Earticle

The type approval system for railway vehicle has been in effect since 2016 in order to establish a regular safety management system to secure railway safety and enhance the technological competitiveness of the railway industry, abolished the conventional performance test system through the reform of the Railroad Safety Act in 2012. Until now, there has been appreciated it has been making significant contributions to railway safety and industry of operation and manufacturing companies, taking their place in accordance with the implementation of the system. But there has been no case of quantitative analysis on the effectiveness of the actual system. In this study, in order to examine the full-scale performance of the approval system and quantitatively analyze effectiveness, we identified and defined the relationships with the major elements of the type approval system based on system thinking principle and determined the calculated outcomes to relevant stakeholders. A method of establishing a type approval performance management system that can be grasped, utilized, and adjusted from a point of various stakeholders' views was proposed. This is expected to be more helpful in the implementation of the system, such as improving and applying quantitative effects to analysis by closely reviewing the effects and influencing factors of the type approval system based on the data accumulated through continuous performance management and reflecting to system improvement.

The purpose of this study is to check whether the satisfaction of the R&D (Research & Development) project directly affects the R&D performance, and to find out whether the satisfaction with regional connectivity and the satisfaction with the R&D operation management significantly mediate the relationship that the satisfaction with the R&D project has on the R&D performance. In order to verify the research hypothesis on this, a total of 51 companies located in Jeollanam-do that actually conducted R&D research projects were surveyed and analyzed. In order to conduct an empirical study based on the collected questionnaire, a survey questionnaire related to the variables of the study model was composed based on a sample of 51 questionnaires. We used the SPSS program to verify the hypotheses in this study, and the hypotheses were verified by analyzing the validity, reliability, correlation, and deflection. As a result, there was a positive (+) significant relationship between R&D project satisfaction and R&D performance. In addition, it was found that the relationship between R&D project satisfaction and R&D performance was significantly mediated by the satisfaction with R&D regional connectivity and satisfaction with R&D project operation management.

In the background of the rapid development of the IoT, smart home work is becoming more and more important to each science and technology company. Smart home provides a safe, comfortable, high-quality, high-performance smart home living space compared to general homes, and at the same time It is responding to the low-carbon, eco-friendly global trend. Growth drivers driving the smart home market are increasing the number of Internet users, increasing disposable income in developing countries, increasing the importance of remote home monitoring, and increasing the need for energy saving and low carbon. In 2013-2014, Xiaomi launched a series of smart routers and smart home hardware devices. In 2015, it announced the latest product of the Xiaomi Ecological Chain, the “Smart Home Package,” and in 2016 launched the MIJIA brand to invest in various smart product companies. In 2017, Xiaomi announced a plan to build an open smart hardware MIOT platform. We investigated the management strategy of Xiaomi home smart service based on IOT. The management strategy was divided into cost lead strategy, differentiation strategy of Xiaomi home service, and AIOT strategy of Xiaomi smart home.

The Internet was created as a decentralized and autonomous system of interconnected computer networks used for data exchange across mutually trusted participants. The element technologies on the Internet, such as inter-domain and intra-domain routing and DNS, operated in a distributed manner. With the development of the Web, the Web has become indispensable in daily life. The existing web applications allow us to form online communities, generate private information, access big data, shop online, pay bills, post photos or videos, and even order groceries. This is what has led to centralization of the Web. This centralization is now controlled by the giant social media platforms that provide it as a service, but the original Internet was not like this. These giant companies realized that the decentralized network’s huge value involves gathering, organizing, and monetizing information through centralized web applications. The centralized Web applications have heralded some major issues, which will likely worsen shortly. This study focuses on these problems and investigates blockchain’s potentials for decentralized web architecture capable of improving conventional web services' critical features, including autonomous, robust, and secure decentralized processing and traceable trustworthiness in tamper-proof transactions. Finally, we review the decentralized web architecture that circumvents the main Internet gatekeepers and controls our data back from the giant social media companies.

