• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.897-906
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• 2022

In this paper, we propose a novel MAC protocol based on the harmonic transmission of ACK, called HAT-LoRa, for improving the reliability and the utilization in multiple gateway LoRa Networks. LoRa is basically vulnerable to collision due to the primitive pure ALOHA-like MAC. Whereas data frame delivery can be guaranteed by the transparent bridge of multiple receiving gateways, ACK is still transmitted by a single gateway in LoRa Network. HAT-LoRa provides the augmented reception opportunity of ACK via the simultaneous transmissions of identical ACK in multiple spreading factors. The proposed method reduces the expected transmission times of ACK double gateway environment as well as single gateway environment, by 55 and 60% in maximum, by 35% and 40% in average, in a single- and double-gateway environment, respectively. Especially, it outperforms under the environment where the distance between end device and gateways are similar to each other.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.2
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• pp.394-405
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• 2022

This paper presents the numerical estimation results of oil outflows from damaged single-hull and double-hull ships by using computational fluid dynamics (CFD) simulations. A CFD method for multi-phase flow analysis was used, and the effects of numerical parameters on oil flows was investigated. Numerical simulations were conducted to predict the changes in oil outflows under various damage conditions owing to grounding or collision accidents and verified through available experimental results. The present numerical results showed a good agreement with the experimental results according to the geometrical characteristics of single and double hulls. In particular, the oil outflows from double hulls accompanying complex interactions between water and oil were reasonably predicted a shown in the experiment. This study established a reliable CFD technique necessary for estimating the oil outflows of damaged ships.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.61-68
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• 2022

In this paper, we propose a system to predict the GPS trajectory of a pedestrian based on a deep learning model. Pedestrian trajectory prediction is a study that can prevent pedestrian danger and collision situations through notifications, and has an impact on business such as various marketing. In addition, it can be used not only for pedestrians but also for path prediction of unmanned transportation, which is receiving a lot of spotlight. Among various trajectory prediction methods, this paper is a study of trajectory prediction using GPS data. It is a deep learning model-based study that predicts the next route by learning the GPS trajectory of pedestrians, which is time series data. In this paper, we presented a data set construction method that allows the deep learning model to learn the GPS route of pedestrians, and proposes a trajectory prediction deep learning model that does not have large restrictions on the prediction range. The parameters suitable for the trajectory prediction deep learning model of this study are presented, and the model's test performance are presented.

• Journal of Aerospace System Engineering
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• v.16 no.4
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• pp.45-52
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• 2022

In the field of UAM, which is attracting attention as a next-generation transportation system, technology developments for using UAVs have been actively conducted in recent years. Since UAVs adopted with these technologies are mainly operated in urban areas, it is imperative that accidents are prevented. However, it is not easy to predict the abnormal flight state of an UAV causing a crash, because of its strong non-linearity. In this paper, we propose a method for predicting a flight state of an UAV, based on a CNN-LSTM hybrid model. To predict flight state variables at a specific point in the future, the proposed model combines the CNN model extracting temporal and spatial features between flight data, with the LSTM model extracting a short and long-term temporal dependence of the extracted features. Simulation results show that the proposed method has better performance than the prediction methods, which are based on the existing artificial neural network model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.1026-1031
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• 2022

Cognitive Radio Ad-Hoc Networks (CRAHNs) enable to overcome the shortage of frequency resources due to the increase of radio services. In order to avoid interference with the primary user in CRANH, channel sensing to check the idle channel is required, and when the primary user appears, the time delay due to handover should be minimized through fast idle channel selection. In this paper, throughput was improved by reducing the number of channel sensing and preferentially sensing a channel with a high probability of being idle, using reinforcement learning. In addition, we proposed a multi-channel MAC (Medium Access Control) protocol that can minimize the possibility of collision with the primary user by sensing the channel at the time of data transmission without performing periodic sensing. The performance was compared and analyzed through computer simulation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.15-20
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• 2024

Path planning for unmanned aerial vehicles (UAV) is crucial in avoiding collisions with obstacles in complex environments that include both static and dynamic obstacles. Path planning algorithms like RRT and A^* are effectively handle static obstacle avoidance but have limitations with increasing computational complexity in high-dimensional environments. Reinforcement learning-based algorithms can accommodate complex environments, but like traditional path planning algorithms, they struggle with training complexity and convergence in higher-dimensional environment. In this paper, we proposed a reinforcement learning model utilizing a cell decomposition algorithm. The proposed model reduces the complexity of the environment by decomposing the learning environment in detail, and improves the obstacle avoidance performance by establishing the valid action of the agent. This solves the exploration problem of reinforcement learning and improves the convergence of learning. Simulation results show that the proposed model improves learning speed and efficient path planning compared to reinforcement learning models in general environments.

