• International journal of advanced smart convergence
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• v.11 no.4
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• pp.206-215
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• 2022

For a long time, traditional culture has been regarded as one of the sources of the inspiration, method and language of Chinese writing. In this article, we studied the medium- and long-term impact of a traditional Chinese culture seminar attended by college students on the output of creative writing. The seminar included traditional Chinese philosophy, history, literature, art, etc. It spanned three years (22 months) and held lectures lasting for approximately two hours once a week. The subjects of the prospective cohort study included 130 first-year college students who participated in the seminar and 130 controls. From September 2016 to June 2018, 72 lectures were held. We measured the creative writing output from the first lecture (September 2016) to December 2021 (64 months in total), including novels, essays, poems, and plays. Two indicators, the total number of words (TNW) and the quality of yield (QY), were evaluated by a 15-member panel. Although the TNW and QY of the participants and their controls were similar before the seminar, we found that the participants have higher TNW and QY than the controls after participating in the seminar. The difference in TNW became significant after month 51 (p<0.05), and the difference in QY became significant after month 46 (p<0.05). After these dates, the differences stabilized. In addition, text analysis indicates that by month 64, traditional cultural elements in the works of the participating group had a higher frequency (p<0.001). The research shows that the traditional culture seminar not only enhanced the yield of college students' creative writing but also improved the quality of their work. The traditional cultural elements enriched the works of the seminar participants.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1660-1665
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• 2022

Recently, many industries are using three dimensional scanning technology. As the performance of the 3D scanner gradually improves, a sampling step to reduce a point data or a remove step to remove a part determined to be noise are generally performed in post processing. However, total point data by long time scanning cannot be processed at once in spite of performing such those additional processes. In general, a method using a multi threaded environment is widely used, but as the scanning process work time increases, the processing performance gradually decreases due to various environmental conditions and accumulated operations. This paper proposes a method to initially remove point data judged to be unnecessary by calculating accumulated fast point feature histogram values from coming point data of the 3D scanner in real time. The entire 3D scanning process can be reduced using this approach.

• Convergence Security Journal
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• v.22 no.2
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• pp.27-42
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• 2022

In the era of the Fourth Industrial Revolution, digital transformation to increase the effectiveness of industry is becoming more important to achieving the goal of industrial innovation. The digital new deal and smart defense are required for digital transformation and utilize artificial intelligence, big data analysis technology, and the Internet of Things. These changes can innovate the industrial fields of national defense, society, and health with new intelligent services by continuously expanding cyberspace. As a result, work productivity, efficiency, convenience, and industrial safety will be strengthened. However, the threat of cyber-attack will also continue to increase due to expansion of the new domain of digital transformation. This paper presents the risk scenarios of cyber-attack threats in the Fourth Industrial Revolution. Further, we propose a preemptive intrusion response model to bolster the complex security environment of the future, which is one of the fundamental alternatives to solving problems relating to cyber-attack. The proposed model can be used as prior research on cyber security strategy and technology development for preemptive response to cyber threats in the future society.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.155-164
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• 2023

Machine learning with its high precision algorithms, Precision agriculture (PA) is a new emerging concept nowadays. Many researchers have worked on the quality and quantity of PA by using sensors, networking, machine learning (ML) techniques, and big data. However, there has been no attempt to work on trends of artificial intelligence (AI) techniques, dataset and crop type on precision agriculture using internet of things (IoT). This research aims to systematically analyze the domains of AI techniques and datasets that have been used in IoT based prediction in the area of PA. A systematic literature review is performed on AI based techniques and datasets for crop management, weather, irrigation, plant, soil and pest prediction. We took the papers on precision agriculture published in the last six years (2013-2019). We considered 42 primary studies related to the research objectives. After critical analysis of the studies, we found that crop management; soil and temperature areas of PA have been commonly used with the help of IoT devices and AI techniques. Moreover, different artificial intelligence techniques like ANN, CNN, SVM, Decision Tree, RF, etc. have been utilized in different fields of Precision agriculture. Image processing with supervised and unsupervised learning practice for prediction and monitoring the PA are also used. In addition, most of the studies are forfaiting sensory dataset to measure different properties of soil, weather, irrigation and crop. To this end, at the end, we provide future directions for researchers and guidelines for practitioners based on the findings of this review.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.291-295
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• 2022

This paper deal with the advanced thchnology of water supply line breakege detection system in singsan green city. the technology apply for construction eco oriented high-tech city to merge residant, industial, tour reasure parts for songsan green city furture direction achivement and response for a life style change of people in the city. Breakege detection system consist of smart prevention seat, pipeline breakege detection sensor, analysis software, server. etc.. Central control unit sent the data to hwa sung city water supply office by WCDMA in SKY. the data are states about water supply pipeline, Location.etc. This system maintain the long term life cycle of water supply plpeline by the prevention the leakege event through ackonwledge information of evnet occurrence locaion. and used to realtime sense method about demage information of the pipeline and prevent to brekege facilities during excavation work.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.385-386
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• 2022