Recently, social technologies have been created to solve problems from businesses for the establishment of generational solidarity ecosystem in terms of employment, residential space, network and social capital, age, cognitive and environmental aspects. This is senior-friendly healthcare business system aimed at meeting the senior needs for health life to enjoy active consumption culture life even after retirement, becoming a catalyst for minimizing generational conflicts, preventing the cognitive and physical deterioration of seniority in the areas of life healthcare, fitness and well-aging, and expanding into systems necessary for seniority selfreliance. We would like to draw up the development and requirements of the concept of the service platform for the study of collective characteristics for generation solidarity with senior class and the establishment of a customized senior health life system for generation solidarity. This system is characterized by a platform that can prevent the decline of seniors' cognitive and physical functions and enhance emotional stability. It is significant in providing feedback on the risk perception index, fall index, and prevention training index information to the child through the analysis and extraction of the senior health index for risk perception, fall probability, and fall prevention.

Gait kinematics and kinetics have a similar tendency between men and women, yet it remains unclear how walking while carrying a load affects the gait mechanism. Twenty adults walked with preferred velocity on level ground of 20 m relative to change of a load carriage (no load, 15%, 30% of the body weights) aimed to observe gait mechanism. We measured gait posture using the three-dimensional image analysis and ground reaction force system during stance phase on left foot. In main effect of gender difference, men showed increased displacement of center of gravity (COG) compared to women, and it showed more extended joint angle of hip and knee in sagittal plane. In main effect of a load difference, knee joint showed more flexed postuel relative to increase of load carriage. In main effect of load difference on the kinetic variables, mediallateral force, anterior-posterior force (1st breaking, 2nd propulsive), vertical force, center of pressure (COP) area, leg stiffness, and whole body stiffness showed more increased values relative to increase of load carriage. Also, men showed more increased COP area compared to women. Interaction showed in the 1st anteriorposterior force, and as a result of one-way variance analysis, it was found that a load main effect had a greater influence on the increase in the magnitude of the braking force than the gender. The data in this study explains that women require little kinematic alteration compared to men, while men in more stiff posture accommodate an added load compared to women during gait. Additionally, it suggests that dynamic stability is maintained by adopting different gait strategies relative to gender and load difference.

AR (Augmented Reality) is a technology that provides virtual content to the real world and provides additional information to objects in real-time through 3D content. In the past, a high-performance device was required to experience AR, but it was possible to implement AR more easily by improving mobile performance and mounting various sensors such as ToF (Time-of-Flight). Also, the importance of mobile augmented reality is growing with the commercialization of high-speed wireless Internet such as 5G. Thus, this paper proposes a system that can provide AR services via GNN (Graph Neural Network) using cameras and sensors on mobile devices. ToF of mobile devices is used to capture depth maps. A 3D point cloud was created using RGB images to distinguish specific colors of objects. Point clouds created with RGB images and Depth Map perform downsampling for smooth communication between mobile and server. Point clouds sent to the server are used for 3D object detection. The detection process determines the class of objects and uses one point in the 3D bounding box as an anchor point. AR contents are provided through app and web through class and anchor of the detected object.

The development of the fourth industry has enabled users to quickly share a lot of data online. We can analyze big data on information about tourist attractions and users' experiences and opinions using artificial intelligence. It can also analyze the association between characteristics of users and types of tourism. This paper analyzes individual characteristics, recommends customized tourist sites and proposes a system to provide the sacred texts of recommended tourist sites as AR services. The system uses machine learning to analyze the relationship between personality type and tourism type preference. Based on this, it recommends tourist attractions according to the gender and personality types of users. When the user finishes selecting a tourist destination from the recommendation list, it visualizes the information of the selected tourist destination with AR.

