• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1301-1308
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• 2018

90/150 CA which are used as key generators of the cipher system have more randomness than LFSRs, but synthesis methods of 90/150 CA are difficult. Therefore, 90/150 CA synthesis methods have been studied by many researchers. In order to synthesize a suitable CA, the analysis of the characteristic polynomial of 90/150 CA should be preceded. In general, the characteristic of polynomial ${\Delta}_n$ of n cell 90/150 CA is obtained by using ${\Delta}_{n-1}$ and ${\Delta}_{n-2}$. Choi et al. analyzed $H_{2^n}(x)$ and $H_{2^n-1}(x)$, where $H_k(x)$ is the characteristic polynomial of k cell 90/150 CA with state transition rule <$10{\cdots}0$>. In this paper, we propose an efficient method to obtain $H_n(x)$ from $H_{n-1}(x)$ and an efficient algorithm to obtain $H_{2^n+i}(x)$ and $H_{2^n-i}(x)$ ($1{\leq}i{\leq}2^{n-1}$) from $H_{2^n}(x)$ by using this method.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1203-1213
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• 2018

In Arctic and Antarctic ocean, remote sensing is the most effective observation for environmental changes due to the inaccessibility of the regions. Even though satellite, UAV (Unmanned Aerial Vehical) are well known remote sensing platforms, and research vessel also used for automatic measurement on the regions, varied environment of Polar regions require time series and wide coverage of data. Especially, in high latitude, apply an optical satellite remote sensing is not easy due to low sun altitude. In this paper, we introduce an operation of hyper-spectrometer (HyperSAS/Satlantic inc.) which is mounted on Ice Breaker Research Vessel ARAON of Korea Polar Research Institute since 2010, to acquire an above water reflectance atomatically through every research cruise on Arctic and Antarctic ocean and transit both regions. In addition to, auxiliary data for the remotely acquired data, in situ water sampling were also obtained. The above water reflectance and in situ water sampling data are continuously acquired since 2010 will contribute to improve an Ocean Color algorithm in the high latitude and help to understand ocean reflectances over from high latitude through low latitude. Preliminary result from above water reflectance showed characteristics of Arctic ocean and Antarctic Ocean and used to develop algorithms for estimating various ocean factors such as chlorophyll and suspended sediment.

• Journal of IKEEE
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• v.23 no.2
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• pp.743-746
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• 2019

In this paper we proposed a new ocean radiation automatic monitoring system. The proposed system has the following characteristics: First, using NaI + PVT mixed detectors, the response speed is fast and precision analysis is possible. Second, the application of temperature compensation algorithm to scintillator-type sensors does not require additional cooling devices and enables stable operation in the changing ocean environment. Third, since cooling system is not needed, electricity consumption is low, and electricity can be supplied reliably by utilizing solar energy, which can be installed at the observation deck of ocean environment. Fourth, using GPS and wireless communications, accurate location information and real-time data transmission function for measurement areas enables immediate warning response in the event of nuclear accidents such as those involving neighboring countries. The results tested by the authorized testing agency to assess the performance of the proposed system were measured in the range of $5{\mu}Sv/h$ to 15mSv/h, which is the highest level in the world, and the accuracy was determined to be ${\pm}8.1%$, making normal operation below the international standard ${\pm}15%$. The internal environmental grade (waterproof) was achieved, and the rate of variation was measured within 5% at operating temperature of $-20^{\circ}C$ to $50^{\circ}C$ and stability was verified. Since the measured value change rate was measured within 10% after the vibration test, it was confirmed that there will be no change in the measured value due to vibration in the ocean environment caused by waves.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.75-80
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• 2018

The smart city is developing an energy system efficiently through a common management of the city resource for the growth and a low carbon social. However, the smart city doesn't counter a verification effectively about a anomaly pattern detection when existing security technology (authentication, integrity, confidentiality) is used by fixed security key and key deodorization according to generated big data. This paper is proposed the "security nonce generation based on security nonce generation" for anomaly pattern detection of the adversary and a safety of the key is high through the key generation of the KDC (Key Distribution Center; KDC) for improvement. The proposed scheme distributes the generated security nonce and authentication keys to each facilities system by the KDC. This proposed scheme can be enhanced to the security by doing the external pattern detection and changed new security key through distributed security nonce with keys. Therefore, this paper can do improving the security and a responsibility of the smart city platform management data through the anomaly pattern detection and the safety of the keys.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.1-12
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• 2021

With the recent 4th Industrial Revolution, the growth and value of big data are continuously increasing, and the government is also actively making efforts to open and utilize public data. However, the situation still does not reach the level of demand for public data use by citizens, At this point, it is necessary to identify research trends in the public data field and seek directions for development. In this study, in order to understand the research trends related to public data, the analysis was performed using topic modeling, which is mainly used in text mining techniques. To this end, we collected papers containing keywords of 'Public data' among domestic and foreign research papers (1,437 domestically, 9,607 overseas) and performed topic modeling based on the LDA algorithm, and compared domestic and foreign public data research trends. After analysis, policy implications were presented. Looking at the time series by topic, research in the fields of 'personal information protection', 'public data management', and 'urban environment' has increased in Korea. Overseas, it was confirmed that research in the fields of 'urban policy', 'cell biology', 'deep learning', and 'cloud·security' is active.

