KJC Korea
Journal Central

In this paper, we implement a control system for an IoT-based backpack type vacuum cleaner using a smart device such as a smart phone or smart watch. The implementation system consists of control module produces, control module programming, and smart device programming. The control module is made of Arduino Nano, HM-10 BLE(Bluetooth Low Energy) module and relays as basic parts. The smart device exchanges signals with the control module via bi-directional BLE communication, which allows it to control the start/stop of the vacuum cleaner. Backpack type vacuum cleaners are effective for cleaning high places that require the use of ladders. However, it is often necessary to take off the backpack type cleaner to start/stop it. The IoT-based vacuum cleaner control system implemented in this paper fundamentally solves the problem by allowing users to control the start/stop of the vacuum cleaner without taking it off.

In this paper, we propose a method predicting the speed of each lane from the link speed using a neural network. We took three measures for configuring learning data to increase prediction accuracy. The first one is to expand the spatial range of the data source by including 14 links connected to the beginning and end points of the link. We also increased the time interval from 07:00 to 22:00 and included the data generation time in the feature data. Finally, we marked weekdays and holidays. Results of experiments showed that the speed error was reduced by 21.9% from 6.4 km/h to 5.0 km/h for straight lane, by 12.9% from 8.5 km/h to 7.4 km/h for right turns, and by 5.7% from 8.7 km/h to 8.2 km/h for left-turns. As a secondary result, we confirmed that the prediction accuracy of each lane was high for city roads when the traffic flow was congested. The feature of the proposed method is that it predicts traffic conditions for each lane improving the accuracy of prediction.

Potholes that occur on paved roads can have fatal consequences for vehicles traveling at high speeds and may even lead to fatalities. While manual detection of potholes using human labor is commonly used to prevent pothole-related accidents, it is economically and temporally inefficient due to the exposure of workers on the road and the difficulty in predicting potholes in certain categories. Therefore, completely preventing potholes is nearly impossible, and even preventing their formation is limited due to the influence of ground conditions closely related to road environments. Additionally, labeling work guided by experts is required for dataset construction. Thus, in this paper, we utilized the Mean Teacher technique, one of the semi-supervised learning-based knowledge distillation methods, to achieve robust performance in pothole image classification even with limited labeled data. We demonstrated this using performance metrics and GradCAM, showing that when using semi-supervised learning, 15 pre-trained CNN models achieved an average accuracy of 90.41%, with a minimum of 2% and a maximum of 9% performance difference compared to supervised learning.

Doodles, often possess irregular shapes and patterns, making it challenging for artificial intelligence to mechanically recognize and predict patterns in random doodles. Unlike humans who can effortlessly recognize and predict doodles even when circles are imperfect or lines are not perfectly straight, artificial intelligence requires learning from given training data to recognize and predict doodles. In this paper, we leverage a diverse dataset of doodle images from individuals of various nationalities, cultures, left-handedness, and right-handedness. After training two neural networks, we determine which network offers higher accuracy and is more suitable for doodle image prediction. The motivation behind predicting doodle images using artificial intelligence lies in providing a unique perspective on human expression and intent through the utilization of neural networks. For instance, by using the various images generated by artificial intelligence based on human-drawn doodles, we expect to foster diversity in artistic expression and expand the creative domain.

The purpose of this study is to examine the progress of negotiations between the two countries regarding the implementation of AFKN's satellite broadcasting on October 4, 1983, as well as the opposition of domestic public opinion, which emerged as an important variable in the negotiation process. Through this, it was intended to lay the foundation for the historical facts necessary to interpret the negotiation process between the two countries over the implementation of AFKN's satellite broadcasting in the context of world history of cultural globalization. As a research method, the historical literature research method was used, focusing on archive documents stored in diplomatic archives. The study revealed that public opinion's movement toward cultural imperialism under domestic political conditions, which had authoritarian control over the media, served as an accidental factor to help carry out the regime's interests of regime protection. Through these findings, this paper interpreted that AFKN-TV's satellite broadcasting, which was implemented under the U.S. Department of Defense plan without the prior consent of the Korean government, clearly shows that Korea has been "semi-forced" into the U.S.-led cultural globalization order.

