• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.9
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• pp.1402-1408
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• 2017

Recently, services for personal biometric data analysis based on real-time monitoring systems has been increasing and many of them have focused on recognition of emotions. In this paper, we propose a classification model to classify anxiety emotion using biometric data actually collected from people. We propose to deploy the support vector machine to build a classification model. In order to improve the classification accuracy, we propose two data pre-processing procedures, which are normalization and data deletion. The proposed algorithms are actually implemented based on Real-time Traffic Flow Measurement structure, which consists of data collection module, data preprocessing module, and creating classification model module. Our experiment results show that the proposed classification model can infers anxiety emotions of people with the accuracy of 65.18%. Moreover, the proposed model with the proposed pre-processing techniques shows the improved accuracy, which is 78.77%. Therefore, we can conclude that the proposed classification model based on the pre-processing process can improve the classification accuracy with lower computation complexity.

• KIISE Transactions on Computing Practices
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• v.21 no.3
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• pp.223-238
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• 2015

Ramp metering is the most effective and direct method to control a vehicle entering the freeway. This paper proposed the new density-based ramp metering method. Existing methods that use the flow data had low reliability data and can have various problems. Also, when the ramp metering was operated by freeway congestion, the additional congestion and over-capacity can occur in the ramp. To solve this problem with the existing method, the proposed method used the density and acceleration data of the freeway and considered the ramp status. The developed strategy was tested on Trunk Highway 62 west bound (TH-62 WB) in Minnesota Twin-City and compared with Stratified Zone Metering(SZM), which had been operating in the Twin-City freeway. To constitute the experiment environment, the VISSIM simulator was used. The Traffic Information and Condition Analysis System (TICAS) was developed to control the PTV VISSIM simulator. The experiment condition was set between 2:00 PM and 7:00 PM, Oct 5th, 2014 during severe traffic congestion. The simulation results showed that total travel time was reduced by 20% for SZM. Thus, we solved the problem of ramp congestion and over-capacity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.4
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• pp.1976-1981
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• 2013

In this paper, we propose a frequency-domain interference cancellation algorithm for direct-sequence spread spectrum systems. In the previously proposed frequency-domain interference cancellation algorithms that protocol defines the rules concerning the collection of means of Transmission Control Protocol (TCP: Transmission Control Protocol) is the most widely used in the transport layer. Two-way traffic through the network path to the same end-to-end transfer of data in the opposite direction between pairs of nodes are infused with two or more TCP connection using the network traffic patterns from the exchanger and routers share results of approval. Per-flow input/output structure of matter using the LTS online reaction when evaluated as this is the most important factor. TCP-MT when the connection duration is one of the largest performance gains.

• The KIPS Transactions:PartC
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• v.16C no.2
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• pp.237-244
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• 2009

The congestion in wireless sensor network increases the ratio of data loss and causes the delay of data. The existing congestion protocols for wireless sensor network reduces the amount of transmission by control the sampling frequency of the sensor nodes related to the congestion when the congestion has occurred and was detected. However, the control method of sampling frequency is not applicable on the situation which is sensitive to the temporal data loss. In the paper, we propose a new congestion control, ACT - Adaptive Congestion conTrol. The ACT monitors the network traffic with the queue usage and detects the congestion based on the multi level threshold of queue usage. Given network congestion, the ACT increases the efficiency of network by adaptive flow control method which adjusts the frequency of packet transmission and guarantees the fairness of packet transmission between nodes. Furthermore, ACT increases the quality of data by using the variable compression method. Through experiment, we show that ACT increases the network efficiency and guarantees the fairness to sensor nodes compared with existing method.

• Journal of Advanced Navigation Technology
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• v.18 no.6
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• pp.594-599
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• 2014

The routinized wireless devices such as smart phone have promoted to expand the use of IEEE 802.11 groups. The challenge environments of the wireless network utilizes effectively and user-oriented seamless services that handover is the most desirable issues under the wireless circumstance. In data center software defined network (SDN) has provided the flow routing to reduce costs and complexities. Flow routing has directly offered control for network administrator and has given to reduce delay for users. Under the circumstance of being short of network facilities, SDNs give the virtualization of network environments and to support out of the isolation traffic conditions. It shows that the mechanism of handover makes sure seamless services for higher density of the network infrastructure which is SDN to support network service re-configurable.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.7
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• pp.297-306
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• 2017

