• Journal of Korea Entertainment Industry Association
• /
• v.15 no.4
• /
• pp.349-357
• /
• 2021

Recently, drones are rapidly becoming common and expanding. There is a great need for diversity in whether drone flight data can be used as entertainment technology analysis data. In particular, it is necessary to check whether it is possible to analyze and utilize the flight and operation process of entertainment drones, which are developing through autonomous and intelligent methods, through data analysis and machine learning. In this paper, it was confirmed whether it can be used as a machine learning technology by using FC data in the evaluation of drones for entertainment. As a result, FC data from DJI and Parrot such as Mavic2 and Anafi were unable to analyze machine learning for entertainment. It is because data is collected at intervals of 0.1 second or more, so that it is impossible to find correlation with other data with GCS. On the other hand, it was found that machine learning technologies can be applied in the case of Fixhawk, which used an ARM processor and operates with the Nuttx OS. In the future, it is necessary to develop technologies capable of analyzing the characteristics of entertainment by dividing fixed-wing and rotary-wing flight information. For this, a model shoud be developed, and systematic big data collection and research should be conducted.

• Journal of Bio-Environment Control
• /
• v.31 no.1
• /
• pp.1-7
• /
• 2022

Strawberry is a stand-out cultivating fruit in Korea. The optimum production of strawberry is highly dependent on growing environment. Smart farm technology, and automatic monitoring and control system maintain a favorable environment for strawberry growth in greenhouses, as well as play an important role to improve production. Moreover, physiological parameters of strawberry plant and it is surrounding environment may allow to give an idea on production of strawberry. Therefore, this study intends to build a machine learning model to predict strawberry's yield, cultivated in greenhouse. The environmental parameter like as temperature, humidity and CO₂ and physiological parameters such as length of leaves, number of flowers and fruits and chlorophyll content of 'Seolhyang' (widely growing strawberry cultivar in Korea) were collected from three strawberry greenhouses located in Sacheon of Gyeongsangnam-do during the period of 2019-2020. A predictive model, Lasso regression was designed and validated through 5-fold cross-validation. The current study found that performance of the Lasso regression model is good to predict the number of flowers and fruits, when the MAPE value are 0.511 and 0.488, respectively during the model validation. Overall, the present study demonstrates that using AI based regression model may be convenient for farms and agricultural companies to predict yield of crops with fewer input attributes.

• Journal of Convergence for Information Technology
• /
• v.11 no.7
• /
• pp.111-117
• /
• 2021

This research work is to suggest the experimental results capable of solving an initial unsuitability of combustion and environment in a constant volume combustion chamber by using LFG(Land Fill Gas) which consists of 40% CO₂ and 60% CH₄. The experimental condition is set as 0.9~1.6 of air-fuel ratio, 3bar of combustion pressure, 25℃ of room temperature, methane for using gas, and 2.5~4.5 of Pre-chamber hole sizes. As a result, it can be seen that diffusion of initial flame is significantly increased by M3.0 model comparing with other one. The reason for the characteristics is that orifice effect is extremely improved by 0.9, 1.0, and 1.2 of air-fuel ratio comparing with other one. Consequently, this experiment is shown that M3.0 model is partially capable of improving combustion performance than a conventional ignition plug in case of applying to LFG with Pre-chamber design.

• Clean Technology
• /
• v.28 no.4
• /
• pp.316-322
• /
• 2022

The flow pattern at the inlet of the catalyst layer in a selective catalytic reduction (SCR) system is one of the key parameters influencing the performance of the denitrification process. In the curved diffusing parts between the ammonia injection grids and the catalyst layers, guide vanes are installed to improve flow uniformity. In the present study, a numerical simulation has been performed to investigate the effect of the geometrical configuration of the guide vanes on the aerodynamic characteristics of a denitrification facility. This application has been made to the existing SCR process in a large-scaled coal-fired power plant. The flow domain to be solved covers the whole region of the flow passages from the exit of the ammonia injection gun to the exit of the catalyst layers. ANSYS-Fluent was used to calculate the three-dimensional steady viscous flow fields with the proper turbulence model fitted to the flow characteristics. The root mean square of velocity and the pressure drop inside the flow passages were chosen as the key performance parameters. Four types of guides vanes were proposed to improve the flow quality compared to the current configuration. The numerical results showed that the type 4 configuration was the most effective at improving the aerodynamic performance in terms of flow uniformity and pressure loss.

• Journal of the Society of Disaster Information
• /
• v.18 no.3
• /
• pp.550-559
• /
• 2022

Purpose: Pipes are widely used as applied devices in many industrial fields such as machinery, electronics, electricity, and plants, and are also widely used in safety-related fields such as firefighting and chemistry. With the diversification of products, the importance of technology in the piping field is also increasing. In particular, when changing the existing copper pipe to stainless steel, it is necessary to evaluate safety and flow characteristics through structural analysis or flow analysis. Method: This study investigated the safety by flow analysis of the 6.35 inch socket model, which are integrated insert type connectors developed by a company, using CFD analysis technique. For CDF analysis, RAN model and LES model are used. Result: As results of the analysis, amplitude of the pressure fluctuation acting on the wall of the piping system is formed at a level of 3,780 Pa or less, which is a very small level of pressure compared with the operating pressure or design stress of the refrigerant piping. Conclusion: These results mean that the effect of vibration caused by turbulence on the structural safety of the pipe is negligible.

