• International Journal of High-Rise Buildings
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• v.1 no.2
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• pp.87-97
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• 2012

The indoor environments in high-rise buildings are generally well enclosed by defined boundary conditions. Here, a numerical simulation method based on the Lattice Boltzmann method (LBM), which aims to model and simulate the turbulent flow accurately in an enclosed environment, and its comparison with traditional computational fluid dynamics (CFD) results, are presented in this paper. CFD has become a powerful tool for predicting and evaluating enclosed airflows with the rapid advance in computer capacity and speed, and various types of CFD turbulence modeling and its application and validation have been reported. The LBM is a relatively new method; it involves solving of the discrete Boltzmann equation to simulate the fluid flow with a collision model instead of solving Navier-Stokes equations. In this study, the LBM-based scheme of flow pattern and particle dispersion analyses are validated using the benchmark test case of two- and three-dimensional and isothermal conditions (IEA/Annex 20 case); the prediction accuracy and advantages are also discussed by comparison with the results of CFD.

• Journal of Korea Game Society
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• v.20 no.3
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• pp.85-94
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• 2020

AI-based smart factory technologies are only increase short-term productivity. To solve this problem, collaborative intelligence combines human teamwork, creativity, AI speed, and accuracy to actively compensate for each other's shortcomings. However, current automation equipmens require high safety measures due to the high disaster intensity in the event of an accident. In this paper, we design and implement a factory safety control system that uses a depth camera to implement workers and facilities in the virtual world and to determine the safety of workers through simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.7B
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• pp.827-833
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• 2011

Directional MAC protocols have drawn great attentions recently in super high speed wireless local/personal area networks due to their higher antenna gain, better spatial reuse, longer transmission range, and lower interference. Despite of these merits, directional MAC protocols suffer from deafness problem. The deafness problem occurs if a node does not answer an RTS frame addressed to it. To overcome this problem, directional MAC protocols have aimed at avoiding the deafness problem using multiple control frames or advance notice techniques or distinguishing deafness from collision. In this paper, we analyze the performance of these schemes in deafness environments with some scenarios. Through performance analysis, we compare the performance of these schemes through evaluating actual network throughput.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.6
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• pp.615-622
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• 2015

Recently Digital-TachoGraph(DTG) was mounted mandatorily in commercial vehicles(Taxi, Bus, etc.). DTG records accurate and detailed information of the running state of vehicles related to traffic accident, such as Time, Distance, Velocity, RPM, Brake ON/OFF, GPS, Azimuth, Acceleration. Thus those standardized data can play an important role in traffic accident investigation and reconstruction. To develope the accurate and objective method using the DTG data for the reconstruction of traffic accident, we had conducted several tests such as driving test, high speed circuit test, braking test, slalom test at Korea Automobile Testing & Research Institute(KATRI), and collision test at Korea Automobile insurance repair Research and Training center(KART) with the vehicle equipped with several DTG. Development of the program which enables the reading and analysis of the DTG data was followed. In the experiments, we have found velocity error, RPM error, brake signal error and azimuth error in several products, and also non-continuous event data. The cause of these errors was deduced to be related to the correction factor, the durability of electronic parts and the algorithm.

• Journal of Information Processing Systems
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• v.13 no.6
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• pp.1575-1584
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• 2017

As interest in big data has increased recently, NoSQL, a solution for storing and processing big data, is getting attention. NoSQL supports high speed, high availability, and high scalability, but is limited in areas where data integrity is important because it does not support multiple row transactions. To overcome these drawbacks, many studies are underway to support multiple row transactions in NoSQL. However, existing studies have a disadvantage that the number of transactions that can be processed per unit of time is low and performance is degraded. Therefore, in this paper, we design and implement a multi-row transaction system for data integrity in big data environment based on HBase, a column-based NoSQL which is widely used recently. The multi-row transaction system efficiently performs multi-row transactions by adding columns to manage transaction information for every user table. In addition, it controls the execution, collision, and recovery of multiple row transactions through the transaction manager, and it communicates with HBase through the communication manager so that it can exchange information necessary for multiple row transactions. Finally, we performed a comparative performance evaluation with HAcid and Haeinsa, and verified the superiority of the multirow transaction system developed in this paper.

