• Journal of Platform Technology
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• v.11 no.3
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• pp.45-55
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• 2023

This paper presents a model that supports decision-makers in the Korean film industry to maximize the success of online movies. To achieve this, we collected historical box office movies and clustered them into types to propose a model predicting each type's online box office performance. We considered various features to identify factors contributing to movie success and reduced feature dimensionality for computational efficiency. We systematically classified the movies into types and predicted each type's online box office performance while analyzing the contributing factors. We used automated machine learning (AutoML) techniques to automatically propose and select machine learning algorithms optimized for the problem, allowing for easy experimentation and selection of multiple algorithms. This approach is expected to provide a foundation for informed decision-making and contribute to better performance in the film industry.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.149-155
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• 2009

Attacks in wireless sensor networks (WSN), are similar to the attacks in ad-hoc networks because there are deployed on a wireless environment. However existing security mechanism cannot apply to WSN, because it has limited resource and hostile environment. One of the typical attack in WSN is setting up wrong route that using wormhole. To overcome this threat, Ji-Hoon Yun et al. proposed WODEM (WOrmhole attack DEfense Mechanism) which can detect and counter with wormhole. In this scheme, it can detect and counter with wormhole attacks by comparing hop count and initial TTL (Time To Live) which is pre-defined. The selection of a initial TTL is important since it can provide a tradeoff between detection ability ratio and energy consumption. In this paper, we proposed a fuzzy rule-based system for TTL determination that can conserve energy, while it provides sufficient detection ratio in wormhole attack.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2016-2029
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• 2023

Accurate prediction of critical illness is significant for ensuring the lives and health of patients. The selection of indicators affects the real-time capability and accuracy of the prediction for critical illness. However, the diversity and complexity of these indicators make it difficult to find potential connections between them and critical illnesses. For the first time, this study proposes an indicator analysis model to extract key indicators from the preoperative and intraoperative clinical indicators and laboratory results of critical illnesses. In this study, preoperative and intraoperative data of heart failure and respiratory failure are used to verify the model. The proposed model processes the datum and extracts key indicators through four parts. To test the effectiveness of the proposed model, the key indicators are used to predict the two critical illnesses. The classifiers used in the prediction are light gradient boosting machine (LightGBM) and eXtreme Gradient Boosting (XGBoost). The predictive performance using key indicators is better than that using all indicators. In the prediction of heart failure, LightGBM and XGBoost have sensitivities of 0.889 and 0.892, and specificities of 0.939 and 0.937, respectively. For respiratory failure, LightGBM and XGBoost have sensitivities of 0.709 and 0.689, and specificity of 0.936 and 0.940, respectively. The proposed model can effectively analyze the correlation between indicators and postoperative critical illness. The analytical results make it possible to find the key indicators for postoperative critical illnesses. This model is meaningful to assist doctors in extracting key indicators in time and improving the reliability and efficiency of prediction.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.563-570
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• 2022

Industrialized and modular construction is a growing construction technique that can transfer a large portion of the construction process to off-site fabrication yards. This method of construction often involves the fabrication, pre-assembly, and transportation of massive and long volumetric modules. The module weight keeps increasing as the modules become more complete (with infill) to minimize the work at the site and, as higher productivity can be achieved at the fabrication shop. Thus, a volumetric module delivery gets more challenging and risky. Despite its importance, past research paid relatively insufficient attention to the problem related to the lifting of heavy modules. This can be a complex and time-consuming problem with multiple lifting for transportation-and-installation operations both in fabrication yard and jobsite, and require complex crane operations (sometimes, more than one crane) due to crane load capacity and load balance/stability. This study investigates this problem by focusing on the structural perspective of lifting such long volumetric modules through simulation studies. Various scenarios of lifting a weighty module from the top using four lifting cables attached to crane hooks (either a single crane or double crane) are simulated in SAP software. The simulations account for various factors pertaining to structural indices, e.g., bending stress and deflection, to identify a proper method of module lifting from a structural point of view. The method can identify differences in structural indices allowing identification of structural efficiency and safety levels during lifting, which further allows the selection of the number of cranes and location of lifting points.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.30 no.2
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• pp.195-200
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• 1985

This experiment was carried out to know the processes of protoplast isolation, culture and plant regeneration in aims of introducing foreign genes into plant cells through plant gene vector, and cellular selection for plant improvement. The main results indicated that 2% cellulase plus 0.5% macerozyme is proper for isolation of protoplasts from leaf mesophyll cells of N. plumbaginifolia, plating efficiency was higher in 1.4-2.0 x 10$^4$ cells/ml, complete cell wall was regenerated after 2 days culture, cell division and cell mass were observed after 4 days and 2 weeks, respectively, colony was developed after 3 weeks culture, addition of 1-2mg/l BA promoted shoot differentiation while root differentiation did not required hormone and seeds were harvested from more than 100 cell lines for further investigation and study.

• Journal of the Korea Society of Computer and Information
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• v.14 no.6
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• pp.83-90
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• 2009

Since traffic is aggregated to a MPP that acts as an Internet gateway, if traffic load is not balanced among the MPPs in a WMN, the overall performance of a WMN becomes poor even though the total traffic load is far below the capacity of the WMN. Therefore, in this paper, we propose a stochastic load balancing scheme where each MP (Mesh Point) probabilistically selects its serving MPP according to the congestion levels of MPPs. Through extensive simulations using ns-2, we have verified that our scheme can stabilize a WMN fast when congestion occurs and reduce packet loss rate by distributing traffic load of a congested MPP to multiple MPPs in the inverse proportional to their congestion levels. Compared to queue-based load balancing scheme, our method can decrease network stabilization time by 34 seconds, and reduce packet loss rate by 7.6%. Since the proposed scheme can reduce network stabilization time by efficiently using network resource, it is expected to contribute to the reliable operation of a WMN.

