Earticle

The purpose of the study is to contribute to the positive development of blockchain technology by providing data to examine security vulnerabilities and threats to blockchain-based services and review countermeasures. The findings of this study are as follows. Threats to the security of blockchain-based services can be classified into application security threats, smart contract security threats, and network (P2P) security threats. First, application security threats include wallet theft (e-wallet stealing), double spending (double payment attack), and cryptojacking (mining malware infection). Second, smart contract security threats are divided into reentrancy attacks, replay attacks, and balance increasing attacks. Third, network (P2P) security threats are divided into the 51% control attack, Sybil attack, balance attack, eclipse attack (spread false information attack), selfish mining (selfish mining monopoly), block withholding attack, DDoS attack (distributed service denial attack) and DNS/BGP hijacks. Through this study, it is possible to discuss the future plans of the blockchain technology-based ecosystem through understanding the functional characteristics of transparency or some privacy that can be obtained within the blockchain. It also supports effective coping with various security threats.

The causes of noise generation according to the classification of indoor spaces are very diverse. Individual happiness is infringed by this noise. In this paper, We tried to visualize the spatial sound characteristics of public places using sound color to express them so that anyone can sympathize. The noise inside a conference room of a medical device company was measured for 100 minutes, and the frequency band was divided into three different types of existing sound pressure expression units. Because the size of the noise is expressed differently depending on the situation, There are cases where there is a difference of opinion between the measurer and the researcher. This noise measurement experiment was conducted, and the sound color was applied to classify it on a log scale considering auditory characteristics. As a result of comparing this with the result expression for different loudness expression units, A specific table in different units yielded almost similar results. In addition, the sound source section for 100 minutes was divided into three analysis sections, the analysis sections were different, and the size of the energy ratio for each analysis section was divided in the form of an envelope. The characteristics of the low-frequency region of the space have a high energy ratio, and the decrease in the energy ratio according to the increase in frequency is constant and regular. You can see that conversations are possible.

This study evaluates the accuracy of corrective feedback from Grammarly, an online grammar checker, on essays written by cyber university learners in terms of detected errors, suggested replacement forms, and false alarms.The results indicate that Grammarly has a high overall error detection rate of over 65%, being particularly strong at catching errors related to articles and prepositions. In addition, on the detected errors, Grammarly mostly provide accurate replacement forms and very rarely make false alarms. These findings suggest that Grammarly has high potential as a useful educational tool to complement the drawbacks of teacher feedback and to help learners improve grammatical accuracy in their written work. However, it is still premature to conclude that Grammarly can completely replace teacher feedback because it has the possibility (approximately 35%) of failing to detect errors and the limitations in detecting errors in certain categories. Since the feedback from Grammarly is not entirely reliable, caution should be taken for successful integration of Grammarly in English writing classes. Teachers should make judicious decisions on when and how to use Grammarly, based on a keen awareness of Grammarly’s strengths and limitations.

This research explored methods for improvements to be made within the field of drone usage within the construction industry based on an investigation of factors which limit their efficiency and productivity. Limiting factors and improvement measures were presented in terms of technology, service, law and policy for employing drones at construction sites. Our first suggestion is, from a technical point of view, that companies need to expand professional manpower and infrastructure for systematic management. Second, in terms of service expansion, it is necessary to have management capabilities for operation such as the use of drones with enhanced safety and reinforced on-site education and personal information management. Third, in terms of legal and institutional support measures, it is necessary to prepare a plan for reforming the legal system for revitalization and to expand the training of professional manpower. This study may contribute not only to the development of drone technology, but also to effectively respond to various problems that appear at construction sites.

Lempel-Ziv coding is one of the most famous source coding schemes. The output of this source coding is usually a non-uniform code, which requires additional source coding, such as arithmetic coding, to reduce a redundancy. However, this additional source code increases complexity and decoding latency. Thus, this paper proposes the optimal maximum a-posteriori (MAP) receiver for non-uniform source non-orthogonal multiple access (NOMA) with symmetric superposition coding (SSC). First, we derive an analytical expression of the bit-error rate (BER) for non-uniform source NOMA with SSC. Then, Monte Carlo simulations demonstrate that the BER of the optimal MAP receiver for the non-uniform source improves slightly, compared to that of the conventional receiver for the uniform source. Moreover, we also show that the BER of an approximate analytical expression is in a good agreement with the BER of Monte Carlo simulation. As a result, the proposed optimal MAP receiver for non-uniform source could be a promising scheme for NOMA with SSC, to reduce complexity and decoding latency due to additional source coding.