Currently, global developed countries in shipping and logistics establish smart ports by introducing various digital technologies such as automated terminals and sharing platforms. This means that the importance of efficiency throughout the port by improving resource utilization efficiency and minimizing work idle time is increasing. Therefore, this study proposes a yard truck dispatching method of improving resource utilization efficiency. And we analyze the problems of the existing dispatching rules and develop Y/T dispatching algorithm that comprehensively considers related constraints. In addition, the simulation takes into account the terminal congestion based on the operation data of the Busan New Port, it is conducted using the existing dispatch method and developed Y/T dispatching algorithm. And the operational effects of analysis result are evaluated.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.388-389
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• 2022

Recently, AI (Artificial Intelligence) has been applied to various technologies such as automatic driving, robot and smart communication. Currently, AI system is developed by software-based method using tensor flow, and GPU (Graphic Processing Unit) is employed for processing unit. However, if software-based method employing GPU is used for AI applications, there is a problem that we can not change the internal circuit of processing unit. In this method, if high-level jobs are required for AI system, we need high-performance GPU, therefore, we have to change GPU or graphic card to perform the jobs. In this work, we developed a CNN-based FPGA (Field Programmable Gate Array) chip to solve this problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3182-3203
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• 2023

With the growing adoption of cloud-based technologies, maintaining the privacy and security of cloud data has become a pressing issue. Privacy-preserving encryption schemes are a promising approach for achieving cloud data security, but they require careful design and implementation to be effective. The integrated approach to cloud data security that we suggest in this work uses CogniGate: the orchestrated permissions protocol, index trees, blockchain key management, and unique Opacus encryption. Opacus encryption is a novel homomorphic encryption scheme that enables computation on encrypted data, making it a powerful tool for cloud data security. CogniGate Protocol enables more flexibility and control over access to cloud data by allowing for fine-grained limitations on access depending on user parameters. Index trees provide an efficient data structure for storing and retrieving encrypted data, while blockchain key management ensures the secure and decentralized storage of encryption keys. Performance evaluation focuses on key aspects, including computation cost for the data owner, computation cost for data sharers, the average time cost of index construction, query consumption for data providers, and time cost in key generation. The results highlight that the integrated approach safeguards cloud data while preserving privacy, maintaining usability, and demonstrating high performance. In addition, we explore the role of differential privacy in our integrated approach, showing how it can be used to further enhance privacy protection without compromising performance. We also discuss the key management challenges associated with our approach and propose a novel blockchain-based key management system that leverages smart contracts and consensus mechanisms to ensure the secure and decentralized storage of encryption keys.

• Journal of KIBIM
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• v.13 no.4
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• pp.96-105
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• 2023

This study focuses on developing a building object recognition technology for efficient use in the remodeling of buildings constructed without drawings. In the era of the 4th industrial revolution, smart technologies are being developed. This research contributes to the architectural field by introducing a deep learning-based method for automatic object classification and recognition, utilizing point cloud data. We use a TD3D network with voxels, optimizing its performance through adjustments in voxel size and number of blocks. This technology enables the classification of building objects such as walls, floors, and roofs from 3D scanning data, labeling them in polygonal forms to minimize boundary ambiguities. However, challenges in object boundary classifications were observed. The model facilitates the automatic classification of non-building objects, thereby reducing manual effort in data matching processes. It also distinguishes between elements to be demolished or retained during remodeling. The study minimized data set loss space by labeling using the extremities of the x, y, and z coordinates. The research aims to enhance the efficiency of building object classification and improve the quality of architectural plans by reducing manpower and time during remodeling. The study aligns with its goal of developing an efficient classification technology. Future work can extend to creating classified objects using parametric tools with polygon-labeled datasets, offering meaningful numerical analysis for remodeling processes. Continued research in this direction is anticipated to significantly advance the efficiency of building remodeling techniques.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.53-58
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• 2024

This paper presents a novel miniaturized 3-D cubic antenna for use in wireless sensor network (WSN) application. The geometry of this antenna is designed as a cube including a meander dipole antenna. A truly omnidirectional pattern is produced by this antenna in both E-plane and H-plane, which allows for non-intermittent communication that is orientation independent. The operating frequency lies in the ISM band (centered in 2.45 GHz). The dimensions of this ultra-compact cubic antenna are 1.25*1.12*1cm3 which features a length dimension λ/11. The coefficient which presents the overall antenna structure is Ka=0.44. The cubic shape of the antenna is allowing for smart packaging, as sensor equipment may be easily integrated into the cube hallow interior. The major constraint of WSN is the energy consumption. The power consumption of radio communication unit is relatively high. So it is necessary to design an antenna which improves the energy efficiency. The parameters considered in this work are the resonant frequency, return loss, efficiency, bandwidth, radiation pattern, gain and the electromagnetic field of the proposed antenna. The specificity of this geometry is that its size is relatively small with an excellent gain and efficiency compared to previously structures (reported in the literature). All results of the simulations were performed by CST Microwave Studio simulation software and validated with HFSS. We used Advanced Design System (ADS) to validate the equivalent scheme of our conception. Input here the part of summary.