Currently, e-commerce is changing from a digital twin to a metaverse world. The metaverse world is an intermediate form between virtual and real worlds and is operated as a coin-based meta-commerce. In this meta-commerce world, blockchain-based NFT coins are used when trading items (contents). In this study, we studied how to issue a large number of NFT coins (certification) rather than issuing a single type of NFT. The research method was designed to produce content layer-based and automatically create the desired quantity using a mass NFT index and automatic generation method. In this study, a layer overlap method (background, body, etc.) was used with a Phyton-based program for mass minting. As a result, it can be used as a blockchain-based certificate that can prove a group of many people. In addition, the content created with the NFT index was registered on the NFT sales site to confirm its utilization and value.

In this paper, a research trend of attack graph studies for Cyber-Physical System (CPS) environments is surveyed, and we analyse the limitations of previous works and prospect the future directions. 35 among around 150 attack graph studies conducted within 5 years target CPS, and we inspect key features of CPS environment in the security aspect. Also, we categorize and analyze target studies in the aspect of modelling physical systems and considering air gaps, which are derived as key features of the security aspects of CPS. Half of 20 research that we surveyed do not reflect those two features, and other studies only consider one of the two features. In this circumstance, we examine challenges that attack graph studies on CPS environment face. Finally, we expect state-led studies or studies targeting open-spec commercial CPS will dominate.

In this paper, we analyze the authentication protocol for DRM proposed by Hussain et al. in 2022, and present an improved solution. Hussain et al. argued that their authentication protocol guarantees man-in-the-middle attack, replay attacks, and mutual authentication. However, as a result of analyzing Hussain et al.'s authentication protocol in this paper, Hussain et al.'s authentication protocol still has an insider attack problem, a problem with Yu et al.'s authentication protocol that they pointed out. For this reason, when an inside attacker acquires information on a mobile device, a user impersonation attack was also possible. In addition, there were problems with the user's lack of ID format verification and the problem of the secret key mismatch of the digital contents between the server and the user. Therefore, this paper proposes an improved solution to solve these problems. As a result of analysis in this paper, the improved solution is safe from various attacks such as smart card attack, insider attack, and password guessing attack and can safely authenticate users of DRM.

In collaborative filtering systems, the item rating prediction values calculated by the systems are very important for customer satisfaction with the recommendation list. In the time-aware system, predictions are calculated by reflecting the rating time of users, and in general, exponentially lower weights are assigned to past rating values. In this study, to find out whether the influence of rating time on the rating value varies according to various factors, the correlation between user rating value and rating time is investigated by the degree of user rating activity, the popularity of items, and item genres. As a result, using two types of public datasets, especially in the sparse dataset, significantly different correlation index values were obtained for each factor. Therefore, it is confirmed that the influence weight of the rating time on the rating prediction value should be set differently in consideration of the above-mentioned various factors as well as the density of the dataset.

The purpose of this study is to improve pain and injury through bicycle fitting and to propose rehabilitation methods. Pain and injuries caused by bicycles can be largely divided into knee and ankle pain, wrist, shoulder, neck, and back pain, and hip pain. The cause of these pains and injuries stems from incorrect bicycle fitting and posture. In order to improve these pain and injuries and prevent recurrence, appropriate bicycle fitting and rehabilitation exercise are needed. Pain and injury are divided into kinetic pain and pain by a fixed posture. In the case of kinetic pain, rehabilitation exercise is required along with inflammatory treatment, and pain by a fixed posture should understand the exact characteristics of the body and learn and practice bicycle posture according to the body's characteristics. Through this method, it can contribute to preventing the recurrence of bicycle pain and injuries and further creating an environment where a safe bicycle culture can be established.

