT, MMASA, FOIS, and VQ showed significant improvement before and after intervention (p<.05). There was no significant difference in the SFT, the MMASA and the FOIS according to the performance of Mendelsohn maneuver (p>.05). In the comparison of dietary levels by volition, the upper group was significantly higher than the lower group (p<.05). These findings suggest that the volition of stroke patients with dysphagia may have a positive effect on dietary levels.

The main injector of a lean premixed prevaporized(LPP) gas turbine combustor for reducing NOx emissions starts to operate from a point where a certain level of thrust is reached and controls to a high thrust. The radial swirler mounted on the main injector plays a large role in thrust control and contributes to stable thrust control. In this paper, the flow characteristics of the air injected from the chamber according to the change of the swirl number are obtained by using Particle Image Velocimetry (PIV), and the flow velocity and spray angle according to the injection position are measured to check the influence of air flow. It was confirmed that the radial swirler, like the axial swirler, also increased the recirculation area as the swirl number increased. When the aerosol was injected into the atmosphere using a radial swirler, the spray angle increased as the number of turns increased, and when the number of turns exceeded a certain number of turns, the aerosol could not move forward direction. This means that the swirl number is increased, when the back pressure gradient is largely formed in front of the slewing machine, the flow must be structurally supplemented so that the flow can proceed forward.

In the underground, facilities such as various types of water supply pipes, sewer pipes, gas pipes, and communication pipes are buried. These underground facilities provide convenience for us to live in the world. The major loss factor in underground facilities is water leakage or pipe breakage. Leakage or damage that occurs among the various types of pipes buried underground is the cause of aging, corrosion, improper work, and subsidence of the pipe. In Korea, the current summer and winter weather is more pronounced than before, so long rainy seasons and typhoons are increasing in summer, and heavy snow and cold waves are occurring in winter. Therefore, although facilities are buried underground, the frequency of occurrence of abnormalities in underground buried materials varies by season. In particular, in summer and winter, when temperature changes are large, the frequency of abnormalities in underground burials increases. In particular, landslides may occur in the basement during certain seasons due to the influence of rainy seasons, typhoons, and heavy snow, or many maintenance problems may occur due to ground subsidence. Despite these problems, existing underground facility management systems are out of date and cannot be prevented in advance, and there is a problem in coping with water leakage or ground subsidence. In addition, there are many problems that the accuracy of monitoring data is also poor. In this paper, we propose an intelligent damage detection system using real-time processing of monitoring data and the probability of seasonal failures to improve the damage detection performance of the existing monitoring system.

The purpose of this study was to investigate the effect of multi-sensory stimulation on swallowing function in stroke patient with dysphagia. Twenty stroke patients with dysphagia participated in this study. Among 20 stroke patients with dysphagia, the 10 patients who have multi-sensory stimulation at the same time were in a experimental group and the other 10 patients who have traditional dysphagia rehabilitation were in a control group. Both groups were randomly assigned. The experimental group received for 4 weeks, for multi-sensory stimulation, visual-auditory stimulation and BPO olfactory stimulation were supplied with traditional dysphagia rehabilitation. For the control group, only traditional dysphagia rehabilitation received. Before and after invention, Videofluoroscopic Swallowing (VFS) was conducted. After that, the data on the test of Functional Dysphagia Scale (FDS), penetration-aspiration scale (PAS), American Speech-Language-Hearing Association National Outcome Measurement System (ASHA NOMS), Olfactory Identification Test was collected. There were significant differences between the data of FDS, PAS, ASHA NOMS before and after invention in the experimental group (p<.05). For the control group, there were significant differences in FDS (p<.05). For change score comparisons between groups, there was greater significant differences in FDS of the experimental group than control group (p<.05). It is confirmed that multi-sensory stimulation has an positive effect on swallowing function in stroke patients with dysphagia.