• The Journal of Society for e-Business Studies
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• v.26 no.2
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• pp.19-43
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• 2021

The prediction of box office performance in performing arts institutions is an important issue in the performing arts industry and institutions. For this, traditional prediction methodology and data mining methodology using standardized data such as cast members, performance venues, and ticket prices have been proposed. However, although it is evident that audiences tend to seek out their intentions by the performance guide poster, few attempts were made to predict box office performance by analyzing poster images. Hence, the purpose of this study is to propose a deep learning application method that can predict box office success through performance-related poster images. Prediction was performed using deep learning algorithms such as Pure CNN, VGG-16, Inception-v3, and ResNet50 using poster images published on the KOPIS as learning data set. In addition, an ensemble with traditional regression analysis methodology was also attempted. As a result, it showed high discrimination performance exceeding 85% of box office prediction accuracy. This study is the first attempt to predict box office success using image data in the performing arts field, and the method proposed in this study can be applied to the areas of poster-based advertisements such as institutional promotions and corporate product advertisements.

• The Journal of Bigdata
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• v.5 no.2
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• pp.53-67
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• 2020

This study employees a supervised learning prediction model to detect nonconformity in advance of processed food manufacturing and processing businesses. The study was conducted according to the standard procedure of machine learning, such as definition of objective function, data preprocessing and feature engineering and model selection and evaluation. The dependent variable was set as the number of supervised inspection detections over the past five years from 2014 to 2018, and the objective function was to maximize the probability of detecting the nonconforming companies. The data was preprocessed by reflecting not only basic attributes such as revenues, operating duration, number of employees, but also the inspections track records and extraneous climate data. After applying the feature variable extraction method, the machine learning algorithm was applied to the data by deriving the company's risk, item risk, environmental risk, and past violation history as feature variables that affect the determination of nonconformity. The f1-score of the decision tree, one of ensemble models, was much higher than those of other models. Based on the results of this study, it is expected that the official food control for food safety management will be enhanced and geared into the data-evidence based management as well as scientific administrative system.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.92-98
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• 2021

Modern society needs constantly the rationality and the efficiency, and this flow of the time has become the paradigm of the whole society. This paradigm has a large influence on the architectural design and industry. Modern technology represented by the development of digital instrument and Information Technology through internet has created and developed two big trend, Parametric Design and BIM(Building information Modeling) in the architectural design and industry. These technologies, though created for different reasons, have a lot of influence on the architectural design and industry for a common purpose such as efficiency and rationality across the boundaries. In this context, this research will be embodied through the example about how parametric design should be made in the beginning of pre-design phase for BIM application. This research aims to consider the design process of Walt Diseny Consert Hall, the work of Frank O. Ghery, a deconstructivism architect, and to embody the shape of National Nederlanden Building in Prague, the Czech Republic, using parametric design tool in pre-design phase. This research later aims to be used as the basic data that can be applied to the entire architectural industry from a planning and a detailed design to a construction for the ultimate BIM application beyond the range of parametric design in pre-design phase. Later, the plan using the parametric design algorithm and BIM application in construction document phase will be conducted.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.200-210
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• 2020

The maintenance of educational facilities was assembled in 12 project classifications of the Educational Improvement Program. The priorities were decided by the evaluation scores derived from the condition investigation, and maintenance works were budgeted in the order of priorities. These priorities were a schedule for conducting maintenance and an important criterion for obtaining a construction order. Several restrictions in the condition investigation exist, which derives budgets and conducts maintenance separately based on the priorities. An educational facility manager has a restriction in quantity take-off, which results in an incorrect budget. Discomfort would occur in an educational environment, and a period of infringing safety would increase. This study proposes applying a BIM in the condition investigation and the planning framework for work-type packaging. A BIM supports a budget calculation and derives evaluation scores by linking a repair and an inspection result. The work-type packaging algorithm divides a budget allocation range and derives the result of a grouped work-types applied in an equivalent space and element. As a result of applying cases, it could shorten the duration by approximately 37.4%. Its usability in selecting a grouped work-type was evaluated through an assessment with workers.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.3
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• pp.101-109
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• 2021

Wave observations using a marine X-band radar are conducted by analyzing the backscattered radar signal from sea surfaces. Wave parameters are extracted using Modulation Transfer Function obtained from 3D wave number and frequency spectra which are calculated by 3D FFT of time series of sea surface images (42 images per minute). The accuracy of estimation of the significant wave height is, therefore, critically dependent on the quality of radar images. Wave observations during Typhoon Maysak and Haishen in the summer of 2020 show large errors in the estimation of the significant wave heights. It is because of the deteriorated radar images due to raindrops falling on the sea surface. This paper presents the algorithm developed to increase the accuracy of wave heights estimation from radar images by adopting convolution neural network(CNN) which automatically classify radar images into rain and non-rain cases. Then, an algorithm for deriving the Hs is proposed by creating different ANN models and selectively applying them according to the rain or non-rain cases. The developed algorithm applied to heavy rain cases during typhoons and showed critically improved results.