In most existing researches on non-orthogonal multiple access (NOMA) with symmetric superposition coding (SSC), uniform sources have been usually considered. For the first part in this two-part paper, for the strongest channel gain user, we showed that the bit-error rate (BER) for the optimal maximum a-posteriori (MAP) receiver for the non-uniform source improves slightly, compared to that of the conventional receiver for the uniform sources. We demonstrate that in communication scenarios of the non-uniform source NOMA schemes, for the weakest channel gain user, the BER performance of the optimal MAP receiver for a non-uniform source improves greatly, compared to that of the conventional receiver for uniform sources. We first derive an analytical expression of the BER for non-uniform source NOMA with SSC. Then, simulations demonstrate that the BER of the optimal MAP receiver for the non-uniform source improves, compared with that of the conventional maximum likelihood (ML) receiver for the uniform sources. In result, the proposed optimal MAP receiver for the non-uniform source could be a promising scheme for SSC NOMA, with improved BER performances.

The purpose of this paper is to present the Over-The-Top (OTT) platforms’ strategies for two-sided markets. For this, we examine six strategic factors influencing OTT’s success in Korea. The analysis reveals, among six OTTs, Netflix utilizes five strategic factors except the same-side network effects. OTTs from pay TV operators and channel providers tend to block the cross-side network effects on the opponent OTTs, because they think their giveaway to content providers is in vein, if the invested content by them would be consumed on opponent rival platforms. Interesting is that after experiencing a negative association between the market entry of Netflix and the subscription revenue growth rate of pay TV services, pay TV operators utilize the sameside network effects by offering hybrid services in partnership with global OTTs like Netflix, Disney+ which are considered as a complementary OTT. In conclusion, it is suggested to target a new connected TV based OTT service offering with collaboration with Korean TV device manufacturers for Korean OTTs’ global strategy, because Netflix-like global market expansion is not easy for them to cover their content cost.

The purpose of this paper is to identify keywords related to museums, gamification, and visitors, and provide basic data that the museum market can be expanded by using gamification. That used to collect data for blogs, news, cafes, intellectuals, academic information by Naver and Daum which is Web documents in Korea, and Google Web, news, Facebook, Baidu, YouTube, and Twitter for analysis. For the data analysis period, a total of one year of data was selected from April 16, 2020 to April 16, 2021, after Corona. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analysed and visualized using the Netdraw function in the UCINET6 program. In addition, We performed CONCOR analysis to derive clusters for similar keywords. As a result, a total of 25,761 cases that analysing the keywords of museum, gamification and visitors were derived. This shows that the museum, gamification, and spectators are related to each other. Furthermore, if a system using gamification is developed for museums, the museum market can be developed.

Currently, the Korean wave is not limited to popular culture, but has a significant impact not only on Korea's national image but also on the improvement of Korean companies' products and image of Korea. In this study, using Textom to confirm the change in foreign tourists' image of Korea, the data collection period was 1 year of 2020, when COVID 19 occurred, as a collection period for "Korea and foreigner" and related key words, each Hallyu content, and ranked in the top 80 keywords were derived. Centrality analysis for semantic network visualization was performed using UCINET6, and through CONCOR analysis, 7 groups 'K-Quarantine ', 'K-Drama', 'K-Movie', 'K-Beauty', 'K-Shopping', It was clustered into 'K-Tech' and 'K-Pop'. As a result of the analysis, the image of Korea abroad generally recognized the Korean Wave as cultural content, but after the outbreak of COVID 19, it is judged that it has been recognized as a country with a successful case of K-Quarantine.

Electronic learning (e-learning) empowers the higher education in providing sustainable instruction during the infrequent circumstance when the wide-spreading disastrous challenge of the COVID-19 results in the closure of various sectors in the society. During this time, e-learning serves the levels of the education sector such as higher education well by delivering and receiving materials from distance with respect to movement restrictions imposed by the government, for example the Movement Control Order (MCO) in Malaysia. In this qualitative survey, the existing e-learning challenges and the recommended solutions to the problems from the senior lecturers’ perspectives were collected through an online open-ended questionnaire. A number of five senior lecturers out of eight at the Universiti Teknologi Malaysia (UTM) answered the questionnaire. The UTM has been capable of providing e-learning courses for all of its lecturers and students during the closure of higher education institutions owing to the pernicious health conditions stemmed from the crisis of the COVID-19. The major existing challenges found in the e-learning program at the UTM and the suggested solutions to address them are listed and the main themes are illustrated in the word cloud format using the NVivo software. In the end, the conclusion is paragraphed and the future work is proposed. Overall, the purpose of this study is to address the e-learning challenges and to prepare a list of recommendations that can serve as solutions from the standpoint of the UTM senior lecturers during the MCO in Malaysia.