The purpose of this study was to the effects of the Sling Neurac stabilization exercise(SNSE) on pain, cervical lordosis angle(CLA), and cervical gravity line(CGL) in young adults with a forward head posture. The subjects of the study were selected as SNSEG(n=10) and control group(n=10), they were conducted for 70 minutes three times a week for 8 weeks. Study results showed that pain(p<.001), CGLe(p<.01) were significantly decreased and CLA(p<.001) were also significantly increased in the SNSEG. In conclusion, SNSE is effective in improving the proprioceptive sense of the LM group and activating the muscle. Co-activation with the GM group was found to be effective in improving the CLA and CGL. Therefore, reactivation of the deep neck flexors and suboccipital muscles is an important factor in pain control and postural alignment, and is suggested as an effective intervention method to improve forward head posture.

This study aims to analyze the relationship with oral health status through oral examinations, microorganism tests, and surveys of college students and present basic data necessary for the development of oral health education programs to prevent. Results of students who did not receive brushing education showed high motile activities of microorganism, and there was a significant relationship in which students with a large amount of microorganism subjectively felt more tooth pain. Symptoms of halitosis were greater in the DT, there were differences in the type of bacteria and the amount of bacteria in the MT, and oral health was worse if oral aids were not used in the DMFT index. Therefore, it was confirmed that oral health behavior, subjective oral health awareness, and the amount of microorganism had a significant relationship with oral health status. It will be necessary to develop and share and spread customized oral health education media for each life cycle.

This study attempted to find out the factors influencing the formation of nursing professionalism in nursing students. As for the research method, a structured self-report questionnaire was surveyed for 3rd year nursing students (n=169) at K University, and the collected data were analyzed using the SPSS/WIN 25.0 program. The results of the study showed that major satisfaction, nurse image, clinical practice education environment, and clinical practice belonging showed a statistically significant positive correlation with nursing professional intuition, and major satisfaction had the greatest effect on nursing professionalism. Therefore, in order to form a positive nursing professional intuition, it is required to develop and apply various and systematic educational programs to increase major satisfaction.

This study aimed to find out the difference in safety knowledge, ability for coping with emergency situations, and first aid awareness before and after introductory scuba diving training. From June 25 to August 30, 2021, data were collected from 86 people who agreed to the study and received introductory education from SSI (Scuba Schools International). Data analysis was analyzed by descriptive statistics, t-test, and χ2-test using SPSS PC/26.0. As a result of the study, safety knowledge and ability to cope with emergency situations after training showed a statistically significant increase in all items, and first aid awareness increased after training in response to the items to be performed first according to the priority of the frequency analysis result. In addition, it was analyzed that the subjects who were well aware of the scuba diving safety rules had a statistically significantly higher safety knowledge and ability to cope with emergency situations. Therefore, considering the characteristics of scuba diving group education of college students, in order to participate in safe aquatic leisure activities, systematic education and institutional arrangements for safety knowledge and emergency response skills should be prepared from the introductory stage.

This study was conducted in the context of the Covid-19 pandemic by analyzing a large amount of press report frames regarding the Covid-19 vaccine which is of great public interest, in order to explore the role and direction of trusted media as core elements of crisis communication. The study period lasted for eight months beginning in November 2020 when the development of the Covid-19 vaccine was in progress until June 2021. Set-up as research subjects were the Chosun Ilbo, Joongang Ilbo, Dong-A Ilbo and Hankyoreh according to their public confidence rankings and number of readers.The analysis method used structured topic Modeling (STM) and semantic network analysis. As a result, based on a clear cluster of word structures and a central analysis value, a total of 64 relevant frames, 16 for each news company, were gathered. In the third phase a comparative analysis of the four news companies was carried out to verify the organizational degree of the frames and substantial differences.