While the fifth generation (5G) and beyond 5G (B5G) mobile communication networks are being rolled over the globe, several world-wide companies have already started to prepare the sixth generation (6G). Such 6G mobile networks targets ultra-reliable low-latency communication (URLLC). In this paper, we challenge to reduce the inherent latency of existing non-orthogonal multiple access (NOMA) in 5G networks of massive connectivity. First, we propose the novel unipodal binary pulse amplitude modulation (2PAM) NOMA, especially without SIC, which greatly reduce the latency in existing NOMA. Then, the achievable data rates for the unipodal 2PAM NOMA are derived. It is shown that for unequal gain channels, the sum rate of the unipodal 2PAM NOMA is comparable to that of the standard 2PAM NOMA, whereas for equal gain channels, the sum rate of the unipodal 2PAM NOMA is superior to that of the standard 2PAM NOMA. In result, the unipodal 2PAM could be a promising modulation scheme for NOMA systems toward 6G.

Recently, applications are increasing the importance of security for published documents. This paper deals with data-publishing where the publishers must state sensitive information that they need to protect. If a document containing such sensitive information is accidentally posted, users can use common-sense reasoning to infer unauthorized information. In recent studied of peer-to-peer databases, studies on the security of data of various unique groups are conducted. In this paper, we propose a security framework that fundamentally blocks user inference about sensitive information that may be leaked by XML constraints and prevents sensitive information from leaking from general user. The proposed framework protects sensitive information disclosed through encryption technology. Moreover, the proposed framework is query view security without any three types of XML constraints. As a result of the experiment, the proposed framework has mathematically proved a way to prevent leakage of user information through data inference more than the existing method.

Recently, studies on wearable devices in ubiquitous computing environments have increased and the technology collecting user’s activities to provide services has received great attention. We have compared the step counting methods according to sensor molding methods in case of counting steps by using the piezoelectric sensor. We have classified the cases which could result from the course of molding the internal module of a smart shoe as follows: (i) the module is unmolded, (ii) molded but only to the extent that a sensor is fixed or (iii) molded to the extent that a sensor is not moved. Moreover, we have made comparison to verify which algorithm should be used to increase the accuracy of counting steps by the respective cases. Based on the comparison result, we have confirmed that the accuracy of counting steps is higher when using gradient value rather than when using threshold value. In the case of no molding and small molding under the condition of using gradient value, it was turned out to be 100% accuracy for step counting.

Over the past few decades, natural language processing research has not made much. However, the widespread use of deep learning and neural networks attracted attention for the application of neural networks in natural language processing. Sentiment analysis is one of the challenges of natural language processing. Emotions are things that a person thinks and feels. Therefore, sentiment analysis should be able to analyze the person’s attitude, opinions, and inclinations in text or actual text. In the case of emotion analysis, it is a priority to simply classify two emotions: positive and negative. In this paper we propose the deep learning based sentimental analysis system according to various optimizer that is SGD, ADAM and RMSProp. Through experimental result RMSprop optimizer shows the best performance compared to others on IMDB data set. Future work is to find more best hyper parameter for sentimental analysis system.

This paper presents a smartphone application for the clinical practice education conducted in hospitals, with an aim to evaluate its effectiveness. A nonequivalent control group posttest design was used, which included a total of 100 nursing of school students who conducted their clinical practice. They were divided into one control and one experimental group (50 students each). The control group was directly trained in the clinical practice orientation, and the experimental group was a group who self-learned the clinical practice orientation using a smartphone application. Research data were collected between March 5 and April 27, 2019. They were analyzed with descriptive statistics and independent t-test, using the SPSS Statistics Version 24. The smartphone application customized for the clinical practice education was implemented through the following four phases: analysis, design, development, and evaluation. The developed application was registered in Google Play (for Android apps) and Apple Store, and related information was provided, making it available for download. The study showed that the satisfaction with and self-confidence in learning differed significantly between the groups. However, technology acceptance and knowledge acquired through practice showed no statistically significant difference. The research results serve as basic data for applying smartphone applications as an educational method that can replace traditional modes of education, serving as a significant indicator of the education delivery method diversification.

