• Journal of Korean Society of Water and Wastewater
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• v.12 no.1
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• pp.81-87
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• 1998

The possibility of collision of two particles slowly settling one after another in water can be described using the collision efficiency factor in differential sedimentation (${\alpha}_{DS}$). ${\alpha}_{DS}$ was found to be a function of several parameters particle size, particle size ratio, Hamaker constant, density of liquid and particle, gravity acceleration. Previous researches were limited to the case when there is no electric repulsion assuming that the suspension is destabilized. In this paper, ${\alpha}_{DS}$ is calculated for the stabilized condition. The relative trajectory of two particles are calculated including hydrodynamics, attraction and repulsion forces. Ionic strength and surface potential significantly affect the collision possibility of two settling particles. Depending on the surface potential and ionic strength, ${\alpha}_{DS}$ value is divided into three regions; stable, unstable and transition zone. ${\alpha}_{DS}$ increases as the ionic strength increases, and as the surface charge decreases. This result can be used to model both destabilized and stabilized suspension incorporating the collision efficiency factors of the other coagulant mechanisms such as fluid shear and Browian motion.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4373-4391
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• 2022

Marine reactor systems experience platform movement, and therefore, the system thermal-hydraulic analysis code needs to reflect the motion effect on the fluid to evaluate reactor safety. A moving reactor model for MARS-KS was developed to simulate the hydrodynamic phenomena in the reactor under motion conditions; however, its applicability does not cover the MULTID component used in multidimensional flow analyses. In this study, a moving reactor model is implemented for the MULTID component to address the importance of multidimensional flow effects under dynamic motion. The concept of the volume connection is generalized to facilitate the handling of the junction of MULTID. Further, the accuracy in calculating the pressure head between volumes is enhanced to precisely evaluate the additional body force. Finally, the Coriolis force is modeled in the momentum equations in an acceleration form. The improvements are verified with conceptual problems; the modified model shows good agreement with the analytical solutions and the computational fluid dynamic (CFD) simulation results. Moreover, a simplified gravity-driven injection is simulated, and the model is validated against a ship flooding experiment. Throughout the verifications and validations, the model showed that the modification was well implemented to determine the capability of multidimensional flow analysis under ocean conditions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.2
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• pp.936-942
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• 2013

This paper presents the results of laboratory tests conducted to investigate the effectiveness of applying methodology of a sand compaction(SCP) and a gravel compaction pile(GCP) on soft ground. The test conditions involved relatively low replacement ratios (=10, 20, and 30%) of a pile to unit cell at 1g (gravity acceleration) level. Results revealed that GCP significantly enhanced bearing capacity, settlement reduction, and consolidation rate compared with SCP.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.249-251
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• 2021

In this paper, we introduce the deep-learning system using Tensorflow for recognizing situations that can occur fall situations when the elderly are moving or standing. Fall detection uses the LSTM (long short-term memory) learned using Tensorflow to determine whether it is a fall or not by data measured from wearable accelerator sensor. Learning is carried out for each of the 7 behavioral patterns consisting of 4 types of activity of daily living (ADL) and 3 types of fall. The learning was conducted using the 3-axis acceleration sensor data. As a result of the test, it was found to be compliant except for the GDSVM(Gravity Differential SVM), and it is expected that better results can be expected if the data is mixed and learned.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.270-270
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• 2019

Although the Inertial Measurement Unit is applied to a variety of applications such as ships, submarines, and aircrafts, it is mainly used in the attitude measurement area. But since such equipment is expensive, it has been used only in special fields. In this study, the ship's seaworthiness is verified by measuring the speed, direction, gravity, and acceleration of the ship in real time using a low-cost Inertial Measurement Unit. A research method for estimating fIuid force coefficients was devised. Therefore, this study measured ship motion factors at sea, processed and analyzed the measured data, and evaluated the overall safety of the ship and estimated the resistance and steering performance of the ship.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.391-393
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• 2021

In this paper, we introduce a long short-term memory (LSTM)-based fall detection system using TensorFlow that can detect falls occurring in the elderly in daily living. 3-axis accelerometer data are aggregated for fall detection, and then three types of parameter are calculated. 4 types of activity of daily living (ADL) and 3 types of fall situation patterns are classified. The parameterized data applied to LSTM. Learning proceeds until the Loss value becomes 0.5 or less. The results are calculated for each parameter θ, SVM, and GSVM. The best result was GSVM, which showed Sensitivity 98.75%, Specificity 99.68%, and Accuracy 99.28%.

