• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.54-69
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• 2021

Policy improvement such as the revision of the Road Traffic Act are proposed for personal mobility(especially e-scooter) usage. However, there is not enough discussion to solve the problem of using shared e-scooter. In this study, we analyze the influencing factors that amount of pick-up and drop-off of shared e-scooter by dividing the Seoul into a 200m grid. we develop spatial auotcorrelation model such as spatial lag model, spatial error model, spatial durbin model, and spatial durbin error model in order to consider the characteristics of the aggregated data based on a specific space, and the spatial durbin error model is selected as the final model. As a result, demographic factor, land use factor, and transport facility factors have statistically significant impacts on usage of shared e-scooter. The result of this study will be used as basic data for suggesting efficient operation strategies considering the characteristics of weekday and weekend.

• Journal of the Korea Society for Simulation
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• v.30 no.1
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• pp.43-54
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• 2021

Since COVID-19 (Severe acute respiratory syndrome coronavirus type 2, SARS-Cov-2) was first discovered at the end of 2019, it has spread rapidly around the world. This study introduces an agent-based simulation model representing COVID-19 spread in South Korea to investigate the effect of detect level (contact tracing) on the virus spread. To develop the model, related data are aggregated and probability distributions are inferred based on the data. The entire process of infection, quarantine, recovery, and death is schematically described and the interaction of people is modeled based on the traffic data. A composite logistic functions are utilized to represent the compliance of people to the government move control such as social distancing. To demonstrate to effect of detect level on the virus spread, detect level is changed from 0% to 100%. The results indicate active contact tracing inhibits the virus spread and the inhibitory effect increases geometrically as the detect level increases.

• Journal of information and communication convergence engineering
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• v.20 no.1
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• pp.22-30
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• 2022

The reinforcement learning algorithm has proven its potential in solving sequential decision-making problems under uncertainties, such as finding paths to route data packets in wireless sensor networks. With reinforcement learning, the computation of the optimum path requires careful definition of the so-called reward function, which is defined as a linear function that aggregates multiple objective functions into a single objective to compute a numerical value (reward) to be maximized. In a typical defined linear reward function, the multiple objectives to be optimized are integrated in the form of a weighted sum with fixed weighting factors for all learning agents. This study proposes a reinforcement learning -based routing protocol for wireless sensor network, where different learning agents prioritize different objective goals by assigning weighting factors to the aggregated objectives of the reward function. We assign appropriate weighting factors to the objectives in the reward function of a sensor node according to its hop-count distance to the sink node. We expect this approach to enhance the effectiveness of multi-objective reinforcement learning for wireless sensor networks with a balanced trade-off among competing parameters. Furthermore, we propose SDN (Software Defined Networks) architecture with multiple controllers for constant network monitoring to allow learning agents to adapt according to the dynamics of the network conditions. Simulation results show that our proposed scheme enhances the performance of wireless sensor network under varied conditions, such as the node density and traffic intensity, with a good trade-off among competing performance metrics.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.4
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• pp.687-697
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• 2023

Botnets, whose attack patterns are becoming more sophisticated and diverse, are recognized as one of the most serious cybersecurity threats today. This paper revisits the experimental results of botnet detection using autoencoder, a semi-supervised deep learning model, for UGR and CTU-13 data sets. To prepare the input vectors of autoencoder, we create data points by grouping the NetFlow records into sliding windows based on source IP address and aggregating them to form features. In particular, we discover a simple power-law; that is the number of data points that have some flow-degree is proportional to the number of NetFlow records aggregated in them. Moreover, we show that our power-law fits the real data very well resulting in correlation coefficients of 97% or higher. We also show that this power-law has an impact on the learning of autoencoder and, as a result, influences the performance of botnet detection. Furthermore, we evaluate the performance of autoencoder using the area under the Receiver Operating Characteristic (ROC) curve.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3D
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• pp.303-311
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• 2010

There have been various forms of systems such as a digital speedometer or a black box etc. to meet the social requirement for reducing traffic accidents and safe driving. However that systems are based on after-accident vehicle data, there is limit to prevent the accident before. So in our previous research, by storing, analyzing the Vehicle-dynamic information coming from driver's behavior, we are developing the decision-device which could provide driver with Alerting-Information in real-time to enhance the driver's safety drive. but the performance valuation is not yet executed. Finally, this study developed positional recognition system by using the DGPS for pre-developed risky driving decision device. The result of test analyzed with the same that the aggregated vehicle dynamics data in DGPS and dangerous risky driving decision device. If the performance of risky driving decision device is verified by precisely positional recognition system, the risky driving management of vehicle would be effected.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.178-188
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• 2024