This study evaluated the effect of simulation training on cardiac arrest in hospitals for inactive nurses with 360 VR content, and attempted to prepare basic data for simulation training for inactiv nurses in the future. The design of this study is an experiment study before and after a single group. The study period was from October 13, 2020 to December 17, 2020. The subjects of the study were a total of 21 nurses who participated in the education program for inactive nurses. For simulation training for inactive nurses, Microsoft Powerpoint, hybrid simulation, high-fidelity simulation, and 360 VR content were applied for theories education and practical education. As a result of the study, the satisfaction level of the curriculum for the cardiac arrest situation in the hospital for inactive nurses was 4.78±0.36 points out of 5 points. Understanding of education was 4.71±0.46 points out of 5 points. Usefulness of education was 4.80±0.40 points out of 5 points. Confidence in airway maintenance before and after training, BLS review, manual defibrillator, emergency medication administration, airway maintenance, emergency situation simulation, and debriefing were all significant. According to the results of this study, simulation training of the situation of cardiac arrest in the hospitals for inactive nurses was effective. In future studies, it will be necessary to develope and verify specific teaching and learning methods by applying various cases of cardiac arrest situations in consideration of the type of hospitals

We study confirmed the factors influencing the organizational culture(collective culture, development culture, rational culture, hierarchical culture) perceived by members of the organization and the manager's authentic leadership(self-awareness, balanced information processing, relational transparency, internalized moral perspective) on job crafting. In addition, the relationship between organizational culture and authentic leadership was empirically analyzed. In order to verify the hypothesis of the research model, the survey results of 269 parts were verified as follows using the statistical program of SPSS 24.0. First, the organizational cultures perceived by members of the organization, development culture and rational culture, showed positive (+) influence on job crafting. In other words, Hypothesis 1 established by the research model was partially adopted. Second, the group culture, development culture, and rational culture of organizational culture were statistically significant in the relationship between the hypothesis 2 organizational culture and authentic leadership. In other words, Hypothesis 2 was partially adopted. Third, the three hypotheses of authentic leadership (self-awareness, balanced information processing, relational transparency, and an internalized moral perspective) all showed positive (+) effects on job crafting. As a result of this study, it was possible to confirm the importance of the organizational culture that improves the job-crafting of the members of the organization and the strategic activation plan for authentic leadership. Therefore, the necessity of strategic human resource development for the development and application of programs to revitalize organizational culture and improve the manager's authentic leadership has emerged.

This paper proposes a probabilistic method in analyzing timing measurements to determine the periodicity of real-time tasks. The proposed method fills a gap in existing techniques, which either concentrate on the estimation of worst-case execution times, or do not consider the stochastic behavior of the real-time scheduler. Our method is based on the Z-test statistical analysis which calculates the probability of the measured period to fall within a user-defined standard deviation limit. The distribution of the measured period should satisfy two conditions: its center (statistical mean) should be equal to the scheduled period of the real-time task, and that it should be symmetrical with most of the samples focused on the center. To ensure that these requirements are met, a data adjustment process, which omits any outliers in the expense of accuracy, is presented. Then, the Z-score of the distribution according to the user-defined deviation limit provides a probability which determines the periodicity of the real-time task. Experiments are conducted to analyze the timing measurements of real-time tasks based on real-time Linux extensions of Xenomai and RT-Preempt. The results indicate that the proposed method is able to provide easier interpretation of the periodicity of real-time tasks which are valuable especially in comparing the performance of various real-time systems.