With the recent spread of 'social distance keeping' with the Corona 19 pandemic, 'untouch' consumption' has become commonplace, and 'untouch society' has emerged as a new paradigm. According to a consumer perception survey of undactored services, post-corona 19 non-face-to-face consumption is expected to increase 1.6 times more than before Corona 19, and 24.7 percent of telemedicine-related industries need to be intensively fostered. We are currently restricted from general face-to-face care due to the Corona 19 Pandemics situation and need to review the introduction of telemedicine at a comprehensive level. However, legal protection such as the Personal Information Protection Act is needed in promoting telemedicine. Due to the nature of telemedicine, a system with the highest level of information security to prevent loss, theft, leakage, tampering, or damage of personal medical information will need to be introduced and established, and the medical law needs to specify laws related to personal information protection. In addition, unlike face-to-face care, which is the principle of the current medical law, telemedicine does not fully guarantee the stability of the outcome of the treatment, as it excludes methods of treatment such as promotion, diagnosis and other diagnosis. Legal attribution of responsibility for misdiagnosis due to problems with telemedicine devices and communication problems, medical personnel between medical personnel at large local hospitals and small hospitals, quality medical services for patients and privacy laws for patients, and government efforts through appropriate social consultations are needed. Currently, the government is temporarily pushing for telemedicine, but legal issues such as the Personal Information Protection Act and imputation issues, as well as problems between medical personnel and patients, need to be discussed and discussed. After these problems are settled, telemedicine needs to be further activated so that it can play a complementary role in face-to-face care for patients in the current Corona19 paradigm, and the effective system between patients and doctors in telemedicine through phased legislation in line with the development of information and communication and medical technology in the future.

We developed a suggestion system that recommends related Korean Medicine symptoms from natural language description of patient's health condition. First, we collected medical information from 200 patients who suffer digestive disorder. Then, three groups of Korean medicine doctors belonging to each of the major Korean medicine associations examined clinical report forms (CRFs) of the patients and specified primary symptoms of the patients. The Korean medicine doctors also attached text evidences of their decision based on the descriptions in the CRFs. Those text descriptions and the symptoms were used as the input text and the label of the system. The features of the multi label support vector machine are term frequencies of the input text. Those terms are the morphemes from Korean morphological analyzer. The model performance measure was the area under cover (AUC) values that is calculated based on the predicted ranks of the true symptom. All AUC values of the models from three independent datasets generated by the three different groups of Korean medicine doctors are more than 0.85 which suggests our system shows consistent and robust performances regardless of the given datasets. Our study is an artificial intelligence (AI) application to Korean medicine and our approach is useful to explore proper symptom names from the thousands of Korean medicine terms. It can be expanded to application to other kinds of disorders easily. Better performance can be achieved by adapting advanced text processing technique and AI models.

In this study was to present the development strategies for beekeeping industry in Korea. Furthermore, the status of royal jelly production was analyzed intensively. Royal jelly was a smart beekeeping among products with high accessibility. The number of beekeepers was about 20,000 or more, with 21.2 thousand in 2012 and 26.5 thousand in 2018. The number of hive was about 2 million by 2015, exceeded 2 million in 2016, 2018. The economic value of the beekeeping industry is estimated at ￦552.7 billion in 2017. In addition, honey bees have the role of pollination, and are responsible for the public benefit of maintaining the natural ecosystem. There was no official statistics on the production of royal jelly worldwide, however China produces more than 90%. In Korea, royal jelly was the third largest beekeeping product in the beekeeping industry, with ￦28.1 billion. As a way to expand the production of royal jelly, the establishment of a smart farm system must be introduced. The current status of smart farm use includes automation technology for supplying to the food and an electric heating device to increase the internal temperature of the hive in early spring. The direction of the smart farm should be automatic monitoring, pest reduction, and labor reduction technologies. The National Assembly promulgated the Act on Support for the Beekeeping Industry on August 28, 2019, and it is in force from August 28, 2020. Through the application of the smart farm system, it is possible to realize stable revenue source creation and labor reduction for beekeepers.