97.5% of our country's exports and 87.2% of imports are transported by sea, making ports an important component of the Korean economy. To efficiently operate these ports, it is necessary to improve the short-term prediction of port water volume through scientific research methods. Previous research has mainly focused on long-term prediction for large-scale infrastructure investment and has largely concentrated on container port water volume. In this study, short-term predictions for petroleum and liquefied gas cargo water volume were performed for Ulsan Port, one of the representative petroleum ports in Korea, and the prediction performance was confirmed using the deep learning model LSTM (Long Short Term Memory). The results of this study are expected to provide evidence for improving the efficiency of port operations by increasing the accuracy of demand predictions for petroleum and liquefied gas cargo water volume. Additionally, the possibility of using LSTM for predicting not only container port water volume but also petroleum and liquefied gas cargo water volume was confirmed, and it is expected to be applicable to future generalized studies through further research.

As the development of the 4th industrial revolution in the maritime industry has accelerated, the technical development and progress of maritime autonomous surface ship(MASS), and the development of international regulations have been accelerated. In particular, the IMO Maritime Safety Committee(MSC) has established a road-map for the development of the non-mandatory goal-based MASS instrument(MASS Code) and started developing a non-mandatory MASS Code at MSC 105th meeting. Many countries are actively participating in the Correspondence Group on the development of MASS Code, and the development of detailed requirements for MASS functions in the MASS Code is underway. Especially, the concept of “Mode of Operation” for MASS functions was mentioned in the Correspondence Group for the first time, and it is expected that discussions on these modes will be conducted from the IMO MASS JWG meeting to held in April 2023. The concept of “Mode of Operation” will be useful in explaining MASS and MASS functions and will be discussed continually for the development of MASS Code. This paper reviews the contents of the IMCA M 220 document, which provides guidelines on operating modes, to conduct research on the benchmark for setting the operating modes of MASS.

This study aims to provide useful information for prevention of doping by investigating and verifying relationships among demographic factors such as athletic career and experience of anti-doping education, controlled motivation, attitude toward anti-doping, perceived behavioral control factors and doping intentions to verify factors affecting doping intentions of domestic elite athletes based on the advance studies that have been carried out various theoretical approaches so far. Method: This study analyzed using SPSS 27.0 program. First, this study confirmed a multicollinearity problem by conducting Pearson’s correlation analysis to examine correlation between variables. And this study conducted stepwise multiple linear regression to confirm how the variables affect doping intentions. Result: Study results show that all factors such as athletic career, experience of anti-doping education, controlled motivation, attitude toward anti-doping and perceived behavioral control have a significant impact on doping intentions, and this study verified significant impact by putting variables in order of each influence. As a result of verification, this study confirmed that controlled motivation has the greatest influence, and perceived behavioral control toward doping, experience of anti-doping education, attitude toward and athletic career came next in order.

In this paper, we studied the impact of outliers on the power of the significance tests for Cronbach alpha reliability coefficient. Four variables were varied: sample size, the number of items, the number of outliers and population Cronbach Alpha levels. We simulated data using multivariate normal distribution and used outliers sampled from uniform distribution. To test the significance of Cronbach Alpha Reliability, parametric approach(F statistic) and permutation method were used. Consequently, we observed that the powers of permutation test are equal to or greater than those of F test under all conditions, and also both F test and permutation test lose the power as the number of outliers increases, and that these effects of outliers on the power are enhanced for increasing population alpha levels.

This study aims to show that "Computer-assisted language learning (CALL)" and "Mobile-based language learning (MALL)" actually influence education, deviating from the traditional "drill and practice" method in foreign language education and learning due to the development of information and communication technology (IT). Specifically, for first-year college students who have relatively poor English skills and do not feel enough motivation for English learning, I will produce educational video content using multimedia authoring tools and upload it to the e-learning system. Video content is configured to be accessed and utilized through various media such as computers, smartphones, tablets, laptops, etc. Ultimately, an exploration of educational value behind the utilization of IT devices in English language Teaching(ELT) and the Second Language Acquisition (SLA) theory behind effective instructional use of such technology are presented. That is to say, the effectiveness of language learning using information and communication technology (IT) is introduced. The article closes by suggesting how to use computers and mobile media for 'Flipped Learning'.