The purpose of our study is to confirm the trend of the muscle activity of the trunk and lower limb muscles by the attack method and phase during volleyball exercise. To achieve this purpose, spike serve and spike were conducted for 9 male middle school students, and at that time, it was divided into four phase, such as run jump, take off, impact, and follow, and the rectus abdominis, erector spine, and left rectus femoris, left biceps femoris, left anterior tibialis, left gastrocnemius midialis, right rectus femoris, right biceps femoris, right anterior tibialis, right gastrocnemius midialis, were examined. Spike serve and spike were each performed three times, and randomly cross-allocated to extract accurate data. We was no difference in all muscles according to the attack method, and the muscle activity of the rectus abdominis was highest in the impact phase and the muscle activity of the vertebral spine muscle was highest in the close-up phase. In addition, all of the measured left and right lower limb muscles showed the highest muscle activity between the assisted devices. As a result, We found out that regardless of the method of spike serve and spike, the lower limbs in the run-up phase for a high jump, the vertebrae in the take off phase, the preparation phase for hitting the ball strongly, and in the impact phase at the moment of hitting the ball. It can be seen that it exerts the greatest power in the rectus abdominis.

The purpose of this study was to investigate the difference in the number of repetitions and the change in electromyographic response during the maximum speed squat exercise according to the depth conditions and the maximum speed squat exercise according to the time of each depth. Ten men in their 20s were selected as subjects and the maximum speed squat was performed for one minute in three environmental conditions (ground, knee depth, waist depth). We found that the number of repetitions according to the depth of water showed a significant difference, and as a result of the post-mortem comparison, the number of repetitions was higher in the ground condition and the knee depth than in the waist depth. And the muscle activity of rectus abdominis, erector spinae, rectus femoris, biceps femoris was increased during ground squat exercise, activity of all muscle was decreased during knee depth squat exercise, and activity of rectus abdominis, erector spinae, biceps femoris, tibialis anterior, gastrocnemius was decreased during waist depth squat. In conclusion, muscle activity of lower extremities during squat exercise in underwater environment can be lowered as the depth of water is deep due to buoyancy, but muscle activity of trunk muscles can be increased rather due to the effect of viscosity and drag.

This paper proposes a new personalized HRTF estimation method which is based on a deep neural network (DNN) model and improved elevation reproduction using a notch filter. In the previous study, a DNN model was proposed that estimates the magnitude of HRTF by using anthropometric measurements [1]. However, since this method uses zero-phase without estimating the phase, it causes the internalization (i.e., the insidethe- head localization) of sound when listening the spatial sound. We devise a method to estimate both the magnitude and phase of HRTF based on the DNN model. Personalized HRIR was estimated using the anthropometric measurements including detailed data of the head, torso, shoulders and ears as inputs for the DNN model. After that, the estimated HRIR was filtered with an appropriate notch filter to improve elevation reproduction. In order to evaluate the performance, both of the objective and subjective evaluations are conducted. For the objective evaluation, the root mean square error (RMSE) and the log spectral distance (LSD) between the reference HRTF and the estimated HRTF are measured. For subjective evaluation, the MUSHRA test and preference test are conducted. As a result, the proposed method can make listeners experience more immersive audio than the previous methods.

With the introduction of China's new policies, the Chinese animation industry has gradually formed a sustainable industrial structure chain, and the output value of the animation market is also in a state of continuous growth. . Since 2013, domestic animation has been developing from “lower age” to “ageing” and “adults”. At the same time, with the popularization of China's pan-entertainment industry model, the multidomain symbiosis of the Internet and mobile Internet has been realized, creating a fan economy of star IP (Intellectual Property), and promoting the linkage of various industries under the same IP. This paper mainly analyzes the development of the animation IP market in China's pan-entertainment mode in recent years, and analyzes the cross-media operation mode of the animation industry. At the same time, it studies the application of self-media in animation.