• Journal of the Society of Naval Architects of Korea
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• v.46 no.6
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• pp.603-610
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• 2009

Ice load is one of the important design parameters for the construction of icebreaking vessels. In this paper, the design ice load prediction for the icebreaking vessels under normal operating condition in ice-covered sea is discussed. The ice loads under normal operating condition are expected from sea trials in moderate ice conditions. In this sense the extreme ice loads during heavy ramming or accidental collision are not considered. Current study describes the global ice load on the hull of the icebreaking vessels. Available ice load data from full-scale sea trials are collected and analyzed according to various ship-ice interaction parameters including displacement, stem angle, speed of a ship and flexural strength and thickness of sea ice. The ice load prediction formula is compared with the collected full-scale sea trials data and it shows a good agreement.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.6
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• pp.529-535
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• 2016

This study focuses on the comparison of measured data from 6-DOF motion sensor and strain gauge installed in the IBRV ARAON during 2015 summer voyage in the Arctic. Procedures to calculate the global ice load from MotionPak II inertial measurement system and the local load from stain gauge system are discussed. The ship's speed and peak load are determined in the concept of an ice collision "event". It is found that the peak values in the global ice calculated form whole ship motion analysis fall in the range of 1.5~3 times of the local ice load based in strain gauge measurement.

• The Journal of Korea Robotics Society
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• v.16 no.2
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• pp.147-154
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• 2021

One of the most challenging issues when robots interact with the environment is to establish contact quickly and avoid high impact force at the same time. The proposed method implements the passive suspension system using the redundancy of the torque-controlled robot. Instead of utilizing the actual mechanical compliance, the distal joints near the end-effector are controlled to act as a virtual spring-damper system with low feedback gains. The proximal joints are precisely controlled to push the mid-link, which is defined as the boundary link between the proximal and distal joints, towards the environment with high feedback gains. Compared to the active compliance methods, the contact force measurements or estimates are not required for contact establishment and the control time delay problems do not occur correspondingly. The proposed method was applied to the landing foot control of the 12-DoF biped robot DYROS-RED in the simulations. In the results, the impact force during landing was significantly reduced at the same collision speed.

• Journal of the Korean Institute of Educational Facilities
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• v.25 no.6
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• pp.21-28
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• 2018

To compare the physical quantity of students circulation along the moving path during recess of a variation type operation middle school, five points were actually observed. The flow coefficient for these points was calculated, and the change in flow coefficient was verified and tracked over time. During the operation of the classroom, the characteristics of crowdedness and congestion time depending on the physical conditions of the frequently moved paths were shown. Even in the same corridor, the difference between the flow coefficient and the congestion time of the corridor facing the open space and the blocked space was noticeably different. As a result, detailed factors such as free walking speed, the degree of freedom of passing and the possibility of collision were also identified. This means that detailed countermeasures for the student's path should be considered first when planning the moving space of a variation type school, and identifying the characteristics of these factors could be used as useful basic materials for developing various models of classroom space.

• Ocean Systems Engineering
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• v.10 no.4
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• pp.415-434
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• 2020

Detecting objects is important for the safe operation of ships, and enables collision avoidance, risk detection, and autonomous sailing. This study proposes a ship detection method from images and videos taken at sea using one of the state-of-the-art deep neural network-based object detection algorithms. A deep learning model is trained using a public maritime dataset, and results show it can detect all types of floating objects and classify them into ten specific classes that include a ship, speedboat, and buoy. The proposed deep learning model is compared to a universal trained model that detects and classifies objects into general classes, such as a person, dog, car, and boat, and results show that the proposed model outperforms the other in the detection of maritime objects. Different deep neural network structures are then compared to obtain the best detection performance. The proposed model also shows a real-time detection speed of approximately 30 frames per second. Hence, it is expected that the proposed model can be used to detect maritime objects and reduce risks while at sea.