• Journal of Industrial Convergence
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• v.20 no.9
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• pp.47-58
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• 2022

Digital content is difficult to distinguish between the original and the replica due to its nature. For this reason, NFT technology using blockchain technology is attracting attention because it can guarantee the proof and scarcity of the original digital content. However, the NFT buyer does not own the copyright to the digital content, but the ownership. In particular, since the minting process of issuing NFTs is possible for anyone, there is a copyright threat to the copyright holder. In this study, we propose a verification protocol based on DID for the process of issuing and transacting NFTs for copyright protection of copyright holders' digital contents. As a research method, the problems of research cases related to digital contents were analyzed and the safety was comparatively analyzed. NFT issuance can only be issued by copyright holders whose identity has been verified through DID, and only users who have completed authentication can participate in the transaction to prevent indiscriminate theft and use of digital content and form a safe and transparent transaction market.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.861-866
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• 2022

Seoul introduced the shared bicycle system, "Seoul Public Bike" in 2015 to help reduce traffic volume and air pollution. Hence, to solve various problems according to the supply and demand of the shared bicycle system, "Seoul Public Bike," several studies are being conducted. Most of the research is a strategic "Bicycle Rearrangement" in regard to the imbalance between supply and demand. Moreover, most of these studies predict demand by grouping features such as weather or season. In previous studies, demand was predicted by time-series-analysis. However, recently, studies that predict demand using deep learning or machine learning are emerging. In this paper, we can show that demand prediction can be made a little better by discovering new features or ordering the importance of various features based on well-known feature-patterns. In this study, by ordering the selection of new features or the importance of the features, a better coefficient of determination can be obtained even if the well-known deep learning or machine learning or time-series-analysis is exploited as it is. Therefore, we could be a better one for demand prediction.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.647-653
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• 2022

Data mining is a technique that explores knowledge such as relationships and patterns between data by exploring and analyzing data. Data that occurs in the real world includes a temporal attribute. Temporal data mining research to find useful knowledge from data with temporal properties can be effectively utilized for predictive judgment that can predict the future. In this paper, we propose an algorithm using time-unit grouping to classify the database into regular time period units and discover frequent pattern itemsets in time units. The proposed algorithm organizes the transaction and items included in the time unit into a matrix, and discovers frequent items in the time unit through grouping. In the experimental results for the performance evaluation, it was found that the execution time was 1.2 times that of the existing algorithm, but more than twice the frequent pattern itemsets were discovered.

• Journal of Practical Engineering Education
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• v.14 no.1
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• pp.75-83
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• 2022

Most of the courses that teach the Python programming language are liberal arts courses that all students in general universities must complete. Through this, non-major students who have learned the basic programming process based on computational thinking are strengthening their convergence capabilities to apply SW in various major fields. In the previous research results, various evaluation methods for understanding the concept of computational thinking and writing code were suggested. However, there are no examples of evaluation problems, so it is difficult to apply them in actual course operation. Accordingly, in this paper, a Python basic programming curriculum that can be applied as a liberal arts subject for non-majors is proposed according to the ADDIE model. In addition, the case of evaluation problems for each Python element according to the proposed detailed curriculum was divided into 1st and 2nd phases and suggested. Finally, the validity of the proposed evaluation problem was analyzed based on the evaluation scores of non-major students calculated in the course to which this evaluation problem case was applied. It was confirmed that the proposed evaluation problem case was applied as a real-time online non-face-to-face evaluation method to effectively evaluate the programming competency of non-major students.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.863-867
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• 2021

In this paper, in order to hide the watermark in the LSB of the color image, a color image watermarking technique with high security is proposed by using the adjacent pixels of the image and the spatial encryption technique. According to the technique proposed in this paper, the quality of the stego-image generated by hiding the watermark in the LSB of the color image is so excellent that the difference from the original image cannot be recognized, and the original watermark can be extracted from the stego-image without loss. If the watermark is hidden in the image using the proposed technique, the security of the watermark is maintained very high because the watermark hidden in the stego-image is multi-encrypted. The proposed watermarking technique can be used in applications such as military and intellectual property protection that require high security.