Citizens want more accurate forecast information using Bus Information System. However, most bus information systems that use an average based short-term prediction algorithm include many errors because they do not consider the effects of the traffic flow, signal period, and halting time. In this paper, we try to improve the precision of forecast information by analyzing the influencing factors of the error, thereby making the convenience of the citizens. We analyzed the influence factors of the error using BIS data. It is shown in the analyzed data that the effects of the time characteristics and geographical conditions are mixed, and that effects on halting time and passes speed is different. Therefore, the halt time is constructed using Generalized Additive Model with explanatory variable such as hour, GPS coordinate and number of routes, and we used Hidden Markov Model to construct a pattern considering the influence of traffic flow on the unit section. As a result of the pattern construction, accurate real-time forecasting and long-term prediction of route travel time were possible. Finally, it is shown that this model is suitable for travel time prediction through statistical test between observed data and predicted data. As a result of this paper, we can provide more precise forecast information to the citizens, and we think that long-term forecasting can play an important role in decision making such as route scheduling.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.82-96
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• 2024

While analyzing traffic flow, speed, traffic volume, and density are important macroscopic indicators, and acceleration and spacing are the important microscopic indicators. The speed and traffic volume can be collected with the currently installed traffic information collection devices. However, acceleration and spacing data are necessary for safety and autonomous driving but cannot be collected using the current traffic information collection devices. 'You Look Only Once'(YOLO), an object recognition technique, has excellent accuracy and real-time performance and is used in various fields, including the transportation field. In this study, to measure acceleration and spacing using YOLO, we developed a model that measures acceleration and spacing through changes in vehicle speed at each interval and the differences in the travel time between vehicles by setting the measurement intervals closely. It was confirmed that the range of acceleration and spacing is different depending on the traffic characteristics of each point, and a comparative analysis was performed according to the reference distance and screen angle to secure the measurement rate. The measurement interval was 20m, and the closer the angle was to a right angle, the higher the measurement rate. These results will contribute to the analysis of safety by intersection and the domestic vehicle behavior model.

• Journal of Korean Society of Transportation
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• v.18 no.4
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• pp.75-85
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• 2000

The Purpose of this study is to analyze wether the composition of training sample have a relation with the Predictive ability and the learning results of ANNs(Artificial Neural Networks) fur predicting one cycle ahead of the queue length(veh.) in a signalized intersection. In this study, ANNs\` training sample is classified into the assumption of two cases. The first is to utilize time-series(Per cycle) data of queue length which would be detected by one detector (loop or video) The second is to use time-space correlated data(such as: a upstream feed-in flow, a link travel time, a approach maximum stationary queue length, a departure volume) which would be detected by a integrative vehicle detection systems (loop detector, video detector, RFIDs) which would be installed between the upstream node(intersection) and downstream node. The major findings from this paper is In Daechi Intersection(GangNamGu, Seoul), in the case of ANNs\` training sample constructed by time-space correlated data between the upstream node(intersection) and downstream node, the pattern recognition ability of an interrupted traffic flow is better.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.5
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• pp.44-56
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• 2009

Multimedia streaming service is susceptible to loss and delay of data as it requires high bandwidth and real time processing. Therefore QoS cannot be guaranteed due to data loss caused by heavy network traffic and error of wireless channel. To solve these problems, studies about algorithms which improve the quality of multimedia by serving differently according to the priority of packets in multimedia stream. Two algorithms are proposed in this paper. The first algorithm proposed is WMS-1(Wireless Multimedia Scheduling-1) algorithm which acts like IWFQ when any wireless loss is occurred but assigns channels first in case of urgent situation like when the running time of multimedia runs out. The second algorithm proposed is WMS-2(Wireless Multimedia Scheduling-2) algerithm that assigns priority to multimedia flow and schedules flow that has higher priority according to type of frame first. The comparison with other existing scheduling algorithms shows that multimedia service quality of the proposed algorithm is improved and the larger the queue size of base station is, the better total quality of service and fairness were gained.

• Journal of the Korea Convergence Society
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• v.11 no.6
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• pp.59-67
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• 2020

Expressway is the main link in promoting the national economic development, which plays a vital part in improving the regional economy and people's living standards, therefore, it is of great significance to accelerate the construction of expressways. However, because it is difficult for the existing system to identify the information of special vehicles quickly, leading to the cumbersome flow of special vehicles passing through the toll station of expressways [1], which brings a certain burden to the work of expressway administrators. The surge in the number of private cars also increased the traffic pressure of toll stations, especially the free expressways traffic policy implemented by the State during holidays, resulting in more frequent traffic jams at high-speed intersections. According to this situation, a intelligent system was created to ameliorate the difficult situation of special vehicle identification on expressways, reduce the congestion at high-speed intersections, and improve the efficiency of staff by data-based means.