• Journal of Communications and Networks
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• v.13 no.3
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• pp.286-297
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• 2011

A novel converged optical network unit (ONU)-base station (BS) architecture has been contemplated for next-generation optical-wireless networks. It has been demonstrated through high quality studies that data traffic carried by both wired and wireless networks exhibit self-similar and long range dependent characteristics; attributes that classical teletraffic theory based on simplistic Poisson models fail to capture. Therefore, in order to apprehend the proposed converged architecture and to reinforce the provisioning of tightly bound quality of service (QoS) parameters to end-users, we substantiate the analysis of the QoS behavior of the ONU-BS under self-similar and long range dependent traffic conditions using custom queuing which is a common queuing discipline. This paper extends our previous work on priority queuing and brings novelty in terms of presenting performance analysis of the converged ONU-BS under realistic traffic load conditions. Further, the presented analysis can be used as a network planning and optimization tool to select the most robust and appropriate queuing discipline for the ONU-BS relevant to the QoS requirements of different applications.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.147-157
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• 2022

Recently, many studies have been conducted to analyze traffic or object recognition that classifies vehicles through artificial intelligence-based prediction models using CCTV (Closed Circuit TeleVision)or drone images. In order to develop an object recognition deep learning model for accurate traffic estimation, systematic data construction is required, and related standardized guidelines are insufficient. In this study, previous studies were analyzed to derive guidelines for establishing artificial intelligence-based training data for traffic estimation using drone images, and business reports or training data for artificial intelligence and quality management guidelines were referenced. The guidelines for data construction are divided into data acquisition, preprocessing, and validation, and guidelines for notice and evaluation index for each item are presented. The guidelines for data construction aims to provide assistance in the development of a robust and generalized artificial intelligence model in analyzing the estimation of road traffic based on drone image artificial intelligence.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.1
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• pp.17-32
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• 1996

In this paper, a model for two-layered video traffic is proposed. The performance analysis of the proposed model and the effects of two-layer coding scehemes in ATM networks are also studied. ATM-based networks give the possibility to support image codingat variable bit rate(VBR). Two layer coding is one of the very promising methods among many proposed methods to compensate the cell loss, the major drawback in ATM networks. From the experimental data of the 2-layer coded video traffics, it is observed that traffic patterns of base layer and enhanced layer are highly correlate to each other, when constant image quality is kept. With this observation, coded two layered video traffic can be modeled as 2-dimensional Markov chain. The model well fit the real experimental data. The model was used for the analysis of the performance of statistical multiplexer with priorites in ATM networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.514-522
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• 2017

Traffic offloading is a promising solution to solve the explosive growth of mobile traffic. One of offloading schemes, in LIPA/SIPTO(Local IP Access and Selected IP Traffic Offload) offloading, we can offload mobile traffic that can satisfy QoS requirement for application. In addition, it is necessary for traffic offloading using social context due to large traffic from SNS. Thus, we propose the LIPA/SIPTO offloading algorithm using social context. We define the application selection probability using social context, the application popularity. Then, we find the optimal offloading weighting factor to maximize the QoS(Quality of Service) of small cell users in term of effective data rate. Finally, we determine the offloading ratio by this application selection probability and optimal offloading weighting factor. By performance analysis, the effective data rate achievement ratio of the proposed algorithm is similar with the conventional one although the total offloading ratio of the proposed algorithm is about 46 percent of the conventional one.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.81-93
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• 2022

Recently, there have been many studies on object recognition around the vehicle and recognition of traffic signs and traffic lights in autonomous driving. In particular, such the recognition of traffic lights is one of the core technologies in autonomous driving. Therefore, many studies for such the recognition of traffic lights have been performed, the studies based on various deep learning models have increased significantly in recent. In addition, as a high-quality AI training data set for voice, vision, and autonomous driving is released on AIHub, it makes it possible to develop a recognition model for traffic lights suitable for the domestic environment using the data set. In this study, we developed a recognition model for traffic lights that can be used in Korea using the AIHub's training data set. In particular, in order to improve the recognition performance, we used various models of YOLOv4 and YOLOv5, and performed our recognition experiments by defining various classes for the training data. In conclusion, we could see that YOLOv5 shows better performance in the recognition than YOLOv4 and could confirm the reason from the architecture comparison of the two models.

• Journal of the Korea Computer Industry Society
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• v.3 no.5
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• pp.631-640
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• 2002

The internet phones that are currently available in use adopt packet exchange system, transferring through various routes and lacking sufficient band width with a result that there is an accompanied delay for packet transmission since the traffic is increased, accordingly affecting a lot in sound quality and speed. Two solutions for such troubles are suggested in this study to improve sound quality of internet phones. Firstly, we minimize the delay and damage regarding packet size based on traffic size by using the data algorithm from variable packets in order to supplement decreased sound quality due to the delay and damage of sound data. The second suggestion is to employ a method of Jitter compensation by giving an appropriate initial delay time with regenerating buffers to bypass troubles from Jitter, From employing the Jitter compensation method, we found that there is a sound quality improvement due to the less stoppage phenomenon.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.313-324
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• 2005

