• Korean Journal of Ecology and Environment
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• v.53 no.1
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• pp.91-101
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• 2020

Stormwater runoff is known as a major non-point water pollution source that transports heavy metals, which have accumulated in road surface, to stream and coastal area. Dissolved and particulate metals in stormwater runoffs have been investigated to understand the outflow characteristics of heavy metals during rainfall events and to identify their pollution sources. The concentration of dissolved Co and Ni decreased after the outflow with high concentrations at the beginning of the rainfall, and other metals showed different characteristics depending on the rainfall and rate of discharge. Particulate metals showed a similar trend with the temporal variation of suspended solids concentration in stormwater runoffs. The results of geo-accumulation index (I_geo) indicated that the stormwater runoffs from industrial region were very highly polluted with Cu, Zn and Cd. As a result of comparing the metal concentrations of <125 ㎛ for road dust near the study area, Cu, Zn and Cd were originated from inside of metal manufacturing facilities rather than traffic activities at road surface and these metals accumulated on the surface area of facilities were transported to the water environments during stormwater event. The average discharged amounts of heavy metals for one rainfall event were Cr 128 g, Co 12.35 g, Ni 98.5 g, Cu 607.5 g, Zn 8,429.5 g, As 6.95 g, Cd 3.7 g, Pb 251.75 g, indicating that metal runoff loads in the stormwater runoffs are closely related to surrounding industry types.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.10a
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• pp.279-282
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• 2015

Fisheries development of the basic law pursuant to article 15 (marine safety management, etc.) one of maritime safety and maritime traffic facilities nationwide network of DGPS in accordance with the building maximize infrastructure utilization and country. Source technology has been improving steadily raised for the benefit daegukmin. In particular, look at the type of product for the marine supply medium-wave receiver Performance products that satisfy most of the IMO Advisory. The antenna and receiver are separate structural supply for some integrated model with a very high Rather it is used as a portable receivers for marine positioning cheap integrated model development is needed. Correction of satellite navigation receivers for the current Marine GPS module, medium-wave modules can be developed one low cost Integrated in independent operating environments do not support the model development done look at what the problem is 285kHz ~ 315kHz in DGPS Beacon receiver structure using a medium wave or Beacon The medium-wave antenna and a GPS receiver signal to noise ratio was studied GPS signal attenuation on the DGPS performance looked at each GPS manufacturer medium-wave signal-to-noise ratio and normalized impact by GPS manufacturers noise power ratio per bandwidth for medium-wave GPS signals affect it was implemented to improve performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.1
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• pp.25-39
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• 1986

In this paper, we analyze the performance, particularly the flow control mechanism, of the CCITT X.25 protocol in a packet-switched network. In this analysis, we consider the link and packet layers separately, and investigate the performance in three measures; normalized channel throughput, mean transmission time, and transmission efficiency. Each of these measures is formulated in terms of given protocol parameters such as windos size, $T_1$ and $T_2$ values, message length, and so forth. We model the service procedure of the inpur traffic based on the flow control mechanism of the X.25 protocol, and investigate the mechanism of the sliding window flow control with the piggybacked acknowlodgment scheme using a discrete-time Markov chain model. With this model, we study the effect of variation of the protoccol parameters on the performance of the X.25 protocol. From the numerical results of this analysis one can select the optimal valuse of the protocol parameters for different channel environments. it has been found that to maintain the trasnmission capacity satisfactorily, the window size must be greater than or equal to 7 in a high-speed channel. The time-out value, $T_1$, must carefully be selected in a noisy channel. In a normal condition, it should be in the order of ls. The value of $T_2$ has some effect on the transmission efficiency, but is not critical.

• KNOM Review
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• v.23 no.2
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• pp.29-41
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• 2020

Networks are growing faster than ever before causing a multi-domain complexity. The diversity, variety and dynamic nature of network traffic and services require enhanced orchestration and management approaches. While many standard orchestrators and network operators are resulting in an increase of complexity for handling E2E slice orchestration. Besides, there are multiple domains involved in E2E slice orchestration including access, edge, transport and core network each having their specific challenges. Hence, handling of multi-domain, multi-platform and multi-operator based networking environments manually requires specified experts and using this approach it is impossible to handle the dynamic changes in the network at runtime. Also, the manual approaches towards handling such complexity is always error-prone and tedious. Hence, this work proposes an automated and abstracted solution for handling E2E slice orchestration using an intent-based approach. It abstracts the domains from the operators and enable them to provide their orchestration intention in the form of high-level intents. Besides, it actively monitors the orchestrated resources and based on current monitoring stats using the machine learning it predicts future utilization of resources for updating the system states. Resulting in a closed-loop automated E2E network orchestration and management system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.527-536
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• 2022