The logistics market is continuously growing due to the development of technology and the growth of the online market. In addition, the social atmosphere that emphasizes non-face-to-face due to the pandemic situation is accelerating the growth of logistics. Delivery of goods ordered online requires delivery process through courier worker. In order for the courier worker to ship the product, the work of loading the product on the truck must be preceded. The accident caused by such delivery and loading work is increasing and it is emerging as a social problem. This study proposes a robot-based automated loading system to efficiently handle the increasing volume of courier service and to construct a more efficient and safe working environment by replacing the physical labor that was overloaded to courier workers. The proposed system replaces the loading of the courier worker and proposes the optimal loading function through the automation system.

The development of CG technology throughout the 2000s brought about a significant growth in the animation market. This phenomenon led to an increase in the number of people required by related industries, which led to an increase in the number of related majors in universities. CG application technologies are becoming more common with the advent of YouTube and virtual YouTubers, but high technology is still required for students to get a job. This situation is not easy to include both technological and creative skills in the college animation curriculum. In order to increase students' creativity, we need a lot of production experience, which requires a lot of knowledge and time if we only use tools like Maya and 3D Max. In this paper, We tried to devote more time to storytelling by minimizing the technical process required for production and proceeding with repetitive or difficult processes for content creation using third-party programs. And through the 12-week class, the experimental production process was applied to the process from planning to completion of animation works that students would submit to the advertisement contest.

In modern society, digital lifestyles are spreading to minimize contact with people and to receive contactless information. The spread trend has established an unmanned distribution system in which transactions through contactless technologies such as kiosks and chatbots are activated in face-to-face transactions with sellers and consumers. In order to streamline logistics supply worldwide, digital new deal based joint logistics hubs, unmanned courier storage platforms, and fresh logistics based last mile services have been developed into unmanned logistics systems, focusing on the intelligent logistics system automation process. Unmanned courier storage system installed in urban areas and home to daily logistics where volume is concentrated are provided with fresh logistics services through cold chain and receiving freights in contactless environments. Development is also underway to minimize safety accidents caused by courier services, such as managing various information based on the integrated control system. This paper defines the concept of integrated operation for the development of a platform for contactless unmanned courier storage device developed into next-generation logistics system. In addition, we intend to develop systems engineering-based output for deriving safety requirements and specifications by identifying risk sources that may occur in the operational scenario. Therefore, the goal is to establish a foundation for safety and reliability between interfaces of logistics systems to be installed in apartment and subway station environments that want to provide unmanned logistics services to various consumers.

Recently, the number of consumers using digital online distribution platforms is increasing. This caused the rapid growth of the e-commerce market and increased delivery volume in urban areas. The logistics system, designed ar006Fund the city center to handle the delivery volume, operates a delivery system from the outskirts of the city to the urban area using cargo trucks. This maintains an ecosystem of high-cost and inefficient structures that increase social costs such as road traffic congestion and environmental problems. To solve this problem, research is being conducted worldwide to establish a high-efficiency urban joint logistics system using urban railway facilities and underground space infrastructure existing in existing cities. The joint logistics system begins with linking unmanned delivery automation services that link terminal delivery such as cargo classification and stacking, infrastructure construction that performs cargo transfer function by separating from passengers such as using cargo platform. To this end, it is necessary to apply the device to the vertical and horizontal transportation machine supporting the vertical transfer in the flat space of the joint logistics terminal, which is the base technology for transporting cargo using the transfer robot to the destination designated as a freight-only urban railway vehicle. Therefore, this paper aims to derive holistic viewpoints needs for design requirements for vertical and vertical transportation machines and freight transportation standard containers, which are underground railway logistics transport devices to be constructed by urban logistics ecosystem changes.

In order to design a real time big data collection and analysis system of manufacturing data in a smart factory, it is important to establish an appropriate wired/wireless communication system and protocol. This paper introduces the latest communication protocol, OPC-UA (Open Platform Communication Unified Architecture) based client/server function, applied user interface technology to configure a network for realtime data collection through IoT Integration. Then, Database is designed in MES (Manufacturing Execution System) based on the analysis table that reflects the user's requirements among the data extracted from the new cutting process automation process, bush inner diameter indentation measurement system and tool monitoring/ inspection system. In summary, big data analysis system introduced in this paper performs SPC (statistical Process Control) analysis and visualization analysis with interface of OPC-UA-based wired/wireless communication. Through AI learning modeling with XGBoost (eXtream Gradient Boosting) and LR (Linear Regression) algorithm, quality and visualization analysis is carried out the storage and connection to the cloud.

Since the first semester of 2020, domestic and overseas universities mostly provided untact online classes and limitedly provided face-to-face classes due to COVID-19 in operating courses. The convergence subjects provided in undergraduate courses attach importance to contents-centered, design-based, hands-on education, and field experience. In the situation where online education was not revitalized, instructors in charge of convergence subjects had difficulty in developing online class materials, and students’ satisfaction with the classes was not high. Especially, a problem was raised that students taking the convergence subjects that included practice had difficulty in communicating with the instructors. We would investigate the present condition of distance learning in domestic universities, which came suddenly due to the global pandemic of infectious disease and make suggestions for effective distance learning in the coming era of Metaverse by emphasizing the interaction and communication between instructors and learners through an analysis of distance learning of a convergence subject.