The current environment is moving toward ubiquitous computing, and among the factors that promote the acceleration of such environmental change, various mobile devices with excellent performance and IoT technology, which is the topic of the 4th industrial revolution, are included. The development of various mobile devices and capabilities and the improvement of mobile network infrastructure have made the exchange and sharing of information and resources using mobile devices more active. Mobile cloud services, which combine cloud computing technology with existing mobile services are supporting various services provided through mobile devices and other cloud services. However, most of the existing personalization services are web-based desktop environment services, they are not very suitable for mobile devices. That is why new method for personalization service is required in order to provide to each user by searching for various services and information scattered in the network in consideration of the user's context and user's personal preference in the mobile cloud environment. New framework is required to support services that provide web resources through the cloud. This paper suggested a method for context-based adaptive personalization service is developed to provide more suitable and efficient services in consideration of the user's context and profile in accordance with the user's demands that change according to the context using the user's context information and profile.

In the information age, smart search is essential due to the enormous amount of accumulated information. However most of the query entered into search engines are general nouns with various meanings and are only about 2.4 words on average, making it difficult for search engines to grasp the exact search intention of users. To mitigate this situation, figuring out exact search intention of users is supported by query expansion. In order to develop the query expansion of Korean Medicine clinical decision support system (KM-CDSS), we suggest novel algorithm that consist of 4 steps; first, symptom names are extracted from the prescription information fetched by the initial query. second, extracted symptoms are embedded into a vector space. third, vector space are clustered and each cluster’s quality is evaluated by silhouette coefficient. finally, each words which are laid nearest to the center is suggested as representative symptom. In the experiments, we examined relevance and comprehensiveness qualitatively by KM doctors and utility are analyzed quantitatively. The results of the evaluation of the three indicators were analyzed in an integrated manner. The proposed model showed good enough results in relevance and comprehensiveness test and best result in utility test. It turned out that the proposed model is most suitable as a query expansion model for KM-CDSS. If user search logs are collected in the future, it is expected that related search words will be provided in more sophisticated ways through improved query expansion.

This study focused on analyzing of diligent learner’s motivation and self-direction in learning according to the purpose of attending the course in online learning. For this purpose, survey was conducted with 119 diligent learners completing over 50% of online course at S university. The results were analyzed by dividing the participants into 2 groups of academic credit learners and self-study learners based on the purpose of attending the online course. As a result, there were a significant difference in 5 types of learning motivation, such as curiosity and excitement, interest on the subject, professor's recommendation, sense of challenge, and self-development, except the knowledge acquisition. In addition, area of learning environment management appeared to have a significant difference among the 4 components of self-direction in learning, such as learning value system, learning skill and strategy, learning performance management and learning environment management. The self-study leaners recognizes themselves as having less ability on the control of the learning environment compare to the academic credit leaners. Therefore, in online learning requiring high intrinsic motivation to success, the need of systematic support such as function for checking self-learning step by sharing other learners' learning history, applying of the course completion system, operating the tutor, and having a meeting, etc. is suggested for the self-study learner, even the diligent learner with highly autonomy in the university context.

The damage of wasps in the beekeeping industry is increasing, but there are limitations in continuous control and monitoring. This study was conducted for the purpose of collecting basic data for the development of automatic monitoring system for occurrence status of wasps. The survey was conducted over a total of three years from 2018 to 2020, and once a week from April to November when wasps start to occur. As a result, 494 were collected in 2018, 1272 in 2019, and 795 in 2020, a total of 2561 wasps were captured, and after divided them according to date, attractant agent, and habitat, and then cluster analysis was performed on them. As a result, in 2018, Vespa ducalis and Vespa analis parallela, in 2019, Vespa velutina nigrithorax and Vespa mandarinia, and in 2020, Vespa analis parallela and Vespa velutina nigrithorax were dominant and subdominant species, respectively. It was confirmed that the Vespa velutina nigrithorax (28%) and Vespa analis parallela (23%) were dominant for three year. We monitored the Yellow-legged wasp, an invasive species that has become a problem each year, and as a result, queen bees occur from early May to early June. It was confirmed that the peak period was achieved from middle of September to middle of October. It is expected that the results of this study can be used as basic data that can be used to refer to considerations such as habitats, target species, attractant agent, and monitoring period to be equipped in the monitoring system when constructing an automated wasp monitoring system.