The purpose of this study is to predict changing traffic environments and related economic effects by reflecting the changed KTDB and socio-economic indicators pertaining to Mulgeum station, a general railway stop, when it is confirmed as a KTX stop. To analyze the data of this study, socioeconomic indicators and the general status of transportation facility operations were investigated with reference to related statistical data, centered on the country overall and on Yangsan city in particular. In addition, we investigated and referenced the railroad facility construction plan and train operation plan, which are national high-level plans related to land development and transportation network construction. Currently, there are only ITX trains (4 times/day) and Mugunghwa trains (29 times/day) that stop at Mulgeum station in Yangsan, meaning that passengers cannot use KTX trains in the Yangsan area. In particular, the need for a KTX stop at Mulgeum station has been continuously raised because train users in the Yangsan area have inconvenient transportation in that they must travel 40 minutes to Ulsan station or 30 minutes to Gupo station to use the KTX. As a result of analyzing railroad transportation demand that will change in the future as the KTX stop at Mulgeum station is confirmed, the number of passengers boarding and arriving at Mulgeum station is predicted to be 1,674 passengers/day by 2025. In addition, the numbers of train passengers that are converted from Ulsan and Gupo stations due to the stop at Mulgeum station are predicted to be 594 passengers/day boarding and 562 passengers/day arriving by 2025. In the future, if Yangsan citizens use the KTX Mulgeum station, the access time to Mulgeum station can be shortened to 22 minutes from 65 minutes, and it is predicted that the inconvenience of transferring between railroads will be resolved, with the waiting time for transfers reduced by up to a maximum of 40 minutes. Therefore, the economic effect of creating a KTX stop at Mulgeum station was analyzed to be B/C=1.823 when general railroad operating costs are not taken into account and B/C=2.127 when general railroad operating costs are considered. In conclusion, when using KTX trains to visit the Seoul Metropolitan Area, it takes 2 hours and 43 minutes to use Mulgeum station without using Ulsan station or Gupo station, which is considered to be very effective for reducing travel times and improving the economic feasibility of this development; it is also expected that Yangsan city will be able to improve accessibility and mobility to the Seoul Metropolitan Area by breaking free from the disgrace of being a remote location given its link to KTX in the future.

• Journal of KIISE:Information Networking
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• v.29 no.6
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• pp.595-612
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• 2002

One of the most important issues in guaranteeing the high degree of QoS on mobile computing is how to reduce hand-off drops caused by lack of available bandwidth in a new cell. Each cell can request bandwidth reservation to its adjacent cells for hand-off calls. This reserved bandwidth can be used only for hand-offs, not for new calls. It is also important to determine how much of bandwidth should be reserved for hand-off calls because reserving too much would increase the probability of a new call being blocked. Therefore, it is essential to develop a new mechanism to provide QoS guarantee on a mobile computing environment by reserving an appropriate amount of bandwidth and call admission control. In this paper. bandwidth reservation and call admission control mechanisms are proposed to guarantee a consistent QoS for multimedia traffics on a mobile computing environment. For an appropriate bandwidth reservation, we propose an adaptive bandwidth reservation mechanism based on an MPP and a 2-tier cell structure. The former is used to predict a next move of the client while the latter to apply our mechanism only to the client with a high hand-off probability. We also propose a call admission control that performs call admission test only on PNC(Predicted Next Cell) of a client and its current cell. In order to minimize a waste of bandwidth caused by an erroneous prediction of client's location, we utilize a common pool and QoS adaptation scheme. In order evaluate the performance of our call admission control mechanism, we measure the metrics such as the blocking probability of new calls, dropping probability of hand-off calls, and bandwidth utilization. The simulation results show that the performance of our mechanism is superior to that of the existing mechanisms such as NR-CAT2, FR-CAT2, and AR-CAT2.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.21-35
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• 2022

With the support of local and central governments, various incentive policies for "green" cars have been established, and the number of electric vehicle users has been rapidly increasing in recent years. As a result, much attention is being given to establishing a user-centered charging infrastructure. A standard for the number of electric vehicle chargers to be supplied is being prepared based on building characteristics, but there is quite limited research on the appropriate ratio of slow and fast chargers based on the characteristics of each place. Therefore, this study derived an appropriate penetration ratio based on data about the distribution ratio of common slow chargers. These data were collected using a survey of actual electric vehicle users. Next, an analysis was done on how to categorize the needs of charging environments and to determine what criteria or characteristics to use for categorization. Based on the results of the survey analysis, three types of places were derived. Type-1 places require 10% of chargers to be slow chargers, Type-2 places require 40-60% of chargers to be slow chargers (i.e., around equal distribution of slow and fast chargers), and Type-3 places require more than 80% of chargers to be slow chargers. The required levels of slow chargers were classified by place type and by individual using latent class cluster analysis, which made it possible to categorize them into five clusters related to socioeconomic variables, vehicle characteristics, traffic, and charging behaviors. It was found that there was a high correlation between charging behavior, weekend travel behavior, gender, and income. The results and insights from this study could be used to establish charging infrastructure policies in the future and to prepare standards for supplying charging infrastructure according to changes in the electric vehicle market.