• Journal of Multimedia Information System
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• v.2 no.2
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• pp.233-240
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• 2015

Mobile devices are becoming increasingly sophisticated and the latest generation of smartphones now incorporates many diverse and powerful sensors. These sensors include acceleration sensor, magnetic field sensor, light sensor, proximity sensor, gyroscope sensor, pressure sensor, rotation vector sensor, gravity sensor and orientation sensor. The availability of these sensors in mass-marketed communication devices creates exciting new opportunities for data mining and data mining applications. In this paper, we describe and evaluate a system that uses phone-based accelerometers to perform activity recognition, a task which involves identifying the physical activity that a user is performing. To implement our system, we collected labeled accelerometer data from 10 users as they performed daily activities such as "phone detached", "idle", "walking", "running", and "jumping", and then aggregated this time series data into examples that summarize the user activity 5-minute intervals. We then used the resulting training data to induce a predictive model for activity recognition. This work is significant because the activity recognition model permits us to gain useful knowledge about the habits of millions of users-just by having them carry cell phones in their pockets.

• Journal of Advanced Navigation Technology
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• v.15 no.3
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• pp.449-455
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• 2011

In this paper, Proposed controller prevent compressor surge and reduce the acceleration time of the fuel flow control system for turbo-jet engine. Turbo-jet engine controller is designed by applying fuzzy PI+D control algorithm and make an inference by applying Mamdani's inference method and the defuzzification using the center of gravity method. Fuzzy inference results are used as the fuel flow control inputs to prevent compressor surge and flame-out for turbo-jet engine and the controller is designed to converge to the desired speed quickly and safely. Using MATLAB to perform computer simulations verified the performance of the proposed controller.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.76-83
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• 2022

With the recent development of IT technology, research and interest in various biosignal measuring devices is increasing. As an aging society is in full swing, research on the elderly population using IT-related technologies is continuously developing. This study is about the development of life pattern detection and fall detection algorithm, which is one of the medical service areas for the elderly, who are rapidly developing as they enter a super-aged society. This study consisted of a system using a 3-axis accelerometer and an electrocardiogram sensor, collected data, and then analyzed the data. It was confirmed that behavioral patterns could be classified from the actual research results. In order to evaluate the usefulness of the human activity monitoring system implemented in this study, experiments were performed under various conditions, such as changes in posture and walking speed, and signal magnitude range and signal vector magnitude parameters reflecting the acceleration of gravity of the human body and the degree of human activity. was extracted. And the possibility of discrimination according to the condition of the subject was examined by these parameter values.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.8
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• pp.531-540
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• 2022

In this paper, we present an algorithm that identifies artillery type and rapidly predicts the impact point based on the IMM filter. The ballistic trajectory equation is used as a system model, and three models with different ballistic coefficient values are used. Acceleration was divided into three components of gravity, air resistance, and lift. And lift acceleration was added as a new state variable. The kinematic condition that the velocity vector and lift acceleration are perpendicular was used as a pseudo-measurement value. The impact point was predicted based on the state variable estimated through the IMM filter and the ballistic coefficient of the model with the highest mode probability. Instead of the commonly used Runge-Kutta numerical integration for impact point prediction, a semi-analytic method was used to predict impact point with a small amount of calculation. Finally, a state variable initialization method using the least-square method was proposed. An integrated algorithm including artillery type identification, impact point prediction and initialization was presented, and the validity of the proposed method was verified through simulation.