Due to the recent increase in consumer demand for high-quality agricultural and fishery products and interest in safety, it is necessary to improve the quality and productivity of agricultural and fishery products. One way to solve this problem is the precision farming technology of smart greenhouses, which increases the productivity of crops while reducing energy. To realize precision agriculture, it is necessary to derive optimal growth environment data for crops in greenhouse. In addition to farms that use hydroponic cultivation methods, there are farmers who harvest crops through soil cultivation at agricultural sites, so to derive optimal growth environment data for farmers, including both hydroponic and soil cultivation, a data collector was developed to provide wired and wireless communication depending on the situation of greenhouses while allowing the linkage of legacy equipment of existing farms. It also established a data sharing platform to store, analyze, and share collected data. Data collected from data collectors installed in smart greenhouses will be delivered to data sharing platforms through cloud communication, and data sharing platforms will be able to derive an optimized environment through comparative analysis by providing users with greenhouse monitoring functions and sharing data collected from nearby farms. Based on this, it is expected that the data will be developed into forecasting growth of crops, forecasting production, and forecasting insect pests in the future.

This study explored the impact of IT capabilities(IT Knowledge, IT Operation) and Business Intelligence & Analytics(BI&A) Capabilities(BI&A Sensing Capability, Business Process Change Capability) on New Product Collaboration Performance. We tested the employees who worked in manufacturing for more than one year with experience in New Product Development(NPD), and the company has IT departments with. The reliability and feasibility was tested by using the sample 272 data for statistical analysis with SPSS 25.0 and Smart PLS 3.0. The results of the study are summarized as follows: First, IT Knowledge and IT Operations, which are the factors of IT Capabilities, have statistically positive affection on BI&A Sensing Capability. Second, BI&A Sensing Capability have statistically positive affection on Business Process Change Capability. Third, BI&A Sensing Capability have statistically positive affection on New Product Collaboration Performance. Fourth, Business Process Change Capability have statistically positive affection on New Product Collaboration Performance. Therefore, all the hypotheses presented in this study were adopted. In order to improve collaboration performance of new products, it is done thought IT Knowledge and IT Operations through BI&A Sensing Capability, decision making can be made, and collaborative performance can be improved through process change. For the successful development of new products, it is important for companies must apply IT in an integrated manner to support effective and rapid decision-making, and improve BI&A Capabilities and organizational management capabilities to create an environment where process changes can be made.

This study designs agricultural big data platform for commercialization of smart agriculture. The agricultural big data platform was designed in consideration of the management and analysis of data for the establishment of an agricultural data system that is the basis of various agricultural technologies. Data collection and distribution standards for smooth operation were established to enhance the efficiency of information use. The composition of agricultural big data platform consists of data standard management, collection data processing, analysis module, statistical module and information provision module. Data standard management controls data standardization and data quality control. In the processing of collected data, it is responsible for data conversion, processing, and storage, and it is stored separately by weather, farmland, soil, sensor, growth information, and pest data. The analysis module provides information by analyzing the growth prediction, pest prediction and yield prediction information. The statistical module provides information on temperature and humidity, yield and farmland information on farmland. The information generated by the analysis module and the statistical module is provided to the user by dividing the information into weather, farmland, statistics, soil, sensors, growth prediction, and pest prediction through the information provision module. The established agricultural big data platform provides information to farmers and agriculture-related enterprises. Improve farm yield by information-based farm operation. It will be operated for smart agricultural development such as big data and artificial intelligence in agriculture-related enterprises.