The success of the IEEE 802.11 standard has prompted research into efficiency of the different medium access methods and their support for different traffic types. A modified version of the point coordination function (PCF) called modified PCF has been introduced as a way to improve the efficiency over the standard method. It has been shown through a simulation study and a mathematical analysis that channel utilization can be much improved compared to the standard, in case there is no so-called hidden station problem. However, under the hidden station problem, the efficiency of the modified PCF would obviously decrease. In this paper, some enhancements of the modified PCF are introduced. Firstly, we propose a retransmission process to allow frames involved in collisions to be retransmitted. Then, we propose a collision resolution mechanism to reduce the frame collision probability due to the hidden station problem. In addition, we propose a priority scheme to support prioritization for different traffic types such as interactive voice and video, and real-time data traffic in the modified PCF. To prevent the starvation of one low priority traffic, minimum transmission period is also guaranteed to each traffic type via an admission control algorithm. We study the performance of the modified PCF under the hidden station problem and the performance of the modified PCF with priority scheme through simulations. To illustrate the efficiency of the priority scheme, we therefore compare its simulation results with those of some standardized protocols: The distributed coordination function (DCF), the enhanced distributed channel access (EDCA), the PCF, and our previously proposed protocol: The modified PCF without priority scheme. The simulation results show that the increment of delay in the network due to the hidden station problem can be reduced using the proposed collision resolution mechanism. In addition, in a given scenario the modified PCF with priority scheme can provide better quality of service (QoS) support to different traffic types and also support a higher number of data stations than the previous proposals.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.2
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• pp.161-167
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• 2008

This paper describes the overview of spectrum requirement estimation recommended in ITU-R Rec. M.1390 and [IMT.METH] and its difference for the IMT mobile service, and a (IMT.METH) methodology is applied to the spectrum estimation of the recent IMT service. The traffic model and traffic calculation algorithm is briefly described for the carried traffic which is determined in terms of the offered traffic, system rapacity, and the criteria of quality of service. And the spectrum requirement demand which is required from year 2010 to year 2015 is calculated as an example for the IMT service which is recently operated and deployed in the current Korean market after obtaining the reasonable market data and the ITU market prediction data.

• International Journal of High-Rise Buildings
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• v.3 no.2
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• pp.155-165
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• 2014

This study measured and compared the variation of ventilation rate and fan energy consumption according to various control strategies after installing wireless sensor-based pilot ventilation system in order to verify the applicability of demand-controlled ventilation (DCV) strategy that was efficient ventilation control strategy for underground parking lot. The underground parking lot pilot ventilation system controlled the ventilation rate by directly or indirectly tracking the traffic load in real-time after sensing data, using vehicle detection sensors and carbon monoxide (CO) and carbon dioxide ($CO_2$) sensor. The ventilation system has operated for 9 hours per a day. It responded real-time data every 10 minutes, providing ventilation rate in conformance with the input traffic load or contaminant level at that time. A ventilation rate of pilot ventilation system can be controlled at 8 levels. The reason is that a ventilation unit consists of 8 high-speed nozzle jet fans. This study proposed vehicle detection sensor based demand-controlled ventilation (VDS-DCV) strategy that would accurately trace direct traffic load and CO sensor based demand-controlled ventilation (CO-DCV) strategy that would indirectly estimate traffic load through the concentration of contaminants. In order to apply DCV strategy based on real-time traffic load, the minimum required ventilation rate per a single vehicle was applied. It was derived through the design ventilation rate and total parking capacity in the underground parking lot. This is because current ventilation standard established per unit floor area or unit volume of the space made it difficult to apply DCV strategy according to the real-time variation of traffic load. According to the results in this study, two DCV strategies in the underground parking lot are considered to be a good alternative approach that satisfies both energy saving and healthy indoor environment in comparison with the conventional control strategies.

• Smart Structures and Systems
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• v.17 no.6
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• pp.995-1015
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• 2016

In the design and condition assessment of bridges, it is usually necessary to take into consideration the extreme conditions which are not expected to occur within a short time period and thus require an extrapolation from observations of limited duration. Long-term structural health monitoring (SHM) provides a rich database to evaluate the extreme conditions. This paper focuses on the extrapolation of extreme traffic load effects on bridges using long-term monitoring data of structural strain. The suspension Tsing Ma Bridge (TMB), which carries both highway and railway traffic and is instrumented with a long-term SHM system, is taken as a testbed for the present study. Two popular extreme value extrapolation methods: the block maxima approach and the peaks-over-threshold approach, are employed to extrapolate the extreme stresses induced by highway traffic and railway traffic, respectively. Characteristic values of the extreme stresses with a return period of 120 years (the design life of the bridge) obtained by the two methods are compared. It is found that the extrapolated extreme stresses are robust to the extrapolation technique. It may owe to the richness and good quality of the long-term strain data acquired. These characteristic extremes are also compared with the design values and found to be much smaller than the design values, indicating conservative design values of traffic loading and a safe traffic-loading condition of the bridge. The results of this study can be used as a reference for the design and condition assessment of similar bridges carrying heavy traffic, analogous to the TMB.