• Journal of Internet of Things and Convergence
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• v.8 no.1
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• pp.79-85
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• 2022

Internet of Things (IoT) connects devices with various platforms, computing power, and functions. Due to the diversity of networks and the ubiquity of IoT devices, demands for security and privacy are increasing. Therefore, cryptographic mechanisms must be strong enough to meet these increased requirements, while at the same time effective enough to be implemented in devices with long-range specifications. In this paper, we present the performance and memory limitations of modern cryptographic primitives and schemes for different types of devices that can be used in IoT. In addition, detailed performance evaluation of the performance of the most commonly used encryption algorithms in low-spec devices frequently used in IoT networks is performed. To provide data protection, the binary ring uses encryption asymmetric fully homomorphic encryption and symmetric encryption AES 128-bit. As a result of the experiment, it can be seen that the IoT device had sufficient performance to implement a symmetric encryption, but the performance deteriorated in the asymmetric encryption implementation.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.59-65
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• 2022

The baby boomers born between 1955 and 1974, recently called the new age, form a huge population group and show characteristics different from the previous traditional older generations. With the retirement of those who make up 33% of the nation's population in earnest, the emergence of a new generation of the elderly population and policy changes are required. The new middle age generation, also called the opal generation, want to spend their old age productively and autonomously, which has increased due to the increase in life expectancy, and have some economic ability, such as enjoying overseas travel in old age. As preparation for old age is insufficient, policy attention is required for the younger generation as a new generation. In this paper, focusing on the baby boom generation, the definition of the opal generation, their consumption lifestyle, attitudes, social activities, leisure activities, and lifestyle such as health efforts are investigated, and job creation, social re-education, and local It is intended to present practical measures for preparing for old age, such as the establishment of medical facilities and social consideration for a leisurely cultural life.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.487-492
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• 2022

Universities are looking for various methods to enhance educational competence level suitable for the rapidly changing social environment. This study suggests a method to promote academic and educational achievements by reducing drop-out rate from their majors through implementation of pre-survey of satisfaction that revised and complemented survey items. To supplement the CQI method implemented after a general satisfaction survey, a pre-survey of satisfaction was carried out. To consolidate students' competences, this study made prediction and analysis of data with more importance possible using the Random Forest of the machine learning technique that can be applied to AI Medici platform, whose design is underway. By pre-processing the pre-survey of satisfaction, the students information enrolled in classes were defined as an explanatory variable, and they were classified, and a model was created and learning was conducted. For the experimental environment, the algorithms and sklearn library related in Jupyter notebook 3.7.7, Python 3.7 were used together. This study carried out a comparative analysis of change in educational satisfaction survey, carried out after classes, and trends in the drop-out students by reflecting the results of the suggested method in the classes.

• Journal of Aerospace System Engineering
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• v.16 no.4
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• pp.109-115
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• 2022

The CNN (Convolution Neural Network) algorithm which combines a deep learning technique, and a computer vision technology, makes image classification feasible with the high-performance computing system. In this thesis, the CNN algorithm is applied to the classification problem, by using a typical deep learning framework of TensorFlow and machine learning techniques. The data set required for supervised learning is generated with the same type of bolts. some of which have undamaged threads, but others have damaged threads. The learning model with less quantity data showed good classification performance on detecting damage in a bolt image. Additionally, the model performance is reviewed by altering the quantity of convolution layers, or applying selectively the over and under fitting alleviation algorithm.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.8
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• pp.241-248
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• 2022

In this paper, the PID controller and Kalman filter are applied to improve the automobile cruise control in the environment with disturbance and noise, and the performance is verified through diverse simulation. First, a mathematical model for a automobile cruise control system is introduced. Second, the performance degradation due to disturbance in the basic open-loop control based cruise control system is shown and then PID controller-based feedback control system to resolve this problem is verified. Third, to improve the performance degradation due to sensor noise that may occur during the feedback process, a Kalman filter is applied and verified. Ultimately, it is verified that the designed cruise control system with PID controller and Kalman filter not only satisfies all performance conditions but also has the ability for disturbance rejection and noise reduction.