In cloud computing service it is important to share the system resource among multiple instances according to user requirements. In particular, the issue of efficiently distributing I/O resources across multiple instances is paid attention due to the rise of emerging data-centric technologies such as big data and deep learning. However, it is difficult to evaluate the I/O resource distribution of a Linux container, which is one of the core technologies of cloud computing, since conventional I/O benchmarks does not support features related to container management. In this paper, we propose a new I/O performance benchmarking framework that can easily evaluate the resource distribution of Linux containers using existing I/O benchmarks by supporting container-related features and integrated user interface. According to the performance evaluation result with trace-replay benchmark, the proposed benchmark framework has induced negligible performance overhead while providing convenience in evaluating the I/O performance of multiple Linux containers

In this paper, we propose an image watermarking technique that effectively hides confidential data in the LSB of image pixels by utilizing the characteristics of the image. In the proposed technique, the image is precisely divided into boundary surface and normal region other than the boundary surface and performs different processing. The boundary surface existing in the image is created by meeting different regions and contains important information of the image. One bit of confidential data is concealed in the LSB of the pixel at the boundary surface to preserve the characteristics of the boundary surface. In normal region other than the boundary surface, the pixel values are similar, and the change with the adjacent pixel values is smooth. Based on this property, even if the 2 bits of confidential data are hidden in the lower 2 bits of the pixel in the normal region, the difference cannot be visually distinguished. When confidential data is concealed in an image as described above, the amount of confidential data concealed in an image can be increased while maintaining excellent image quality. Concealing confidential data by applying the proposed method increases the amount of confidential data concealed by up to 84.6% compared to the existing method. The proposed technique can be effectively used for commercial image watermarking that hides copyright information.

This study proposes a plan to construct an integrated platform that reduces manufacturing costs and efficiently produce by integrating the systems of main producers, production subcontractors, and raw material subcontractors for the production of food packaging containers. The production plan of food packaging containers and raw materials is established in real time between the main producers, production subcontractors, and raw material subcontractors in consideration of the demand characteristics of each product. It establishes basic information that all processes from the production planning stage to the forwarding stage of the product are linked to each other. The progress of each producer of interlinked processes is shared in real-time to improve productivity and quality of food packaging containers and raw materials and reduce manufacturing costs. By monitoring the system of the main producer and the production subcontractor in real time, the production of food packaging containers is performed in a timely manner, thereby improving productivity. The application of the plan-do-check-action (PDCA) process, which includes planning, execution, evaluation and improvement in the production operation processes of the main producer, production subcontractor and raw material subcontractor, enables improved production compliance rate. The contents of the main producers, production subcontractors, and raw material subcontractors are managed in real time, then a converged production management system is established through the platform proposed in this study to ensure timely supply and demand of raw materials without delay in ordering.

The term, eGovernmen or e-Government, uses technology communications devices such as computers and the Internet to provide public services to citizens and others. The eGovernment or e-government provides citizens with new opportunities to access the government directly and conveniently, while the government provides citizens with direct services. Also, in these days, cloud computing is a feature that enables users to use computer system resources, especially data storage (cloud storage) and on-demand computing power, without having to manage themselves. The term is commonly used to describe data centers that are available to many users over the Internet. Today, the dominant Big Cloud is distributed across multiple central servers. You can designate it as an Edge server if it is relatively close to the user. However, despite the prevalence of egovernment and cloud computing, each of these concepts has evolved. Research attempts to combine these two concepts were not being made properly. For this reason, in this work, we aim to produce independent and objective analysis results by separating progress steps for the analysis of e-government cloud service platforms. This work will be done through an analysis of the development process and architectural composition of the e-government development standard framework and the cloud platform PaaS-TA. In addition, this study is expected to derive implications from an analysis perspective on the direction and service composition of the e-government cloud service platform currently being pursued.

CNN (Convolutional Neural Network), a type of deep learning algorithm, is a type of artificial neural network used to analyze visual images. In deep learning, it is classified as a deep neural network and is most commonly used for visual image analysis. Accordingly, an AI autonomous driving model was constructed through real-time image processing, and a crosswalk image of a road was used as an obstacle. In this paper, we proposed a low-cost model that can actually implement autonomous driving based on the CNN model. The most well-known deep neural network technique for autonomous driving is investigated and an end-to-end model is applied. In particular, it was shown that training and self-driving on a simulated road is possible through a practical approach to realizing lane detection and keeping