In the near future, it is expected that there will be billions of connected devices using fifth generation (5G) network services. The recently available base stations (BSs) need to mitigate their loads without changing and at the least monetary cost. The available spectrum resources are limited and need to be exploited in an efficient way to meet the ever-increasing demand for services. Device to Device communication (D2D) technology will likely help satisfy the rapidly increasing capacity and also effectively offload traffic from the BS by distributing the transmission between D2D users from one side and the cellular users and the BS from the other side. In this paper, we propose to apply D2D overlay communication with cognitive radio capability in 5G networks to exploit unused spectrum resources taking into account the dynamic spectrum access. The performance metrics; throughput and delay are formulated and analyzed for CSMA-based medium access control (MAC) protocol that utilizes a common control channel for device users to negotiate the data channel and address the contention between those users. Device users can exploit the cognitive radio to access the data channels concurrently in the common interference area. Estimating the achievable throughput and delay in D2D communication in 5G networks is not exploited in previous studies using cognitive radio with CSMA-based MAC protocol to address the contention. From performance analysis, applying cognitive radio capability in D2D communication and allocating a common control channel for device users effectively improve the total aggregated network throughput by more than 60% compared to the individual D2D throughput without adding harmful interference to cellular network users. This approach can also reduce the delay.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.98-108
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• 2013

The number of Hi-Pass lanes became 793 lanes at 316 expressway tollgates in 2011 due to the increase in the Hi-Pass use. In spite of the increase in the number of Hi-Pass lanes, there have been increased potential risks in tollgates where vehicles using a Hi-Pass lane must weave with other vehicles using a TCS lane. Therefore, there is a need for study on the safety in tollgates. To this end, this study aims at developing a methodology to evaluate the performance measures of diverse location countermeasures of Hi-Pass lanes in an efficient and systematic way. This study measured the mobility, safety and the convenience of installation and operation of Hi-Pass lanes using a microscopic traffic simulation tool, the surrogate safety assessment model and survey. In addition, this study aggregated the above three performance indexes using weight factors estimated using the AHP technique. For the test site, Dongsuwon interchange was selected. After building the microscopic traffic simulation model for the test site, the location countermeasures of Hi-Pass lanes applicable to the test site were compared with each other in terms of the mobility, safety and installing and operating convenience. As a result, there has been no apparent difference in mobility index based on delays. However, the countermeasures where Hi-Pass lanes are located in inside lanes generally showed better safety performance based on the number of conflicts. In addition, countermeasures with neighboring Hi-Pass lanes were favorable in terms of the safety and the convenience of installation and operation. The methodology proposed in this study was found to be useful to support decision makings by providing critical and quantitative information regarding the mobility, safety and the convenience of installation and operation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.34-44
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• 2016

This study was initiated to evaluate the performance of methodologies to estimate the space mean speed(SMS) using the time mean speed(TMS) which was collected from the vehicle detection system(VDS) in expressways. To this end, the methodologies presented in prior studies were firstly summarized. It is very hard to achieve exact SMSs and TMSs due to mechanical and communication errors in the field. Thus, a microscopic traffic simulation model was utilized to evaluated the performance. As a result, the harmonic mean and volume-distance weighted harmonic mean were close to the SMS in the case in which the TMSs of individual vehicles were used. However, when the 30-second-interval aggregated TMS were used, the volume-distance weighted harmonic mean was outstanding. In this study, a radar detector was installed in the Joongbu expressway to collect the SMS. The trajectory of individual vehicles collected from the detector were used to calculate the SMS, which was compared with the estimates using other methodologies selected in this study. As a result, the volume-distance weighted mean was turned out to be close to the SMS. However, as the congestion becomes severe. the deviation between the two speed becomes bigger.

• Journal of the Korean association of regional geographers
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• v.3 no.2
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• pp.209-225
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• 1997

Today, rapid progress of urbanization is discovered commonly in many countries, especially in developing countries, which has led to spatial order and development process of city. Historically, Taegu was a walled city and formed mono-nucleus which was restricted by the castle. As the city grew gradually, the castle was removed as a result of diversification in traffic network, change of socio-economic environment, formation of industrial base and functional distribution. According to reconstruction maps of residential patterns, there was distinctive residential segregation among ethnic groups. Koreans in Taegu in 1939, aggregated densely in the southern and western parts of the city. The Japanese were concentrated densely in the northern and eastern parts of Taegu. And the street pattern within residential areas of the Korean people was shaped like a maze type in contrast with Japanese residential areas, which showed grid pattern of streets. This is another general pattern of almost all colonial cities, especially in Asia. Through this process, today it appears that, out of overall residential areas which occupy the highest ratio in urban land use, those for eminent people influence the functional development of urban spatial structure very heavily as a key point in urban residetial structure. Truly, residential segregation can be seen as the spatial manifestation of uneven distribution of such important scarce resources as housing and residential environment. In this study, the characteristics of locational distribution of the eminent people show their socially and economically stabilized standing in Taegu, taking the aforesaid situation as a background of the study. And the process of this study is as follows ; to examine the forming process of residential areas in the city as a theoretical supporting, to put in order on classical interpretation to formation of residential areas, and general type modern residential areas formation, and economic decision factor of land use. Therefore, this study aims to examine growth and development of eminent persons' residential areas and, at the same time, extract locational characteristics through the pattern of eminent persons' location and predict changes in the future.