• Journal of the Korea Computer Graphics Society
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• v.30 no.4
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• pp.1-10
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• 2024

In the fields of computer animation and robotics, reaching a destination while avoiding obstacles has always been a difficult task. Moreover, generating appropriate motions while planning a route is even more challenging. Recently, academic circles are actively conducting research to generate character motions by modifying and utilizing VAE (Variational Auto-Encoder), a data-based generation model. Based on this, in this study, the latent space of the MVAE model is learned using a reinforcement learning method[1]. With the policy learned in this way, the character can arrive its destination while avoiding both static and dynamic obstacles with natural motions. The character can easily avoid obstacles moving in random directions, and it is experimentally shown that the performance is improved, and the learning time is greatly reduced compared to existing approach.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.12 no.4
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• pp.209-215
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• 1979

The manoeuvrabilities of a ship are decided by the values of her manoeuvring indices. The manoeuvring indices consist of two kinds: indices K and T. The former decides a ship's turning ability and the latter, the length of time delay to a steady turning motion after her rudder has finished the turn of an ordered angle. In this paper, the author figured out the values of the manoeuvring indices of the m. s. 'SAEBADA' (GT: 2,275,7 ton), the training ship of tile National Fisheries University of Busan through her Z test and analyzed these values and the other data which were obtained from her Z test to study her manoeuvrabilities. The results of]tamed are summarized as follows: 1. The manoeuvring indices K' of the m. s. 'SAEBADA' were $1.052(at\;10{\circ}\;Z\;test)\;0.925(at\;20{\circ}\;Z\;test)\;and\;0.877(at\;30{\circ}\;Z\;test)$. Her manoeuvring indices $0.815(at\;10{\circ}\;Z\;test)\;0.502(at\;20{\circ}\;Z\;test)\;and\;0.441(at\;30{\circ}\;Z\;test)$. Her above calculated values K', T' showed that her obeying ability to the turn of her rudder was more increased when her rudder was used to large angle than to small angle, but on the other hand in this case her turning ability was slightly reduced. 2. As it appeared that the calculated K'-values of the m.s. 'SAEBADA' were slightly smaller than the standard K'-values of the fishing boats similar in length, and her overshoot angles at her Z test were greater than other general ships, her turning ability was found to t]e slightly lower. 3. When the m. s. 'SAEBADA' took a turn at her $10^{\circ}\;Z$ test, running distance was about 8.6 times her own length and didn't exceed the standard manoeuvrability distance, 5 to 11 times general ships' own length, therefore she was considered to have a good manoeuvrability synthetically.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.5
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• pp.628-636
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• 2018

Because large buoys are mainly made of steel, they are heavy and vulnerable to corrosion by sea water. This makes buoy installation and maintenance difficult. Moreover, vessel collision accidents with buoys and damage to vessels due to the material of buoys (e.g., steel) are reported every year. Recently, light buoys adopting eco-friendly and lightweight materials have come into the spotlight in order to solve the previously-mentioned problems. In Korea, a new lightweight buoy with a 7-Nautical Mile lantern adopting expanded polypropylene (EPP) and aluminum to create a buoyant body and tower structure, respectively, was developed in 2017. When these light buoys are operated in the ocean, the visibility and angle of light from the lantern installed on the light buoys changes, which may cause them to function improperly. Therefore, research on the performance of light buoys is needed since the weight distribution and motion characteristics of these new buoys differ from conventional models. In this study, stability estimation and motion analyses for newly-developed buoys under various environmental conditions considering a mooring line were carried out using ANSYS AQWA. Numerical simulations for the estimation of wind and current loads were performed using commercial CFD software, Siemens STAR-CCM+, to increase the accuracy of motion analysis. By comparing the estimated maximum significant motions of the light buoys, it was found that waves and currents were more influential in the motion of the buoys. And, the estimated motions of the buoys became larger as the sea state became worser, which might be the reason that the peak frequencies of the wave spectra got closer to those of the buoys.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.5 s.347
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• pp.84-93
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• 2006

Ethernet-PON is an emerging access network technology that provides a low-cost method of deploying optical access lines between OLT and ONUs. It has a point-to-multipoint and multipoint-to-point architecture in downstream and upstream direction, respectively. Therefore, downstream packets are broadcast from an OLT toward all ONUs sithout collision. On the other hand, since alt ONUs share a common channel, the collision may be occurred for the upstream transmission. Therefore, earlier efforts on Ethernet-PON have been concentrated on an upstream MAC protocol to avoid collision. But it is needed to control downstream traffic in practical access network, where the network provider limits available bandwidth according to the number of users. In this paper, we propose a traffic control scheme for supporting the fairness of the downstream bandwidth. The objective of this algorithm is to guarantee the fairness of ONUs while maintaining good performance. In order to do this, we define the service probability that considers the past traffic information for downstream, the number of tokens and the relative size of negotiated bandwidth. We develop the simulation model for Ethernet-PON to evaluate the rate-limiting algorithm by using AWESIM. Some results are evaluated and analyzed in terms of defined fairness factor, delay and dropping rate under various scenario.