The aim of this study was to investigate the learning styles with personalities of medical students which may affect the efficiency of teaching-learning system of clinical education to determine the association with the clinical performance examination achievement of the students. The learning styles and personality traits of 147 students of medical college were investigated. The obtained data were analyzed by statistical analysis including independent t-test and correlation analysis. The results of the analyses are as follows: there was significant difference in the participation model in the different genders; of the personality traits, there was significant difference in self-transcendence in the different genders, whereas there was significant difference in the persistence for past failure experiences; and there was significant association between the 6 sub-learning models (Independent vs. Dependent, Collaborative vs. Competitive, and Participant vs. Avoidant learning styles) and the personality traits (Novelty Seeking, Harm Avoidance, Reward Dependence, Persistence, Self-directedness, Cooperativeness and Self-transcendence). In addition, the participant type of students had higher scholastic achievements in clinical performance, and the students who scored high in self-transcendence and persistence also had higher clinical performance. In conclusion, the student’s learning style and personalities affected the clinical scholastic performance. We believe that considering this current study, it would be possible to improve the quality of clinical education of medical teaching as well as helping medical students to choose career paths that are suitable for their personalities.

This study aimed to help build a quality control program to improve cardiac arrest treatment via analysis of medical records in a local tertiary general hospital to evaluate factors that influence clinical outcomes of inhospital cardiac arrest. At first, the medical records of in-hospital cardiac arrest were analyzed, and targeted surveys about functional and structural factors associated with cardiopulmonary resuscitation (CPR) were conducted amongst the workforce in charge of cardiac arrest treatment. From January 2012 through June 2013, a total of 486 adult cases of in-hospital cardiac arrests, except for those occurring in the emergency room, were enrolled in this study. Among the patients, those of recovery of spontaneous circulation were 57.8%; 13.8% of patients were discharged alive; 8.9% of patients were discharged without significant neurologic sequela. Despite CPR is usually successful when administered as quickly as possible, in this analysis showed that prompt reaction after initial recognition was significantly lower in nurses compared with doctors. Analysis of survey results showed that confidence in performing CPR was significantly associated with the experience of CPR in doctors, while in nurses educational experience showed a correlation. In order to improve quality of in-hospital CPR system maintaining and increasing confidence of CPR performance is the most important factor. Therefore it can be helpful to develop and apply a phased, customized education program using training simulators as well as personalizing them to increase the personnel's confidence in CPR performance.

Game theory has been regarded as a useful theoretical tool for modeling the interactions between distinct entities and thus it has been harnessed in various research field. In particular, research attention has been shown to how to apply game theory to modeling the interactions between malign and benign entities in the field of wireless networks. Although various game theoretic modeling work have been proposed in the field of wireless networks, our proposed work is disparate to the existing work in the sense that we focus on mobile malign node detection problem in static wireless sensor networks. More specifically, we propose a Bayesian game theoretic modeling for mobile malign node detection problem in static wireless sensor networks. In our modeling, we formulate a two-player static Bayesian game with imperfect information such that player 1 is aware of the type of player 2, but player 2 is not aware of the type of player 1. We use four strategies in our static Bayesian game. We obtain Bayesian Nash Equilibria with pure strategies under certain conditions.

Although many different types of covert channels have been suggested in the literature, there are little work in directly applying game theory to building up covert channel. This is because researchers have mainly focused on tailoring game theory for covert channel analysis, identification, and covert channel problem solving. Unlike typical adaptation of game theory to covert channel, we show that game theory can be utilized to establish a new type of covert channel in IoT devices. More specifically, we propose a covert channel that can be constructed by utilizing the Nash Equilibrium with sensor data collected from IoT devices. For covert channel construction, we set random seed to the value of sensor data and make payoff from random number created by running pseudo random number generator with the configured random seed. We generate I × J (I ≥ 2, J ≥ 2) matrix game with these generated payoffs and attempt to obtain the Nash Equilibrium. Covert channel construction method is distinctly determined in accordance with whether or not to acquire the Nash Equilibrium.