• Journal of IKEEE
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• v.26 no.1
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• pp.62-66
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• 2022

Recently, there have been many research efforts based on data-based deep learning technologies to deal with the interference problem between heterogeneous wireless communication devices in unlicensed frequency bands. However, existing approaches are commonly based on the use of complex neural network models, which require high computational power, limiting their efficiency in resource-constrained network interfaces and Internet of Things (IoT) devices. In this study, we address the problem of classifying heterogeneous wireless technologies including Wi-Fi and ZigBee in unlicensed spectrum bands. We focus on a data-driven approach that employs a supervised-learning method that uses received signal strength indicator (RSSI) data to train Deep Convolutional Neural Networks (CNNs). We propose a simple measurement methodology for collecting RSSI training data which preserves temporal and spectral properties of the target signal. Real experimental results using an open-source 2.4 GHz wireless development platform Ubertooth show that the proposed sampling method maintains the same accuracy with only a 10% level of sampling data for the same neural network architecture.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.85-85
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• 2021

CDOM(Colored or Chromophoric Dissolved Organic Matter)은 바다, 호수 및 강에서 담수, 오수, 퇴적물 등으로부터 공급된 유기물질의 일종으로 가시광선에서 빛을 흡수하는 성질을 가지며, 2016년부터 환경부에서 선정한 하천, 호수 등 방류수의 수질오염 표준인 TOC(Total Organic Carbon)를 간접 추정할 수 있는 매개변수가 될 수 있다. 따라서, 본 연구에서는 백제보 상류 23 km 구간을 대상으로 2개년(2016~2017) 중 7일의 초분광영상 자료를 활용하여 내륙지역의 CDOM에 대한 적정 반사도 밴드값(R_rs)과 CDOM을 추정하는 알고리즘을 개발하고자 한다. CDOM은 흡수계수(α_CDOM)를 통해 간접 추정되며, 흡수계수의 기준 파장값(λ)은 연구별로 350 nm, 375 nm, 400 nm, 412 nm 및 440 nm 등 다르게 나타난다. 초분광영상은 AsaFENIX 초분광 센서에서 관측된 380~970 nm까지 4 nm 간격, 127개 대역의 분광해상도와 2 m의 공간해상도를 가진 영상을 활용하였으며, 자료의 연속성을 위해 smoothing 기법을 활용하여 가공하였다. 추정 알고리즘은 Random forest를 활용하였으며, 70%의 trainning과 30%의 test로 구분하여 적용하였다. 산출된 CDOM은 결정계수(R²), Nash-Sutcliffe efficiency(NSE)를 이용하여 실측 CDOM과 비교하였다. 흡수계수별 CDOM의 산정 결과 α_CDOM(350 nm)의 trainning, test에서 각각 R²가 0.71, 0.74, NSE가 0.25, 0.49로 가장 높았으며, 적정 반사도 밴드값은 R_rs(466), R_rs(493), R_rs(548), R_rs(641)를 사용하였을 때 trainning, test에서 각각 R²가 0.93, 0.90, NSE가 0.85, 0.69로 가장 높게 나타났다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6B
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• pp.617-625
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• 2010

The selection of a site where strong wind blows is important to increase effectively the electricity of wind power in proportion to the cube of the wind speed. It is advisable to establish the wind turbine in the coastal area with strong wind speed rather than in the inland. And the development of offshore wind energy is expected to solve the noise problem that is one of the important weaknesses in the wind turbine. In the process of the development business of wind energy, knowing forehead the wind power possibility in any area is one of the essential factors to choose the most optimum site of wind power. In this paper, the potential of wind power around JeJu coastal area is examined by using the wind data that Korea Meteorological Administration has surveyed for 10 years in 14 observation points. Wind speed data is revised to wind speed in 80 meters assuming installation height of the wind turbine, and wind power density and annual wind energy are also calculated. And annual electricity generation and percent of energy efficiency in all the observation points are estimated by using the information about 3,000 KW wind turbine.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.20-20
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• 2022

A traditional wheat breeding program needs more than 12-13 years to develop a new cultivar. In recent years, 'Speed breeding (SB)' system, which uses extremely extended photoperiod (22 h), enabled up to 4-6 generations of spring wheat per year. However, since almost 70% of wheat cultivars are winter type, and over 95% of total cultivation area is for winter wheat in Korea, optimized vernalization treatment was essential for improving the SB system. Several vernalization temperatures and durations were tested with various genotypes, and the 4 weeks of 8-10 ℃ vernalization treatment was the most effective to develop 4 generations per year, for both spring and winter type wheat cultivars. This 'Speed vernalization (SV)' system followed by SB, allowed developing a new F₆ recombinant inbred lines (RILs) within 2 years. Among the 184 RILs, which derived from a cross between Jokoyung and Joongmo2008, two outstanding lines were selected for yield trial test, and then named Milyang52 and Milyang53. Compared to the traditional wheat breeding program, over 60% of the time was saved to develop these two lines. Marker-assisted selection and backcross were also combined with the SV system. YW3215-2B-1 (Jokoyung*3/Gamet), which has similar agronomic traits with Jokyoung and the same Glu-B1 allele with Garnet, was developed within 2.5 years. Thus, the SV system combined with molecular breeding technology would help breeders to make a new cultivar with less time and high efficiency.