Earticle

Recently, research is being conducted on the rapid service provision and reliability of the instance-based rather than the existing IP-based structure. Research is mainly conducted through Block cloud, a platform that combines service-centric networking (SCN) and blockchain. In addition, the Internet of Things network has been proposed as a fog computing environment in the structure of the existing cloud computing. Fog computing is an environment suitable for real-time information processing. In this paper, we propose a new Internet network structure based on fog computing that requires real-time for rapid processing of IoT services. The proposed system applies IoTA, the third-generation blockchain based on DAG, to the block cloud. In addition, we want to propose a basic model of the object block chain and check the application services of electric vehicles.

Because of the importance of the information, encryption algorithms are heavily used. Raw data is encrypted and secure, but problems arise when the key for decryption is exposed. In particular, large-scale Internet sites such as Facebook and Amazon suffer serious damage when user data is exposed. Recently, research into a new fourth-generation encryption technology that can protect user-related data without the use of a key required for encryption is attracting attention. Also, data clustering technology using encryption is attracting attention. In this paper, we try to reduce key exposure by using homomorphic encryption. In addition, we want to maintain privacy through similarity measurement. Additionally, holistic similarity measurements are time-consuming and expensive as the data size and scope increases. Therefore, Min-Hash has been studied to efficiently estimate the similarity between two signatures Methods of measuring similarity that have been studied in the past are time-consuming and expensive as the size and area of data increases. However, Min-Hash allowed us to efficiently infer the similarity between the two sets. Min-Hash is widely used for anti-plagiarism, graph and image analysis, and genetic analysis. Therefore, this paper reports privacy using homomorphic encryption and presents a model for efficient similarity measurement using Min-Hash.

As the number of data and devices explodes, centralized data processing and AI analysis have limitations due to the load on the network and cloud. On-device AI technology can provide intelligent services without overloading the network and cloud because the device itself performs AI models. Accordingly, the need for ondevice AI technology is emerging. Many smartphones are equipped with On-Device AI technology to support the use of related functions. In this paper, we compare software tools that implement On-Device AI.

Artificial intelligence is used in fusion with image processing techniques using cameras. Image processing technology is a technology that processes objects in an image received from a camera in real time, and is used in various fields such as security monitoring and medical image analysis. If such image processing reduces the accuracy of recognition, providing incorrect information to medical image analysis, security monitoring, etc. may cause serious problems. Therefore, this paper uses a mixture of YOLOv4-tiny model and image processing algorithm and uses the COCO dataset for learning. The image processing algorithm performs five image processing methods such as normalization, Gaussian distribution, Otsu algorithm, equalization, and gradient operation. For RGB images, three image processing methods are performed: equalization, Gaussian blur, and gamma correction proceed. Among the nine algorithms applied in this paper, the Equalization and Gaussian Blur model showed the highest object detection accuracy of 96%, and the gamma correction (RGB environment) model showed the highest object detection rate of 89% outdoors (daytime). The image binarization model showed the highest object detection rate at 89% outdoors (night).

The purpose of this study is to investigate the effect of social support of table tennis players on exercise stress and athletic performance. To clarify the purpose of this study, middle and high school table tennis players registered with the Korea Table Tennis Association in 2020 were targeted. After that, a total of 300 subjects (150 males and 150 females) were selected using the convenient sampling method. The survey tool consisted of a questionnaire on a 5-point scale. Also, the collected data were statistically processed using SPSS version 20.0. The results obtained through this research procedure are as follows. First, it was found that the social support of athletes partially affected the exercise stress. Second, it was found that the social support of athletes partially affected athletic performance. Third, exercise stress of athletes was found to have a partial effect on athletic performance.

It has been common since ancient times to use fashion accessories to make a positive impression on others and develop personal brands. For this manuscript, I've designed a range of personalized electronic sounds and perfume accessories that use personalized scents and sounds to create memorable experiences. These have built-in auditory and olfactory actuators that can generate unique sound and fragrance signatures from the wearer and the other party. Based on the design explorations, I also discussed the issues of design and implementation of personalized electronic sound and fragrance accessories, as well as issues and additional business opportunities for the use of these personalized electronic sound and odor accessories in everyday life.

Recenlty, the category of luxury wearbles has expanded and the relevant reseach has been scarce. The study tests whether the emotional mechanism regarding luxury wearables within e-tail affects luxury brand perceptions. Furthermore, it tests the moderation effect of gender in the mechanism. A total of 393 responses from U.S. populations were collected through an international research company with using online survey methods. In the results, the positive and direct effect of dominance on positive emotion was significant, and the positive emotion significantly increases perceived brand luxury. However, no direct effect of dominance was found on perceived brand luxury. The moderation effect of gender in the relationship between positive emotion and perceived brand luxury was found positive and significant, but the hypothesized moderation effect of gender was insignificant in the relationship between dominance and perceived brand luxury. Implications and study limitations are discussed.

In precision agriculture (PA), the differences of the agriculture related parameters such as temperature, humidity, soil moisture among different fields are considered and analyzed to precisely utilize water, pesticides, fertilizer, seeds, etc. in fields. Hence, it becomes possible to increase the profit, reduce waste and maintain quality products. This paper suggests a framework for RFID sensor network in view of PA, especially, associated with Container-grown seedlings(CGS), and presents the analysis and simulation by using Ultra High Frequency (UHF) RFID tag system. The simulation is divided into the transmitter and receiver part using Matlab/Simulink. The architecture of the model is flexible to achieve different modulation and encoding types. Finally, some results of the simulation are presents.

Currently, Korea is building traffic infrastructure using Intelligent Transport Systems (ITS), but the pedestrian traffic accident rate is very high. The purpose of this paper is to prevent the risk of traffic accidents by jaywalking pedestrians. The development of this study aims to detect pedestrians who trespass using the public data set provided by the Artificial Intelligence Hub (AIHub). The data set uses training data: 673,150 pieces and validation data: 131,385 pieces, and the types include snow, rain, fog, etc., and there is a total of 7 types including passenger cars, small buses, large buses, trucks, large trailers, motorcycles, and pedestrians. has a class format of Learning is carried out using YOLOv5 as an implementation model, and as an object detection and edge detection method of an input image, a canny edge model is applied to classify and visualize human objects within the detected road boundary range. In this study, it was designed and implemented to detect pedestrians using the deep learning-based YOLOv5 model. As the final result, the mAP 0.5 showed a real-time detection rate of 61% and 114.9 fps at 338 epochs using the YOLOv5 model.

Although telecommuting of SMEs has been activated due to the COVID-19 phenomenon, the security model for this is insufficient. Accordingly, the study was divided into threats centered on smartphones and threats centered on smartphone users. As a result of the study, one-third of SMEs are working from home. At this company with 100 employees, more than 50% of them work from home.and In the metal, machinery and chemical industries with factories, 20% of them work from home. As a result of analyzing the correlation between telecommuting according to the presence or absence of a factory, the correlation coefficient (r=-.385) has a clear linear relationship. And, as a result of the regression analysis, the R-squared value was 0.148, so companies with factories are highly related to telecommuting. In other words, we found that SMEs with factories do not want to work from home. In addition, as a result of analyzing the level of security threats, there were great concerns about theft, hacking, and phone taking during remote work. As limitations of the study, there were difficulties in selecting SMEs from the population in a non-face-to-face work environment, and there were limitations in the questionnaire items for deriving a non-face-to-face work environment.