Estimating the locations of workers in a shipyard is beneficial for a variety of applications such as selecting potential forwarders for transferring data in IoT services and quickly rescuing workers in the event of industrial disasters or accidents. In this work, we propose a human movement stream processing system for estimating worker locations in shipyards based on Apache Spark and TensorFlow serving. First, we use Apache Spark to process location data streams. Then, we design a worker location prediction model to estimate the locations of workers. TensorFlow serving manages and executes the worker location prediction model. When there are requirements from clients, Apache Spark extracts input data from the processed data for the prediction model and then sends it to TensorFlow serving for estimating workers’ locations. The worker movement data is needed to evaluate the proposed system but there are no available worker movement traces in shipyards. Therefore, we also develop a mobility model for generating the workers' movements in shipyards. Based on synthetic data, the proposed system is evaluated. It obtains a high performance and could be used for a variety of tasks in shipyards.

Recently, by applying the 4th industrial revolution technologies such as A.I., IoT, and big data to general residential infrastructure, various application services of residential-based are provided to residents through linkage and utilization between technologies. Accordingly, smart housing system is increasing as advanced living spaces that can improve the quality of life and convenience of residents. Such a smart housing is expected to be an item that can create new demands and markets in the construction industry since it provides a new paradigm that combines construction technology and IT by combining IT technology with existing construction industry. Based on this, it is expected that it will be possible to gradually develop large-scale markets such as smart buildings and smart cities. In this paper, therefore, we propose an artificial intelligence multiplex smart housing system as an intelligent platform that can autonomously manage and control the size of places and spaces, used for various purposes based on smart housing technology by using artificial intelligence systems.

The purpose of this study is to develop and validate the disaster safety awareness scale for high school students. For this purpose, the previously developed disaster safety awareness scale and related prior research was analyzed. Questionnaire data was collected from March 22 to May 25, 2021 from 1054 students (male: 569, female: 485) in the first, second, and third grades of 5 high schools in 3 cities. Through the process of revising, supplementing, and reviewing the items extracted through preliminary research and preliminary test together with experts and students, a final disaster safety awareness scale consisting of 24 items was developed. This scale consists of four sub-factors: 'disaster prevention', 'disaster response A', 'disaster response B', and 'disaster recovery'. Good reliability and validity were secured through exploratory and confirmatory analyses. The significance of this study is that it laid a basic and objective foundation for high school students' disaster safety awareness research by developing a validated scale in a situation where the development of disaster safety awareness scales for high school students was still insufficient. It can be used as useful data for fire safety education as well as a psychological measurement tool for fostering fire safety awareness.

The purpose of this study was to investigate the relationship between the formation of advertising attitudes and purchase intentions for users' products according to the difference in engagement of SNS sports advertisements and provide them with evidence to suggest directions for SNS sports advertising strategies. For this purpose, after establishing a hypothesis between engagement, advertising attitude, and purchase intention, a questionnaire was distributed to employees of sports administration organizations that have experienced or are using SNS and statistically processed using 460 copies of self-administeration. Through this process, we obtained the following results. First, it was found that engagement had a significant effect on advertising attitude. Second, it was found that engagement had a significant effect on purchase intention. Third, it was found that advertising attitude had a significant effect on purchase intention. From the results of this study, it can be seen that the SNS sports advertisement engagement has a positive effect on the attitude and purchase intention of advertisements conducted on SNS. In other words, it should be actively used to increase more efficient advertising attitudes and purchase intentions through this identified engagement.

This study aims to examine 1) the influence of festival emotional and function values on travelers’ positive festival memory, festival attachment, and experience sharing behavior, and (2) the moderation effect of online friendship among the path. In the present study, the proposed model was developed based on the MTS from 340 collected participants who have experienced the festival held in Guangdong Province in China. The SPSS and AMOS were used for statistical analysis. The results revealed that emotional and function festival values are positively related to the positive festival memory of travelers; positive festival memory significantly influences festival attachment and experience sharing behavior of travelers. Meanwhile, festival attachment also has a significantly positive effect on the experience-sharing behavior of travelers. Moreover, the presented differential experience sharing behavior of travelers follows the level of their online friendship. Travelers with high online friendships presented higher sharing behavior than travelers with low online friendships. Depending on the results of this study, we could provide some theoretical implications for future festival research and online communication research. These results could provide some practical implications for festival managers to develop more communication strategies.