• Journal of the Korean Society of Radiology
• /
• v.16 no.4
• /
• pp.453-462
• /
• 2022

In this paper, the artificial intelligence (AI) technology used in the medical image analysis field was analyzed through a literature review. Literature searches were conducted on PubMed, ResearchGate, Google and Cochrane Review using the key word. Through literature search, 114 abstracts were searched, and 98 abstracts were reviewed, excluding 16 duplicates. In the reviewed literature, AI is applied in classification, localization, disease detection, disease segmentation, and fit degree of registration images. In machine learning (ML), prior feature extraction and inputting the extracted feature values into the neural network have disappeared. Instead, it appears that the neural network is changing to a deep learning (DL) method with multiple hidden layers. The reason is thought to be that feature extraction is processed in the DL process due to the increase in the amount of memory of the computer, the improvement of the calculation speed, and the construction of big data. In order to apply the analysis of medical images using AI to medical care, the role of physicians is important. Physicians must be able to interpret and analyze the predictions of AI algorithms. Additional medical education and professional development for existing physicians is needed to understand AI. Also, it seems that a revised curriculum for learners in medical school is needed.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.11
• /
• pp.449-456
• /
• 2021

An intrusion detection system is a technology that detects abnormal behaviors that violate security, and detects abnormal operations and prevents system attacks. Existing intrusion detection systems have been designed using statistical analysis or anomaly detection techniques for traffic patterns, but modern systems generate a variety of traffic different from existing systems due to rapidly growing technologies, so the existing methods have limitations. In order to overcome this limitation, study on intrusion detection methods applying various machine learning techniques is being actively conducted. In this study, a comparative study was conducted on data preprocessing techniques that can improve the accuracy of anomaly detection using NGIDS-DS (Next Generation IDS Database) generated by simulation equipment for traffic in various network environments. Padding and sliding window were used as data preprocessing, and an oversampling technique with Adversarial Auto-Encoder (AAE) was applied to solve the problem of imbalance between the normal data rate and the abnormal data rate. In addition, the performance improvement of detection accuracy was confirmed by using Skip-gram among the Word2Vec techniques that can extract feature vectors of preprocessed sequence data. PCA-SVM and GRU were used as models for comparative experiments, and the experimental results showed better performance when sliding window, skip-gram, AAE, and GRU were applied.

• Clean Technology
• /
• v.16 no.3
• /
• pp.213-219
• /
• 2010

Vortex tube is the device that can separate small particles from the compressed gas, as well as compressed gas into hot and cold gas. Due to energy and particle separation ability, a vortex tube can be used as the main component of the $CO_2$ absorption device. In this study, experimental approach has been performed to analyze the energy separation characteristics of the vortex tube. To obtain the preliminary design data, energy separation characteristics of the vortex tube has been tested for orifice diameter, nozzle area ratio, and tube length. As a result, the orifice diameter is the major factor of the vortex tube design. The nozzle area ratio and tube length have a minor effect on the energy separation performance. For Dc=0.6D, AR=0.14~0.16, and L=16D, maximum energy separation has been occurred. The result from this study can be used as the basic design data of the $100Nm^3$/hr class vortex tube applied to the $CO_2$ absorption device. Compared with the $CO_2$ absorption process containing an absorption tower, the process with a vortex tube is expected to have a huge advantage of saving the installation space and the operating cost.

• The Journal of the Acoustical Society of Korea
• /
• v.42 no.3
• /
• pp.250-261
• /
• 2023

In this study, the noise contributions by the duct, stator and rotor, which are the propulsor components, are evaluated to identify the flow noise source in cavitation and non-cavitation conditions on pumpjet propulsion and the noise levels in both conditions are compared. The unsteady incompressible Reynolds averaged Navier-Stokes (RANS) equation based on the homogeneous mixture assumption is applied on the suboff submarine hull and pumpjet propeller in the cavitation tunnel, and the Volume of Fluid (VOF) method and Schnerr-Sauer cavitation model are used to describe the two-phase flow. Based on the flow simulation results, the acoustic analogy formulated by Ffowcs Williams and Hawkings (FW-H) equation is applied to predict the underwater radiated noise. The noise contributions are evaluated by using the three types of impermeable integral surface on the duct, stator and rotor, and the two types of permeable integral surface surrounding the propulsor. As a result of noise prediction, the contribution by the stator is insignificant, but it affects the generation of flow noise source due to flow separation in the duct and rotor, and the noise is predominantly radiated into the upward and right where the flow separations are. Also, the noise is radiated into the thrust direction due to pressure fluctuation between suction and pressure sides on the rotor blades, and the it can be seen that the cavitation effect into the noise can be considered through the permeable integral surface.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.29 no.1
• /
• pp.24-35
• /
• 2023

Rapid industrialization and urbanization have led to severe marine pollution. A Water Quality Index (WQI) has been developed to allow the effective management of marine pollution. However, the WQI suffers from problems with loss of information due to the complex calculations involved, changes in standards, calculation errors by practitioners, and statistical errors. Consequently, research on the use of artificial intelligence techniques to predict the marine and coastal WQI is being conducted both locally and internationally. In this study, six techniques (RF, XGBoost, KNN, Ext, SVM, and LR) were studied using marine environmental measurement data (2000-2020) to determine the most appropriate artificial intelligence technique to estimate the WOI of five ecoregions in the Korean seas. Our results show that the random forest method offers the best performance as compared to the other methods studied. The residual analysis of the WQI predicted score and actual score using the random forest method shows that the temporal and spatial prediction performance was exceptional for all ecoregions. In conclusion, the RF model of WQI prediction developed in this study is considered to be applicable to Korean seas with high accuracy.